RoboRuby

Ruby AI News - March 27th, 2026

Matt Solt — Fri, 27 Mar 2026 16:31:53 +0000

Happy Friday! Welcome to the one year anniversary edition of Ruby AI News! The 27th edition features the rise of AI agent-driven business creation, tooling to deploy your AI experiments more than ONCE, a new cognitive architecture for Ruby AI, and much more.

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Welcome to the One Year Anniversary Edition
Top Stories
Need to Know AI News
Content
Events
- Previous
- Upcoming
Open Source Updates
Jobs & Opportunities
- Featured
One Last Thing

Welcome to the One Year Anniversary Edition

One Year of Ruby AI: From First Edition to Ruby Renaissance. A year ago, I attended Artificial Ruby and saw the beginning of something special. Rubyists were reinvigorated by the rise of new artificial intelligence capabilities. Inspired by that meetup and Lucian Ghinda’s incredible work on Short Ruby News, Ruby AI News launched in March of last year with a simple premise: Ruby belongs in the generative AI conversation. What happened over the course of the next year exceeded all of my expectations.

Spring 2025: The foundations. RubyLLM 1.0 hit the front page of Hacker News. Within weeks, both Anthropic and OpenAI released official Ruby SDKs, validating what the community already knew. MCP arrived in the Rails ecosystem almost overnight, with Stan Lo, Mario Chávez, and others building servers simultaneously. Then Matz himself keynoted RubyKaigi with "Programming Language for AI Age," calling Ruby's expressiveness and DSL extensibility a natural fit. Y Combinator piled on, revealing that 25% of its Winter '25 batch wrote 95% of their code with AI, and recommended Rails.

Summer 2025: Builders ship. Shopify open-sourced Roast. Kieran Klaassen shipped Cora, a full AI email client, as a solo developer on Rails + RubyLLM, and coined "compounding engineering" to describe the new workflow. The first-ever Ruby AI Hackathon brought dozens of developers to San Francisco. Claude Code arrived and changed how Rubyists work. Tidewave launched a browser-based Rails coding agent. RubyLLM blew past 2 million downloads, and ruby-openai was selected for GitHub's Secure Open Source Fund.

Fall 2025: The ecosystem matures. DSPy.rb shipped 15 versions in two weeks. Rails World in Amsterdam went heavy on AI. Phoenix by Def Method launched self-healing test generation for Rails. Anthropic released Claude Skills and Plugins, and Kieran immediately built a marketplace. Then came the San Francisco Ruby Conference: 400 attendees, dozens of AI-powered demos, and a keynote from RubyLLM creator Carmine Paolino declaring "One API, One Person, One Machine."

Winter 2025: Acceleration. The RubyLLM ecosystem exploded into a category of its own: agents, monitoring, instrumentation, evaluation, skills, and templates, all from independent contributors. EverAI revealed it serves 28 million monthly users on a single Rails monolith. Obie Fernandez ported Cloudflare's Code Mode pattern to Ruby, collapsing 21 MCP tool calls into one. Ruby 4.0 shipped. The community started talking about context graphs and what comes after RAG.

March 2026: The proof arrives. Ruby core committer Yusuke Endoh ran a 15-language, 300-run Claude Code benchmark. Ruby was the fastest, cheapest, and most stable, with a perfect test pass rate. The Rails Foundation updated its homepage: "Ruby on Rails scales from PROMPT to IPO." Garry Tan called it a "crazy unlock." A PE fund started building an investment thesis around Rails businesses.

We have come a long way, and it is all thanks to the Ruby community. This newsletter wouldn’t be possible without the incredible community contributions and work developers do every day to build and document the next generation of Ruby AI tools. We now have an ecosystem with thousands of AI libraries, multiple conferences, a podcast, a discord, a hackathon, and production apps serving millions, most of it in the last twelve months. The question a year ago was whether Ruby had a place in the AI era. The answer, backed by benchmarks, community, and shipped products, is unequivocal.

So what comes next? The answer is I don’t know. Next year will look entirely different than anything that has come before in software development. Alot is happening behind the scenes of the newsletter as I build out tooling to track the entire Ruby ecosytem of millions of repositories, hundreds of thousands of developers, tens of thousands of companies building with Ruby, and 2,431 Ruby AI gems and counting. But I need your help. Please spread the word about the newsletter and keep supporting the community with all of the amazing work you do day in and day out. And I want to hear from you. What do you want to see in Year Two? What tools, topics, and stories should I cover? How can the newsletter better support your work with Ruby AI? Let me know: matt@roboruby.com.

Welcome to the second year of Ruby AI News. Let's keep building.

Need to Know AI News

Introducing the Machine Payments Protocol Tempo and Stripe announced an open standard that lets AI agents pay for services programmatically. Agents request resources, receive payment requests, and authorize transactions without human involvement, supporting fiat and stablecoin payments via Stripe's PaymentIntents API.

Sandboxing AI Agents, 100x Faster Cloudflare launched Dynamic Workers, V8 isolate-based sandboxes for AI-generated code that start in milliseconds with megabytes of RAM instead of containers. Code Mode lets agents chain API calls in a single execution, cutting token usage by 81%. $0.002/worker/day, free during beta.

The .agent Community launched by Open Agent Registry is pursuing a community-led ICANN application to secure .agent as a top-level domain for AI agents. The initiative has 3,000+ members and includes a map of the agentic web cataloging companies building autonomous agents.

Issue Tracking Is Dead Linear announced an AI-native transformation with Linear Agent, Skills (reusable slash-command workflows), and Automations that trigger on issue creation, with code intelligence and a coding agent coming soon.

Skill Issue: Harness Engineering for Coding Agents Kyle Mistele of HumanLayer argued that coding agent failures are configuration problems, not model problems. The article covered six harness techniques: give agents better instructions, more capabilities, isolated subtask execution, lifecycle automation, and self-verification.

Hyperagents Jenny Zhang et al. introduced self-referential AI agents that modify both their task-solving behavior and the process that generates future improvements. By extending the Darwin Gödel Machine with metacognitive self-modification, hyperagents outperform prior self-improving systems with meta-level improvements transferring across domains.

Parameter Golf OpenAI launched a competition to train the smallest possible language model within a 16MB artifact constraint, evaluated on bits per byte against the FineWeb dataset. Entries must complete training in under 10 minutes on 8 H100 GPUs, with $1M in compute credits available and top submissions using quantization, test-time training, and architectural innovations.

Content

Announcements

AI Scanner 0DIN.ai, the Mozilla zero day investigative network, released an open-source web platform for AI model security assessments built with Ruby on Rails and NVIDIA garak. It offers 179 probes across 35 vulnerability families aligned with OWASP LLM Top 10, multi-target scanning for API and browser-based LLMs, Attack Success Rate scoring, PDF reports, and SIEM integration.

Superpowers Ruby Lucian Ghinda forked obra/superpowers and adapted it for Ruby on Rails projects. The skills library covers Ruby idioms, Minitest testing, Brakeman security scanning, Sandi Metz rules, 37signals patterns, Hotwire, and Rails guides. Works with Claude Code, Cursor, Codex, OpenCode, and Gemini CLI.

Rubyn Matthew Suttles launched as an AI-powered CLI and mountable Rails engine for Rails projects. The launch post introduced context-aware refactoring, spec generation, and code review, while the open-source gem includes a web dashboard and targets Rails conventions that general-purpose AI tools miss.

Maquina MVP Creator Mario Alberto Chávez released a Claude Code agent that generates MVP documentation for Rails applications through guided research and discovery. It produces five deliverables: competitive research report, business plan with user stories, brand guide, technical architecture following 37signals conventions, and a pre-configured CLAUDE.md files for development handoff.

Ruby on Vibes Eric Arnold launched a platform for generating full-stack Rails apps with AI through natural language. Users describe what they want, and the platform produces a live app with auth, chat, LLM integration, and multi-tenancy built in, showcased in a new demo video.

Kreuzberg v4.5.0 released with document layout understanding powered by Docling's RT-DETR v2 model embedded in a Rust-native pipeline. The open-source framework extracts text, structure, and metadata from 79 formats with native bindings for 12 languages including Ruby.

FOSM-Rails Abhishek Parolkar created a Rails engine for Finite Object State Machines that models business objects through declarative lifecycle definitions. The generator produces models, controllers, views, and AI agents bounded by the state machine. The companion book argued AI coding agents eliminate the upfront specification cost that historically made state machines impractical versus CRUD.

NDAV Kitaiti Makoto released a Ruby gem enabling zero-copy data sharing between multi-dimensional array libraries via Ruby's MemoryView protocol. It acts as a glue layer between Numo::NArray, Torch::Tensor, OnnxRuntime::OrtValue, and Arrow::Array, eliminating redundant memory copies when moving data across AI/ML libraries.

AIAS Dewayne VanHoozer released a Ruby gem for scheduling AI prompts as cron jobs. Users add a schedule: key to any AIA prompt's YAML frontmatter and aias update installs it into the system crontab with MCP server support and per-prompt overrides.

Ruby LLM Contract Justyna Wojtczak released a companion gem for RubyLLM that evaluates prompts across models to compare accuracy vs. cost, with CI gating, parallel eval, drift detection, and pipeline per-step regression tracking to identify which step broke.

Claude Code Project Boundary Justyna also introduced a Claude PreToolUse hook for safer --dangerously-skip-permissions usage. The Bash plugin allows destructive operations inside the project directory but blocks them outside, with protections for chained commands, path traversal, symlink resolution, and built-in Rails safety rules.

ContextQMD Tom Ho built a local-first Context7 alternative using Rails 8.1, Inertia.js, and PostgreSQL. The registry crawls documentation from GitHub repos, llms.txt files, and OpenAPI specs, then serves versioned bundles that MCP clients and a CLI install locally.

Relay Robert (0x1eef) released an early preview of an interactive llm.rb application built with HTMX, Roda, Falcon, and WebSockets. The reference implementation demonstrates streaming chat, custom tool support, and Sidekiq background workers in a Ruby-first architecture, with a companion screencast.

Rails LLM Integration Nagendra Dhanakeerthi created a Claude Code skill that establishes Rails conventions for LLM calls. It teaches Claude to generate service objects with retries and cost tracking, async jobs with typed retry rules, ERB prompt templates, and an eval pipeline.

Rails Agent Skills Ismael Marin Cabrera shared a curated library of AI agent skills for Rails development. The collection enforces a tests-gate-implementation methodology where tests must exist, run, and fail before any code is written.

Uberblick Skills Ben Kubota released a Claude Code and Codex skill pack for the Uberblick planning platform. The /uberblick command provides guided workflows with structured roles that read PRDs via MCP, run completion gates, and write outputs back through the server.

Rails App Generator Preview Avi Flombaum teased a Rails app generator that scaffolds a complete application from a single command ./bin/generate_app my_app). Avi is seeking early feedback before deciding whether to open-source it or release it as a paid starter kit.

Basecamp Agents Basecamp announced an agent-first approach with a CLI, agent skill, and SDKs (including Ruby) that let AI agents perform the same actions as human users: writing docs, managing to-dos, answering check-ins, and handling projects.

Articles

RubyLLM 1.14: From Zero to AI Chat App in Under Two Minutes Carmine Paolino added Rails generators for agents, tools, and schemas plus a production-ready Tailwind chat UI to RubyLLM. Two commands after rails new produce a working AI chat app with Turbo Streams, background jobs, and ActiveRecord persistence. Additionally, Carmine shared a product strategy update for Chat with Work in Comb Shaped Slices.

Ruby Deserves Beautiful Documentation Carmine also released Jekyll VitePress Theme, a Jekyll theme gem that replicates VitePress's documentation design without requiring Node. Includes support for serving plain markdown files. Already adopted by the recently updated RubyLLM Rails Integration docs and Anjan Jagirdar’s Rails Error Dashboard.

The Illusionist and the Conjurer Scott Werner explored how AI shifts creative work from precision to curation, comparing single-attempt "illusionists" with abundance-generating "conjurers." Scott released Conjure, a Rails 8 app that generates multiple AI image variations per presentation slide using Gemini, letting users curate the best results into a final deck. Scott’s other recent piece, Warranty Void If Regenerated, about a near-future where farmers generate their own software tools, made the front page of Hacker News!

Claude Code for the Semi-Reluctant, Somewhat Curious Ruby on Rails Developer Robby Russell published a practical guide to using Claude Code in Rails codebases. Covers model selection, a "lazy-loading" convention system with scoped rule files, and field notes showing debugging sessions dropping from 45 minutes to under 10.

OpenClaw, NanoClaw, and the Problem Nobody's Solving Jonathan Spooner analyzed the two leading personal AI agent projects and argued that both are Claude Code wrappers requiring developer skills, locking out the majority of potential users. Jonathan made the case for a Rails-based alternative using RubyLLM, Solid Queue, and purpose-built service objects instead of giving an LLM full computer access.

I Built an MCP Server That Lets AI Agents Debug Running Ruby Processes Ryo Hayakawa released girb-mcp, an MCP server that connects AI agents to live Ruby processes via the debug gem. Agents can set breakpoints, inspect variables, evaluate code, and step through execution autonomously. Includes Rails-specific tools for route inspection, model schemas, and HTTP request triggering.

How to Add RuboCop MCP to Claude Code and OpenCode Lucian Ghinda walked through configuring RuboCop's built-in MCP server (added in v1.85.0) for Claude Code and OpenCode. The MCP server exposes two tools for inspection and autocorrection, returning structured JSON instead of CLI output so agents can act on offenses reliably.

RAG Without Leaving Rails and LLM Extraction at Scale Henrique Cardoso de Faria documented building a full RAG pipeline in Rails using pgvector, the neighbor gem, Ollama for embeddings, and RubyLLM with Groq for chat completions. The companion article covered scaling structured LLM extraction across thousands of YouTube transcripts, detailing schema enforcement pitfalls, fuzzy speaker deduplication, and serializing results into seed files for deployment without runtime API calls.

Observability for Your LLM-Powered Apps: OTel Instrumentation for RubyLLM Clarissa Borges introduced an OpenTelemetry instrumentation gem for RubyLLM that automatically captures latency, token costs, and tool call traces following GenAI semantic conventions.

The Lobotomy Pipeline: What Happens When AI Removes All Friction and The Bloat Industry: 30,000 Lines to Count Pageviews Abdelkader Boudih shared that LLMs used without domain expertise produce developers who ship more code while understanding less of it. In a companion piece, Abdelkader critiqued AI-generated bloat by building Kaunta, a 15MB Go binary for pageview tracking.

Why I Bet on Rails — and Why I'm Building Maquina Mario Alberto Chávez argued that Rails' convention-over-configuration philosophy makes it ideal for AI-assisted development because agents already know where everything goes. He introduced Maquina, a toolkit of generators, UI components, and AI tools for Rails.

Maquina Generators: From Rails New to Production-Ready Mario followed that post with the announcement for the Maquina Rails generators that automate post-setup configuration: passwordless auth, password-based auth with roles, Rack Attack throttling, Solid Queue, Solid Errors, and Mission Control dashboards.

Right-Sizing Engineering Teams for AI and AI Slop: A Slack API Rate Limiting Disaster Daniel Doubrovkine argued that AI tools solved the effort problem but not the judgment problem, recommending smaller senior-heavy teams of 5-7. He illustrated the point with a cautionary tale where AI-generated Ruby code for a Slack app that ignored Slack's global rate limits, producing code that was "locally coherent, globally wrong."

Setting Up Your Ruby on Rails Monolith for AI Development Colin Soleim outlined five strategies for preparing large Rails monoliths to work with AI coding tools: contextual README files per namespace, fast Guard-based test suites, gradual Sorbet/RBS type adoption, Replit sandboxes for non-technical stakeholders, and service object architecture with explicit interfaces.

Building Mathematical Testing Agents for RSpec Viktor Schmidt built a multi-agent system that applies formal testing techniques to generate mathematically derived RSpec test cases across 60+ models. The key finding was that the real bottleneck was FactoryBot overhead consuming 70-95% of test time, not test quality. The article sparked discussion on r/ruby and led to a companion piece on TestProf optimization.

My Harness: How I Stopped Babysitting AI and Went Kitesurfing Marcin Ostrowski shared his Rails workflow for autonomous AI coding with Claude Code, built on Jesse Vincent's Superpowers framework. The harness uses intent-level task plans, convention skills enforced via hooks, and multi-agent review pipelines to move mid-sized features from idea to production in about four hours.

How to Launch a Lovable MVP in 2026 Ran Craycraft argued that while AI tools like Lovable compress development timelines, they also enable building the wrong product faster. Ran advocated for sprints that identify risks before coding and recommended Thoughtbot's ReadySetGo Rails generator for moving beyond prototypes.

Shopify Liquid: 53% Faster Parse+Render, 61% Fewer Allocations Simon Willison analyzed a pull request from Shopify CEO Tobi Lütke who used an AI coding agent with the autoresearch methodology to optimize the Liquid Ruby template engine. Simon highlighted how robust test suites and measurable benchmarks make optimization an ideal use case for AI agents.

Engineering Rigor in the AI Age: Building a Benchmark You Can Trust Eileen Alayce described how Shopify's Rails Infrastructure team built an open-source benchmarking toolkit for Bundler performance, achieving 3.2x faster cold installs on a 452-gem Gemfile. While Claude scaffolded the initial code, it missed a cache contamination bug that required human expertise to catch.

Dual-Loop BDD Is the New Red-Green TDD Justin Searls proposed a dual-loop BDD workflow for AI coding agents: an outer integration test confirms observable behavior while inner red-green-refactor cycles handle unit-level work. Justin built prove_it, a quality harness for Claude Code, after finding that agents pursue local optimization while missing global functionality.

Building an AI-Native Web Platform Austin French described how a solo developer built a 40,000-line Rails 8 platform with 8 GPU-powered creative tools, booking system, and invoicing. A Discord-integrated AI agent named Hermes handled code generation from voice descriptions, automated audits, and git workflows.

How We Translated Our Entire Platform with AI Ángel Castañeda Crespo, Tom Reinert, and Zakir Khan documented translating Agile Academy's Rails and CMS platforms from 2 to 8 languages using Claude Code. Through iterative refinement of AI agents, they compressed per-language deployment from one month to two days, with Claude Code generating routes, locale files, and infrastructure automatically.

How I Built a Complete Analytics Dashboard for My Rails Blog with Claude Code Jorge Alvarez built a privacy-first analytics dashboard in under 600 lines of code using Ahoy for server-side tracking, Geocoder with MaxMind for local IP geolocation, and pure SVG charts. Jorge used Claude Code with Ariadna's three-phase planning workflow to generate clean implementations on the first pass.

CodeTracer: A Bash Script That Traces Code Faster Than Your IDE and Saves AI Tokens Mirza Lazuardi released a bash script that uses ripgrep to trace symbol definitions, call sites, and data flow across Ruby and JS/TS codebases without an IDE or LSP. It includes Rails route tracing through callbacks and jobs, and reduces AI context by 30x by extracting focused code rather than full files.

After 10 Years of Rails, Here's What AI Coding Agents Get Wrong and How I Fixed It Cris Joseph open sourced rails-ai-context, an MCP server that gives AI agents live schema, model association, controller filter, and route context that static file reading misses.

Why I Choose Ruby on Rails in the AI Coding Era Jesse Waites wrote about how Rails' convention over configuration makes codebases more legible to AI assistants, while Ruby's conciseness uses roughly three times fewer tokens than equivalent TypeScript.

Context Is the Hard Part: Coordinating AI Across Microservices at Teachable Kim Gonzales-Lapp described using GitHub's SpecKit and Claude Code to coordinate a billing migration across Teachable's Rails monolith and three microservices. The approach used a dedicated planning repo with per-service memory files, a constitution of non-negotiable principles, and structured spec-to-task workflows.

The Analogue Programmer in the Land of LLMs Marian Posaceanu reflected on the cognitive debt incurred by using LLMs for coding, describing how generating a Ruby deduplication script felt hollow compared to writing it manually. Marian concluded that while LLMs are here to stay, programmers should be mindful of skill atrophy.

The Real Cost of Rolling Your Own Auth Justin Smestad, maintainer of Warden, argued that authentication's biggest cost is long-term maintenance. He cautioned against delegating security to AI agents, noting auth requires deterministic, auditable decisions rather than probabilistic ones.

Videos

Scott and Rob Use Claude Code to Build an App Using Test-Driven Development Rob Myers and Scott Werner pair-programmed a Ruby "Salvo" game entirely through Claude Code using TDD, demonstrating prompt patterns for test-driven AI development. The session showed Claude reading a PRD, generating user stories, and implementing features.

Can Ruby on Rails Become a Superpower for Agentic Engineering? Jordan Treviño of Telos Labs hosted Cody Watters, Ken Kantzer, and Colleen Schnettler for a panel on how Rails' conventions offer structural advantages for building AI agent systems in production. Discussion covered managing state and constraints in agentic architectures, controlling AI-generated output, and lessons from deploying AI in fintech.

AI in Focus: Turning ReadySetGo into a Rails App Chad Pytel and Louis Antonopoulos took Thoughtbot's ReadySetGo AI proof-of-concept beyond a script and built it into a Rails application with a web UI, exploring the transition from quick experiment to a structured, maintainable app that users can interact with.

Before Writing a Line of Code Mario Alberto Chávez shared a video walkthrough of his pre-coding planning process for Rails projects, explaining how he moved from informal scattered notes to a structured approach for defining users, identifying the real problem, and making early technical decisions.

Rails + AI: Build Smart Apps at Startup Speed Athira Ramanan live-coded an AI-powered PDF chatbot in Rails using OpenAI for document parsing and question answering. The session covered practical integration patterns, performance considerations, and avoiding overcomplication when adding AI to existing Rails apps.

Podcasts

The Ruby AI Podcast: You Can't Vibe-Code Trust: Why Real SaaS Still Wins in the AI Era Joe Leo and Valentino Stoll interviewed Kelly Sutton, CTO of Scholarly, about building a faculty information system for higher education. Kelly discussed using an admin MCP server to convert faculty handbooks into structured workflows and treating AI as an implementation detail rather than a feature in compliance-heavy environments.

Strictly From Nowhere: From Recession to Reinvention with Scott Werner Mike Rispoli interviewed Scott Werner, CEO of Sublayer and organizer of the Artificial Ruby NYC meetup. They discussed why Ruby's conciseness gives it an advantage over TypeScript for AI development, the volume advantage in agentic coding, and Scott's sci-fi newsletter exploring future software mechanics.

Remote Ruby: Heroku, Hosting, and the AI Era Chris Oliver and David Hill welcomed back Adam McCrea from Judoscale to discuss Heroku's uncertain future after Salesforce stopped taking new enterprise customers. The conversation covered what maintenance mode means for Rails developers, platform alternatives like Render, autoscaling, and building durable developer businesses in the AI era.

Latent Space: Retrieval After RAG: Hybrid Search, Agents, and Database Design Alessio Pando and Shawn Wang interviewed Simon Hørup Eskildsen, founder of Turbopuffer, about building a search engine on object storage that reduced Cursor's costs by 95%. Simon explained how agentic workloads are transforming search from single retrieval calls into massively parallel concurrent tool calls.

IndieRails: John Nunemaker - The Conductor Jeremy Smith and Jess Brown talked with John Nunemaker about managing his portfolio of Rails products including Flipper Cloud, Boxout, and Fireside. John discussed how AI has transformed his development workflow and reflected on the current opportunities for indie developers.

Ruby Türkiye: AI Coding Experiences, Claude Code Ruby LSP, Skills and More Episode 131 of the Turkish Ruby podcast covered Claude Code's Ruby LSP plugin support, Heroku AI integration for production deployments, and Thoughtbot's Claude Skill for generating Postman collections from Rails code.

Discussions

Intercom's Internal Claude Code Plugin System Brian Scanlan shared how Intercom built 13 Claude Code plugins with 100+ skills and hooks as a full-stack engineering platform. The thread revealed they self-host MCP servers for internal Rails tools with Okta auth, are auto-approving "safe" PRs, and use only 2% of the context window for their full engineering platform configuration.

Events

PLRUG: Get AI to Work in Complex Codebases Paweł Strzałkowski presented at the PLRUG Ruby Warsaw Meetup on strategies for making AI coding tools effective in large, complex codebases.

Boulder Ruby: Git Worktrees: Embrace the ADD Patrick Reagan demonstrated using Git worktrees for context switching and running AI agents on independent features in parallel. The talk showed how worktrees enable developers to pursue ideas that pop up mid-task without abandoning current work.

Upcoming

March 26th - Conference: RBQ Conf 2026 takes place March 26th and 27th in Austin, Texas. AI-related talks include Kinsey Durham Grace's keynote on building GitHub's coding agents and Chris Gratigny on lessons learned from a first AI implementation in Rails using the Anthropic API and RubyLLM, covering prompt versioning and tool calls.

April 9th - Conference: Tropical on Rails 2026 will be held on April 9th and 10th in São Paulo, Brazil. AI content includes Luiz Carvalho on DefGPT, an AI agent platform built on Rails; Rodrigo Serradura on why AI agents love Rails monoliths; and Paweł Strzałkowski on building a production-ready AI app with MCP and OAuth on Rails.

April 14th - Meetup: SF Ruby Meetup is meeting on April 14th at the Intercom office in San Francisco, and will feature Brian Scanlan on Intercom's use of Claude Code with a Rails focus.

April 17th - Conference: wroclove.rb 2026 on April 17th through the 19th in Wrocław, Poland. AI presentations includes Paweł Strzałkowski on building a production-ready AI app with MCP and OAuth on Rails; Nicolò Rebughini on accidentally building a neural network for Ruby product recommendations; and Adam Okoń on building agentic workflows in Ruby as a replacement for traditional forms.

April 22nd - Meetup: Artificial Ruby will be hosting a Ruby AI meetup on April 22nd at Betaworks in New York City.

April 22nd - Conference: RubyKaigi 2026 on April 22nd through the 24th in Hakodate, Japan. Ruby AI content includes Nate Berkopec on brute-forcing Ruby performance issues with LLMs, Koichi ITO on exploring RuboCop with MCP, and Justin Bowen on million-agent Ruby with Ractor-local GC in the age of AI.

April 30th - Conference: Blue Ridge Ruby 2026 on April 30th and May 1st in Asheville, North Carolina. The two AI speakers include David Paluy on LLM telemetry as a first-class Rails concern and Kevin Murphy on successful practices in an agentic world.

Open Source Updates

Code Spotlight

Chewy — AI Image & Video Generation in Your Terminal

A beautiful terminal UI for AI image and video generation with Stable Diffusion, FLUX, Wan, DALL-E, Imagen, and more. Run locally or connect to cloud providers.

chewytui.xyz

Aaron Dov Turkel released Chewy, a terminal UI for AI image and video generation built with Ruby's Charm ecosystem. The project supports 6 providers including local generation via stable diffusion with Metal GPU acceleration, plus cloud APIs from OpenAI, Gemini, and HuggingFace. Features include a model/LoRA browser with CivitAI integration, click-to-paint inpainting, AI prompt enhancement, Wan 2.1 video generation with in-terminal playback, and 10 color themes. As announced on Reddit, it installs via Homebrew and requires Ruby 4.0+.

Inboxed

The dev inbox. Capture SMTP, webhooks, and HTTP requests in one place. No third-party servers. No leak risks. Built for senior engineers.

inboxed.notdefined.dev

Adrian Castillo open sourced Inboxed, a self-hosted dev inbox for catching test emails, webhooks, and HTTP requests. Built with Rails 8, it includes an SMTP server, REST API with long-polling, real-time dashboard via ActionCable, and an MCP server with 15 tools that let AI agents extract OTPs, links, and webhook data. Compatible with Claude Code, Cursor, and n8n.

Multi-Gem Frameworks

This edition saw the release of three multi-gem AI frameworks:

LegionIO - Cognitive architecture framework for AI agents (200+ gems)

ACE - Agentic Coding Environment harness for AI coding agents (41 gems)

Spurline - Rails-inspired framework for AI agents (8 gems)

New Gems

Links to the RubyGems page, newest releases are first. Some obvious spam-related AI gems have been omitted.

aias - Schedule AIA prompts as cron jobs — no config file, just frontmatter

browserbeam - Official Ruby SDK for the Browserbeam API

ruby_llm-gitlab - GitLab AI Gateway provider for RubyLLM

ruby_llm-pollinations - Pollinations AI provider for RubyLLM

rubric_llm - Lightweight LLM evaluation framework for Ruby

mock_openai - A local mock server for OpenAI-compatible APIs

token-lens - Flame graphs for Claude Code token usage

i18n-context-generator - Extract translation context from source code using AI

ruby_llm-contract - Know which LLM model to use, what it costs, and when accuracy drops

ragify - RAG for Rails with pgvector and OpenAI

solid_agents - Database-backed Rails AI agent runtime bridge

google-apis-agentregistry_v1alpha - Simple REST client for Agent Registry API

ollama_agent - CLI agent that applies small code patches using Ollama tool calling

rails-ai-bridge - Give AI assistants deep, live knowledge of your Rails app via MCP

vivlio-starter-pdf - Advanced PDF processor for vivlio-starter using HexaPDF

superkick - Live context for AI coding agents

hinow-ai - Official Ruby SDK for the HINOW AI Inference API

e11y-devtools - Developer tools for E11y: TUI, Browser Overlay, MCP Server

mppx - Ruby implementation of the Machine Payments Protocol SDK

AIFaker - AI-powered, schema-aware Rails seeding

remitmd - remit.md - Universal payment protocol SDK for AI agents

your_ai_insight - AI-powered facility management dashboards & compliance reports

signalwire_agents - SignalWire AI Agents SDK

feather-ai - Identify birds from photos and audio using LLMs

yorishiro - CLI LLM agent with tool execution, MCP support, and provider backends

rails-ai-context - Give AI agents a complete mental model of your Rails app via MCP

zernio-sdk - Zernio API Ruby Gem

agentgif - CLI for AgentGIF - upload, manage, and share terminal GIFs

whoosh - AI-first Ruby API framework

humanizer-rb - Detect AI-generated writing patterns

faure - Agent codeur autonome GitLab CI/CD + backend OpenAI-compatible

ruby_llm-ups - ups.dev integration for RubyLLM

layered-assistant-rails - Open source, multi-provider, streaming AI assistant engine for Rails built on layered-ui-rails.

context.dev - Ruby library to access the Context Dev API

fosm-rails - Finite Object State Machine for Rails - declarative lifecycles for business objects

toolkami - Toolkami Ruby SDK for the local Rust daemon

jekyll-aeo - Answer Engine Optimization for Jekyll

html2md_mcp_client - Ruby client for the Model Context Protocol

sessionvision - Sessionvision analytics SDK for Ruby

ndav-numo-narray - N-Dimensional Array View for Numo::NArray

woods - Rails codebase extraction and indexing for AI-assisted development

bonchi - Git worktree manager

e2b - Ruby SDK for E2B sandbox API

rubyrlm - Recursive Language Models for Ruby

probatio_diabolica - DSL testing framework with classic and LLM-powered matchers

riteway - Unit tests that always supply a good bug report when they fail

coplan-engine - CoPlan - AI-assisted engineering design doc review

New Open Source

Links to the Github repository:

Rails Upgrade Assistant Skill - Claude Code skill that automates Rails version upgrades from 2.3 through 8.1, generating detection scripts, migration reports, and configuration previews based on 60,000+ hours of upgrade experience

MCP Rogue - Roguelike dungeon crawler where an AI plays the hero through Model Context Protocol, built with Rails 8 and Turbo Streams

Simulator LLM Pilot - AI-driven iOS E2E test runner from Automattic that executes plain-language Markdown test cases against iOS Simulator using Claude

Agent Harness - Multi-provider LLM agent framework with async runtime, Telegram bot integration, observability, and encrypted secrets management

Smith - Multi-agent orchestration framework built on RubyLLM with named states, transitions, budgets, guardrails, tool policy, and composable agent patterns

AI DevLog - Rails-powered developer knowledge base that uses AI to auto-summarize, tag, and embed code snippets and solutions, with RAG-based natural language search

Fizzy Agent Orchestrator - Rails engine that enables per-board and per-column AI agent configuration for Fizzy, using OpenClaw as the agent backend

Ruby LLM Eval - Behavioral evaluation framework for RubyLLM agents with multi-trial execution, deterministic and LLM-as-judge graders, and baseline regression detection

Personal Finance Agent - Connects to bank accounts via Plaid, runs spending analytics, and uses the Claude API to generate recommendations and reports

HermitClaw - AI agent runtime that embeds an AI character into your product with multi-channel support, 3-layer memory, and multi-model backends via RubyLLM

ErinOS Core - Local-first AI assistant with Ollama inference, voice I/O via Whisper and Kokoro, smart home skills, and Telegram/console channels powered by RubyLLM

Claude Hive - Web UI and CLI for running Claude Code agents in parallel with batch task management, result review, and agent-to-agent delegation via CLI

SessionLens - AI session visualizer that converts raw JSON logs from AI platforms into HTML reports with cost tracking, token metrics, and tool call auditing

RubyClaw - Self-hosted Telegram AI assistant with a ReAct agent loop, pluggable skills, multi-agent routing with delegation, and LLM adapters

AI Secretary - Slack integration that uses Claude Code CLI as a backend to provide multi-turn AI conversations with per-channel system prompts

Resilience - Mission operations console with real-time signal fusion, correlation rule engine, geospatial map view, audit log, and AI-assisted briefings via Claude

Hyperon Wiki MCP - MCP and CLI for the Hyperon Wiki Decko knowledge graph with role-based security, batch operations, CQL queries, and AI agent integration

Jobs & Opportunities

Are you an organization searching for an expert Ruby AI developer, or a Rubyist looking for your next development role with AI? Please reach out and let me know the type of opportunity you’re pursuing: matt@roboruby.com

Featured

Software Engineer: Ruby on Rails (Remote, US Based) DOPE Marketing CEO Dave Carroll announced hiring two AI-driven Ruby on Rails engineers ($110K-$140K) to help build their fully AI-integrated platform. Stack includes Rails, PostgreSQL, and React. Applicants must share a recent AI project. The bootstrapped $30M company provides unlimited token usage and dedicated AI tooling budget.

One Last Thing

Product-market fit methodology for early-stage devtool companies—Martian Chronicles, Evil Martians’ team blog

How do you measure product-market fit for a developer tool? A PMF scoring model from Evil Martians built on data from 37 devtools companies across AI, infrastructure, and cybersecurity. Five metrics, real benchmarks, and a dual score that tells you whether to invest in product or go-to-market.

evilmartians.com/chronicles/product-market-fit-methodology-devtools

Irina Nazarova of Evil Martians published Product-Market Fit Methodology for Devtools, a benchmark-driven PMF scoring system built from analyzing product metrics across 37 devtools companies including Cursor, Supabase, Datadog, and Stripe. The framework uses five observable metrics (time to first value, retention, NRR, free-to-paid conversion, and organic signups) to produce dual scores for product signal strength and revenue stage. As announced on Twitter/X, the interactive "PMF Compass" tool on the Evil Martians homepage lets founders input their metrics to diagnose whether they face a product problem or a distribution problem.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - March 12th, 2026

Matt Solt — Thu, 12 Mar 2026 17:12:09 +0000

Welcome to the 26th edition of Ruby AI News! This edition features the realization of Ruby’s AI superpowers, a safe “enclave” for running AI-generated Ruby code, how Autoresearch is the new Vibe in AI, and much more.

Read on the web

Top Stories
Need to Know AI News
Content
Events
- Previous
- Upcoming
Open Source Updates
Jobs & Opportunities
- Featured
One Last Thing

Need to Know AI News

Everything Is Context: Agentic File System Abstraction for Context Engineering A new paper proposed treating all AI context as files in a unified persistent repository, inspired by Unix's "everything is a file" philosophy. The framework includes three layers for history, memory, and scratchpad with token-aware compression.

Stop Calling Tools, Start Writing Code (Mode) Jeremiah Lowin introduced FastMCP 3.1's Code Mode, which replaces sequential MCP tool calls with sandboxed Python scripts that compose multiple tools in a single execution. This eliminates context bloat from large tool catalogs and reduces token waste from round-trip intermediate results.

Can AI Agents Build Real Stripe Integrations? Carol Liang and Kevin Ho of Stripe built a benchmark of real-world integration scenarios to test whether AI agents can autonomously construct Stripe payment integrations.

Impeccable Paul Bakaus released a design skills toolkit for AI coding assistants that provides commands like /polish, /audit, and /distill to give developers designer-level vocabulary when prompting.

QMD 2.0 Tobi Lütke released version 2.0 of his hybrid search tool that combines BM25, vector, and LLM-powered query expansion with local models. The update introduced a stable library interface, with the CLI, MCP server, and HTTP interfaces now built on top.

Content

Announcements

New RubyLLM Tailwind-based Chat UI

RubyLLM 1.13.0 Carmine Paolino released v1.13 with safer tool calls, explicit tool control via choice and calls parameters, structured output for Anthropic and Bedrock, and improved error handling with retries. Carmine also rewrote the Agentic Workflows guide using the new Agent DSL, covering sequential, routing, parallel, fan-out/fan-in, and RAG patterns in plain Ruby. And a Tailwind Chat UI generator is coming in 1.14!

Roast 1.0 Obie Fernandez announced the 1.0 release of Shopify's AI workflow framework, rebuilt around a Ruby DSL replacing the previous YAML configuration. The new version features composable "cogs" (chat, cmd, agent, ruby, map, repeat) for chaining multi-provider LLM workflows with parallel processing support.

ClaudeMemory v0.6.0 Valentino Stoll released a major update to his long-term memory gem for Claude Code, adding native vector search via sqlite-vec, async hooks, database maintenance commands, and comparative benchmarks showing it outperforms QMD on cross-category multi-fact reasoning queries.

Ruby LSP Plugin for Claude Code Omar Bahareth contributed the Ruby LSP plugin to Claude Code's official marketplace, enabling Claude Code to use Ruby LSP for language intelligence on Ruby files. The addition was noted on Reddit as a significant step for Ruby's AI tooling support.

AG-UI Protocol Ruby SDK Antonio Neto and the Buk team made a community Ruby SDK for the AG-UI Protocol, providing Sorbet-validated typed events, camel case serialization, and SSE-ready encoding for building agent-user interaction frontends in Ruby and Rails.

Zvec Ruby Dewayne VanHoozer released an embedded vector database gem wrapping a C++ engine via Rice bindings. It provides in-process vector storage and similarity search with HNSW/IVF/Flat indexes, filtered queries, and persistent on-disk storage without requiring an external database server.

KBS Decompiler Dewayne also added a YARV bytecode decompiler to the KBS rule engine gem, motivated by the need to inspect dynamically generated code in running processes. It reconstructs readable Ruby source from procs and lambdas by simulating the YARV stack machine.

Benchmarking Tool Pre-Filtering for RubyLLM Additionally, Dewayne benchmarked five Ruby approaches to pre-filtering LLM tools before passing them to RubyLLM: KBS (RETE), TF-IDF, Zvec, sqlite-vec, and LSI/SVD. LSI achieved the fastest filter time at 1ms using the classifier gem.

OpenTrace Ruby Adham El-Deeb released a Rails observability gem that auto-captures SQL queries, N+1 detections, view renders, ActiveJob events, and exceptions with built-in PII scrubbing. Data is sent to a self-hosted Go+SQLite server that exposes 75+ MCP tools, letting AI assistants like Claude Code query metrics and take actions such as resolving errors and setting alerts.

CovLoupe v5.0.0 Keith Bennett announced a major update to his SimpleCov coverage analysis toolkit with renamed MCP tool prefixes file_project_), single-letter CLI abbreviations, and a new screencast demonstrating the CLI, MCP integration with AI assistants, and CI gatekeeping features.

RailsForge Matt Quinto released a CLI toolkit that generates Rails components (services, queries, jobs, forms, policies), analyzes code for security and performance issues, and provides auto-refactoring that detects large controller actions and extracts service objects. Built as an AI-assisted development experiment.

Ariadna Jorge Alvarez and Mario Alvarez Navarro built a Ruby gem that structures Claude Code into a plan-execute-verify workflow for Rails projects, spawning specialized parallel agents for backend, frontend, and testing with persistent memory and wave-based concurrent execution.

Rails AI Kit Rohit Kushwaha announced an AI-first toolkit for Rails providing guardrails (toxicity detection, PII identification, prompt injection prevention) and vector classification using pgvector embeddings that requires no ML expertise to use.

Zuzu Abhishek Parolkar released a JRuby framework for building AI-native desktop apps that run entirely offline. It uses llamafile for local inference, a SQLite-backed sandboxed filesystem for agents, and ships as a single .jar for privacy-sensitive environments like healthcare and auditing.

Vibe on Rails Abhishek also launched a curated resource collecting articles, essays, talks, and community voices arguing that Rails is well-suited for AI development, citing convention-driven code generation, token efficiency, and two decades of quality training data in LLMs.

HiTank Alan Alves released a Ruby gem that manages Claude Code skills as installable packages. Each skill is pure Ruby using only stdlib, keeping token costs low. Includes 40+ integrations for Stripe, Jira, Slack, Heroku, and more.

Claude Console Bruno Bornsztein created a Ruby gem that lets developers pair with Claude directly inside Rails console. It shells out to Claude Code with console history as context, enabling natural language requests and iterative code execution without leaving the REPL.

Uberblick is an MCP-first Rails app for small teams that surfaces AI planning documents as shared specs. Product managers write requirements while developers use Claude Code or Cursor to generate implementation plans, building persistent institutional knowledge outside of ephemeral chat sessions.

BooRails Abraham Kuri released a set of security-focused Claude/Codex skills for auditing Rails applications. The scripts scan for XSS, SQL injection, CSRF, and command injection vulnerabilities while running diagnostics, safety checks, and quality gates before shipping.

Claude Skills Toolkit Sergey Moiseev released an updated version of his Claude Code plugin for creating, testing, and packaging skills. The update renamed skill-creator to skill-refiner and streamlined the interview process to avoid redundant questions.

Lapidary 蒼時弦也 introduced a Ruby knowledge graph builder that uses LLMs to extract contributor and maintainer relationships from bugs.ruby-lang.org issue discussions. Built with Falcon and SQLite, it visualizes Ruby community collaboration patterns via Cytoscape.js.

Rails Simplifier Mario Alberto Chávez released a Claude Code plugin that refactors Rails codebases toward 37signals's vanilla Rails philosophy. It converts service objects into model concerns, refactors custom actions into RESTful CRUD, detects N+1 queries, and enforces Rails conventions.

Mechanical Turk Trevor Turk launched an LLM-authored blog "by bots, for bots" to reduce the friction of sharing technical learnings. Topics include Ruby async with Falcon, mono-repo Rails architecture, Claude Code workflows, and AI agent permissions.

Rails Agent Server Andy Waite created a gem that lets AI agents execute Rails commands without the boot-time overhead of rails runner. It maintains a persistent background server via Unix sockets, delivering near-instant responses after initial startup.

OpenTIL: A Blogging Platform Built for AI Agents A Rails 8 platform where AI agents are the first author and humans are the editor. Agents autonomously discover and publish learning moments via skill injection and MCP protocol, with support for active recording, passive suggestions, and conversation extraction.

ru.Bee v2.7.0 Oleg added a built-in CLI assistant called "Bee" to his Puma-based Ruby web framework. The assistant is fed by the README and answers questions about the framework to help onboard new adopters. ru.Bee features contract-driven development, React integration, and WebSocket support.

Security for Rails Developers Greg Molnar, an OSCP-certified penetration tester, published his Rails security course with all video and text content now available. An AI security section is planned as a future addition.

Rage::Deferred Roman Samoilov announced zero-setup background job processing built into the Rage web process, eliminating the need for separate workers and message brokers. Jobs use fibers for concurrent execution and a write-ahead log for durability across server restarts. Very nice to quickly setup asynchronous AI agents.

Articles

Docker + Traefik + SSE: Managed AI Hosting Platform | Daniel Samer

Nginx silently breaks SSE. Docker CP refuses symlinks. Config crash loops at 2 AM. Post-mortem: building a managed hosting platform for AI agents. Real bugs.

clawhosters.com/blog/posts/building-managed-hosting-platform-tech-deep-dive

Building a Managed Hosting Platform: Tech Deep Dive Daniel Samer detailed the architecture of ClawHosters, a Rails 8 managed hosting platform for OpenClaw AI agents. The post covered Docker orchestration with Traefik routing, SSE streaming challenges across five proxy layers, per-token LLM billing, ZeroTier networking, and crash loop prevention for 50+ paying customers on Hetzner VPS instances.

Building a RAG Tool in Ruby Robby Russell walked through building Clarion, an internal CLI tool at Planet Argon that uses RAG to surface historical Jira context when analyzing tickets. The tool uses OpenAI embeddings with Pinecone, applies relationship boosting and temporal decay scoring, and integrates with Claude Code via MCP.

TDD and BDD in Ruby on Rails: How AI Is Changing the Game Georg Keferböck argued for test-first development in Rails, comparing RSpec, Minitest, and Cucumber while advocating "human-directed, AI-assisted testing" where AI handles edge-case discovery and scaffolding but developers retain responsibility for test strategy.

Building Semantic Search with AI and Vector Embedding in Rails Joao Gilberto Saraiva showcased implementing semantic search in Rails using RubyLLM, pgvector, and OpenAI embeddings. The tutorial covered chunking, batch embedding, hybrid scoring, and HNSW indexing without a separate vector database.

Why I Built Active Canvas Giovanni Panasiti introduced ActiveCanvas, a Rails engine that adds CMS capabilities directly into Rails apps with drag-and-drop page building via GrapeJS, AI-powered content generation, Tailwind CSS integration, and page versioning without requiring a separate CMS deployment.

Chat Bot Per-User Rate Limits Steve Polito demonstrated implementing per-user rate limiting for Rails chatbot applications using RubyLLM, Redis fixed-window tracking for both RPM and TPM, and a queue-based fallback with background job retries to prevent individual users from exhausting organizational API limits.

Cursor and Modern Rails: From Zero to Production Joseph Combs documented building a Rails 8 app from scratch to production using Cursor as an AI pair programmer. The walkthrough covered native auth, Minitest, Kamal deployment on Hetzner, Cloudflare DNS, Amazon SES email, and inbound email routing.

Rails Testing on Autopilot: Building an Agent That Writes What Developers Won't Maxime Langelier and Mathis Grosmaitre described how Mistral AI built an autonomous RSpec test generation agent using their Vibe coding assistant. The agent achieved 100% pass rate across 275 files through context engineering, file-type-specific skills, and SimpleCov-integrated self-correction loops.

Claude Code + Ruby LSP = Senior Dev Pairing Stéphane Paquet explained how Ruby LSP integration gives Claude Code IDE-level language intelligence including go-to-definition, references, type info, and diagnostics. This results in more accurate code understanding, lower token usage, and better handling of large Rails monorepos.

The Hidden Cost: AI's Time Complexity Trap Ender Ahmet Yurt warned that AI-generated code often contains hidden performance costs like O(N²) array operations, N+1 queries, and nested loop inefficiencies. The article included Ruby examples and a review checklist for catching these issues before they reach production.

Faster Bug Triaging with AI LLMs via MCP Enrico Teotti demonstrated using Claude Code with MCP-connected production database replicas to debug a Rails app. The AI agent diagnosed a comment ordering bug caused by missing ORDER BY clauses in minutes, though human oversight was needed to correct an initial misanalysis.

Building an AI Chat Agent with RubyLLM and Groq Henrique Cardoso de Faria built a conversational AI agent for his personal site using RubyLLM with Groq's free tier, streaming responses via Hotwire and Turbo Streams. The agent uses custom tool classes for search and content lookup, skipping RAG in favor of llms.txt.

Rails Audit Claude Skill Chard Gonzales released a Claude Code skill that performs comprehensive Rails application audits across code quality, security, testing, architecture, and performance. Invoked via /rails-audit, it generates PDF health reports with severity-scored findings and prioritized recommendations.

Neither Too Much nor Too Little: A Touch Base on the Current State of AI Giménez Silva Germán Alberto shared experiences testing AI tools while developing Ruby gems, finding them useful for brainstorming but unreliable for production code.

Dear Future Me: How to Write Code You Won't Hate in 6 Months Zil Norvilis outlined a documentation strategy for Rails developers, recommending a DECISIONS.md for technical choices, a SCRATCHPAD.md session journal, and commenting the "why" rather than the "what" to preserve context across sessions.

The Prompt Is the Least Important Part David Paluy launched part 1 of a 10-part series on Claude Cowork for knowledge workers, arguing that context files matter more than prompts. The article explained how three plain-text workspace files enable autonomous agents to deliver client-ready work from ten-word task descriptions.

Building with AI Agent Bots in Ruby on Rails Ravi Prakash wrote a step-by-step guide to integrating AI agent bots like OpenClaw and ClawdBot into Rails workflows for code generation, test writing, refactoring, and database analysis using service objects connected to AI agent APIs.

MCP Is Dead, Long Live the CLI Eric Holmes argued that MCP is unnecessary because LLMs already excel at using command-line tools. He notes CLI advantages in debuggability, composability, authentication, and operational simplicity over MCP servers that require background processes and JSON transport.

Open Source, SaaS, and the Silence After Unlimited Code Generation Scott Werner argued that AI code generation has broken open source feedback loops as the cost of self-sufficiency dropped below the cost of communication. Developers now fork and customize privately rather than contribute upstream, eliminating the signals maintainers rely on to improve their projects.

From Nodes to Stories: Fiction as a Tool for Thinking and The Long Freight Scott also launched Near Zero, a speculative fiction publication exploring a world where software development costs have collapsed. The companion story followed a software critic and safety reviewer navigating an economy where natural language precision replaced coding as the critical skill.

Software Is Never "Done" and ai-jail: Sandbox for AI Agents Fabio Akita used four personal projects to debunk the "one-shot prompt" myth, showing that post-deploy iteration is inevitable even with AI-generated code. In a companion post, he evolved his AI agent sandbox from a bash script into a proper tool using bubblewrap for system-level isolation of Claude Code and other agents.

I Built a Data Mining System for My Influencer Girlfriend Fabio also built a Rails and SQLite influencer analytics platform with LLM tool calling for autonomous database queries, Chrome headless scraping, Discord bot integration, YAML-based composable prompts, and scheduled jobs collecting metrics across social platforms.

Capybara Without the Browser Tax Sam Ruby proposed transpiling Ruby system tests to JavaScript and running them in jsdom via Vitest, eliminating Selenium overhead. The approach achieved a 5x speedup, arguing that system tests failed because of tooling, not the testing concept itself. Should be useful for running browser agents.

Generating Postman Collections with AI Sami Birnbaum introduced a Claude Code skill at Thoughtbot that automatically generates Postman API collections from Rails codebases by scanning controllers, routes, and RSpec request specs. The skill can be integrated into CI pipelines to keep API docs current without manual curation.

Quality You Can't Generate: AI Is Only as Good as Your Constraints Dave Mosher of Test Double argued that AI has commoditized code output, shifting value to the taste, judgment, and constraints developers encode into their systems, emphasizing designing architecture boundaries, tests, and feedback loops.

AI Made Writing Code Easier. It Made Being an Engineer Harder. Ivan Turkovic argued that AI tools silently raised output expectations while expanding engineer responsibilities. He cited studies showing 83% of workers reported AI increased their workload and 67% spend more time debugging AI-generated code than writing it.

Using Claude Code with Heroku AI Heroku published a guide for configuring Claude Code to use Heroku Managed Inference as a backend, covering addon setup, API token configuration, and environment variable settings to route Claude Code requests through Heroku's inference endpoint.

10 AI Prompts to Speed Your Team's Software Delivery Chandler Gibbons shared ten AI prompts targeting the 80% of software delivery beyond coding, covering code review, security scanning, documentation generation, epic breakdown, test coverage gaps, and pipeline debugging within GitLab's workflow.

Videos

How to Setup a Code Mode MCP Server for Your API with Stainless CJ Avilla of Stainless walked through generating a code mode MCP server from an OpenAPI spec, connecting it to Claude Code, and deploying a hosted MCP endpoint. The tutorial demonstrated how code mode enables multi-step API workflows in a single execution with less context clutter than one-tool-per-endpoint approaches.

CovLoupe: Semantic Querying of SimpleCov Ruby Test Coverage Data Plus CI Gatekeeping Keith Bennett demonstrated CovLoupe, a tool for semantically querying SimpleCov coverage data via MCP server, CLI, or Ruby library. He showed how AI assistants can analyze code coverage and how custom validation criteria can enforce minimum test coverage in CI pipelines.

Hello World: Our AI App Generator Comes to Life Thoughtbot's Chad Pytel and Rob Whittaker livestreamed building ReadySetGo, an AI-powered Rails app generator that takes an app idea, scaffolds a new Rails application using Suspenders with Clearance and Roux, then uses an LLM to build out a unique feature complete with tests.

Podcasts

The Ruby AI Podcast: CRMs Don't Have to Suck: Rebuilding Business Software with AI and Ruby Joe Leo and Valentino Stoll interviewed Thomas Witt about building an AI-native CRM where conversations replace rigid form fields as the primary data source. Discussion covered hybrid vector search with OpenSearch, async Ruby with Falcon, multi-model LLM orchestration, and prompt tracing with Langfuse.

Rails Business: John Nunemaker on AI Development Brendan Buckingham and Ryan Frisch interviewed John Nunemaker about his team's AI workflow including Claude Code reviews before PRs, an internal knowledge system built, and isolated worktrees with Conductor for parallel development. John also wrote a companion blog post summarizing his recommendations for tech leaders adopting AI tooling.

Strictly From Nowhere: Building Better Software with Rails Mike Rispoli interviewed Evil Martians CEO Irina Nazarova about the Rails renaissance driven by AI and agentic coding, how AnyCable monetizes open source infrastructure, and why smaller teams can now be more ambitious.

The Pragmatic Engineer: Mitchell Hashimoto's New Way of Writing Code Gergely Orosz interviewed the HashiCorp co-founder and Ghostty creator about constantly running AI agents in the background for research while coding. Mitchell discussed why open source is shifting from "default trust" to "default deny" and why Git and GitHub may need redesigning for the agentic era.

The Opinionated Thoughtbotter: Linting Is Non-Negotiable Svenja Schäfer and Rémy Hannenquin discussed team code consistency through automated linting, formatting entire codebases at once, naming "time bombs," and maintaining PR review sanity.

Newsletters

Static Ruby Monthly Issue 14, March 2026 Andrey Eremin discussed how static typing has become essential infrastructure for AI-assisted Ruby development. Highlights included Stripe's Minions agents using Sorbet types, experimental type systems like T-Ruby and Typewriter, and MCP tools like rails_mcp_engine that feed type information to AI agents.

FastRuby.io News issues #147 and #146 The FastRuby team covered test suite optimization, 37signals' Upright monitoring tool, Ruby 3.2 EOL, Heroku's shift to sustaining engineering, Delayed Job to Solid Queue migration, RubyLLM agents, prompt caching, and RubyConf 2026 tickets going on sale.

RubyCrow Alex Kovalevsky launched a community-powered Ruby and Rails newsletter that automatically syncs RSS feeds from hundreds of registered blogs. The weekly digest features a Crow's Pick standout article, newly released gems, and community discussions with zero filler or tracking.

Pragmatic Programmers Newsletter Dave Thomas reframed the Luddite movement, arguing they weren't anti-technology but sought proper training during transitions. He urged AI developers to enhance human capabilities rather than replace workers, drawing parallels between mechanical knitting machines and modern AI adoption.

Discussions

Is Anyone Doing True TDD with AI for Ruby on Rails Projects? Marc Köhlbrugge asked the Ruby on Rails community whether writing tests first with AI produces better results than writing tests after, sparking a discussion with 26 replies on the topic of AI-assisted test-driven development workflows.

AI: How to Adapt or Die A Ruby developer asked Reddit’s r/ruby how teams are using Claude and similar tools in day-to-day engineering work. The 77-comment thread revealed a spectrum from developers who haven't written a line of code manually all year to those using AI only for commit messages and pre-review checks.

Current State of How I Use AI as an Engineer Adrian Marin (Avo HQ) shared his four-week AI workflow combining Claude Code with tweaked CLAUDE.md files and a pseudo-monorepo pattern, Cursor for completions and Bugbot PR reviews, and Chief for large PRD-style tasks with Ralph loops.

Events

Artificial Ruby: Chaos to the Rescue Valentino Stoll pushed the boundaries of Ruby by hooking it up to the meta-generator it was built for with chaos_to_the_rescue, a Ruby gem that uses RubyLLM to dynamically generate missing methods and provide AI-powered fix suggestions for Rails exceptions in development.

Artificial Ruby: Realtime AI Agents in Ruby Also at the Artificial Ruby February meetup, Andrew Denta walked through his open source Pokemon-playing AI agent built in Ruby, discussing the challenges of implementing realtime AI agent interactions.

SF Ruby: January 2026 Meetup at Persona SF Ruby hosted talks by Samuel Giddins on Ruby object performance optimization, Enrique Mogollán on fixing nil-related bugs, Vitor Oliveira on what to expect from Ruby 4.0, and Todd Kummer on customizing Rails form and tag helpers.

SF Ruby: February 2026 Meetup at Sentry SF Ruby hosted talks by Neil Manvar introducing Sentry Seer, Sohil Kshirsagar on why coding agents need a harness, Mike Dalton on turning images into calendar events with AI, and Vladimir Dementyev on whether architecture still matters when AI writes the code.

Ruby Australia: Moving from RSpec to Minitest for an AI-Friendly Codebase Alex Finkel discussed rewriting a production test suite from RSpec to Minitest to make it cleaner, more discoverable, and better suited for AI-assisted development.

RubyConf Thailand: Making Canvas Prints from Artwork Photos: Pipeline Constraints and Upscaling Models Alex Timofeev presented at RubyConf TH 2026 on building an image processing pipeline for converting artwork photos into canvas print-ready formats, covering pipeline constraints and AI upscaling models.

Upcoming

March 13th - Virtual: From Prompt to Production: What is Agentic Engineering? Reinteractive announced a virtual webinar on March 13th from 11am to 12pm AEDT with Kane Hooper and Errol Schmidt covering how Rails reduces AI token waste and creates blueprints for agents, defensive coding with guardrails, and shipping from concept to live URL in 48 hours.

March 13th - Conference: The Ruby Community Conference Winter 2026 in Cracow, Poland will have a heavy focus on Ruby and AI, with presentations and workshops including:

Obie Fernandez: Ruby & AI Conversation
Irina Nazarova: Startups on Rails and AI Integration Patterns
Carmine Paolino: Building AI Apps in Ruby and Rails with RubyLLM
Paweł Strzałkowski: Model Context Protocol in Ruby on Rails

March 15th - Hackathon: The Big Philly Meetup MashUp Indy Hall announced a one-day hackathon on March 15th in Philadelphia themed "Good Neighbors," bringing together nineteen local meetup communities including Philly.rb to build projects that improve the city, with teams judged on creativity and Supabase usage.

March 25th - Meetup: Artificial Ruby is hosting a Ruby AI meetup on March 25th at Betaworks in New York City. If you are interested in speaking at the event, please fill out this form.

April 9th - Conference: Tropical on Rails 2026 on April 9th and 10th in São Paulo, Brazil. AI content includes Luiz Carvalho on DefGPT, an AI agent platform built on Rails; Rodrigo Serradura on why AI agents love Rails monoliths; and Paweł Strzałkowski on building a production-ready AI app with MCP and OAuth on Rails.

Open Source Updates

Code Spotlight

https://github.com/mrjonesbot/sage

Nathan Jones’s Sage is a Rails engine that adds LLM-powered natural language reporting on top of Blazer. Sage translates plain English requests into SQL queries using Anthropic Claude or OpenAI, with database schema introspection and Rails model scope awareness for more accurate query generation. Requires Rails 7.1+ with Turbo and Stimulus.

New Gems

Links to the RubyGems page, newest releases are first. Due to an influx of low quality submissions to RubyGems the past few weeks, over 90 spam AI-related gems have been omitted from this edition.

skillrouter - Official Ruby client for the SkillRouter API

rails_agent_server - Persistent Rails server for AI agents that avoids boot overhead for repeated queries

orkestr - Rails Engine for workflow orchestration

oopsie-ruby - Ruby client for Oopsie error reporting

langdetect-ruby - Language detection for Ruby using n-gram profiles

loader-ruby - Document loader library for Ruby RAG pipelines

prompter-ruby - Prompt template engine for Ruby

ner-ruby - Named Entity Recognition for Ruby using ONNX models

keyword-ruby - Keyword extraction for Ruby using RAKE, YAKE, and TF-IDF

gorgias-ruby - Ruby client for the Gorgias REST API

claude-matrix - Privacy-first TUI analytics dashboard for Claude Code

trafilatura - Extract readable content, comments, and metadata from web pages

onnxruntime-torch-tensor - Torch::Tensor support for ONNX Runtime

rails_console_ai - AI-powered Rails console assistant

kakugosearch-rails - Rails integration for the KakugoSearch AI-enhanced search engine

ndav-torch-tensor - N-Dimensional Array View for Torch::Tensors

ndav-ort_value - OnnxRuntime extension for MemoryView exporters and pointers

ndav - N-Dimensional Array View

sastrawi-ruby - Indonesian language stemmer for Ruby

altertable - Altertable Product Analytics Ruby SDK

gemlings - Code-first AI agent framework for Ruby

ai_sentinel - Lightweight AI task scheduler with conditional actions

opa-ruby - A Ruby library for generating Open Prompt Archive (OPA) files

uncaught - Local-first, AI-ready error monitoring for Ruby

reranker-ruby - Cross-encoder reranking for Ruby RAG pipelines

eval-ruby - Evaluation framework for LLM and RAG applications in Ruby

guardrails-ruby - Input/output validation and safety framework for LLM applications

smart_brain - Agent memory runtime and context composer

rag-ruby - RAG pipeline framework for Ruby and Rails

onnx-ruby - Ruby bindings for ONNX Runtime

smart_rag - A hybrid RAG system with vector and full-text search

agentf - Ruby multi-agent workflow engine with Redis memory

jrubyagents - A radically simple, code-first AI agent framework for Ruby & JRuby

duckdb-polars - This module provides Polars table adapter for duckdb

rails_ai_kit - AI-first toolkit for Rails: embeddings, vector search, and classification

chunker-ruby - Text chunking/splitting library for Ruby, designed for RAG pipelines

tokenizer-ruby - Ruby bindings for HuggingFace tokenizers

pattern-ruby - Deterministic pattern detection and intent matching engine for Ruby

zvec-ruby - Ruby bindings for zvec vector database

jekyll-third-audience - Generate clean Markdown versions of Jekyll posts for AI agents

omaship - Omaship command-line interface

anima-core - A personal AI agent with desires, personality, and personal growth

xero-apimatic-sdk - SDK for Xero by APIMatic

lara-sdk - Official Lara SDK for Ruby

claude-agent-server - HTTP server wrapping the Claude Agent Ruby SDK

collavre_completion_api - OpenAI-compatible chat completions API for Collavre

zuzu - JRuby framework for AI-native desktop apps

rails_mcp_code_search - Semantic codebase search for Claude Code via MCP

baid - CLI for Baid - AI agent skill management for development teams

hindsight-ruby - Standalone Hindsight API client for Ruby

pylonite - SQLite-backed kanban board for agents and humans

hitank - Claude Code skills written in Ruby

skillme - Claude Code skills written in Ruby

superthread - Unofficial Ruby client and CLI for Superthread project management

traductor - AI-powered locale file translator for Ruby applications

onde-inference - On-device AI inference for Ruby, powered by Rust

agentic-guild - Reserved for agentic:guild

tomos - Token-aware text chunking for RAG pipelines, powered by Rust

ruby-ai-gem-context - Generate AI context files for Ruby projects

nanobot - Ultra-lightweight personal AI assistant framework

claw-tools - OpenClaw Skills & MCP

cm-cli - CLI tool for pulling Claude Skill and MCP resources

searxng - SearXNG Ruby client and MCP server

driftgate-sdk - DriftGate canonical V4 envelope SDK

datagrout-conduit - MCP client with mTLS, OAuth 2.1, and semantic discovery

girb-mcp - MCP server for Ruby runtime debugging

seedream6-ai - Seedream 6.0 AI image generator

copilot3d-ai - Copilot 3D platform for AI 3D generation

bingimagecreator-ai - Bing Image Generator for AI image creation

seedance3-ai - Seedance 3.0 AI video generator

acp_ruby - Ruby SDK for the Agent Client Protocol (ACP)

rubycode_agent - Deterministic AI-powered code modification agent

ares-runtime - Deterministic Multi-Agent Orchestrator

mddir - Local personal knowledge base - save web pages as markdown

mentant - Mentant: Secure Rails agent

rubycode - AI coding assistant with autonomous task execution

agentmail - Lightweight Ruby client for the AgentMail API

mlld - Ruby wrapper for the mlld CLI

claude_console - Pair with Claude Code in your Rails console

mlx-ruby-lm - LLM inference and fine-tuning on MLX for Ruby

ocak - Autonomous GitHub issue processing pipeline using Claude Code

console_agent - AI-powered Rails console assistant

codebase_index - Rails codebase extraction and indexing for AI-assisted development

zvec - Ruby bindings for Alibaba zvec vector database

llm_meta_client - Engine for integrating multiple LLM providers into your application

flowengine-cli - Terminal-based interactive wizard runner for FlowEngine flows

flowengine - Declarative flow engine for building rules-driven wizards and intake forms

torchcodec - Media encoding and decoding for Torch.rb

enclave - Sandboxed Ruby for AI agents

active_canvas - A mountable Rails CMS engine for managing static pages

searchapi-ruby - Ruby client for SearchAPI.io - 49 search engines in one gem

chat_manager - Rails engine for managing LLM chat conversations with CSV export and auto-titling

prompt_navigator - Rails engine for managing and visualizing LLM prompt execution history.

action_prompter - Rails-native conventions for integrating Large Language Models

New Open Source

Links to the Github repository:

PatchCaptain - Rails gem that automatically captures exceptions and generates GitHub pull requests with AI-proposed fixes

Rails Markup - Point-and-click annotation tool that lets users highlight view elements in the browser and route feedback to AI agents via MCP

rubocop-harness - Custom RuboCop rules enforcing architectural patterns with fix instructions readable by AI coding agents

Riteway Ruby - Testing library enforcing simple, readable, and explicit unit tests optimized for AI-driven development

MFP Basecamp - Comprehensive MCP server providing 146 tools covering the entire Basecamp 4 API surface for use with AI clients

Ruby Voice Agent - Demo application for building conversational voice agents using Deepgram's Voice Agent API

Budget AI - Personal finance app that imports transactions from Emma via Google Sheets and provides AI-powered insights through a local LLM

AI Search Assistant - Secure AI-powered search assistant with structured tool calling, a tool registry, multi-step agent loops, and prompt injection mitigation

Wayfinder - Rails 8 app that ingests family and school artifacts, runs AI-powered extraction and classification, and exposes a child artifact timeline

Project Tracker - Claude Code autonomous agent system with a dashboard, MCP server, and cron orchestrator for managing development work

Anchor - Web app that deploys GitHub repositories to Google Cloud Run with automatic framework detection and AI-powered repo analysis

LocalVault - CLI secrets manager that stores encrypted credentials locally with an MCP server for AI agent access

Guild Board - AI-powered Kanban board where human developers and AI coding agents collaborate on shared project tasks through an MCP server interface

Jobs & Opportunities

Featured

AI Operations Engineer at Veracross Veracross is hiring their first AI Platform Engineer to build agentic AI products for K-12 school operations. The role involves integrating AI into Ruby on Rails applications, operating LLM systems on AWS Bedrock, and designing safety guardrails for EdTech. Fully remote.

One Last Thing

World Monitor - Real-Time Global Intelligence Dashboard

Real-time global intelligence dashboard with live news, markets, military tracking, infrastructure monitoring, and geopolitical data. OSINT in one view.

www.worldmonitor.app

Elie Habib released World Monitor, an open-source real-time global intelligence dashboard built with TypeScript. The app aggregates 435+ news feeds across 15 categories into a unified interface with interactive 3D/2D maps, 45 toggleable data layers, and AI-synthesized briefs. AI features include LLM-powered world briefs with local Ollama support, geopolitical deduction and forecasting grounded in live headlines, and a browser-local RAG system using ONNX embeddings for semantic headline queries. Available as a web app, PWA, and native desktop app for macOS, Windows, and Linux.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - February 26th, 2026

Matt Solt — Thu, 26 Feb 2026 13:00:00 +0000

Welcome to the 25th edition of Ruby AI News! This edition features Code Mode, Bombing mode, and NSFW mode. But more importantly, its time for build mode.

I will be presenting Introduction to Generative AI Programming with RubyLLM on March 7th, 2026 at CultureWorks Greater Philadelphia, if you’re in the area, I encourage you to check it out.

Read on the web

Top Stories
Need to Know AI News
Content
Events
- Previous
- Upcoming
Open Source Updates
Jobs & Opportunities
- Featured

Need to Know AI News

The Complete Guide to Building Skills for Claude Anthropic published a guide covering how to build skills that teach Claude repeatable workflows across three categories: document creation, workflow automation, and MCP enhancement, with patterns for testing, iteration, and distribution.

WebMCP Is Available for Early Preview André Cipriani Bandarra announced a proposed standard that enables websites to expose structured tools for AI agents through declarative HTML forms.

Making Wolfram Tech Available as a Foundation Tool for LLM Systems Stephen Wolfram announced Computation-Augmented Generation, making Wolfram's computational platform available to LLMs through three access methods: an MCP service, a unified Agent API, and fine-grained CAG Component for custom integration.

Introducing Markdown for Agents Cloudflare announced that their network now supports real-time content conversion to Markdown at the source using content negotiation headers, treating AI agents as first-class citizens alongside human visitors.

A Guide to Which AI to Use in the Agentic Era Ethan Mollick introduced a framework for selecting AI tools that distinguishes between models, apps, and harnesses, arguing that agents which autonomously complete multi-step tasks are fundamentally more valuable than chatbot conversations.

Content

Announcements

RubyLLM::Agents v3.7 Adham El-Deeb updated the Rails engine with a middleware pipeline for tenant resolution, budget enforcement, caching, a mountable dashboard with cost charts and execution tracking, and an eval framework for benchmarking agents with scorers.

MLX Ruby Alex Skryl released Ruby bindings for Apple's MLX array framework, bringing NumPy-like operations, automatic differentiation, neural network layers, and Metal GPU acceleration to Ruby with performance within 25% of the Python bindings. With the ONNX + WebGPU update, Alex also added ONNX export and WebGPU browser harness generation to run ML models in the browser.

WebMCP-Rails Jesse Waites released a Rails gem that extends form helpers with WebMCP support, a new standard that lets websites expose HTML forms as structured tools for AI agents. The gem adds a webmcp: option to form_with and input helpers to annotate forms with tool names, descriptions, and parameter metadata.

Real World Rails Steve Clarke published a curated collection of 200+ open source Rails applications as git submodules, designed for developers and AI coding agents to research architectural patterns across production codebases. The repo includes a Claude Code skill for querying all apps simultaneously.

RubyLLM::MCP v1.0.0 Patrick Vice released v1.0 of the MCP client for RubyLLM, supporting tools, resources, prompts, OAuth authentication, client interactivity, and an adapter pattern compatible with the official MCP gem. The release adds MCP extensions, JRuby support, and hardened transports for building AI agents.

Recuerd0 Mario Chavez launched a context management tool for dev teams that serves curated project knowledge to AI coding tools via REST API. Built with Rails 8, SQLite, and Solid Queue, it uses full-text search instead of embeddings, with self-hosting available under the O’SASSY license.

RuboCop MCP Server Koichi ITO added a built-in MCP server to RuboCop, enabling AI coding agents to invoke analysis and autocorrection as structured tools via the official MCP Ruby SDK. [h/t to Short Ruby News for surfacing this.]

RapidRails Ahmed Nadar launched Rapidfy, an agentic CLI that generates full Rails 8 applications using ViewComponents with Turbo and Stimulus. The tool generates models, controllers, migrations, and UI for apps, positioning itself as a Rails-native alternative to v0 and Lovable.

Hotwire Club AI Tooling Now Open Source Julian Rubisch open-sourced The Hotwire Club's AI tooling: an agentic skills pack providing six Claude skills for Hotwire patterns extracted from 45+ tutorials, and an MCP server for searching the Hotwire Club knowledge base.

Awesome Ruby AI Extended Saroj Maharjan published a curated list of Ruby AI/ML resources including API clients, agent frameworks, RAG/embeddings, MCP tools, and learning resources.

Daily Vibe Valentino Stoll launched a Rails app that gathers local news for cities worldwide, analyzes sentiment, and generates AI-created artwork and songs with lyrics to match each day's mood.

LLM.rb v4.1.0 Robert (0x1eef) announced a new release of the zero-dependency Ruby toolkit for LLMs. The gem provides chat with streaming, tool calling, structured output, multimodal input, embeddings, audio, image generation, and stateful agent sessions.

VibeRails Brendan Carroll launched an AI-powered full-codebase review tool with Ruby support that scans projects file-by-file across detection categories including security, performance, and maintainability.

Rails Diff MCP Server Alex Zeitler released an MCP server that exposes Rails version diffs as tools, allowing AI agents to list versions, compare file changes, and retrieve patches between any two Rails releases. The server is meant to pair well with Claude Code skills like skill-rails-upgrade for AI-assisted Rails upgrades.

News Curator Ashish Rao built a Ruby application that uses Claude to automatically curate news, fetching articles from GNews and selecting the top 2 most significant stories on foreign policy and diplomacy. The tool includes MCP for a /news command in Claude Code, a feedback loop for improving selections, and scheduled runs.

Rails + Claude Code Is a Crazy Unlock Irina Nazarova built Evil Martians' internal planning, HR, and financial system in two weeks using Rails, SQLite, Claude Code, and Vladimir Dementyev's Layered Rails skills, arguing that Rails' convention-over-configuration approach gives LLMs a compound advantage.

Code on Incus Maciej Mensfeld updated his container runtime for sandboxing AI coding agents in isolated Incus containers with session persistence, network filtering, and multi-slot parallel sessions. The latest changes add anomaly detection with automatic container pausing, network monitoring, and OpenCode support.

RubyOnVibes Eric Arnold launched the beta of a Rails-native cloud vibecoding platform that generates full-stack web applications from chat descriptions, with built-in authentication, payments, file storage, and deployment to live HTTPS URLs.

Splitwise MCP Aman Kumar built a Ruby MCP server exposing Splitwise API operations, enabling AI assistants to manage expenses, groups, and friends through natural language. The server supports receipt image parsing, fuzzy name matching, and built-in arithmetic tools to prevent hallucinated calculations when splitting bills.

Add to_markdown to Action Text Mike Dalessio submitted a PR for markdown conversion for Action Text, mirroring to_plain_text, motivated by HTML being verbose for LLM agents.

Vanilla Rails Skills for Claude Code Iuhoay released a collection of Claude Code skills for Rails development including vanilla-rails for designing apps the Basecamp way with thin controllers and rich models, plus rails-deps for dependency management and ruby-lsp integration.

TaskYou Bruno Bornsztein released a Kanban board for managing AI coding agents running in parallel via git worktrees and tmux. The worktree setup allows Rails apps to run multiple tasks in parallel with isolated databases and ports.

How I Became a (Rails) One-Man App Studio A reddit user shared a portable Rails AI Playbook living in ~/.claude/ that starts each project with a 15-question interview, generates structured documentation, and produces a phased roadmap for Claude Code to execute across a Rails/Inertia/React stack.

Learn Ruby & IDE - CoddyKit Mehmet Canker released an Android app for learning Ruby with AI-powered tutoring, two built-in Ruby editors, an integrated compiler, and a structured curriculum from basics to advanced topics including Rails.

Articles

Ruby Is the Best Language for Building AI Apps Carmine Paolino argued that most AI app development is web engineering not model training, making Ruby and Rails a better fit than Python, citing RubyLLM's simpler API compared to LangChain, Rails' full product stack, and Ruby's fiber-based concurrency for network-bound LLM workloads.

RubyLLM 1.12: Agents Are Just LLMs with Tools Carmine also introduced a class-based Agent DSL for defining reusable agents with declarative model, tools, and temperature settings, plus Rails-backed persistence, ERB prompt templates in app/prompts/, and AWS Bedrock and Azure Foundry support. [New Agentic Docs]

AI Agent Orchestration on Rails Jesse Waites described building Jarvis, a Rails platform where an orchestrator agent delegates tasks to specialized sub-agents with constrained tool access using RubyLLM, Hotwire for real-time updates, and Solid Queue for background jobs.

Introducing Agent Gateway for Ruby on Rails Jesse also released Agent Gateway, a Rails engine that gives AI agents secure, read-only access to production data through a single JSON endpoint with two-layer authentication and an allowlist DSL for declaring which models, fields, and aggregations to expose.

As Complexity Grows, Architecture Dominates Material Scott Werner argued that AI agent chains multiply failure rates and proposed "prompt objects" where recovery emerges from arrangement rather than explicit error handling, demonstrating the approach with an ARC-AGI solver using Claude Haiku 4.5.

The Great Zipper of Capitalism Scott additionally explored how falling AI development costs enable hyper-niche software, illustrating with "Where Is Everyone," a tool he built for the Artificial Ruby community to track attendance patterns across Luma and Mailchimp after his meetup unexpectedly grew from 20 to 60 attendees.

Agents as Teammates at ZAR Obie Fernandez described deploying autonomous AI agents as full organizational participants, built on knowledge graph and agent orchestration Rails apps. Agents autonomously triage production errors, clean technical debt, and communicate via Slack with their own identities and budgets.

It Might Be Time to Say Goodbye to HTML Inputs Obie also wrote about replacing all create and edit forms in a Rails app with MCP prompt bubbles that users paste into Claude Code, turning the web interface into a read-only layer updated in real time via Turbo Streams.

AI Agents in Ruby: Why Is It So Easy? Fernando Martinez argued that Ruby's expressiveness makes it ideal for AI agent development and demonstrated with Detritus, a 250-line coding agent built with RubyLLM featuring file editing, bash commands, web search, and subagent tools.

Evaluating LLM Prompts in Rails Patricio Mac Adden introduced RubyLLM::Evals, a Rails engine for testing, comparing, and improving LLM prompts with support for exact match, regex, LLM judges, and human judge evaluation types, plus integration with RubyLLM::Monitoring for production tracking.

SchnellMCP: Ruby Native MCP Server Experience Josef Šimánek created SchnellMCP, a Ruby library that transforms YARD-documented methods into MCP servers by adding a single @mcp.tool annotation, enabling the same Ruby script to serve as an MCP server for AI assistants, a CLI tool, and a library.

From Context Engineering to Recuerd0 Mario Alberto Chávez described how maintaining layered documentation across multiple tools for AI-assisted development led him to build Recuerd0, a versioned knowledge base server built on Rails 8 with SQLite FTS5 that centralizes project context for AI tools via a REST API.

Your AI Has No Memory. Your Rails Codebase Does. Marcin Ostrowski used the film Memento as a metaphor for how AI coding assistants start fresh each session, arguing that well-documented Rails conventions serve as "tattoos" that guide AI toward consistent, maintainable code.

My Tmux + Rails + AI TUIs Development Setup Alexander Zeitler shared his tmuxinator configuration for Rails development with dedicated windows for dev server, Neovim, Rails & Kamal, the opencode AI agent TUI, and sqlite database management.

How I Built 60-Second VPS Provisioning for OpenClaw Hosting Daniel Samer detailed building ClawHosters, a managed hosting platform for the OpenClaw AI agent framework, using Rails with pre-baked Hetzner snapshots and a prewarmed VPS pool to achieve sub-60-second provisioning.

ActiveRecord Neighbor Vector Search with Per-Document Max Jonathan Rochkind solved the RAG document diversity problem using PostgreSQL CTEs with the neighbor gem, applying ROW_NUMBER() window functions partitioned by document to limit vector search results to a maximum number of chunks per source document.

I Didn't Want AI to Be Good at This Robby Russell argued that AI-assisted development has made custom builds economically viable where SaaS previously dominated, illustrating with a Slackbot replacement built in half a day and a custom band CRM handling unstructured data.

From 6 Codebases to 1: How We Rebuilt PrayAI on Rails 8 + Turbo Native Jonathan Spooner rebuilt PrayAI, an AI-powered prayer app using GPT-4 mini, from four repositories with 15+ services and 35,000 lines of CloudFormation code into a single Rails 8 app with Turbo Native, SQLite, and 184 lines of infrastructure code.

Checkset: A Ruby Gem for Repeatable Verifications Using Playwright Andrea Fomera released Checkset, a Ruby gem for running repeatable browser-based verification checks against development, staging, and production environments using Playwright, with support for AI-assisted checks via Claude with Playwright MCP.

Setting Up Your Ruby on Rails Monolith for AI Development Colin Soleim outlined five strategies for preparing large Rails monoliths to work with AI coding tools: namespace-level .context.md files, fast test feedback with Guard, incremental Sorbet type annotations, Replit sandboxes for design iteration, and service object architecture with explicit interfaces.

AI Coding Assistants for Rails: What Actually Works and What Wastes Your Time Roger Heykoop shared a practical evaluation after six months of using Copilot, Cursor, and Claude with Rails. Test generation showed the highest impact while complex ActiveRecord queries, business logic, and security-sensitive code remained unreliable, with effectiveness correlating to how conventional the task is.

How I Went from One Button to Building Entire Rails Apps in 10 Seconds Ahmed Nadar described building Rapidfy, an AI agent trained on his RapidRails component library that generates complete Rails 8 applications with models, migrations, and Turbo/Stimulus UI in about 10 seconds from a prompt.

FrankMega: A Self-Hosted Mega Clone Built with Rails 8 in One Day Fabio Akita built a self-hosted file sharing service with Rails and Claude Code in 3 hours. Fabio argued that "AI is the mirror of your own competence," detailing the security fixes the initial AI-generated code required including OTP replay attacks and race conditions.

Stop Overcomplicating Claude Code: 3 Rules That Actually Work Vince Canger distilled effective Claude Code usage into three rules: full-stack debugging visibility, LLM-friendly documentation via llms.txt files (which use less context than MCP servers), and opinionated framework selection including Rails.

How I Came to Understand the 100x Claim Brandon Casci described building an agent orchestration system to manage multiple codebases including Rails deployments and a litestream-ruby fork. Brandon concluded the gains aren't literally 100x but make solo operation of multiple production systems feasible.

The Four Most Common Security Risks When Vibe Coding Your App Nina Torgunakova identified exposed API keys, weak authentication, insecure dependencies, and unvalidated user inputs as the top security vulnerabilities in vibe-coded applications, with practical mitigations for each.

Neither Too Much nor Too Little: A Touch Base on the Current State of AI Giménez Silva Germán Alberto presented a balanced critique of AI's probabilistic nature, noting that while testing multiple LLMs during Ruby gem development, AI worked for brainstorming and prototyping but rarely produced production-ready code.

Ruby on Whales: Dockerizing Ruby and Rails Development Vladimir Dementyev and Travis Turner updated their Docker development environment guide, replacing Webpacker with Vite and adding Claude Code CLI integration that runs inside the container with access limited to project files.

Getting Nondeterministic Agents into Deterministic Guardrails Łukasz Reszke described using automated workflows and pre-commit hooks to constrain AI agents working on a legacy Rails codebase, running checks through a /verify command that provides structured feedback when agents ignore instructions.

The Death of the Software Craftsman David Bryant Copeland argued that AI code generation challenges the value of traditional software craftsmanship since stakeholders only care about outcomes. David outlined three paths forward: rejecting AI tools entirely, going all-in, or positioning as a specialist who understands AI's gaps.

Claude Code Skills: Automating FDA-Required Documentation for Software as a Medical Device Thoughtbot built a Claude Code skill to generate FDA software design specifications. The skill produced useful first drafts but made factual errors like referencing Devise instead of the actual has_secure_password implementation, reinforcing that AI-generated regulatory documentation requires human review.

Lightweight Markdown Publishing Inside Rails Mark Holton described building a database-free publishing system within an existing Rails app using git-stored Markdown files with YAML frontmatter, CommonMarker, Nokogiri and Rouge for post-processing, and Redis caching for automatic invalidation across container deploys.

RubyMine MCP and the Rails Toolset Daniel Domjan explained how RubyMine's built-in MCP server provides AI models with processed Rails project data including models, controllers, and routes, using offset-based pagination and property-based filtering to handle large codebases within context window limits.

Ruby on Rails for IoT Application Development Nikhil Singh explored using Rails as a backend for IoT systems, covering API-first device communication, WebSocket real-time updates, and background job processing across smart home, healthcare, manufacturing, and fleet logistics use cases.

Videos

Building CreatorSignal: AI Agent Teams Build Features in Parallel In part 2 of his live stream, Damian Galarza live-coded a Rails app using Claude Code's Agent Teams to run multiple AI agents in parallel via Git worktrees, shipping features from plan to merged PR in ~15 minutes.

Building a "Lovable" for Rails Apps Chad Pytel and Richard Newman from Thoughtbot mapped out an MVP for a Rails-powered AI web app generator inspired by Lovable. They debated key architectural decisions including local vs. cloud execution, container strategies, and Claude integration for generating a production-ready app.

Hello World: Our AI App Generator Comes to Life Chad Pytel and Rob Whittaker from Thoughtbot began building ReadySetGo, an AI-powered Rails app generator that takes an app idea, scaffolds a new Rails application using Suspenders with Clearance and Roux, and uses an LLM to build out a unique feature complete with tests.

Podcasts

The Ruby AI Podcast: Innovating Development: The Future of GitHub Agents and AI in Rails Joe Leo and Valentino Stoll interviewed Kinsey Durham Grace from GitHub's Coding Agent Core Team about Agent HQ, which assigns coding tasks to Claude and Codex models directly from GitHub issues. Discussion covered building custom language-specific agents, persisting decisions for agent reference, and ensuring Ruby remains competitive in AI tooling.

Strictly From Nowhere: A Night Out at Artificial Ruby Justin Abrams and Mike Rispoli attended the Artificial Ruby meetup in NYC organized by Scott Werner, reflecting on community networking, the Valentino Stoll, and Andrew Denta demos, and how AI is changing the shape of work rather than solving its fundamental challenges.

Giant Robots Smashing Into Other Giant Robots: Refactoring with AI and Call of Duty Zombies Chad Pytel and Sami Birnbaum discussed refactoring Rails code with AI, what MCP servers actually do, and whether LLM tools are making engineers faster or just busier.

Giant Robots Smashing Into Other Giant Robots: The Product We Are Going to Build Chad Pytel and Sami Birnbaum discussed Thoughtbot's new AI-powered Rails app generator in pre-production, with Chad outlining how it will differ from existing tools and Sami asking hard questions about accessibility and target audience.

Dev Propulsion Labs: Harjot Gill of CodeRabbit on AI Growth, Going Viral in Japan, and Using Open Source for Marketing Victoria Melnikova of Evil Martians interviewed Harjot Gill, co-founder of CodeRabbit, about why AI code generation makes code review more important, not obsolete.

Newsletters

Token Ruby #7: Back from the Break and Building Yatish Mehta covered agentic AI development patterns, CLAUDE.md configurations for Rails projects, and a development workflow using Zed and Claude Code for parallel agent orchestration.

Static Ruby Monthly Issue 13 Andrey Eremin covered the latest in Ruby static typing including Dmitry Pogrebnoy's ruby-agent-skills repo for turning AI agents into dependable typing partners that write better RBS signatures.

Discussions

What Do You Do to Stop AI Agents from Piling Up Tech Debt? A r/rails Reddit discussion where developers shared strategies for managing AI agent code quality, with top responses on using plan mode before coding, enforcing TDD, heavy CLAUDE.md constraints, and treating agent output like junior developer PRs requiring review.

Advice for an Aspiring Junior Developer In this r/rails Reddit discussion, advice diverged between mastering Ruby/OO fundamentals first and embracing agentic coding tools. Top-voted advice emphasized candidates should learn why Ruby was designed the way it was, while others argued juniors should focus on learning agent orchestration.

Appreciation for RubyLLM A r/rails Reddit appreciation post for RubyLLM praised its handling of document uploads, streaming, and structured responses across multiple providers.

Events

RubyConfTH: Ruby Is the Best Language for Building AI Web Apps Carmine Paolino delivered the keynote at RubyConf Thailand 2026 in Bangkok, making the case for Ruby as the best language for building AI-powered web applications.

Paris.rb: FastMCP Yorick Jacquin presented on the FastMCP Ruby gem for building MCP servers at the October 2025 Paris.rb meetup hosted at Algolia.

Paris.rb: AI, Offline Chris Hasiński presented on running AI models offline in Ruby at the October 2025 Paris.rb meetup.

Paris.rb: Claude Swarm Eric Proulx presented on Claude Swarm, a multi-agent orchestration tool for Claude Code, at the October 2025 Paris.rb meetup.

SF Ruby: December 2025 Meetup Evil Martians hosted the monthly meetup at Intercom featuring Noel Rapping on Ruby 4.0, Irina Nazarova on a JS runtime for Rails, and Justin Bowen on Rails AI with Active Agent.

Upcoming

March 4th - Meetup: ChicagoRuby will meet on March 4th in Chicago at Vibes, and will include a presentation by Jason Swett on Building a CI platform on Rails with AI leverage.

March 7th - Workshop: I will be leading a workshop for Philly.rb for Introduction to Generative AI Programming with RubyLLM on March 7th in Philadelphia at CultureWorks. The session will cover RubyLLM fundamentals from basic chatbots to advanced techniques including tool calling, RAG, and multi-agent systems.

March 12th - Meetup: KRUG Meetup at Ruby Community Conference 2026 Visuality announced a KRUG meetup on March 12 in Cracow, Poland at the Zendesk Office, the day before Ruby Community Conference 2026, featuring Andrzej Krzywda, José Valim, and Piotr Dąbrowski. No conference ticket required.

March 13th - Conference: The Ruby Community Conference Winter 2026 in Cracow, Poland will have a heavy focus on Ruby and AI, with presentations and workshops including:

Obie Fernandez: Ruby & AI Conversation
Irina Nazarova: Startups on Rails and AI Integration Patterns
Carmine Paolino: Building AI Apps in Ruby and Rails with RubyLLM
Paweł Strzałkowski: Model Context Protocol in Ruby on Rails

March 25h - Meetup: ArtificialRuby is hosting a Ruby AI meetup on March 25th at Betaworks in New York City. If you are interested in speaking at the event, please fill out this form.

Open Source Updates

Code Spotlight

Hivemind — AI Agent Teams That Actually Work Together

Build teams of AI agents that collaborate, delegate, and get real work done. 28 tools, 16 templates, 5 messaging platforms. Self-hosted, fully sandboxed, open source. The OpenClaw alternative with encrypted keys and agents that learn.

hivementality.ai

Hive Mentality released Hivemind, a self-hosted Rails platform for deploying teams of specialized AI agents that collaborate through shared chat interfaces with @mentions. The platform includes 34 built-in tools (shell execution, web browsing, email, Jira, cloud storage, image vision, text-to-speech), a skills system compatible with OpenClaw SKILL.md files, and integrations with Discord, Slack, WhatsApp, Telegram, and Signal. Agents support sub-agent orchestration via synchronous delegation, asynchronous spawning, or conversational team chat, with an autonomous heartbeat mode for periodic unsupervised execution.

New Gems

Links to the RubyGems page, newest releases are first:

earl-bot - A Mattermost bot that spawns Claude Code CLI sessions

rspec-ai-formatter - AI-friendly RSpec formatter with minimal token usage

rralph - A self-improving task orchestrator for AI-assisted development

activerabbit-cli - CLI for ActiveRabbit.ai — monitoring and issue analysis

buttercut - Video Editor XML generator with Agent skills for analyzing video, creating rough cuts and sequences.

agent_settings - Discover config locations for Claude Code, OpenCode, and Codex

weft-sdk - Unified Weft SDK for the Weft API and x402 Facilitator

tokenr-ruby - Automatic LLM cost tracking for OpenAI, Anthropic, and more

botiasloop - Minimal agentic AI application with ReAct loop

claude-office - A TUI companion for Claude Code — animated kaomoji agents in a virtual office

dickless - Official Ruby SDK for the dickless.io API platform

nous - Crawl websites and extract readable markdown for LLM workflows

origen_llm - This plugin enables a simple LLM connector for Origen

supermemory - Ruby SDK for the Supermemory API - Memory API for the AI era

ticktick-mcp-server - MCP server for TickTick task management

agent_gateway - Rails engine exposing app data as a single AI-agent-friendly JSON endpoint

ruby-mana - Embed LLM as native Ruby — write natural language, it just runs

revox - Ruby library to access the Revox API

rails-llm-structured - Rails DSL for LLM structured outputs

ai_record_finder - Natural language to safe ActiveRecord::Relation queries

kodo-bot - Security-first AI agent framework

summarize-ruby - Ruby wrapper for the summarize CLI

dexter_llm - Unified LLM agent core (providers, tools, sessions, compaction)

marketing_mario - A marketing meta-prompting and context engineering system for Claude Code

ai-bros - Everything AI but brought into the ruby world.

aivory_monitor - Runtime exception monitoring agent for Ruby applications

promptmenot - Detect and sanitize prompt injection attacks in user-submitted text

ai_safety_rails - LLM guardrails and evaluation harness for Ruby

rails_chatbot - AI-powered chatbot system with knowledge base integration for Rails applications

ruby_llm-text - ActiveSupport-style LLM utilities for Ruby

webmcp-rails - WebMCP attributes for Rails forms

commitcraft - AI-powered git commit message generator

agent-client-protocol - Ruby schema/runtime helpers for the Agent Client Protocol (ACP)

kairos-chain - Memory-driven agent framework with blockchain auditability

panda-mcp - MCP server for Panda CMS

sage-rb - Unified LLM adapter for Ruby

vestauth - Auth for agents – from the creator of dotenv and dotenvx

llm_capabilities - 4-tier capability detection for LLM models

llm_providers - Multi-provider LLM client for OpenAI, Anthropic, Google, OpenRouter

mlx - Ruby bindings for the native MLX library

agent-chat - Chat messaging tool for inter-agent communication

rspec-agents - RSpec testing framework for AI agent conversations

copilot-sdk-supercharged - Ruby SDK for the GitHub Copilot CLI

linear-toon-mcp - Token-efficient MCP server for Linear using TOON format

muxi - MUXI Ruby SDK

x-aeon_agents_skills - AI agents skills to be used for X-Aeon projects

broadlistening-viewer - Standalone viewer for Broadlistening analysis results

spaghetti_rails - Productivity boosting tools powered by LLMs

monarchic-agent-protocol - Monarchic Agent Protocol protobuf types

New Open Source

Links to the Github repository:

Rubyagents - Code-first AI agent framework where LLMs write and execute actual Ruby code in a sandbox rather than JSON tool calls

Kodo - Security-first AI agent framework that runs locally and communicates through messaging platforms, with encrypted memory storage and multi-LLM support

Recurgent - Agent framework that synthesizes tool implementations at runtime based on method calls, with self-delegating sub-agents and contract-driven validation

Similarity Search - Semantic document storage and search API using vector embeddings with hybrid BM25/cosine search, LLM reranking, and a RAG pipeline

BotiasLoop - ReAct-loop AI agent framework with shell access, SearXNG web search, multiple LLM providers, and bot interfaces

OpenFang - Personal AI assistant that wraps Claude Code CLI as an agent runtime with dashboards, heartbeat monitoring, scheduled tasks, and MCP tools

Fracture - MCP server that provides Discord tools for guild management, messaging, role administration, and channel organization via the MCP Ruby SDK and discordrb

Spurline - Rails-inspired framework for building production AI agents with prompt injection controls, streaming-first architecture, and structured audit logs

Gmail MCP - Local MCP server that exposes Gmail as read-only tools for AI agents, providing email listing, search, and unread counts via the Google Gmail API

AI Agent Fleet - SaaS platform for managing fleets of AI agents with monitoring, execution tracking, and policy-based behavior controls built on Rails and Hotwire

girb-mcp - MCP that gives agents access to running Ruby processes through the debug gem, enabling runtime inspection of variables, call stacks, and breakpoints

AgentGridOS - Self-hosted platform for deploying AI agents with individual identities, persistent memory, tool access, and Docker sandbox execution environments

Steward - Multi-agent AI platform where each agent runs as a separate Telegram bot with its own personality, layered memory architecture, and tool execution

Voice Agent - Phone agent system with pluggable VoIP, SIP, and voice components that supports multiple personalities, voice cloning, and local voice processing

SOT MCP Server - Source of Truth server built with Sinatra and SQLite that provides REST and MCP interfaces for AI agents to manage structured data

Clawkit - Tool for managing OpenClaw agent workspaces across remote hosts using SSH and rsync, with Git-based change detection and interactive review workflows

AI Code Review Assistant - Rails-based code review platform that provides structured feedback on issues with real-time conversational follow-up

Companies That Use MCP - Scanner that probes domains for MCP servers and fingerprints their SDK type, authentication, transport protocols, and available tools

Jobs & Opportunities

Featured

FRDM AI is hiring a Full Stack Software Engineer (AI + LLM Integration Focus), a remote position ($130k–$150k + equity) requiring Ruby on Rails backend experience and hands-on LLM integration skills. The role involves building supply chain intelligence tools that use LLMs from OpenAI, Anthropic, and AWS Bedrock to help companies identify modern-day slavery, child labor, and environmental risks in their global supply chains.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - February 11th, 2026

Matt Solt — Wed, 11 Feb 2026 13:01:43 +0000

Welcome to the 24th edition of Ruby AI News! This edition features the 2026 return of the Ruby AI meetup Artificial Ruby, the most important need to know AI news for Ruby developers, the “crazy unlock” of Rails + Claude Code, and much more.

I will be presenting Introduction to Generative AI Programming with RubyLLM on March 7th, 2026 at CultureWorks Greater Philadelphia, hosted by Wale Olaleye and RailsFever. The workshop covers basics such as building an interactive chatbot, text & image generation, transcription, and data extraction, through intermediate topics like tool calling and the Model Context Protocol, with further discussion on advanced concepts including Retrieval Augmented Generation for custom datasets, prompting strategies, cost optimization, monitoring, multi-agent systems, and deployment. The session runs from 10:00am to 1:30pm ET with networking, a presentation, and hands-on coding, designed for technical founders, software engineers, and students interested in AI integration.

Read on the web

Top Stories
- Artificial Ruby is Back for 2026
Need to Know AI News
Content
Events
- Previous
- Upcoming
Open Source Updates
Jobs & Opportunities
- Featured
One Last Thing

Need to Know AI News

Claude $50 Credit To celebrate the launch of Opus 4.6, Anthropic is giving away $50 of usage credits to subscribers. Go to the Claude AI usage page or use the /extra-usage slash command in Claude Code to claim your credits by February 16th.

Docker Sandboxes Docker announced disposable microVM-based execution environments for coding agents like Claude Code, Gemini CLI, Codex, and Kiro, providing hard isolation so agents can run unattended with full system access without affecting the host machine.

Claude Code Is the Inflection Point Doug O'Laughlin, Jeremie Eliahou Ontiveros, Jordan Nanos, Dylan Patel, and Daniel Nishball argued that Claude Code represents a pivotal moment in AI comparable to ChatGPT's launch, noting that 4% of GitHub public commits are already authored by Claude Code with projections reaching 20%+ by year-end. The article examined the broader threat to the $15 trillion information work economy and projected Anthropic will surpass OpenAI in quarterly revenue growth.

Agent Trace Cursor proposed an open standard for tracing AI-generated code in version-controlled codebases. The spec provides vendor-neutral, granular attribution at file and line levels to track which code was written by AI versus humans.

The Potential of RLMs Drew Breunig explored Recursive Language Models (RLMs) as a solution to context rot, where LLM performance silently degrades as context grows. RLMs separate tokenized from programmatic context by loading data into a coding environment and letting models interactively explore it, handling datasets without degradation.

How StrongDM's AI Team Build Serious Software Without Even Looking at the Code Simon Willison examined StrongDM's "Dark Factory" approach where AI agents produce and validate code without human review, using behavioral clones of third-party services and satisfaction metrics for probabilistic validation. The team spends roughly $1,000 daily per engineer on tokens and tests thousands of scenarios hourly against digital twins of APIs like Okta and Slack.

Pi: The Minimal Agent Within OpenClaw Armin Ronacher wrote about Pi, a minimal coding agent with just four tools (Read, Write, Edit, Bash) and no MCP that extends itself by generating its own plugins. Shopify CEO Tobi Lütke endorsed Pi as the most interesting agent harness, noting he had it spawn Claude Code in tmux and reverse-engineer its tasks system. Aakash Gupta highlighted that Pi powers OpenClaw, which reached 145,000 GitHub stars in a single month, beating VC-funded agent frameworks with four system calls and a package manager.

QMD Tobi Lütke shipped updates to QMD, his local markdown search MCP server, adding a fine-tuned query expansion model, GEPA-optimized synthetic training data, and semantic chunking. Jared Palmer praised the combination of Compound Engineering's workflow:compound agent with QMD, while Andrew Levine shared a clawdbot that uses QMD for private knowledge base search with hybrid BM25 + local embeddings to token consumption by 95%.

How to Make Your Agent Learn and Ship While You Sleep Ryan Carson described a nightly automation loop where an AI coding agent reviews the day's threads, extracts learnings into persistent AGENTS.md files, then picks the top priority from a backlog and ships a PR while you sleep. The setup combines Compound Engineering, Compound Product, and Ralph to create a self-improving cycle where patterns discovered each day inform the next day's work.

Content

Announcements

https://x.com/paolino/status/2019865875650867279

Carmine Paolino announced several RubyLLM updates: Datadog AI Guard integration making RubyLLM the first Ruby library with Datadog's AI observability support, AWS Bedrock and Azure AI Foundry support adding 263 models to push the registry past 1,000 total, and a new Agent interface coming in the next release.

Compound Engineering: The Definitive Guide Kieran Klaassen published a comprehensive handbook for AI-native development where each unit of work compounds into the next, built from experience creating Cora at Every. The guide covers a Plan-Work-Review-Compound loop, parallel review agents, and adoption stages. Kieran also shared a video walkthrough of the guide.

AgentFerrum Florian Lamache released a Ruby gem for AI agent browser automation that wraps Ferrum with an accessibility tree and markdown snapshot layer, achieving up to 90%+ token reduction versus raw HTML. Features ref-based element interaction, stealth profiles, and a CLI mode for stateless agent workflows.

Chaos to the Rescue Valentino Stoll released an gem that uses LLMs via RubyLLM to dynamically generate missing methods at runtime and suggest fixes for Rails exceptions during development, with safety guardrails including allowlists, secret redaction, and no auto-execution of generated code.

Self Agency Dewayne VanHoozer created a Ruby mixin that generates and installs methods at runtime from natural language descriptions using LLMs via RubyLLM, inspired by Valentino Stoll's chaos_to_the_rescue gem.

Pocketrb Maciej Mensfeld released a minimal Ruby AI agent framework built on RubyLLM with async message processing, multi-LLM support, and deployment via CLI, Telegram, or WhatsApp. Features include context compaction, browser automation, cron scheduling, a keyword-matched memory system, and a runtime skills system.

Typed Bus Dewayne VanHoozer open sourced a Ruby gem for in-memory fiber-async pub/sub messaging with typed channels, ACK/NACK delivery semantics, dead letter queues, and adaptive throttling, inspired by the message bus in Pocketrb.

Code-on-Incus Maciej Mensfeld also updated his container runtime for sandboxing AI coding agents, with automatic UID mapping, credential isolation, parallel sessions, and snapshot support. Maciej noted his Ruby-based agent now features PARA (Projects, Areas, Resources, Archives) memory and self-improving code capabilities.

GemChat Saroj Maharjan launched an AI-powered chat tool that lets developers ask questions about any Ruby gem in plain English and get actionable code examples, built with Hotwire and sign in with GitHub to start chatting.

EasyTalk Sergio Bayona released version 3.3.1 of his Pydantic-style Ruby gem for defining structured data contracts, adding RubyLLM integration that lets developers use schema models directly with structured outputs and tool calling.

Building LLM Applications with Ruby on Rails Damian Galarza announced a book for Rails developers covering LLM integration with OpenAI and Anthropic, prompt management, streaming via Turbo Streams and Action Cable, testing non-deterministic AI systems, and cost tracking, built around a support ticket example project.

Kimurai Framework Victor Afanasev updated his Ruby web scraping framework with AI-assisted extraction that uses an LLM to generate XPath selectors on the first request, then caches them for zero-AI subsequent scrapes. The framework supports LLMs via Nukitori, alongside traditional Capybara-based browser automation.

CovLoupe Keith Bennett released v4.0 of his SimpleCov analysis toolkit (renamed from simplecov-mcp), providing an MCP server that lets AI assistants query coverage gaps and prioritize untested code.

QueryLens Bryan Beshore released a mountable Rails engine that lets non-technical team members query databases in plain English using any LLM via RubyLLM, with safety layers including read-only transactions, SQL parsing, function blocklists, and two-stage schema handling for large databases.

Claude Code Skills Obie Fernandez started a shared collection of Claude Code skills including applying betterstimulus.com patterns and zero-configuration OAuth for MCP server connections.

Conductor Setup for Rails Apps Jeremy Smith posted about his Conductor scripts for Rails development, covering workspace setup with Docker, mise, and Foreman, isolated per-workspace databases, and automated cleanup on archive.

Claude Rails Dev Alexey Poimtsev created a modular Claude Code configuration that transforms the AI assistant into a team of specialist roles for Rails development, with slash commands for architecture, coding, auditing, DevOps, i18n, and an orchestrator that routes tasks to the appropriate persona.

Claude Agent SDK Ruby Rob Zolkos highlighted this community-maintained Ruby port of Anthropic's Claude Agent SDK, which provides feature parity with the official Python SDK including bidirectional conversations, custom tool definitions, streaming, permission callbacks, and Rails integration.

Claude Code Skill for Self-Testing with Playwright Jankees van Woezik shared a Claude Code skill that teaches the agent to start a dev server, authenticate via Rails console, and verify features in a browser using Playwright MCP, creating a self-improvement loop where the agent tests its own work.

LLM QuickGenerate for Rails Matt Swanson showed his full Cursor chat log showing the iterative development of a reusable LLM::QuickGenerate Ruby model for auto-titling and summarizing text, covering prompt design, token estimation, and LLM adapter support.

Claude Worktree Ben Garcia released a Ruby TUI built with ratatui-ruby for managing git worktrees during parallel Claude Code sessions, with auto-symlinking of .env and node_modules, custom setup scripts, and safety checks for uncommitted changes.

Ruby-TI Hamachan shared a zero-annotation static type analyzer for mruby that integrates into LLM workflows via a skills layer, letting models query type signatures and structured documentation instead of raw source code.

Pro Editor Pocket Hamachan also built a VS Code-inspired PicoRuby editor for the T-Deck Plus handheld device, featuring syntax highlighting, code completion, trackball navigation, and SD card storage for writing and executing Ruby on embedded hardware.

David Paluy reviewed Layered Design for Ruby on Rails Applications by Vladimir Dementyev, calling it the missing manual for post-MVP Rails projects. He highlighted the AI chapter, noting Vladimir's treatment of agents as first-class abstractions for non-deterministic interactions with references to RubyLLM and ActiveAgent.

Ruby Community Awards to Honor Matz, Chad Fowler, Rich Kilmer, David A. Black and More at Gala Dinner Ahead of RubyConf 2026 Ruby Central announced its inaugural gala dinner on July 13 in Las Vegas, awarding Lifetime Achievement to Matz, Chad Fowler, Rich Kilmer, and David A. Black, plus honors to Emily Samp, Saron Yitbarek, and Nadia Odunayo for community service, mentorship, and innovation.

The Ruby Users Forum Is Now Live Javier Cervantes launched a new community forum for Ruby developers with categories for help, learning resources, announcements, and community discussions.

RubyConf 2026 Call for Speakers RubyConf Las Vegas opened its CFP with a March 15 deadline, accepting 30-minute talks and 2-hour workshops including a track for AI-assisted Ruby development called "Living with the Robots".

Y Combinator president Garry Tan called Ruby on Rails + Claude Code a "crazy unlock", noting that Rails was designed for syntactic sugar and LLMs are "sugar fiends."

Articles

Teach Your AI to Think Like a Senior Engineer Kieran Klaassen presented eight planning strategies for AI-assisted development, using parallel research agents to investigate best practices, reproduce bugs, and analyze existing codebase patterns before writing code.

How I Think About Building Rails Apps in 2026 Yuri Sidorov overhauled his Rails starter template to be AI-native by default, adding MCP tool parity for every feature, RubyLLM integration, Claude Code conventions, and TDD-first development alongside vanilla Rails choices like SQLite, Hotwire, magic links, and UUIDv7.

Essential Ruby Gems for Working with Agent Skills Files Lucian Ghinda released three foundation gems for AI agent tooling in Ruby: agent_skills_configurations for discovering agent config paths, agent_skill_parser for parsing YAML frontmatter skill files, and agents_skill_vault for downloading and syncing skills from repositories.

Your AI Doesn't Write Every Framework Equally Well Steve Clarke had Claude Code build the same UI in five stacks and found React and Rails + Hotwire produced polished results on the first pass while Vue consistently struggled, suggesting training data density now matters when choosing a framework for AI-assisted development.

RAG on Ruby on Rails Jesse Waites walked through building a production RAG pipeline for a hiking club using Rails 8, pgvector, Voyage AI embeddings, and Solid Cable for real-time streaming without Redis.

Using Conductor with Ruby on Rails Andrea Fomera demonstrated configuring Conductor for Rails apps, covering required shell scripts for setup, run, and archive phases along with database isolation strategies across git worktree-based workspaces.

Conducting Rails John Nunemaker shared practical tips for running Rails apps across multiple Conductor workspaces with Claude, covering per-workspace test databases, dynamic port handling, and setup scripts that made parallel AI-assisted development reliable.

How to Build an AI Agent for Talent Matching, Part 2 Paulo Tarso built a Rails-based talent matching system using Active Genie's Scorer module and Claude 4.5 Sonnet to convert developer profiles into narrative prompts and score them against job criteria, returning ranked candidates with AI reasoning for human review.

Let Agents Test Their Own Work Jankees van Woezik showed how giving Claude a Playwright MCP testing script enabled the agent to self-verify its work through browser automation, turning one-shot code generation into an iterative self-correction loop.

Claude Code Found Bugs I Wasn't Looking For Chris Sonnier asked Claude Code to document Rails models for data layer reconstruction and discovered it surfaced hidden bugs including a hardcoded || true condition and inconsistent JSON field naming across dozens of background jobs.

Prompt Decision Records: A Documentation Pattern for LLM Systems Chris also proposed adapting Architecture Decision Records for LLM systems, capturing prompt strategies, model configurations, failed approaches, and known gotchas alongside code.

How I Actually Use AI to Write Ruby on Rails Code Mario Alberto Chávez Cárdenas described a layered documentation approach for AI-assisted Rails development, building context through architecture docs, pattern guides, and implementation specs to generate shippable code for both legacy and greenfield applications.

RIP "There's a Gem for That": How AI Flipped the Script Zil Norvilis argued that AI-generated bespoke code is making many mid-tier Ruby gems obsolete, as LLMs can produce tailored, dependency-free utilities faster than finding, configuring, and maintaining external libraries.

How I Coded a Rails 8 CFP App in 30 Minutes with Antigravity Riccardo Carlesso used Google's Antigravity AI agent to build a Rails 8 conference submission management app for Rubycon, going from prompt to working MVP with Devise and data ingestion from Gmail via MCP in under 30 minutes.

Stream AI Responses from Rails to React Ganesh Navale demonstrated using Server-Sent Events with ActionController::Live to stream OpenAI responses token-by-token from a Rails API to a React frontend, avoiding WebSocket complexity.

The Single Most Important Thing That Made Me Believe AI Coding Could Work Marcin Ostrowski found that Claude Code hooks, scripts that block file edits until convention skills are loaded, solved the problem of AI ignoring Rails coding guidelines and became essential for enforcing project standards.

How Do You Know the Software Is Working? Marcin also outlined a local CI pipeline for AI-assisted Rails development using Rubocop, Brakeman, RSpec, and Undercover, combined with a code review process using separate agents to catch what LLMs miss.

Why Ruby Is Excellent for AI Development Mijo Kristo argued that Ruby's 40% token efficiency advantage over Python, combined with gems like Rumale, LangChain.rb, and ruby-openai, makes it well-suited for AI-powered web apps, RAG systems, and LLM orchestration.

Building Breakwater with AI Ben Curtis recounted building Breakwater, a Docker image licensing platform, using ChatGPT for architecture planning and Claude for implementation, arguing that AI shifted the SaaS bottleneck from technical capability to market viability.

Database-per-Branch Workflow in Ruby on Rails Using the BranchDb Gem Ali Fadel introduced BranchDb, a gem from that automatically creates isolated PostgreSQL databases for each git branch by hooking into db:prepare and cloning via pg_dump | psql, with parent branch detection through git reflog.

AI Agents in Ruby: Why Is It So Easy? Fernando Martinez used a 250-line coding agent built with RubyLLM to argue that two factors make Ruby ideal for AI agents: LLMs reducing AI to an integration problem, and Ruby's high capability-to-effort ratio for orchestrating complex interactions with minimal code.

The Future of Coding Agents Is Vertical Integration José Valim argued that generic coding agents create inefficient workflows because they can't see what they build, and proposed vertically integrating agents into frameworks like Rails so they can interact with running applications, access the DOM, and read real-time logs.

Clankers with Claws David Heinemeier Hansson built an AI agent named Kef using OpenClaw that navigated human-facing UIs without any special APIs or MCP accommodations, demonstrating that agents don't need specialized infrastructure since human-centered interfaces will prove sufficient.

When an AI Agent Gives Advice and One of the World's Most Influential Devs Takes It Errol Schmidt examined how DHH accepted an architectural recommendation from an AI agent to flatten nested routes in the Basecamp API, arguing this signals a shift where AI agents are becoming credible participants in design review for production Rails applications.

How to Build a Copilot Agent That Debugs Production Errors Joshua Wood walked through building a custom GitHub Copilot agent that connects to Honeybadger via MCP to retrieve error details, analyze stack traces, and open pull requests with fixes and regression tests.

So, Your Developers Use AI Now: Here's What to Know Ivan Eltsov analyzed research showing AI-assisted development yields 30-40% productivity gains under limited circumstances, with benefits highest on greenfield projects using popular stacks and potentially negative on mature codebases.

Ruby on Rails + Claude Code = Magic Miles Woodroffe revisited his AI-assisted Rails workflow eight months later, reporting productivity gains in the "mythical 10x range" thanks to Opus 4.5 and refined AGENTS.md conventions, with a practical example of adding exercise tracking to an iOS app in under 30 minutes using only screenshots.

Convention Over Configuration Was Always an AI Multiplier Matthew Karsten argued that opinionated frameworks like Rails produce more consistent AI-generated code because conventions reduce the "decision surface area" LLMs must navigate, while blank-canvas frameworks cause architectural drift across sessions.

It Takes a Village: Building Gusto's First AI Risk Agent Xao Yang described building GROW, an AI agent for onboarding risk assessment built inside Gusto's Rails monolith, where operations specialists co-created structured prompts encoding years of institutional knowledge.

Building AI Bots in a Ruby on Rails Application Ravi Prakash provided a step-by-step tutorial for integrating an AI chatbot into a Rails app using OpenAI's API, service objects for clean architecture, and Rails credentials for secure key management.

Building a Customer Service Chatbot in Ruby on Rails Ravi also walked through building a Rails chatbot using service objects for a rules engine with regex-based FAQ matching, conversation persistence, and OpenAI integration for handling questions.

Ruby on Rails AI Integration: From Setup to Deployment Devot surveyed four approaches for adding AI to Rails apps: direct API calls via ruby-openai and langchain.rb, Ruby-native ML with torch-rb, polyglot Python microservices, and Rails-native agent frameworks like Raix and Sublayer.

Your IDE Is a Comfort Blanket Robert Matsuoka argued that while traditional IDE features augment cognition, AI code generation replaces it, citing the METR study showing developers were slower with AI tools while believing they were faster. He advocated for CLI-based specification-driven workflows that force developers to articulate intent before generating code.

How AI Broke the Syntax Barrier and Let Me Ship Alone Dávid Ondruš described how AI tools enabled him as a software architect to ship projects in languages he understands conceptually but not syntactically, including building Ruby on Rails plugins for Redmine that previously weren't worth the learning investment for a quick prototype.

Announcing the 2026 Gem Fellowship Mike Perham announced eight Ruby open source projects selected to share $100,000 in grants, including Rouge, ruby-git, SimpleCov, Herb, Ferrum, and Bridgetown.

Videos

Claude Code David Kimura of Drifting Ruby demonstrated using Claude Code for Rails development, covering installation, context windows, test generation, the VS Code extension, and running local models.

A New Claude Skill for Rails Code Audits Chad Pytel of Thoughtbot built a Claude Code skill that audits Rails applications against Thoughtbot's coding standards and best practices, inspired by Jose Blanco's work on automated code auditing.

RailsFast: The Vibe Coding Template for Rails 8 Javi Ramírez deployed a full-stack Rails 8 SaaS boilerplate to production on a Hetzner VPS using Kamal, with built-in authentication, Stripe payments, admin dashboard, and Solid Queue/Cache/Cable.

Building CreatorSignal: Rails Auth and Deploy from Scratch Damian Galarza live-coded a Rails SaaS app using Claude Code as the sole development partner, demonstrating plan mode for feature architecture, a custom TDD skill enforcing outside-in testing, iterating on CLAUDE.md to teach coding patterns, and sub-agent code reviews of AI-generated code.

Podcasts

The Ruby AI Podcast: New Year, New Ruby: Agents, Wishes, and a Calm Ruby 4 Joe Leo and Valentino Stoll discussed Ruby 4's quiet Christmas release, agent-driven development workflows with Claude Code, and survey data showing workers spend 4.5 hours weekly fixing AI-generated "slop."

The Ruby AI Podcast: From Writing Code to Orchestrating It: Agentic Development with Ben Scofield Joe Leo and Valentino Stoll interviewed Ben Scofield about the shift from writing code to orchestrating AI agents, covering deliberate practice research applied to developer skill growth, Ruby's dynamic primitives in agentic contexts, and strategies for mentoring in an AI-enhanced landscape.

Technology for Humans: Tech Roundup: Heroku's Demise, the AI Coding Wars, Events Errol Schmidt of reinteractive covered Heroku's shutdown, the intensifying competition among AI coding models, and upcoming Ruby events including RubyConf and RailsWorld.

Builder Stories: Build Your Own Marketing Tools with Claude Code Brian Casel interviewed Colleen Schnettler, a Rails developer and SimpleFileUpload founder, who built a voice-note-to-LinkedIn publishing system in two days using Claude Code with the Compound Engineering framework for planning and multi-agent execution.

Discussions

People Are Sleeping on How Much Rails+Claude Is a Crazy Unlock The r/rails community debated Y Combinator CEO Garry Tan's claim about Rails and Claude, with commenters noting that convention-over-configuration makes Rails particularly LLM-friendly while others pointed out Claude still struggles with Rails-specific patterns like callbacks and base controller conventions.

Which Agents and MCPs Are You Using to Develop Ruby on Rails with Hotwire? Lucian Ghinda asked the Ruby community to share their Claude MD instructions, skills, plugins, and MCP configurations optimized for Rails and Hotwire development with LLMs.

How I Forced Claude to Follow Rails Conventions with Pre-Edit Hooks Two r/rails discussions explored enforcing Rails conventions with AI agents described using Claude Code hooks to enforce guidelines that CLAUDE.md and skills alone couldn't reliably maintain, while the follow-up I Don't Read My AI Agent's Code Until CI and Three Code Reviews Pass detailed a workflow where local CI and reviewer agents validate generated code before the first human review.

Events

Wnb.rb: Fake Minds Think Alike: AI, Ruby, and Similarity Search Valerie Woolard presented at Wnb.rb on vector data types and their role in LLMs, walking through a practical example of building similarity search with Ruby.

Upcoming

February 18th - Meetup: ArtificialRuby is hosting a Ruby AI demo night on February 18th at Betaworks in New York City, featuring Andrew Denta on "Realtime AI Agents in Ruby" and Valentino Stoll on "Chaos to the Rescue" with networking and drinks from 6 to 9 PM.

February 25th - Meetup: SF Ruby’s monthly meetup will be on February 25th in San Francisco at Sentry featuring talks on startup demos, open-source contributions, and real-world engineering stories.

March 13th - Conference: The Ruby Community Conference Winter 2026 in Cracow, Poland will have a heavy focus on Ruby and AI, with presentations and workshops including:

Obie Fernandez: Ruby & AI Conversation
Irina Nazarova: Startups on Rails and AI Integration Patterns
Carmine Paolino: Building AI Apps in Ruby and Rails with RubyLLM
Paweł Strzałkowski: Model Context Protocol in Ruby on Rails

Open Source Updates

Code Spotlight

Transform AI Output into Shared Understanding

insAIght Hub transforms scattered AI output into structured, searchable, and actionable knowledge. Capture, organize, and share AI insights with your team.

insaight-hub.com

Chris Sonnier open sourced insAIght Hub, a Rails 8 application for organizing and collaborating on AI-generated outputs. The platform turns scattered AI insights into a structured, searchable knowledge base with audience-based tagging, threaded discussions, multi-file insight creation, and MCP server integration for AI agents.

New Gems

Links to the RubyGems page, newest releases are first:

graph-agent - A Ruby framework for building stateful, multi-actor agent workflows

runway-ruby - A Ruby client for RunwayML's API

understand - Understand your codebase with a LLM

query_lens - Natural language SQL query builder for Rails, powered by AI

agent_ferrum - Wraps Ferrum with AI-optimized content extraction

monty-rb - Ruby bindings for Monty

collavre_slack - Slack integration for Collavre

collavre_github - GitHub integration for Collavre

git-markdown - Convert GitHub PRs to Markdown for local AI code review

google-apis-ces_v1 - Client for Gemini Enterprise for Customer Experience API V1

wardstone - Ruby SDK for the Wardstone LLM security API

agent_c - Batch processing for pipelines of steps for AI

clawthor - DSL and compiler for Claude Code plugins

pocketrb - Pocket-sized Ruby AI agent framework with multi-LLM support

admin_suite - Reusable admin suite engine

rainbow_llm - A routing gem for multiple LLM providers with automatic failover

deepseek-video - DeepSeek Video - AI Video Generator Online

prompt_guard - Prompt injection detection for Ruby using ONNX models

perplexity-image - AI Image Generator - Create stunning visuals instantly

supermaker-ai-pose-generator - High-quality integration for https://supermaker.ai/blog/unlock-perfect-poses-the-ultimate-guide-to-ai-pose-generators/

ai-replace-prompt - High-quality integration for https://supermaker.ai/blog/best-ai-replace-prompts-to-transform-your-photos-instantly/

collavre_notion - Notion integration for Collavre

collavre_openclaw - OpenClaw AI Gateway integration for Collavre

ai-walking-video-generator - High-quality integration for https://supermaker.ai/blog/ai-walking-video-generator-create-realistic-walking-videos-free/

nanabananaimg - NanaBanana IMG - AI-powered image generation platform

vishalo - Vishalo - AI-powered visual creation platform

formy3d - Formy 3D - AI 3D model generator

murekav8 - Mureka V8 - AI-powered music generation platform

hunyuan-3d - Hunyuan 3D - AI-powered 3D model generation platform

voe4 - VOE4 - AI-powered video generation and editing platform

dreaminai - DreaminAI - AI-powered creative platform

girb-gemini - Gemini provider for girb

girb-ruby_llm - RubyLLM provider for girb

girb - AI-powered IRB assistant

ralph.rb - Autonomous agentic loop for Claude Code, Codex & OpenCode

ralph - Autonomous agentic loop for Claude Code, Codex & OpenCode

rails_orchestrator - Framework to build AI agents in Rails with tool support, memory and orchestration

llmemory - Persistent memory system for LLM agents

vibecode - A local-first “Codex-style” CLI but powered by Ollama

rubeno - The Ruby implementation of Testeranto

seedance-2 - Seedance 2 - Next-generation AI platform

seedream5-ai - Seedream5 AI - AI-powered video generation platform

agent_skills_configurations - Unified interface for discovering AI coding agent skill paths

self_agency - LLM-powered runtime method generation for Ruby classes

rubyrana - Build production-ready AI agents in Ruby

kling3-ai - Kling 3 AI - Next-generation AI video creation platform

sprites-ruby - Ruby client for the Sprites API

daimond - Deep Learning framework for Ruby with Rust backend

clyro - The Agent Kernel

claude-worktree - A TUI tool to manage Git Worktrees for AI coding agents

agent_skills - Ruby implementation of the Agent Skills open standard

og_pilot_ruby - Ruby client for the OG Pilot Open Graph image generator

agent_skill_parser - Parse agent skill files with YAML frontmatter and markdown body for agent/AI systems

semantic-cache - Semantic caching for LLM API calls

agents_skill_vault - A Ruby gem for managing AI agent skills from GitHub repositories

chaos_to_the_rescue - Safe-by-default LLM-powered method generation and Rails error rescue suggestions

rails_skills - Organize AI skills for Rails projects, shared between Claude and Codex

collavre - Collavre platform engine

exa-rb - Exa API for neural and keyword-based web search with content retrieval capabilities

kiribi-ruri_v3-30m - Easy to use onnx models

New Open Source

Links to the Github repository:

FrankMD - Self-hosted markdown note editor and organizer built with Rails that stores notes as plain files with AI-powered grammar checking via LLM

AI Agent Refactoring System - AI-assisted legacy code refactoring system that uses characterization testing to validate cross-language conversions

MultiAgentProtocols - Provides unified client and server implementations for MCP, ACP, and A2A agent communication protocols

Pipes - File-based AI agent orchestration system that uses Unix philosophy to queue work items as JSON files and process them via Claude in parallel tmux sessions

News Curator - AI-powered news curation tool that fetches articles daily from Google and uses Claude to select and score the most relevant pieces

Fizzy Pop - Polling daemon that monitors Fizzy for unread notifications and forwards them to OpenClaw AI agent webhooks at configurable intervals

Houston - Self-hosted AI life assistant with goal-oriented autonomous agents, persistent memory, scheduled check-ins, and MCP integrations

Smart Catalog - Rails 8 demo app showcasing AI patterns including RAG with pgvector, hybrid search, and LLM query classification using Google Gemini

SwarmPod - Mountable Rails engine for real-time multi-agent orchestration featuring a live WebSocket dashboard and parallel agent execution organized by Gemfile groups

PlaceAgent - LLM-powered business discovery gem that combines Google Places API with nagentic tool-calling to search and rank local businesses

Thinkn't - AI-powered multimedia quiz generator that uses GPT-4 to create customizable group quizzes with audio, video, and image questions

Wgit MCP - MCP server that enables AI LLMs to interact with the Wgit web indexing and search library

Customer Pulse - Feedback aggregation system that collects from Linear, Google Forms, and Slack to sends daily email digests with Claude

Color Grade AI - AI-powered .cube LUT generator that analyzes video frames and creates targeted color correction look-up tables, usable as a Claude Code skill

Jobs & Opportunities

Featured

Tangible Careers

Join the Tangible Materials team - View open positions and apply today

careers.tangiblematerials.com/jobs/cad58c98-2666-466a-94d2-4f16c7dd5ff6

Remote - US & Canada: Tangible Materials Is Hiring an AI Software Engineer to build an AI-driven construction intelligence platform using Ruby on Rails, TypeScript, and React, working with 3D models and PDF construction documents to optimize carbon emissions in commercial real estate.

One Last Thing

Speeding Up PostgreSQL Full-Text Search with Persistent TSVectors

Learn how to dramatically speed up PostgreSQL full-text search by persisting TSVectors and using GIN indexes in Rails apps.

danielabaron.me/blog/speed-up-pg-fts-with-persistent-ts-vectors

Daniela Baron wrote Speeding Up PostgreSQL Full-Text Search with Persistent TSVectors, showing how the default pg_search gem configuration computes tsvectors at query time, forcing PostgreSQL into sequential scans that degrade at scale. The fix involves adding a persistent tsvector column with a GIN index and a database trigger to keep it in sync, reducing query time from ~283ms to ~2.4ms (a 118x speedup) on 100k rows. The article includes the complete Rails migration with concurrent index creation following strong_migrations best practices and the one-line pg_search configuration change needed.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - January 27th, 2026

Matt Solt — Tue, 27 Jan 2026 18:43:37 +0000

Welcome to the 23rd edition of Ruby AI News! This edition features tons of content and a look at the big year ahead for RubyLLM, with library updates, a maturing ecosystem, and my upcoming workshop on the Introduction to Generative AI Programming with RubyLLM.

Read on the web

Top Stories
Need to Know AI News
Content
Events
- Previous
- Upcoming
Open Source Updates
- New Gems
- New Open Source
Jobs & Opportunities
- Featured
One Last Thing

Need to Know AI News

Big Ideas 2026 ARK Invest released their annual research report, with sections covering AI infrastructure buildout, AI as a consumer operating system collapsing discovery and commerce, and AI productivity reshaping how software is built and sold.

Cowork Anthropic launched Cowork, bringing Claude Code-style execution to knowledge work through a macOS desktop app that connects files and tools, letting Claude complete non-technical tasks with greater agency than standard chat mode.

New Tech and Tools for Retailers to Succeed in an Agentic Shopping Era Google announced the Universal Commerce Protocol, an open standard developed with Shopify, Etsy, Wayfair, Target, and Walmart that enables AI agents to communicate across every step of the shopping journey.

ClawdBot (now renamed to Moltbot) Peter Steinberger’s open-source personal AI assistant that runs locally with persistent memory, browser automation, and integrations has taken over the AI discussion since its release. Shruti Mishra and Brian Roemmele highlighted its potential for autonomous AI workflows and multi-agent systems.

Code and Let Live Fly.io introduced Sprites, durable cloud computers that persist state between AI agent sessions instead of ephemeral sandboxes, enabling agents to maintain development environments with checkpoint/restore functionality and automatic pause during inactivity.

Why We Built Our Background Agent Ramp Engineering explained how they built Inspect, a background coding agent with sandbox access to their testing infrastructure, monitoring tools, and feature flags.

How to Write a Good Spec for AI Agents Addy Osmani outlined five principles for AI agent specifications: starting high-level before expanding, structuring like formal PRDs, breaking into modular tasks, building in quality safeguards with three-tier boundaries, and treating specs as living documents that evolve through iteration.

Content

Announcements

Classifier Lucas Carlson released an update to his text classification gem from 2005, adding five algorithms (Bayesian, Logistic Regression, LSI, KNN, TF-IDF), native C extensions for speedups, incremental Latent Semantic Indexing, and streaming support.

ClaudeMemory Valentino Stoll released a Ruby gem that gives Claude Code long-term memory across conversations by automatically extracting facts from transcripts and storing them in SQLite via MCP tools and hooks.

Agentation Chris Sonnier released a Ruby gem that ports Benji Taylor's visual feedback tool for AI agents to Rails, enabling developers to annotate web page elements and export structured selectors that coding agents can use to locate and fix UI issues.

Nukitori Victor Afanasev released a Ruby gem for HTML data extraction that uses an LLM once to generate reusable XPath schemas, then extracts structured data from similarly structured pages using plain Nokogiri for repeated scraping.

Raif 1.4.0 Ben Roesch released Raif 1.4.0 with an adapter for Gemini models, typed message classes for conversation history, and web admin improvements for token cost tracking, while replacing ReActAgent with NativeToolCallingAgent for better cross-provider tool support.

Mutant 0.14 Markus Schirp released version 0.14 of the mutation testing framework to help verify AI-written code, with Ruby 4.0 compatibility, bitwise operator mutations, and a visual progress bar while dropping Ruby 3.1 support.

FactDb Dewayne VanHoozer released a Ruby gem implementing the Event Clock concept for capturing organizational knowledge through temporal facts with validity periods, entity resolution, and LLM-powered extraction via the RubyLLM gem.

RobotLab Dewayne also released a Ruby gem for building multi-agent AI systems where specialized robots collaborate through network orchestration, hierarchical shared memory, and MCP connectivity using RubyLLM extensions.

SimpleACP And finally Dewayne created a Ruby gem implementing the Agent Communication Protocol (ACP), an open standard for AI agent communication with support for sync, async, and streaming modes plus pluggable storage backends.

FastEmbed Ruby Chris Hasiński ported FastEmbed from Python to Ruby, enabling local text embeddings via ONNX Runtime at 500+ documents per second on a Macbook CPU with support for dense models and reranking.

LEANN Chris also ported a Python vector index to Ruby that achieves 85-96% storage savings by storing only graph structure and computing embeddings on-the-fly during search, with built-in RubyLLM integration for RAG workflows.

SigLIP2-rb Chris continued with a Ruby wrapper for Google's SigLIP2 model, providing natively multilingual image and text embeddings via ONNX for semantic image search and content matching without manual tagging.

AiBouncer And finally Chris created an experimental Rails middleware using a small ML model with embeddings to detect SQL injection, credential stuffing, bot scanning, and 11 other attack types in real time with ~2ms inference.

RubyML RJ Robinson is launching a comprehensive course teaching machine learning in Ruby on Rails using Andrew Kane's gems, covering semantic search, recommendations, forecasting, and LLM integration without requiring Python.

Upgrading Rails Apps with AI MagmaLabs released a free ebook providing a practical, engineering-first guide to adopting AI safely for upgrading Ruby on Rails applications without breaking tests.

Agent Browser Skill Kieran Klaassen integrated Vercel's agent-browser CLI into his compound engineering plugin as a Claude Code skill, replacing Playwright MCP with a simpler ref-based element selection approach optimized for LLM workflows.

Rails Claude Code Plugins Mario Alberto Chávez Cárdenas adapted Anthropic's open-sourced code simplification tool for Rails, providing Claude Code agents for refactoring code following 37signals patterns, assisting Rails version upgrades, and generating consistent UI components.

Minerva Jorge Alvarez released a Rails 8 MCP server that functions as a knowledge base for AI agents, providing RAG capabilities through document management, PDF processing, website scraping, and vector similarity search via pgvector.

Rails AI Agents Thibaut Baissac updated his suite of skills and specialized agents for AI-driven Rails development, providing deep knowledge modules for Hotwire patterns, caching strategies, authorization, Action Cable, and other Rails-specific expertise to help AI write idiomatic Rails code.

Ruby Skills: Teaching Claude Code About Ruby's Tooling and Ecosystem Stan Lo released ruby-skills, a Claude Code plugin that detects Ruby version managers (rbenv, chruby, asdf, mise, etc.) to activate the correct environment and provides authoritative documentation for Ruby's typing ecosystem.

skill-rails-upgrade Rob Zolkos released a Claude Code skill that automates Rails upgrade assessments by detecting version differences, fetching official upgrade guides and railsdiff configurations, and generating complexity-rated summaries with deprecations, breaking changes, and recommended steps.

Conductor Workspace Setup Scripts John Nunemaker shared scripts for managing multi-workspace development environments in Conductor, solving port allocation by deriving all service ports from a single CONDUCTOR_PORT variable and symlinking shared configuration files.

RbToon: Toon Decoder for Ruby Taichi Ishitani released a Ruby gem that decodes Toon, a structural text format optimized for LLM input, into Ruby objects using a Racc-based parser.

Ruby JSON TOON Jitendra Neema released a gem for bidirectional JSON-to-TOON conversion that achieves 30-60% token reduction for LLM context optimization by eliminating structural overhead while preserving data integrity.

aws-sdk-http-async Thomas Witt released a fiber-friendly async HTTP handler plugin for the AWS SDK for Ruby, solving the reactor stall issue when using fibers with DynamoDB and other AWS services alongside gems like RubyLLM.

VCMatch.ai Avi Flombaum launched an AI-powered fundraising intelligence platform built on Rails that analyzes pitch decks and matches startups with relevant VCs from a database of 2,150+ investors.

Claude Code in AviNYC Avi also shared a collection of Claude Code plugins for Ruby, Rails, and SaaS development including rspec-writer for generating tests, rails-frontend for Hotwire/Tailwind, and rails-expert for POODR-based code discussions.

README Generator Skill Josh Pigford shared a Claude Code skill for generating thorough README documentation that covers local setup, architecture, and deployment for Rails projects with PostgreSQL, Inertia.js, Solid Queue, and Kamal.

Code on Incus Maciej Mensfeld released a tool for running Claude Code and other AI coding agents in isolated Incus containers, enabling unsupervised execution with sudo and Docker while keeping host credentials protected through session persistence and multi-slot support.

Terminalwire Brad Gessler added an AI-friendly Markdown file combining all documentation chapters after watching Kieran Klaassen demo Terminalwire with Claude Code at SF Ruby without access to a consolidated docs file.

RailsFast Javi Rameerez made all documentation for his AI SaaS template available as Markdown in LLMs.txt format, enabling developers to feed the docs to any AI coding assistant for faster development.

Humanizer Siqi Chen released a Claude Code skill that detects and removes 24 patterns of AI-generated writing based on Wikipedia's "Signs of AI writing" article, making text sound more natural and authentic.

RubyShell Albert Álef released a gem that enables writing shell scripts using Ruby syntax, allowing shell commands to be called as Ruby methods with command chaining, piping, directory scoping, and structured error handling.

Running Notebooks the Ruby Way: From PoC to Production with RubyPyMill Giménez Silva Germán Alberto introduced RubyPyMill, a lightweight tool that enables Ruby to orchestrate Jupyter notebook execution via Papermill, bridging data science prototypes with Ruby-driven production workflows for batch scheduling, CI/CD integration, and automated reporting.

Ruby GSoC 2026 Ideas List The Ruby Organization called for mentors and project ideas for Google Summer of Code 2026, with Google spotlighting AI, Security, and Machine Learning this year. Ideas must be submitted by February 1st.

SF Ruby Irina Nazarova updated the community website following the conference, now featuring Ruby jobs, monthly meetups, Ruby startups, and talk videos for the San Francisco Bay Area community.

Articles

Which Programming Languages Are Most Token-Efficient? Martin Alderson analyzed 19 languages using RosettaCode data, finding a 2.6x efficiency gap between Clojure and C. Lucian Ghinda highlighted the article noting Ruby is well-positioned as the third most token-efficient language for LLM workloads.

Why Ruby Might Be the Most AI-Friendly Language Nobody's Talking About Ivan Turkovic expanded on the token efficiency report, arguing that Ruby's expressiveness and minimal boilerplate make it the third most token-efficient mainstream language for LLMs, ideal for AI-assisted development as context windows become the new bottleneck.

Why Ruby Shines in the Age of AI-Powered Development Davide Santangelo also argued that Ruby's syntactic conciseness, dynamic typing, and semantic density make it ideal for AI-powered development, using 15-25% fewer tokens than Python while enabling longer context windows and lower API costs.

What If We Took Message-Passing Seriously? Scott Werner proposed reimagining AI agents through Smalltalk-style "prompt objects" that communicate via natural language with semantic late binding, arguing this captures Alan Kay's vision of computing as a living, reshapable environment.

Helmsman: Adaptive Instructions for AI Agents Abdelkader Boudih released a Rust-based MCP server that serves model-aware instructions to AI coding agents, providing minimal guidance for capable models like Opus while giving verbose step-by-step instructions to less capable ones like Haiku.

Building Enterprise Vector Search in Rails Part 1: Architecture & Multi-Tenant Implementation and Part 2: Production Resilience & Monitoring Mijo Kristo demonstrated building a production-grade vector search system, covering self-hosted embeddings for GDPR compliance, Qdrant integration with tenant isolation, circuit breakers, and rate limiting to maintain availability during a traffic spike.

Vectra: The Unified Vector Database Client for Ruby Mijo also released version 1.1.0 of the unified vector database client with Rack-style middleware for logging, retry logic, APM instrumentation, PII redaction, and cost tracking across Pinecone, Qdrant, Weaviate, and pgvector.

The Inference Pattern: Tracking AI Usage with Polymorphic Models in Rails Jesse Waites demonstrated using a polymorphic Inference model to track AI usage across multiple providers, enabling native charting, cost attribution by customer, and latency monitoring without external SaaS tools.

Chroma for Ruby Philip Thomas built an official Ruby client for Chroma vector search, leveraging new features like sparse vectors and hybrid search to improve keyword and semantic search in his Booklet project without custom layers.

Why My Second RAG System Was Built in Rails, Not Python's FastAPI Ganesh Navale compared building identical RAG systems in both frameworks, completing the Rails version in 24 hours versus weeks with FastAPI due to built-in infrastructure like Sidekiq and ActiveRecord rather than AI-specific advantages.

Your Guide to the Prompt-Chaining Framework Kim Nguyen of Gusto introduced the RTRI framework (Role, Task, Rules, Input/Output) for structuring LLM prompts, demonstrating how to chain multiple prompts together for complex tasks like generating the article itself.

I Taught AI to Write End-to-End Tests in Rails Pasha Kalashnikov created an AGENTS.md file for his Tramway Rails plugin that provides RSpec + Capybara patterns for CRUD features, enabling AI tools to generate consistent end-to-end tests automatically.

Use AI to Describe Images as a Background Job in Ruby on Rails Frank Rietta demonstrated using a state machine pattern with Sidekiq background jobs to generate image alt text via LLM APIs, emphasizing idempotency guards, soft failure detection, and human-in-the-loop review for AI-generated content.

Claude on Incus: All the Autonomy, Securely Maciej Mensfeld explained how his claude-on-incus tool isolates Claude Code in Incus containers, protecting host credentials while allowing full autonomy for installing dependencies and running Docker without privileged mode workarounds.

Claude Skill for Maquina Components Mario Alberto Chávez Cárdenas created a Claude Skill that teaches the AI to generate Rails UI code using the Maquina Components library, reducing back-and-forth corrections by providing structured documentation for components, forms, layouts, and Turbo integration.

Introduced git-wt Koichi Ito adopted git-wt for managing Git worktrees in parallel development workflows, configuring it to store worktrees in a .worktrees subdirectory within repositories rather than alongside them in the repository root.

Code Quality Skill for AI-Assisted Development Vitalii Elenhaupt introduced a Claude Code skill that enforces SOLID principles, named constants, and single-responsibility patterns while preventing drive-by refactoring during AI-assisted development.

Integrating AI into Ruby on Rails the Right Way Burraq Ur Rehman outlined production-ready patterns for Rails AI integration including mandatory background jobs, service object abstractions, LLM provider decoupling, and confidence threshold handling.

We Have to Re-Learn to Walk Alone Julik Tarkhanov argued that LLM-assisted development requires shifting consensus decisions to high-level stakeholders while granting individual developers autonomy to micromanage AI through precise directives, with quality enforced through automated tooling rather than human review cycles.

Fast Claude @file Suggestion in Big Repos Martin Emde shared a custom script using git ls-files, ripgrep, and fzf that reduces Claude Code's file suggestion latency from 1000ms to 62ms in large repositories.

It Is 2026; Where Were We? Victor Shepelev reflected on his 2025 writing including the Ruby 4.0 annotated changelog and shared skepticism about AI's industry transformation while comparing it to early 20th-century industrialization.

Building an AI-Powered Mobile App with Ruby on Rails and DigitalOcean Augusto Ruibal of 10 Grounds described an architecture where Rails serves as the source of business logic while AI acts as a supporting capability for a cooking app, emphasizing pragmatic engineering choices on DigitalOcean's infrastructure.

Why Ruby on Rails Dominates Vibe Coding Leo Trieu argued that Rails' convention-over-configuration philosophy produces cleaner code that LLMs understand better, making it ideal for AI-assisted development with faster iteration cycles.

From a Stalled Map to an Async AWS SDK Thomas Witt explained how the official AWS SDK for Ruby isn't fiber-friendly and shared his solution: a new gem that provides async-http transport for true concurrent I/O with DynamoDB and other AWS services under Falcon.

Gemini Nano in Production: 41% Eligibility, 6x Slower, $0 Cost Mike Buckbee documented implementing Chrome's built-in Gemini Nano AI into SendCheckIt's Email Subject Line Tester, revealing 6x slower inference than server-based alternatives, but maintained the feature for privacy benefits and Rails Turbo integration despite discovering prefetching inadvertently triggered multiple concurrent AI calls.

ChatGPT Agent: Experimenting with QA Automation Chad Pytel, Michelle Taute, and Yaser Mahmoud explored using ChatGPT's agent mode to identify visual and functional issues across FrontrowMD's embedded widgets, finding it viable for one-off audits but limited by lack of programmable APIs for production scaling.

Prevent the Robocalypse with TDD Louis Antonopoulos demonstrated using Test-Driven Development with Claude Code, showing how the Red-Green-Refactor cycle prevents AI-assisted development pitfalls by maintaining clear changesets and developer ownership of commits.

Rapid Prototyping with Claude Code Chad Pytel, Kevin Kwon, and Michelle Taute explained how Thoughtbot transformed their design sprint process by using Claude Code to generate functional prototypes in hours instead of static Figma mockups in days.

Building Programmable QA with AI Chad Pytel, Clarissa Borges, and Michelle Taute built a scriptable QA solution using Playwright MCP, discovering that letting Claude generate its own detection strategy produced better results than manually-crafted instructions.

Code Audits Using Thoughtbot Best Practices with Claude Skills Jose Blanco created a Claude Skill for auditing Rails applications that leverages thoughtbot resources like Ruby Science and Testing Rails to identify code smells, security issues, and testing gaps.

Humans in the Loop Robby Russell described how the Oh My Zsh project updated its CONTRIBUTING.md to address AI-assisted contributions, requiring contributors to understand every line they submit and be able to explain their changes, emphasizing that review remains the bottleneck and stewardship stays a human job.

A Software Library with No Code Drew Breunig introduced whenwords, a relative time formatting library that ships only specifications and tests rather than code, designed to be implemented on-demand by AI coding agents like Claude.

Videos

AI on Rails: Custom Tool Calls with LangChain.rb Pete Hawkins of Rapid Ruby demonstrated creating custom tools with LangChain.rb, starting with a simple date and time tool to unlock AI capabilities in Rails applications.

AI on Rails: Process File Uploads Pete also demonstrated using LangChain.rb helpers to process file uploads and extract text summaries in Rails applications.

Vibe Coding a Rails Travel App: Modeling Travel Preferences and Frequency Rhiannon Payne continued building a Rails travel map app using GitHub Codespaces, Copilot, and Claude Opus 4.5, focusing on data modeling decisions to represent travel frequency and what makes a place a favorite.

AI로 Rails 웹 프레임워크 사용한다면? (Ruby on Rails AI Agent) WeekdayCode demonstrated building an AI agent with Ruby on Rails, referencing ThibautBaissac's Rails AI project on GitHub.

Debug Production Errors in 5 Minutes with Claude AI Damian Galarza demonstrated using Claude Code with the Sentry MCP to investigate and fix production errors in a Rails application, walking through installation, prompting Claude to investigate issues by ID, and using TDD to verify fixes before deploying.

Podcasts

The Ruby AI Podcast: Real vs. Fake AI with Evan Phoenix Joe Leo and Valentino Stoll interviewed Evan Phoenix about distinguishing genuine AI implementations from marketing buzzwords, discussing how AI transforms codebase analysis, the potential resurgence of monolithic systems, and ambient agents in development workflows.

Ruby Rogues: Autogenetic AI Agents and the Future of Ruby Development Charles Max Wood interviewed Valentino Stoll about self-generating AI agents, exploring his experimental Agentic gem, plan-and-execute workflows, and how LLMs are pushing Ruby developers up the abstraction ladder toward systems thinking and architecture.

The Code[ish] Podcast: Building Agentic Apps with RubyLLM Julián Duque interviewed Freedom Dumlao, CTO of Vestmark, about how AI assists advisors managing $1.7 trillion in assets and why all their new products are being built using Ruby.

Technology for Humans: Kinsey Durham Grace: Talking to a GitHub Copilot Developer Errol Schmidt of reinteractive interviewed Kinsey Durham Grace about her role on the GitHub Copilot team, discussing the impact of AI tools on developer productivity, her transition from DevOps to user-facing product development, and advice for new developers utilizing AI tools effectively.

Code and the Coding Coders who Code it: Episode 60: Jeremy Smith Drew Bragg interviewed Jeremy Smith about organizing Blue Ridge Ruby, covering CFP strategy, accessible venue selection, and voice-first AI workflows for Rails development using Whisperflow and LLMs.

The Bike Shed: Large Language Misadventure Sally Hall and Aji Slater examined AI's dual nature, discussing where LLM tools deliver genuine value versus their limitations and harms, including differences between AI-generated and human-written code quality.

X/Twitter Broadcast: AI Talk with Avi, Nate, and Kieran Kieran Klaassen, Avi Floumbaum, and Nate Berkopec discussed their perspectives on AI coding in a live conversation.

Rails Business: Striving for Ideal Code Brendan Buckingham and Ryan Frisch discussed the tension between aspirational coding standards and business realities, covering AI's effectiveness for writing tests versus architectural decisions and the importance of well-defined code boundaries for agentic coding.

Rooted & Reaching: Building with Intention: Craft, Code, and Community with John Nunemaker Marty Mechtenberg interviewed John Nunemaker about his entrepreneurial journey as Partner at Fireside.fm, discussing flexibility, curiosity, choosing passion over profit, and the importance of community and mentorship in the tech ecosystem.

Next Token: DHH: Why AI Isn't Writing My Code (Yet) Ryan Carson and Thorsten Ball interviewed David Heinemeier Hansson about AI's real-world usage at 37signals, where 95% of the code for their new Fizzy project was still written by humans. Discussion covered AI as a learning tool versus code generator, the danger of "vibe coding" eroding developer competence, and their savings from leaving the cloud.

David Senra: My Conversation with Tobi Lütke, Co-Founder and CEO of Shopify David Senra interviewed Tobi Lütke about building Shopify from a Ruby on Rails snowboard shop to a $200B company, covering his approach to hiring founders, engineering company culture from first principles, and views on AI's impact beyond 2026.

Newsletters

Follow Your Curiosity: My Unexpected Path into AI Engineering Landon Gray recounted his career transition from traditional software engineering to AI engineering, describing how he combined Ruby expertise with AI knowledge through talks, certification, and a focus on RAG systems to establish himself in the Ruby AI community.

Static Ruby Monthly Issue 12 Andrey Eremin covered RBS 3.10.1's new pure C parser and Ruby 4.0 signature support, the growing TRuby project, editor tooling improvements, and the convergence of static typing with AI/LLM agent workflows.

Four Line Fridays: Agent Hooks, Agent-Native Applications, Ruby 4.0 and gRPC, and 1080p Smart Glasses Nate Berkopec shared agent security hooks for intercepting destructive commands, discussed agent-native application architecture, flagged gRPC's Ruby 4.0 compatibility challenges, and reviewed Viture Luma Ultra XR smart glasses for mobile coding.

Discussions

With Agentic Coding, Would You Still Choose to Build with Hotwire over React? The Reddit Rails community discussed whether AI tooling favors React over Hotwire, with commenters arguing that Hotwire's backend-focused approach keeps business logic simpler, reduces bug surface area, and avoids the Node ecosystem regardless of AI assistance.

LLM Skills for Ruby/Rails Lucian Ghinda asked the community for links to LLM skills specifically designed for Ruby on Rails projects to generate commit messages.

Events

San Francisco Ruby Conference: Building Agents with Rails Workshop Justin Bowen presented a hands-on workshop for building AI agents using Active Agent, Rails, and modern AI tools at the San Francisco Ruby Conference 2025.

XO Ruby Portland: I Know Kung Fu! RubyGems for AI Renée Hendricksen explored whether AI can take an app from idea to production faster than a human, finding the answer was no but identifying gaps in context loading that could help level up AI assistants for complex Ruby tasks.

XO Ruby Austin: RAG Demystified Landon Gray shared how a side project to find local events evolved into a full AI-powered event recommendation engine built with Ruby, demonstrating practical RAG implementation.

XO Ruby New Orleans: The State of the Ruby AI Toolbox Thomas Carr provided a builder's guide to the leading Ruby AI gems in 2025, exploring libraries for LLM integration, agent-based automations, and helping teams make informed decisions about which frameworks fit their projects.

Upcoming

January 29th - Meetup: The Sibiu Web Meetup will host Lucian Ghinda for a presentation on Good Enough Testing: AI-assisted, human-approved testing strategies that balance AI speed with human validation in Sibiu, Romania on January 30th.

January 31st - Conference: RubyConf Thailand is hosting a conference on January 31st and February 1st in Bangkok, Thailand featuring presentations by Irina Nazarova, Marco Roth, Alex Timofeev on Ethical AI, and a closing keynote by RubyLLM author Carmine Paolino.

February 25th - Meetup: SF Ruby is hosting a meetup on February 25th in San Francisco at Sentry featuring talks on startup demos, open-source contributions, and real-world engineering stories.

February - Meetup: ArtificialRuby will host their next event sometime in late February in New York City, more details to follow soon.

March 13th - Conference: The Ruby Community Conference Winter 2026 in Cracow, Poland will have a heavy focus on Ruby and AI, with presentations and workshops including:

Obie Fernandez: Ruby & AI Conversation
Irina Nazarova: Startups on Rails and AI Integration Patterns
Carmine Paolino: Building AI Apps in Ruby and Rails with RubyLLM
Paweł Strzałkowski: Model Context Protocol in Ruby on Rails

Open Source Updates

New Gems

Links to the RubyGems page, newest releases are first:

agent-harness - Unified interface for CLI-based AI coding agents

rubocop-claude - AI-focused Ruby linting via StandardRB plugin

google-apis-threatintelligence_v1beta - Client for Threat Intelligence API

itak - Audio editing tool for podcasters

gtcrn - Denoises audio

skills - The open agent skills ecosystem

agentation - Visual feedback toolbar for annotating web pages

cc-sessions - Bookmark and resume Claude Code sessions with tags

dristi-client - Ruby client for Dristi error tracking

choose-your-bed - High-quality integration for https://supermaker.ai/blog/how-to-make-the-viral-choose-your-bed-videos-with-ai/

bundleup-sdk - Official Ruby SDK for BundleUp

wralph - Human-In-The-Loop AI Factory

kling-26-motion-control - High-quality integration for https://supermaker.ai/blog/how-to-use-kling-26-motion-control-ai-free-full-tutorial-ai-baby-dance-guide/

pardon-dance - High-quality integration for https://supermaker.ai/video/blog/unlocking-the-magic-of-pardon-dance-the-viral-video-effect-taking-over-social-media/

tesla-api-sdk - Tesla API SDKs

vagrant-claude-sandbox - Vagrant plugin for Claude Code sandbox environment

human-attestation - Official SDK for HAP (Human Attestation Protocol)

simple_acp - Simple Agent Communication Protocol (ACP) implementation for Ruby

wakatime-mcp - WakaTime MCP server implementation in Ruby

eleven_rb - Client for the ElevenLabs Text-to-Speech API

shakaflow-cli - CLI client for ShakaFlow API

tork-governance - Ruby SDK for Tork AI Governance Platform

tapo - Ruby client for TP-Link Tapo smart devices

bluescroll-hap - Official HAP (Human Attestation Protocol) SDK for Ruby

gliner - Schema-based information extraction (GLiNER2) via ONNX Runtime

aws-sdk-http-async - Async HTTP handler plugin for AWS SDK for Ruby

ai-french-kiss-video-generator - High-quality integration for https://supermaker.ai/video/ai-french-kiss-video-generator/

bot_verification - Verify legitimate search engine and AI bots by IP

imago - A unified Ruby interface for multiple image generation AI providers

dsa_visualizer - Learn DSA from Zero to Hero with Ruby and C++ comparisons

acp_client_rb - Ruby client library for Agent Client Protocol (ACP)

branch_db - Automatic per-branch PostgreSQL databases for Rails development

ai_bouncer - AI-powered HTTP request classification for Rails

robot_lab - Ruby framework for building and orchestrating multi-robot LLM workflows

siglip2 - Google SigLIP2 embeddings using ONNX models

agent_runtime - Deterministic, policy-driven runtime for safe LLM agents

prompt_objects - LLM-backed entities as first-class autonomous objects

blish-image-captions - AI supported image captions for Alchemy images

nano-banana-pro-prompt - High-quality integration for https://supermaker.ai/blog/nano-banana-pro-prompt-use-cases-ready-to-copy-paste/

ai-snow-trend - High-quality integration for https://supermaker.ai/blog/how-to-make-ai-snow-trend-photos-for-tiktok-free-tutorial/

ai-twerk-generator - High-quality integration for https://supermaker.ai/blog/how-to-make-ai-twerk-video-with-supermaker-ai-free-online/

grok-image-generator - High-quality integration for https://supermaker.ai/blog/-grok-image-generator-model-on-supermaker-ai-twitterready-images-made-simple/

ruby_llm-skills - Agent Skills extension for RubyLLM

ruby_llm-tribunal - LLM evaluation framework for Ruby

kling-motio-control - High-quality integration for https://supermaker.ai/blog/what-is-kling-motion-control-ai-how-to-use-motion-control-ai-free-online/

cf-mcp - MCP server providing documentation tools for Cute Framework

grok-video-generator - High-quality integration for https://supermaker.ai/blog/grok-ai-video-generator-the-ultimate-guide-to-creating-ai-videos-2025/

ruby_llm-monitoring - Monitoring engine for RubyLLM

legnext-ruby-sdk - Legnext.ai Midjourney API Ruby SDK

ollama-client - An agent-first Ruby client for Ollama (planner/executor + safe tool loops)

fluxtokens - Official FluxTokens Ruby SDK

rubber_duck - RubberDuck is a Developer error helper gem to help you analyze errors with AI in Rails

traylinx_auth_client - Traylinx Sentinel Agent-to-Agent Authentication Client

its-showtime - Interactive data visualization UI framework for Ruby

claude_agent - Ruby SDK for building AI agents with Claude Code

openclacky - A command-line interface for AI models (Claude, OpenAI, etc.)

renamed - Official Ruby SDK for renamed.to API

rbtoon - Toon parser for Ruby

kie-ruby - Ruby client library for Kie.ai API

rb-edge-tts - Ruby gem for Microsoft Edge's online text-to-speech service

fact_db - Temporal fact tracking with entity resolution and audit trails

fastembed - Fast, lightweight text embeddings for Ruby

archsight - Enterprise architecture visualization and modeling tool

sm-tomusic-ai - High-quality integration for https://tomusic.ai/

ai-homeless-man - High-quality integration for https://supermaker.ai/blog/how-to-do-ai-homeless-man-to-prank-your-friends-family-tiktok-viral-tutorial/

ai-soulmate-sketch-filter - High-quality integration for https://supermaker.ai/image/blog/ai-soulmate-drawing-free-tool-generate-your-soulmate-sketch/

ai-minecraft-image - High-quality integration for https://supermaker.ai/image/blog/how-to-turn-your-image-into-minecraft-skin/

torch-dl - Multi-GPU training for torch.rb

firestore-https-ruby - Model Context Protocol server for Google Cloud Firestore.

firestore-mcp-server - Model Context Protocol server for Google Cloud Firestore.

mcp-https-ruby - Model Context Protocol server implemented in Ruby.

vectra-client - Unified Ruby client for vector databases

New Open Source

Links to the Github repository:

AI Trading Agent - Trading agent combining LLM reasoning via Ollama with real-time DhanHQ market data using a planner-based architecture for options trading analysis

Agent Kit - Toolkit providing shared guardrails, helper scripts, and an automated memory capture system for AI agents to document task outputs in Markdown

MCP UI Rails - Rails engine that renders MCP UiResources into HTML fragments with auto-scaffolding and HTMX support for AI-driven UI composition

MCP Interchange - Bidirectional conversion layer between Rails ViewComponents and MCP::UiResource for serving and consuming UI components across distributed systems

Insight Blog - Rails 8 blogging application featuring a hybrid AI system for content summarization and writing assistance

Agentic UI - UI component system enabling AI agents to dynamically control interfaces through declarative configuration with agents driving real-time styling and behavior

Rails Personal Money Manager - MCP-first personal finance application with double-entry bookkeeping that enables AI assistants to manage finances

Minesweeper for AI - Spectator-only Minesweeper game with an authenticated API designed for AI agents to play through MCP server integration

Rails AI Front - Gem enabling zero-cost AI inference by running LLMs directly in users' browsers using WebGPU and WebAssembly with bidirectional WebSocket orchestration

Azkaban - Autonomous LLM-powered agent that writes code, executes commands, and iterates until tasks complete with OpenAI-compatible APIs

SUSHI Self-Maintenance MCP Server - MCP server providing AI-assisted development support for the SUSHI bioinformatics framework

Prism - Automates i18n file translation using ChatGPT, detecting source language changes and updating target language files via pull request or direct commit

MCP Dev Workflows - MCP for Claude Code that automatically installs packages, generates configuration files, and updates CLAUDE.md with workflow guidelines

Coding Agent - Controlled code-modification agent with read-only exploration, patch-based edits, and linter-verified correctness using Ollama

AI Analytics Demo - Convert natural language questions into SQL queries using GPT-4o-mini for a law firm management system with interactive chart visualizations

Granola CLI - CLI for reading Granola AI meeting notes directly from the local cache with document listing, markdown export, and transcript retrieval

Jobs & Opportunities

Featured

Senior Software Engineer, AI Fleetio is hiring a remote senior engineer to build AI-enabled features for their fleet management platform, requiring 5+ years of Ruby on Rails experience with backend architecture expertise, React/TypeScript proficiency, and demonstrated success building AI-enabled solutions.

One Last Thing

Building a Naver News Watchlist With Ruby on Rails

A complete tutorial showing how to use SerpApi with Ruby on Rails to fetch Naver News results and deliver an automated email digest.

serpapi.com/blog/building-a-naver-news-watchlist-with-ruby-on-rails

Braden Roth of SerpApi demonstrated Building a Naver News Watchlist with Ruby on Rails, creating an API-driven Rails 8 application that automatically monitors South Korea's dominant search portal for keyword-matching articles and delivers daily email digests. The implementation covers service layer isolation for SerpApi interactions, Gmail SMTP configuration, background jobs for scheduling, and comprehensive error handling with admin notifications.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - January 7th, 2026

Matt Solt — Wed, 07 Jan 2026 16:16:21 +0000

Happy New Year! Welcome to the 22nd edition of Ruby AI News! This edition features a look at the exploding trillion-dollar context graph opportunity, the upcoming Ruby Community Conference, a “Charm”-ing new Ruby CLI library, and much more.

Read on the web

Top Stories
Need to Know AI News
Content
Events
- Previous
- Upcoming
Open Source Updates
Jobs & Opportunities
One Last Thing

Need to Know AI News

ClawdBot Peter Steinberger released an open-source personal AI assistant that runs locally on your own devices and connects to WhatsApp, Telegram, Slack, Discord, Signal, and iMessage, with extensible skills available through ClawdHub.

Welcome to Gas Town Steve Yegge released Gas Town, his orchestrator for running 10-30 parallel Claude Code instances, built on his Beads issue tracker with tmux as the UI, seven worker roles, and a "Molecular Expression of Work" (MEOW) stack for durable workflow execution across agent crashes and context exhaustion.

The Importance of Agent Harness in 2026 Philipp Schmid argued that while 2025 was the beginning of agents, 2026 will be about Agent Harnesses, the infrastructure layer that wraps around AI models to manage long-running tasks with prompt presets, human-in-the-loop handling, lifecycle hooks, and context durability to solve model drift.

Step-by-Step Guide to Get Ralph Working and Shipping Code Ryan Carson wrote a detailed guide on Ralph, Geoffrey Huntley's autonomous AI coding loop that runs Claude Code repeatedly in a bash loop, picking stories from a file, implementing them, running tests, and committing until all tasks pass with memory persisting through git commits and text files.

How I Use Claude Code Boris Cherny, creator of Claude Code, shared that his personal setup is surprisingly vanilla since Claude Code works great out of the box, emphasizing there is no single correct way to use it and that each team member uses it differently.

Content

Announcements

A2UI Rails Vicente Reig released a Ruby implementation of Google's Agent-to-User Interface framework for LLM-driven UI generation with DSPy.rb and Turbo Streams. The library enables AI agents to produce structured data describing component types rather than executable code, with data binding via JSON Pointers and Stimulus controllers for reactive updates.

ExecuTorch Ruby Ben Garcia released Ruby bindings for Meta's ExecuTorch runtime to run exported PyTorch models (.pte files) directly in Ruby applications. The gem provides a lighter alternative to torch.rb for production inference while retaining model metadata and introspection capabilities that ONNX compilation loses.

SolidAgent Justin Bowen released a Rails engine extending ActiveAgent with a persistence layer including database-backed context management, declarative tool definitions for LLM function-calling, and real-time UI feedback via ActionCable during tool execution.

HTM Robots: Workers with Collective Memory Dewayne VanHoozer released v0.0.18 of the HTM memory gem with a refactored configuration system. The updated documentation explains the deliberate choice of "robots" over "agents," emphasizing workers with individual identity and working memory that share knowledge through a collective long-term "Hive Mind" stored in PostgreSQL.

AIA v0.10.2 Dewayne also released a breaking change that refactored configuration using anyway_config and added fiber-based parallel MCP server connections via simple_flow. The update introduced --tokens for usage tracking, --no-mcp for faster startup, enhanced logging with lumberjack across three separate logger instances.

TrakFlow Dewayne followed that with a distributed task tracking gem for AI agents featuring DAG-based workflow modeling, Git-tracked JSONL persistence, and content-hashed IDs to prevent merge conflicts in multi-agent environments.

CLAUDE.md for Rails + Inertia.js Josh Pigford shared his starter CLAUDE.md template for AI-assisted development, featuring Rails 8, Inertia.js, and React 19 with emphasis on "Always Works" principles, Minitest-only testing, and a reality check before marking tasks complete.

RailsPrompts Ritesh Chaudhary released a gem for managing AI prompts in Markdown files with ERB interpolation, centralizing prompt management outside business logic for easier version control and review in Rails applications.

Add PostgreSQLAdapter.register_type_mapping Abdelkader Boudih submitted a pull request for a public API for PostgreSQL type registration in Rails, allowing gems like PostGIS and Neighbor to register custom SQL types without monkey-patching internal methods.

Opus 4.5's Playwright Testing Superpower Kieran Klaassen highlighted Claude Code's playwright-test command for end-to-end browser testing during code reviews. The feature maps changed files to routes, navigates pages, captures snapshots, checks console errors, and verifies interactions while knowing when to pause for human input.

TraceBook David Paluy released a Rails engine for LLM interaction telemetry with automatic PII redaction, cost tracking, review workflows, and a Hotwire dashboard for auditing AI usage across providers.

Rails AI Agents Thibaut Baissac expanded his collection of AI development agents with 18 new prompts inspired by 37signals' Fizzy codebase, supporting both vanilla Rails patterns and standard Rails practices.

RubyOnVibes Eric Arnold launched a Rails-based app generator platform that transforms ideas into working applications. The service features an interactive form for specifying requirements with community templates coming soon.

Vanilla Rails Claude Code Plugin Chris Zempel distilled Basecamp's Recordables pattern into a Claude Code skills plugin featuring seven production-tested Rails conventions. The /vanilla-rails:shape command generates scoping and PR decomposition documents that can flow into planning and execution skills.

POSSE Party Rails Architecture Analysis Andy Waite used Claude Sonnet 4.5 to analyze the POSSE Party social media syndication app, finding it diverges from Rails conventions with primarily service objects instead of fat models. The analysis identified patterns including composition-based nested classes, platform adapter strategy implementations, and deliberate model minimalism with business logic fully delegated to services.

Task Master Keith Schacht built a voice-first to-do list that updates in real-time as you speak, using Rails with Turbo patterns and a Python LiveKit agent for voice processing. The architecture flows from WebRTC audio through LiveKit Cloud speech synthesis, executing tools via Rails API calls and broadcasting updates over ActionCable.

JsonMend Oleksii Vasyliev released a Ruby gem to repair malformed JSON strings generated by LLMs. The library handles common AI output issues including missing quotes, trailing commas, Markdown code block wrappers, Python-style booleans, and truncated structures that cause standard JSON.parse to fail.

PicoRuby Calculator Hamachan released a handheld Ruby REPL for the M5Stack Cardputer powered by PicoRuby. The device features real-time code execution, syntax highlighting, multi-line input with auto-indentation, and customizable themes.

Layered Design for Ruby on Rails Applications v2 Vladimir Dementyev announced the second edition of his book covering practical design patterns and modern abstractions for maintainable Rails applications, with additions on AI-related abstraction patterns for Rails.

BrowserPod launched a platform for in-browser code sandboxes using WebAssembly, with Ruby on Rails support coming soon alongside Node.js and Python. The service targets AI agents running code securely at scale, web-based IDEs, and educational platforms with full client-side execution requiring no server provisioning.

Pet Artist AI Mason Wang shipped their first side project in one week, building an AI pet portrait generator using Seedream for creative pet image generation. The tech stack included Rails with ruby-openai, Inertia, Sidekiq, Avo, Pay, and Kamal.

Starship Claude Martin Emde created a Starship prompt integration for Claude Code's status line that displays context window usage as a color-coded progress bar with warning thresholds.

The Ruby Runway Pitch Competition Ruby Central opened applications for RubyConf 2026's startup pitch competition offering up to $30,000 in prizes for Ruby-built products that have raised less than $500K, with regional semifinal winners advancing to live finals at the conference.

Working on ActionMCP for Rails David Heinemeier Hansson shared that he is developing “ActionMCP” for Rails with the help of AI-assisted coding agents.

Articles

AI Needs Its MVC Moment Vicente Reig suggested that LLM development lacks standardized patterns like MVC brought to web frameworks and prompt engineering should be treated as regular programming. Vicente presented DSPy.rb's approach using signatures, type safety, composable modules, and evaluation metrics to bring production-grade discipline to AI systems.

MIPROv2 Paper: How Stanford's Prompt Optimization Works in Ruby Vicente also explained the MIPROv2 algorithm implemented in DSPy.rb, which treats prompt engineering as a machine learning search problem using Bayesian optimization, instruction bootstrapping, and per-predictor tuning.

How I (Accidentally) Started a Newsletter Scott Werner reflected on building Works on My Machine in 2025, which evolved from AI tool demos into philosophical essays about software development in the post-LLM era.

Rails MCP Server 1.5.0: Security Hardening and Sandboxed Environment Support Mario Alberto Chávez Cárdenas released a major update adding centralized path validation, sensitive file filtering, and safer shell execution. The new --single-project flag enables operation in restricted containers like GitHub Copilot and Claude Code with automatic Rails app detection.

Promoting AI Agents David Heinemeier Hansson declared AI agents a paradigm shift, praising Claude Opus 4.5, Codex 5, and Gemini 3 for producing production-grade code while preferring autonomous agents that work like team members over in-editor autocomplete.

Building an AI Agent Inside a 7-Year Old Rails Application Catalin Ionescu demonstrated how LLM function calls can encode authorization logic, enabling secure AI agent integration within an existing multi-tenant Rails monolith. The implementation uses RubyLLM, Algolia search, Pundit policies, and Turbo Streams.

Resilient AI Workflows in Rails 8.1 with Active Job Continuations Islam Gagiev of JetRockets explained how Rails new ActiveJob::Continuable feature enables long-running AI pipelines to resume from checkpoints after interruptions, avoiding wasted LLM API calls. The article demonstrated a four-step report-generation workflow with text extraction, AI summarization, formatting, and delivery.

From Weeks to Days: Rebuilding My Blog with Rails 8 and Cursor AI Keith Wedinger rebuilt his personal blog in days by adopting an architect role while Cursor AI handled model, controller, and view implementation. The stack included Rails 8.1, SQLite3, Hotwire, Tailwind CSS, and Kamal deployment.

Implementing AI Features in Ruby on Rails with LLM APIs Pavel Pershko of Rubyroid Labs provided a comprehensive guide covering SDK selection, AI gem comparison, and production patterns for LLM integration. The article included a Gemini API example and common pitfalls like context overflow and prompt injection.

Exposing a Rails App to LLMs with Model Context Protocol (MCP) Manoj Mishra built a step-by-step tutorial showing how to connect a Rails JSON API to Claude Desktop using a Node.js MCP server as a translator layer. The architecture keeps AI logic separate from Rails while providing explicit permissions, typed inputs, and auditable access.

Stop Using AI to Go Faster. Start Using It to Go Bigger. Joe Leo argued the software industry is misusing AI by treating it as an efficiency tool rather than a transformation catalyst. Joe recommended auditing where manual heroics have the most business impact and targeting long-running cross-functional pain points to find opportunities that collapse entire workflows.

Composable Rules: How Small Teams Match Big Company Output Without the Bloat Brandon Casci demonstrated a modular approach to Claude Code conventions using markdown files with dependency frontmatter in .claude/rules/. His hustler-rails plugin detects project dependencies from Gemfile.lock and copies only relevant rules, enabling systematic knowledge accumulation across projects.

Speak to LLMs with Voice-to-Text Rich Steinmetz advocated for voice-to-text when prompting LLMs, citing brain dumping, speed advantages (80-95 WPM vs typing), and energy management as key benefits. Rich recommended WisprFlow and noted that LLMs can correct minor transcription errors.

How a Scotsman Saved Hours of My Time by Turning an LLM into My Virtual Assistant Rich followed with invoice extraction from a legacy bookkeeping app using Claude Desktop, after a colleague suggested browser automation over hiring a virtual assistant. Rich plans to transition to Playwright MCP server with Claude Code for more autonomous agentic workflows.

Sisyphus Versus the Conductor Obie Fernandez explored why AI feels like cheating to some people, contrasting "monadic" identities built on isolated struggle with "polyadic" selves that maintain coherence through coordination. Obie argued that LLMs collapse the cost of externalized cognition, threatening those who equate visible effort with authenticity while enabling others to focus on direction over execution.

It's Just Their Tokens: Code Review Etiquette in the Vibe Era Martin Emde argued that AI coding agents are straining traditional code review processes and reviewers should request significant changes since regenerating code is now feasible.

Rails + AI: Are You Using These Capabilities Yet? Pichandal Solarajan of RailsFactory outlined six AI capabilities Rails developers can add to applications: vector search with pgvector, personalized recommendations, conversational interfaces via LLM APIs, automated content generation, document intelligence, and predictive insights like churn detection.

Relocating Rigor: The Phoenix Architecture Chad Fowler argued that paradigm shifts from dynamic languages to AI don't eliminate discipline but relocate rigor closer to operational reality, advocating for "probabilistic inside, deterministic at the edges" where easier generation demands stricter judgment.

The Auditability Gap Vicente Reig argued that modern AI systems lack the ability to explain individual decisions, comparing the need for audit trails to Sarbanes-Oxley requirements in finance. Vicente demonstrated an evidence-based approach that traces matched candidates, rejection reasons, and confidence breakdowns to enable accountability.

Dictation Is the New Prompt Carmine Paolino advocated for voice input as a faster, more natural way to interact with AI and introduced Voxtype, a Rust-based local dictation tool using OpenAI's Whisper model that now ships with Omarchy 3.3.

Component Language Interface Brian Shirai proposed replacing JSON serialization between components with executable code as the interface, using Ruby examples to demonstrate how language-based interfaces could enable peer-to-peer architectures and dynamically generated connections produced by machine intelligence.

One Year of Bootstrapping a Profitable AI SaaS on a Side Kirill Shevchenko shared his journey building Roundups, an AI content generator for affiliate marketers, using Rails, Hotwire, OpenAI, and the Solid stack.

Back to the Starting Line Jorge Manrubia reflected on how AI has fundamentally reset programming expertise, suggesting that while traditional skills like editor mastery have diminished in importance, technical excellence and good design principles remain essential as developers learn to collaborate with agentic coding tools.

2025 Wrap Up from the Rails Foundation Amanda Perino summarized the Rails Foundation's year including Rails World 2025 in Amsterdam, the inaugural Rails at Scale Summit, and new educational content like the "On Rails" podcast. Marco Roth received the Rails Luminary Award, and Rails World 2026 was announced for Austin.

Videos

Building an Agent-Native CLI for Cora Kieran Klaassen live-streamed building a CLI for Cora in 90 minutes using Terminalwire for server-streamed updates, demonstrating his Compound Engineering workflow with parallel sub-agents for planning, implementation, review, and triage phases.

Vibe Coding Rails Travel App Series Part 1, Part 2, Part 3, Part 4. Rhiannon Payne streamed a four-part series building a Rails travel map app using AI-assisted "vibe coding" with GitHub Codespaces, Copilot, and Claude Opus 4.5 from initial deployment through UX improvements and feature additions. And don’t forget to check out Rhiannon’s other Ruby Around the World newsletters and interviews.

AI on Rails: Broadcasting Messages Live with Turbo Streams Pete Hawkins of Rapid Ruby refactored an AI chat application to use Turbo Streams for live message broadcasting, making the UI feel more responsive as messages are pushed in real-time.

AI on Rails: Give Your Agents Internet Access Pete also demonstrated using the Tavily search tool included with LangChain.rb to give AI agents web search capabilities and improve their knowledge.

Podcasts

Remote Ruby: Jumpstart Pro Evolution: Streamlining Rails Development Chris Oliver, Andrew Mason, and David Hill discussed Chris's Jumpstart refactoring to reduce merge conflicts and dependencies, AI-assisted coding pitfalls and practical applications, and new web security headers for CSRF protection.

Remote Ruby: Ruby Upgrades & RAM Shortages Chris, Andrew, and David’s next episode discussed the Ruby 4.0 preview release, celebrated Marco Roth's Rails Luminary award, and explored the challenges of self-hosting LLMs on Mac minis including RAM constraints and token costs versus cloud APIs.

Strictly From Nowhere Podcast: A Ruby Gem for Optical Character Recognition (OCR) The hosts discussed Active Storage OCR, a self-hosted Rails gem built with Rust that extracts text from images and PDFs without cloud APIs. The companion article by Justin Abrams provided implementation details and a live demo.

Discussions

Any Vanilla Rails Front-End Setup That Can Compete with ShadCN for LLM Code Generation? A Reddit user asked the r/rails community about frontend setups that work as well as ShadCN with LLMs like Opus 4.5. Top suggestions included InertiaJS with React/Svelte and Claude Code skills, DaisyUI with its MCP server, and Tailwind/Flowbite with ViewComponents.

Events

XO Ruby Chicago:

We Were Voyagers. We Can Voyage Again! Scott Werner presented at XO Ruby Chicago arguing that Generative AI offers Ruby developers a chance to reclaim the playful, creative spirit of the "Golden Age" era of why the lucky stiff, Camping, and Sinatra.

Ruby Warsaw Meetup:

Adding MCP in 5 Minutes Live Demo Paweł Strzałkowski delivered a lightning talk at PLRUG Ruby Warsaw Meetup demonstrating how to quickly add Model Context Protocol to a Rails application.

AI, Offline Chris Hasiński presented at PLRUG Ruby Warsaw Meetup on running AI capabilities without an internet connection.

San Francisco Ruby Meetup:

SF Ruby Meetup, October 2025 The October SFRuby meetup covered a graph-based Ruby DSL for Excel reporting, Ruby-Rust native extensions with the Fjall embedded key-value store, encrypted commit-safe secrets with dotenvx, LiveComponent for stateful ViewComponents on Hotwire, and AI-backed domain logic in Foobara.

San Francisco Ruby Conference:

32 videos were posted from the San Francisco Ruby Conference, some of the AI-related and relevant videos below:

Herb to ReActionView Marco Roth delivered the opening keynote concluding his 2025 journey on modernizing the Rails view layer with Herb, the HTML-aware ERB parser and tooling ecosystem including a formatter, linter, and language server.

Play with Your Code Rachael Wright-Munn explored why programming games are more fun than day jobs and how their lessons can improve the developer experience.

Real-Time Collaboration with Rails, AnyCable and Yjs JP Camara demonstrated how to add sophisticated collaborative editing features to Rails apps using AnyCable for performance and Yjs for CRDT-based conflict resolution.

Programming Language Evolution in the AI Era José Valim shared his pragmatic take on how web frameworks and developer tools need to evolve to meet the demands of AI-assisted development, drawing on experience as Elixir and Tidewave.ai creator.

The Role of Software Design in an AI World Sarah Mei shared insights at SF Ruby Conference from six months of working with code assistants in real Rails codebases, offering a perspective on using AI to enhance developer roles rather than replace them.

Rails X Vladimir Dementyev delivered the closing keynote presenting a vision for the future of Rails informed by developer surveys and his work with Ruby startups.

RubyLLM Keynote Carmine Paolino keynoted the conference arguing that complexity is a liability in AI development, explaining the design decisions behind RubyLLM's unified API for every model and vendor.

Upcoming

January 20th - Meetup: Scott Werner will present at Philly.rb on January 20th in Philadelphia exploring whether AI agents represent a new programming paradigm, drawing parallels to Alan Kay's original object-oriented concepts and demonstrating a minimal Ruby environment where markdown files are the program.

January 31st - Conference: RubyConf Thailand is hosting a conference on January 31st and February 1st in Bangkok, Thailand featuring presentations by Irina Nazarova, Marco Roth, Alex Timofeev on Ethical AI, and a closing keynote by RubyLLM author Carmine Paolino.

February: ArtificialRuby will host their next event sometime in early February in New York City, more details to follow soon.

March 13th - Conference: The Ruby Community Conference Winter 2026 in Cracow, Poland will have a heavy focus on Ruby and AI, with presentations and workshops including:

Obie Fernandez: Ruby & AI Conversation
Irina Nazarova: Startups on Rails and AI Integration Patterns
Carmine Paolino: Building AI Apps in Ruby and Rails with RubyLLM
Paweł Strzałkowski: Model Context Protocol in Ruby on Rails

Open Source Updates

Code Spotlight

GitHub - swombat/helix_kit: Core template for full-featured Svelte/Rails/Inertia apps

Core template for full-featured Svelte/Rails/Inertia apps - swombat/helix_kit

github.com/swombat/helix_kit

Daniel Tenner is working on Helix Kit, a Rails 8 and Svelte 5 starter template designed with the philosophy that modern apps require heavy AI integration. The stack combines Inertia.js, TailwindCSS, and ShadcnUI on the frontend, with PostgreSQL and ActionCable for real-time synchronization on the backend. AI features include OpenRouter support, a prompt system, conversation management, and agentic systems with tools, alongside collaborative features like group chat with memory management. The template is marketed as "Claude Code Ready" with documented setup for AI-assisted development workflows.

New Gems

Links to the RubyGems page, newest releases are first:

semantic_chunker - Split long text into chunks based on semantic meaning.

first-last-frame - High-quality integration for https://supermaker.ai/video/first-last-frame/

ai-kissing - High-quality integration for https://supermaker.ai/video/ai-kissing/

openrouter_client - Ruby client for OpenRouter API

omniai-sdk - Official Ruby SDK for OmniAI API

nukitori - Generate reusable XPath schemas with an LLM, then scrape HTML without AI

ruby-json-toon - Convert JSON to TOON (Token-Oriented Object Notation)

ai-make-music - High-quality integration for https://supermaker.ai/music/ai-make-music/

ai-baby-generator - High-quality integration for https://supermaker.ai/image/ai-baby-generator/

bigfoot-video-generator - High-quality integration for https://supermaker.ai/video/bigfoot-video-generator/

ruby_llm-instrumentation - Rails instrumentation for RubyLLM

airbrake_mcp - MCP server for Airbrake error tracking

opencv-ruby - Modern Ruby bindings for OpenCV4

sm-chat - High-quality integration for https://supermaker.ai/chat/

seedance-ai-video - High-quality integration for https://supermaker.ai/video/seedance-ai-video/

chat-1 - High-quality integration for https://supermaker.ai/chat/

sora-ai-video - High-quality integration for https://supermaker.ai/video/sora-ai-video/

mcp_stdio_ruby - A Ruby based Model Context Protocol (MCP) server

reve_ai - Ruby client for the Reve image generation API

fastlane-plugin-ovo_onetrust - Fastlane plugin to upload mobile app builds to OneTrust and trigger automated SDK scanning

flowmyna - FlowMyna SDK

banana-prompts - High-quality integration for https://bananaproai.com/banana-prompts/

diffrhythm.ai - High-quality integration for https://diffrhythm.ai/

makeshot.ai - High-quality integration for https://makeshot.ai/

ruby_llm-responses_api - OpenAI Responses API provider for RubyLLM

trak_flow - A distributed task tracking system for Robots

crucible - MCP server for browser automation using Ferrum/Chrome

webxr - WebXR Device API bindings for Ruby

vaultkit - VaultKit CLI

executorch - Ruby bindings for ExecuTorch

larb - Linear algebra library for 2D/3D graphics in Ruby

pixoo - A Ruby client for Pixoo displays

gw - Git worktree manager with bare repository pattern

chromadb-experimental - Chroma Ruby client

rubyllm-semantic_router - Semantic routing for RubyLLM multi-agent systems

smart_domain - Smart Domain-Driven Design and Event-Driven Architecture for Rails

nano-banana-2 - High-quality integration for https://supermaker.ai/image/nano-banana-2/

veo - High-quality integration for https://supermaker.ai/video/veo/

wgpu - Ruby bindings for WebGPU via wgpu-native

a2ui-rails - A2UI for Rails - LLM-driven UI generation with Turbo Streams

sotavideo.ai-1 - High-quality integration for https://sotavideo.ai/

sotavideo.ai - High-quality integration for https://sotavideo.ai/

tomusic.ai-1 - High-quality integration for https://tomusic.ai/

bananaproai-com - High-quality integration for https://bananaproai.com/

copy_for_ai - Copy Rails error messages in AI-friendly format

devex - Ruby CLI framework with unified dx command for development tasks

tencentcloud-sdk-cloudmate - Tencent Cloud SDK for Ruby - CLOUDMATE

tabula-rb - Extract tables from PDF files (Ruby port of tabula-java)

sm-ai-pose-generator - High-quality integration for https://supermaker.ai/image/ai-pose-generator/

ai-pose-generator-3 - High-quality integration for https://supermaker.ai/image/ai-pose-generator/

ai-pose-generator-1 - High-quality integration for https://supermaker.ai/image/ai-pose-generator/

ai-pose-generator - High-quality integration for https://supermaker.ai/image/ai-pose-generator/

nano-banana-1 - High-quality integration for https://supermaker.ai/image/nano-banana/

ai-twerk-video-generator - High-quality integration for https://supermaker.ai/video/ai-twerk-video-generator/

adk-ruby - Agent Development Kit (ADK) for Ruby

opencode_client - OpenCode Ruby Client Gem

pobo-sdk - Official Ruby SDK for Pobo API V2

tensorrt - Minimal TensorRT bindings for Ruby using Rice

invoiceai - Official Ruby SDK for the InvoiceAI API

signalbox - DCC model railroad automation framework with sensor-driven control

supermaker-ai-image-master-2 - High-quality integration for https://supermaker.ai/image/

rails_claude_skills - Rails generators for Claude AI skills and agents

supermaker-ai-image-master-1 - High-quality integration for https://supermaker.ai/image/

qy-soulmate-drawing-generator - Professional AI Soulmate Drawing Generation Integration

qy-minecraft-skin-generator - Professional AI Minecraft Skin Generation Integration

Anti-gravity-qy - High-quality integration for https://antigravity.google/

qualspec - RSpec DSL for qualitative LLM-judged testing

ag-ui-protocol - Ruby SDK for AG-UI protocol

luciq-cli - Luciq CLI for developers

supermaker-ai-video-downloader - A lightweight utility library for managing and generating dynamic links with tracking parameters

supermaker-ai-image-master - A lightweight utility library for managing and generating dynamic links with tracking parameters

activestorage-ocr - OCR support for Rails Active Storage

claude_usage - Track Claude Code token usage and costs in Rails applications

json_mend - Repair broken JSON

langsmith-sdk - Ruby SDK for LangSmith tracing and observability

riffer - The all-in-one Ruby framework for building AI-powered applications and agents

simple_inference - A lightweight, Fiber-friendly Ruby client for OpenAI-compatible LLM APIs

daytona - Ruby SDK for Daytona

daytona_toolbox_api_client - Daytona Daemon API Ruby Gem

decision_agent - Deterministic, explainable, auditable decision engine for Ruby

New Open Source

Links to the Github repository:

HyperSense - Autonomous AI trading agent for cryptocurrency markets using Claude AI with multi-agent architecture, technical analysis, and real-time risk management

Orion - Distributed automation platform combining workflow orchestration with AI-powered generation, fiber-based concurrency, and multi-language plugin support

Aura - Declarative programming language for AI/ML pipelines that transpiles to Ruby, combining model training and web deployment in a single human-readable syntax

Debrief PWA - Voice memo progressive web app that records audio, transcribes via Groq Whisper, and pushes transcripts to Claude Code for processing

SaneProcess - Enforcement framework for Claude Code that prevents AI failure loops through circuit breakers, structured rules, and persistent memory tracking

Decision Agent Example - Demo showcasing the decision_agent gem with rule-based evaluation, A/B testing, versioning, and use cases like loan approval and fraud detection

Ruby Agent Skills - Claude Code plugin providing five auto-activated skills for generating, validating, and maintaining RBS type signatures

AICR - Automated code review tool combining RuboCop static analysis with LLM intelligence to review only changed lines and post suggestions to GitHub PRs

MindMush - Rails platform for creating and sharing AI-generated HTML5 Canvas games from natural language prompts using Groq

Reddit MCP - MCP server that provides Reddit search, post retrieval, and trending content tools for Claude Code and other MCP-compatible clients

Blazer Querygen - Blazer extension that generates SQL queries from natural language using OpenAI while only transmitting schema metadata for security

TaAgent - CLI-based technical analysis agent for Indian stock markets with multi-timeframe trend analysis and optional LLM-powered insights via Ollama

PlacesAgent - AI-powered gem combining Google Places API with LLM intelligence to discover and rank businesses through natural language queries

Page Migration - CLI tool for extracting, exporting, and migrating organization page content using the Dust AI API with a Rails dashboard for monitoring

Rails Project Templates - Automated menu system that generates and configures common Rails features including AI support, Data.gov API ingestion, and default views

Output Workflows Rails - Rails SDK for Output.ai enabling AI workflow execution via webhooks, background polling, or synchronous blocking with database tracking

Voice Gen BE - Rails API for AI-powered text-to-speech generation using ElevenLabs with S3 storage, Pusher real-time updates, and email notifications

Systools Ruby MCP - MCP server providing Claude Code-style tools with reduced token overhead for file operations, shell commands, code search, and LSP integration

Banana AI Assistant - Rails 8.1 chat interface for Azure DevOps project management using Llama 3 via Groq to summarize work items, sprints, and team workloads

Store MCP Server - Experimental Rails app demonstrating MCP server integration with product CRUD tools and AI-powered summaries via Claude SDK

AI Voice Tutor - Real-time voice conversation system enabling natural dialogue with AI using AssemblyAI, Gemini, and Cartesia with full-duplex bidirectional communication

SUSHI Self-Maintenance MCP Server - MCP server providing AI-assisted development support for the SUSHI bioinformatics framework

Rails Error to Clipboard - Development gem that adds a "Copy for AI" button to Rails error pages, formatting stack traces as Markdown for AI assistants

Jobs & Opportunities

One Last Thing

Ductwork

Build Powerful Pipelines in Ruby

www.getductwork.io

Tyler Ewing introduced Beyond Job Queues: Introducing Ductwork for Ruby, a framework for orchestrating multi-step background job pipelines that addresses the limitations of traditional queues like Sidekiq and GoodJob. Ductwork provides a declarative DSL for defining workflows as a single visible unit with self-contained, testable steps and automatic data coordination. The framework supports sequential chains, parallel branches via Expand/Collapse and Divide/Combine patterns, and database-backed execution state for monitoring. A paid tier adds concurrency controls, timeouts, delays, and priority support.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - December 19th, 2025

Matt Solt — Fri, 19 Dec 2025 13:01:28 +0000

Welcome to the 21st edition of Ruby AI News! This edition features a RubyLLM backed startup, an AI YouTube video repsitory, Videos on Ruby AI, and much more.

That’s all for Ruby AI News in 2025. Have a great holiday and a safe and happy new year. See you in 2026!

Read on the web

Top Stories
Need to Know AI News
Content
Events
Open Source Updates
One Last Thing

Need to Know AI News

Relevant AI News for Ruby Developers

State of AI: An Empirical 100 Trillion Token Study OpenRouter analyzed over 100 trillion tokens of LLM usage across 300+ models, finding that programming surged to more than 50% of LLM usage with Claude dominating 60% of that share. The study revealed open-source models captured roughly 30% of usage, agentic inference became the default with reasoning models exceeding 50% of tokens, and Chinese models like DeepSeek and Qwen reshaped competitive dynamics.

Donating the Model Context Protocol and Establishing the Agentic AI Foundation Anthropic is donating MCP to the Agentic AI Foundation, a fund under the Linux Foundation. In its first year, MCP grew to over 10,000 active servers, with adoption across major AI coding platforms.

Introducing x402 V2: Evolving the Standard for Internet-Native Payments x402 released version 2 of the protocol that embeds payments into HTTP using the 402 status code. Since its May 2025 launch, x402 has processed over 100 million transactions, with the new version adding wallet-based sessions and extensible architecture to support AI agents purchasing compute and data on-demand.

Introducing the Agentic Commerce Suite Stripe announced a platform for businesses to sell through AI agents, featuring hosted ACP endpoints for product discovery, Shared Payment Tokens for secure transactions, and fraud protection via Stripe Radar.

Chrome in Claude Anthropic launched a beta browser extension enabling Claude to navigate, click, and fill forms directly in Chrome. The extension integrates with Claude Code via the /chrome command, allowing automated testing of code in the browser and visibility into client-side errors through console logs.

Agent Skills Anthropic released Agent Skills as an open standard for giving AI agents new capabilities through discoverable folders containing instructions, scripts, and resources. The format has been adopted by Cursor, Claude Code, GitHub, VS Code, and OpenCode, enabling skill authors to build once and deploy across multiple agent products.

Content

Announcements

https://x.com/alxshp/status/2001715201469747291

ActiveRabbit Alex Shapalov launched an open-source AI-powered performance monitoring and error tracking platform for Rails applications. The tool provides real-time monitoring across error types with AI root cause analysis and auto-fix suggestions under the Once O’Saasy license.

NanoGPT-rb Chris Hasiński ported Andrej Karpathy's nanoGPT to Ruby using torch.rb for training GPT-2 style language models from scratch. The implementation includes Flash attention optimization, GPU acceleration via MPS and CUDA, and achieves coherent text generation after roughly 2000 iterations on Apple Silicon.

Leva Kieran Klaassen added DSPy.rb integration to the Leva Rails prompt management engine, enabling automatic prompt optimization with Bootstrap, GEPA, and MIPROv2 strategies. The latest release includes a PromptOptimizer service, SignatureGenerator, and optimization tracking powered by the dspy.rb gem.

Google ADK for Ruby Landon Gray released an unofficial Ruby port of Google's Agent Development Kit. The gem supports LLM agents, sequential/parallel/loop workflows, tool integration, and session management using Gemini models.

HTM MCP Server Dewayne VanHoozer added an MCP server to the Hierarchical Temporal Memory gem enabling AI assistants to store, recall, and manage memories. The latest release includes Robot Groups for high-availability coordination with shared working memory, automatic failover, and synchronization across multiple robots.

dspy-rb-skill Vicente Reig released a Claude Skill that equips Claude Code with DSPy.rb knowledge for type-safe LLM development in Ruby, featuring Sorbet type annotations, ReAct/CodeAct agents, and MIPROv2 optimization.

Security in the Age of AI Workshop Greg Molnar announced a live online workshop (paid, $50) on December 19th at 5:30pm GMT covering LLM security risks and how AI-powered features can be exploited when integrated into applications.

Sentry Agents Istvan Hoka extracted a Ruby gem that brings Sentry's Generative AI monitoring to Ruby applications. The gem provides observability for agent execution flows, token tracking, and tool execution with auto-instrumentation for RubyLLM and LangChain.rb.

AI Guardrails Faisal Raza built a Ruby gem that validates, repairs, and secures LLM outputs. The gem automatically fixes broken JSON, enforces schema validation, blocks unsafe content, and includes retry logic with auto-correction for production use.

Rails AI Agents Thibaut Baissac released a collection of 20+ specialized GitHub Copilot agents for Rails 8.1 development that follow TDD workflows. The agents cover feature planning, red-green-refactor testing cycles, and implementation specialists for models, services, controllers, policies, ViewComponents, and Solid Queue jobs.

LLM Classifier Dmitry Sychev created a Ruby gem for building LLM-powered classifiers with a clean DSL. The gem supports multi-label classification, domain knowledge injection, Rails integration with ActiveRecord concerns.

Claude Ruby Plugins Stephen Ierodiaconou released a Claude Code plugin marketplace providing skills, agents, and commands for writing Ruby RBS type signatures. The plugin includes agents for creating, maintaining, reviewing, and converting RBS annotations, plus a runtime type tracer that helps discover actual method return types during execution.

Unofficial 37signals Coding Style Guide Marc Köhlbrugge extracted transferable Rails patterns from analyzing pull requests in 37signals's Fizzy codebase, documenting conventions for CRUD controllers, Stimulus/Hotwire, multi-tenancy, and AI/LLM integration with emphasis on rich domain models and vanilla Rails.

Fizzy Skill Rob Zolkos made a Claude Code skill that integrates with Fizzy for managing boards, cards, and tasks through natural language commands in the terminal.

fizzy-cli Rob also released a Ruby CLI for 37signals' Fizzy project management tool, designed to be LLM-friendly for AI assistant integration. The tool was built using the newly released Fizzy API.

Custom GitHub Copilot Agent for Fixing Rails Errors with Honeybadger Joshua Wood shared an agent that integrates Honeybadger's MCP server to debug Rails production errors. The agent fetches real-time error data, stack traces, and affected user patterns, then follows a structured workflow to diagnose root causes.

DeepRails launched a guardrails platform that detects and fixes LLM hallucinations in real-time. The service offers SDKs for Ruby, Python, Go, and TypeScript with metrics for correctness, completeness, adherence, and safety evaluation.

Ruby Users Forum Is Launching Soon Javier Cervantes announced a new discussion platform for Ruby featuring topic-based organization, advanced search, and discussions designed to preserve knowledge that gets lost in chat-based communities.

Articles

AI for Ruby Devs Part I: From the Basics to Building a Neural Network David Sanchez walked through machine learning fundamentals and built a working neural network from scratch in pure Ruby. The tutorial implemented forward propagation, backpropagation, and gradient descent using a student test score prediction example.

AnyCable, Rails, and the Pitfalls of LLM Streaming Vladimir Dementyev of Evil Martians exposed Action Cable's threading issues causing out-of-order messages and connection loss problems when streaming LLM responses, then demonstrated how AnyCable provides message ordering and at-least-once delivery guarantees with a simple gem swap. He also revealed AnyCable has begun adopting Durable Streams!

Announcing Raix 2.0 Obie Fernandez released a major update to the Ruby AI eXtensions library featuring RubyLLM as a unified backend for multiple providers and a new before_completion hook system. The hooks enable dynamic model selection, PII redaction, request logging, system prompt injection and A/B testing.

Design Previews for Ruby on Rails Avi Flombaum introduced ActionVersionPreview, a Rails gem that preserves multiple LLM-generated UI iterations for side-by-side comparison. The gem uses Rails view variants with a +variant suffix pattern and requires zero configuration. Learn more at the ActionVersionPreview documentation site.

Rails MCP Server: Context-Efficient Tool Architecture Mario Alberto Chávez redesigned the Rails MCP Server to reduce context consumption by cutting registered tools from 12 to 4 with progressive discovery via search_tools. The update replaced regex parsing with Rails reflection APIs and Prism AST analysis, added a sandboxed execute_ruby tool, and introduced an interactive configuration tool with Quick Start guides.

Introducing the Rails Superhero Card Generator Fiona Lapham of OmbuLabs walked through building a Rails-themed holiday card generator (in Python) using LlamaIndex orchestration. Ernesto Tagwerker announced the open-source release as one of several experiments exploring practical AI applications, while Gelsey Torres wrote about Hacktoberfest Open Source Contributions featuring updates to Active Agent, DSPy.rb, and langchain.rb.

Same Revolution, Different Tools Robert Beene synthesized insights from three conference talks into a framework for developers directing AI systems: control the objective through clear intent, control the context via mandatory guidelines, and control access with proper governance.

Why We Built Claude OS and What It Actually Is Bob Roberts released Claude OS, a persistent memory system for Claude Code that reduces the time spent rebuilding context across sessions. The local-first tool combines SQLite storage, vector embeddings, and tree-sitter AST parsing to index files, and works well with Ruby on Rails projects.

Building LLM-Powered Applications in Ruby: A Practical Introduction Germán Giménez Silva summarized Koichi Ito’s “Ruby × LLM Ecosystem” Ruby World Conference presentation covering RAG implementation, LangChain.rb, and the Model Context Protocol's new Ruby SDK.

Exploring the World of Electronic Engineering with PicoRuby and A Definitive Guide to Running PicoRuby on ESP32 Germán also published companion guides covering PicoRuby's hardware capabilities on RP2040 and ESP32 microcontrollers, including GPIO, PWM, and sensor control with practical examples from Hayao Kimura's Ruby World Conference presentation.

Git Worktrees with Parallel Agents in Practice Rich Steinmetz offered an assessment that parallel agent workflows remain limited by both engineer skill and agent behavior (tasks complete too quickly, agents exit early when in doubt), but shared his Ruby script with Ultrathink A/B mode for evaluating multiple Claude Code solutions simultaneously.

A Trap with GlobalIDs Julik Tarkhanov warned that Rails GlobalIDs are unsafe for LLM tool calls because models can fabricate GIDs that bypass authorization and access other users' records. Julik recommended using signed IDs with purpose parameters or a custom locator that validates numeric primary keys.

What Happens When the Coding Becomes the Least Interesting Part of the Work Obie Fernandez argued that "senior thinking" (blast radius awareness, sequencing instincts, reversibility preferences, social awareness) is what coding agents can't replicate, but pair programming with Claude Code forces engineers to articulate this tacit knowledge aloud, making them better.

Vibe Coding in style.md Irina Nazarova and Vladimir Dementyev of Evil Martians documented how they created an AGENTS.md file by comparing vibe-coded Rails apps against Vladimir's refactored versions, capturing patterns like domain naming, enums for state, and namespaced classes to make AI-generated code maintainable.

Cooking with Gas, Saving an Afternoon in the Library, and On Thoughts About Language The Weekly Vivarium by Brian Shirai detailed progress reviving the Rubinius language platform with a new rbx compiler that unifies Ruby and Python via LLVM that preserves dynamic features through deoptimization, with plans for unified testing specifications across Ruby implementations.

Compound Engineering: How Every Codes with Agents Dan Shipper and Kieran Klaassen shared details on compound engineering, a methodology where each feature makes the next easier through a learning loop that documents bugs and solutions for future agents. Their four-step process (Plan, Work, Assess, Compound) uses Claude Code with 12 parallel review subagents, enabling single developers to run entire products.

Is Traditional Machine Learning Dead? Comparing LLMs and Gradient Boosting Wouter Massa of Gusto compared LLMs against XGBoost for mapping Gusto categories to bookkeeping accounts, finding gradient boosting achieved 20% higher user acceptance and reduced inference time. The article concluded that LLMs enable rapid prototyping, but specialized machine learning algorithms excel at specific ranking tasks.

Git Worktree: Scaling Your AI Workflow Harisankar P S explained how git worktree enables parallel AI development by creating sibling directories where multiple Claude Code or Cursor instances can work simultaneously on different branches.

The AI Wildfire Is Coming Justin Searls shared Dion Lim's analysis on the coming AI market correction, noting that he and Scott Werner used the same wildfire analogy in their Hot Fix episode. Justin argued that rather than retreating during downturns, companies should invest aggressively when competitors are cashing out.

Rails 6 to Rails 8 in 130 Minutes Roger Heykoop documented upgrading an open-source API across two major Rails versions in just over two hours, combining AI assistance with 19 years of Rails expertise to handle the compatibility debugging while the agent performed repetitive fixes.

How the Junior to Senior Dev Problem Will Be Solved Daniel Tenner argued that the traditional conveyor belt from junior to senior developer is economically dead since tokens are cheaper than training humans, but predicted passionate developers will bootstrap themselves using AI tutors while the rest exit the field.

Rich Prompting, Agentic Viewports, and More José Valim announced Tidewave updates including agentic viewports that allow AI coding agents to automatically resize browser dimensions when debugging responsive design issues. Depth-Based Inspector, Sunsetting /tidewave, and More introduced a depth-based inspector that displays all DOM elements at a clicked position via contextual menu, eliminating full DOM traversal. The /tidewave route is also being deprecated in favor of a dedicated app to support long-running processes required by coding agents.

RubyMine 2025.3: Multi-Agent AI Chat, Rails-Aware MCP Server, Faster Multi-Module Projects Startup, and More Alexey Varfolomeev of JetBrains announced RubyMine 2025.3 featuring a unified multi-agent AI chat combining Claude Agent with Junie and a Rails-aware MCP server for AI-assisted code exploration.

Videos

Technology for Humans: The Survey Results Errol Schmidt from reinteractive presented findings from a survey of Ruby and Rails leaders and executives on current trends, AI, and the future of Rails.

DSPy Interview Series: Vicente on DSPy for Ruby, BAML, and the New Era of AI Engineering Information Shelf interviewed Vicente Reig, author of dspy.rb, about porting Stanford's DSPy framework to Ruby, integrating with RubyLLM, the importance of observability in AI projects, and the evolving landscape of AI agents and workflows.

Building a Podcast Directory in Rails with an AI Assistant Chad Pytel and Moses Amama from Thoughtbot kicked off development of a creator-friendly podcast directory in Rails, demonstrating how AI can accelerate both design and development workflows during their livestream.

AI (on Rails) 101 Episode II: Uncluttered AI-Driven Experiences in Rails João Malheiros of Codeminer42 explored and compared Ruby gems that integrate LLM providers into Rails projects as part of their ongoing AI on Rails series.

Building Insignia Live: Learning and Building (Rails + Hotwire) Ft ChatGPT x Codex Abdulrasaq Mustapha livestreamed building a digital ID card SaaS platform with Rails 8, Hotwire, and Stimulus, working through user roles, organization onboarding, and card creation workflows in public.

Podcasts

The Ruby AI Podcast: Running Self-Hosted Models with Ruby Joe Leo and Valentino Stoll interviewed Chris Hasiński about self-hosting AI models for control over updates and fine-tuning, LLM limitations when generating Ruby code, and the need for investment in Ruby's ML tooling ecosystem.

Indie Rails: Ernesto Tagwerker: OmbuLabs on AI Jeremy Smith and Jess Brown talked with Ernesto Tagwerker about how OmbuLabs uses LLMs to accelerate Rails application upgrades, their Bonsai fixed-cost maintenance service, and new AI-powered offerings for code assessments and development.

Shawn Ryan Show: Tobi Lütke: How Shopify Became a Cheat Code for Entrepreneurs Shawn Ryan interviewed Shopify CEO and Rails core contributor Tobi Lütke about building Shopify on Ruby on Rails from a snowboard shop, creating Active Merchant, and AI's growing role in business and the future of work.

Discussions

LLM Request Logging for Ruby Avi Flombaum asked the community for recommendations on logging LLM requests in Ruby, seeking tools to track tokens, response time, and costs with RubyLLM integration, ideally as a Rails engine.

Ruby Is the Perfect Language for This Style of Vibe Coding A thread on Reddit introduced "Inside-Out Vibe Coding," an experimental approach where method_missing intercepts undefined calls and triggers small LLMs to generate missing code iteratively, leveraging Ruby's metaprogramming and Prism parser.

What Does Your AI Dev Setup Look Like? A Reddit user considering Tidewave asked Rails developers about their AI coding setups, with responses ranging from Claude Code with claude-on-rails and superpowers in devcontainers to RubyMine with Junie, Zed with Copilot, Gemini CLI, and Cursor with Opus plan mode.

Events

There are currently no Ruby AI events scheduled within the next month.

Previously: Victoria Melnikova and Irina Nazarova recapped Why Evil Martians Hosted a Ruby Conference in San Francisco, explaining how monthly San Francisco Ruby meetups starting in March 2024 grew into a three-day conference at Fort Mason in November of this year. The event brought 400+ Ruby engineers together with dozens of startup demos, with technical talks covering YJIT performance, MCP tooling, and Rails scaling. The organizers positioned SF Ruby as a statement that Ruby remains the framework powering the next generation of startups, with talk recordings coming soon.

Open Source Updates

Code Spotlight

GitHub - parruda/swarm

Ruby gems for general-purpose AI agent systems: automation, research, data processing, customer support, content creation. SwarmSDK provides single-process orchestration, persistent memory with sem...

github.com/parruda/swarm

Paulo Arruda's Swarm Ruby framework for orchestrating multi-agent AI systems has constantly improved and innovated. Built on RubyLLM , and recently decoupled from Claude Code, it enables agents to collaborate with specialized roles, tools, and delegation capabilities across agentic coding providers. The latest improvements introduced include context preservation controls for delegation, citation extraction with streaming support, lazy tool activation, asynchronous execution timeouts, and intelligent LLM retry logic differentiating client from server errors.

New Gems

Links to the RubyGems page, newest releases are first:

exaonruby - Client for the Exa.ai API with CLI, middleware, and Rails integration

jules-ruby - Ruby CLI for the Jules API

hotwire_club-mcp - MCP server for Hotwire Club knowledge base - provides tools for searching, browsing, and discovering documentation

action_version_preview - Preview multiple view variants side-by-side using Rails built-in view variants.

rails_prompts - Manage AI prompts in Rails applications with ERB templates

sentry-agents - Sentry Gen AI instrumentation for AI/LLM agents in Ruby

google-adk - Unofficial Ruby implementation of Google's Agent Development Kit

ferrum-mcp - Browser automation server implementing the Model Context Protocol

personality - MCP server for personality communication rules

labnocturne - Ruby client for Lab Nocturne Images API

ruby_llm-semantic_cache - Semantic caching for RubyLLM applications

ai_screen_analyzer - Adds a floating button on any page to capture the screen, send for analysis, and display the result on a sidebar

ai_guardrails - Schema validation and safety layer for AI-generated output in Ruby

tensor - Fast tensor/matrix operations for Ruby using OpenMP and OpenBLAS

shai-cli - CLI tool for managing shared AI agent configurations

ruby_llm-red_candle - Red Candle provider for RubyLLM - local LLM execution using quantized GGUF models

helicone-rb - Ruby client for Helicone AI Gateway with agentic tool support

dspy-ruby_llm - RubyLLM adapter for DSPy.rb - unified access to 12+ LLM providers

naiso - Auto-split long detailed images based on solid/gradient background areas

portable_mruby - Build portable Ruby executables using mruby and Cosmopolitan Libc

cov-loupe - MCP server + CLI for SimpleCov coverage data

fal-ai - Ruby client for fal.ai generative AI platform

torch-ddp - Distributed data parallel support for torch-rb

magika - Determines file content types using AI

New Open Source

Links to the Github repository:

Hotwire Club MCP - MCP server providing searchable access to Hotwire Club documentation with category filtering and related content discovery

Decision Agent - Deterministic decision-making engine with explainable outputs, audit replay, conflict resolution, and optional AI enhancement for regulated domains

MCP on Rails - Rails server implementing the Model Context Protocol to connect AI assistants with Azure DevOps and PostgreSQL databases

Trait AI - Rails chatbot with persistent user memory, adaptive personality traits, and content moderation that evolves through conversation patterns

AI Shopping Assistant - Conversational e-commerce platform using OpenAI with multi-agent architecture for natural language product search and basket management

Redmine MCP - Redmine plugin that exposes an MCP server with tools for AI assistants to manage issues, projects, time tracking, and wikis

AI Screen Analyzer - Rails engine that captures page screenshots and sends them to an LLM for visual analysis with results displayed in a sidebar

AI Voice Bot - Embeddable voice-enabled chat widget using Web Speech API with OpenAI integration and an admin dashboard for managing FAQs and products

One Last Thing

Tnkr

Where The World Builds Robots

www.tnkr.ai

Tnkr is a collaboration platform for robotics builders that unifies hardware documentation, software integration, operational data, and model deployment. The platform introduces Leonardo, an AI assistant that analyzes POV build videos, CAD files, and code to automatically generate step-by-step assembly documentation. Key features include integration with development tools like Onshape, SolidWorks, and GitHub, along with a data contribution loop where community members can deploy VLA models to hardware and contribute real-world operational data back to improve training. The platform targets open-source robotics projects ranging from humanoids to quadrupeds with 3D visualization and documentation capabilities.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - December 3rd, 2025

Matt Solt — Wed, 03 Dec 2025 19:31:21 +0000

Welcome to the 20th edition of Ruby AI News! This edition features notes on the SF Ruby conference and community, DSPy.rb’s LLM-enabled documention, the surprise open source release of Fizzy, and much more.

I’m trying out a modified content format, let me know what you think. While I can’t always incorporate everything, feedback is always welcome: matt@roboruby.com. Let me know how I can improve the newsletter and make it more valuable read!

Read on the web

Top Stories
Content
Events
Open Source Updates
Jobs & Opportunities
One Last Thing

Content

Announcements

Compounding Engineering - AI Development Tools

Get 12 expert code reviews in 30 seconds. 23 specialized agents that make today's work easier than yesterday's.

everyinc.github.io/compounding-engineering-plugin

Compounding Engineering Plugin Kieran Klaassen released v2 of the Claude Code plugin featuring commands for planning, working in isolated git worktrees, and multi-agent code review with specialized reviewers. Kieran noted in a video tutorial on the plugin that Opus 4.5's ability to maintain context across parallel threads made this release possible.

Blazer AI Kieran Klaassen also released a Ruby gem that adds AI-powered natural language to SQL generation for Andrew Kane's Blazer gem using RubyLLM. The gem supports all RubyLLM providers with built-in security restricting queries to SELECT and WITH statements only.

Leva Kieran kept on shipping and updated the design on his LLM evaluation framework for Rails that enables systematic testing of language models against production ActiveRecord data with experiment tracking and a built-in UI at a mountable /leva endpoint.

Ruby LLM Agents Adham EL-Deeb released a Rails engine for building LLM-powered agents with RubyLLM, featuring execution logging, cost tracking, and a Turbo-powered analytics dashboard.

We're Doing It Live Joe Leo announced Phoenix's first public onboarding event "Get Flying with Phoenix" offering live setup assistance, 1,000 free credits, and direct team interaction for repository activation.

OG Pilot Raul Popadineți launched an AI-powered service that automatically generates branded Open Graph preview images for websites, pulling titles, colors, and favicons to create social media previews across multiple design styles without manual design work.

FerrumMCP Eth3rnit3 released a Ruby-based browser automation server implementing Model Context Protocol support with tools for navigation, DOM interaction, screenshots, and JS execution. The gem features multi-session management, BotBrowser anti-detection mode, and Docker images.

CraftDesk Maciej Mensfeld announced his Rails-built package manager for AI capabilities in Claude Code will be going open source. The current CLI tool manages skills, agents, commands, hooks, and plugins with dependency resolution, lockfiles, and knowledge sharing via the command line.

Claude Code Architecture Thibaut Baissac released a Rails-specific configuration for Claude Code with specialized skills for MVC patterns, ActiveRecord, and Hotwire, plus agents for code review, refactoring planning, and RSpec debugging.

Intelligence Kristoph updated his Ruby gem for uniformly interacting with LLM APIs across multiple providers to support Google's Gemini 3.0 API changes.

Ruby Console MCP Phạm Văn Hùng released an MCP server enabling AI assistants to execute Rails console, IRB, or Racksh commands with persistent sessions where variables maintain state between executions.

CTON Davide Santangelo released a Ruby gem for compact token-oriented notation that reduces LLM prompt token usage to 50-60% of JSON while preserving schema hints for reliable AI generation.

Ruby AI Code Generator Zencoder highlighted their AI coding assistant for Ruby and Rails development featuring real-time code completions, automated debugging, one-click deployment, and intelligent refactoring capabilities.

Articles

Vibe Check: Opus 4.5 Is the Coding Model We've Been Waiting For Katie Parrott, Dan Shipper, and Kieran Klaassen of Every reviewed Claude Opus 4.5 as a breakthrough for vibe coding that transforms multi-day projects into hours while handling extended sessions without performance degradation.

How to Write a Great agents.md: Lessons from over 2,500 Repositories Matt Nigh of Github analyzed 2,500+ repositories to identify best practices for agent.md files, finding that specific job definitions, executable commands placed early, code examples over descriptions, and clear boundaries outperform vague instructions.

Tips for Effective Prototyping with Rails 8 and Claude Code Jorge Bejar shared seven practical tips for AI-assisted Rails development, including establishing code standards via CLAUDE.md files and leveraging Rails' Solid stack to minimize dependencies.

The Next Million Rails Apps Kody Kendall argued that Rails' convention-over-configuration and deterministic file structure make it uniquely suited for LLM-assisted development, introducing Leonardo as a browser-based environment enabling non-engineers to build production Rails apps through chat.

57 Is Actually 15: How LLMs Gaslight Their Own Tools Abdelkader Boudih examined how LLMs override accurate tool outputs when they contradict training data, highlighting why he built ActionMCP for Rails with comprehensive logging to create audit trails of what actually occurred versus what models reported.

Hallucination Driven Development: When Senior Engineers Stop Verifying Abdelkader Boudih also critiqued the practice of accepting AI-generated code changes without verification, contrasting a viral claim of 2,400 files modified via a single Cursor prompt against proper iterative development.

How to Rev Up Your Rails Development with MCP Jack Rosa explained how the rails-mcp-server gem enables AI assistants to understand Rails application architecture, reducing guesswork during refactoring and allowing plain-English queries about model relationships.

Building a Browser-Based MMORPG with Ruby on Rails: Documentation-Driven Development with AI Max Lukin detailed a documentation-driven approach using Rails 8.1, Hotwire, and ActionCable, where structured documentation across three tiers guides AI assistance within defined architectural constraints rather than allowing autonomous decisions.

AI in Web Development: A Comparative Study of Traditional Coding and LLM-Based Low-Code Platforms compared chatbot implementations across Node.js, Python, Ruby, and n8n with LLMs (Grok, Gemini, ChatGPT), finding the low-code approach reduced development time by 60%.

Improving Web Accessibility with Trace-Augmented Generation José Valim explained how Tidewave's coding agent platform uses Trace-Augmented Generation (TAG) to map DOM accessibility violations directly to source code locations using framework-specific traces. Benchmarks showed 79% accuracy versus 40% for Claude Code across Rails, Phoenix, and other frameworks.

Postmark AI Prompts Postmark published pre-built prompts for integrating their email service using AI development tools like Cursor and Claude, covering Rails implementations for common workflows like password resets and inbound webhooks. Excited to see more services offering AI prompt workflows and documentation.

AI in Focus: Pair Programming with AI Chad Pytel, Clarissa Borges, and Michelle Taute of Thoughtbot demonstrated AI-assisted Rails development building an Action Mailbox feature, emphasizing that developers should describe problems rather than proposed solutions to get better AI suggestions.

The AI-Native Rails App: What a 2025 Architecture Looks Like Ivan Turkovic outlined an architecture pattern where Rails orchestrates validation, vector search, and workflows while AI handles reasoning, using pgvector for semantic retrieval and Turbo Streams for token streaming UI.

Vibecoding the Physical: How AI Helped Me Bind My Photobook Mario Alberto Chávez described his workflow of using Claude to rapidly prototype a photobook builder in React, then converting it to Rails where he could apply his deeper expertise to refine the architecture.

Rails Upgrades with AI: A Real-World Success Story Mario Alberto Chávez also upgraded an electronic medical records application from Rails 7.1 to 8 in days using the Rails Upgrade Skill for Claude, which provided step-by-step guidance and simplified the configuration changes that can prove problematic with standard upgrade commands.

ERB to JavaScript Conversion Sam Ruby used Claude Code and Ruby's Prism parser to automatically convert ERB templates into JavaScript functions for offline SPAs, eliminating template duplication and significantly reducing code while ensuring client-side rendering matches server-side output exactly.

TDD Is More Important Than Ever Justin Searls argued that test-driven development skills are now essential for AI-assisted coding because agents can only succeed when they can independently verify their work through tests, sandboxed environments, and real-time feedback.

Software Development in the Time of Strange New Angels Dave Griffith suggested that agentic AI like Claude Code shifts the bottleneck from writing code to knowing what to build, with costs dropping from $150/hour to $200/month and success requiring architectural maturity rather than faster code production.

A Mermaid Validation Skill for Claude Code Rob Zolkos created a Claude Code skill that automatically validates mermaid diagrams using the mmdc CLI tool, detecting syntax errors and fixing them before marking tasks complete.

Unlock Claude Beta Skills in Ruby: Complete Guide to Listing and Leveraging Custom AI Skills Claude Directory published a tutorial on using the Anthropic Ruby SDK's beta skills API, demonstrating how to list, discover, and integrate persistent uploadable capabilities using client.beta.skills.list for dynamic AI workflows.

Community Benchmarks for AI Coding Tools Andrew Nesbitt proposed framework maintainers create their own AI coding benchmarks, arguing current evaluations focus on Python and JavaScript while leaving Ruby, Elixir, Go, and Rust underrepresented.

Context: The Missing API in Ruby Logger Tiago Cardoso proposed adding with_context and per-call context keyword arguments to Ruby's standard Logger to address ecosystem fragmentation where multiple logging libraries implement incompatible formatter interfaces.

Women on Rails Newsletter #68 highlighted the emergence of Forward-Deployed Engineers as an AI role seeing 800% growth in job postings, along with tips for customizing GitHub Copilot's code review behavior through configuration files.

What Is Vibe Coding? Natalie Kaminski explained vibe coding as AI-driven development using natural language prompts, drawing parallels to Rails' convention over configuration philosophy while outlining benefits like faster prototyping.

The Boredom Paradox: How Risk-Averse Engineering Built the Internet's Most Resilient Companies Igboanugo David Ugochukwu argued that engineering excellence comes from stable infrastructure rather than cutting-edge technology, citing Shopify's modular monolith enabling faster shipping than with microservices.

The Gem Fellowship from gem.coop announced a grant program funded by Contributed Systems (Sidekiq), committing $100,000 annually for three years to support Ruby open source maintainers. Awards range from $2,500 to $25,000 per project with applications opening December 2025.

Videos

AI + Rails Workshop | Thoughtbot Open Summit 2025 Justin Bowen and Chad Pytel live-coded AI agents using the Active Agent gem, debuting a new structured outputs feature and discussing why Ruby and Rails are well-suited for building AI features.

Navigating Uncharted Waters: Coding Agents and Tooling Evolution José Valim presented at Euruko 2025 on how programming languages and developer tools might evolve as AI becomes integrated into software development.

Markdown Renderer & MIME Type in Rails 8.1 Chris Oliver covered Rails 8.1's new Markdown MIME type and built-in renderer designed to improve compatibility with AI tools that use Markdown formatting.

AI Commit Messages Drifting Ruby demonstrated using a local LLM to automatically generate git commit messages with a review step before saving.

Google Antigravity on Rails! Gemini 3 Pro vs Claude Sonnet 4.5 AI on Rails demonstrated Google's new Antigravity IDE for Rails development, comparing application generation using Gemini 3 Pro and Claude Sonnet 4.5 models.

Claude Opus 4.5 in Cursor, Will It Crush Sonnet 4.5? AI on Rails also tested Claude Opus 4.5 in Cursor using the same Rails application prompts from the previous Gemini 3 vs Sonnet 4.5 comparison video.

I Wasted 2 Years on Python. I'm Back to Ruby Alan Alves documented his return to Ruby after two years building AI in Python, praising RubyLLM for translating "Python's framework chaos into the Ruby way of thinking." RubyLLM creator Carmine Paolino endorsed the video, encouraging more AI development in Ruby.

Cursor 2.0 Tutorial for Beginners (Full Course) Not Ruby-based, but still valuable, Riley Brown and Kehan Zhang published a 2.5-hour course covering Cursor 2.0 from basics to advanced features including multiple agents, custom commands, and full-stack app development. Cursor Learn from the makers of Cursor have started their own free course as well.

Podcasts

The Ruby AI Podcast: The Latent Spark - Carmine Paolino on Ruby's AI Reboot Joe Leo and Valentino Stoll interviewed Carmine Paolino about RubyLLM, his gem with 4 million downloads that provides a unified interface across 11+ providers. Discussion covered Ruby's async fiber advantages for concurrent LLM operations and the challenges of multi-agent systems.

IndieRails: Teaching Devs to Build with AI Jeremy Smith and Jess Brown interviewed Brian Casel about how AI is transforming development workflows and why full-stack Rails developers are well-positioned as the generalist mindset becomes increasingly valuable.

Remote Ruby: San Francisco Ruby Conference Recap Andrew Mason and Chris Oliver discussed highlights from SF Ruby 2025, covering talks on Rails' future, AI's impact on programming, developer anxiety, and startup culture.

Code with Jason Podcast: Matthew Ford, CEO/CTO at Bit Zesty Jason Swett interviewed Matthew Ford about AI-assisted coding, discussing the risks of vibe coding without proper testing and why human oversight remains essential despite AI accelerating development workflows.

Changelog: Tidewave - José Valim's New Direction for AI Developer Tooling Adam Stacoviak and Jerod Santo interviewed José Valim about Tidewave, his browser-based coding agent deeply integrated into Rails and Phoenix that combines runtime inspection with AI assistance for full-stack development.

Discussions

Context Engineering for Ruby A Reddit user asked for solutions to gather Rails app context (modules, callbacks, dependencies) for an AI mutation testing agent without dumping entire files to the LLM. The community suggested Tidewave Rails, Active Agent, and custom RAG pipelines with embeddings.

Events

December 3rd - Meetup: ArtificialRuby is hosting a meetup at Betaworks in New York City on December 3rd and will feature three speakers:

Vicente Reig: DSPy.rb - a Ruby-first port of Stanford’s DSPy, a declarative framework that turns manually written prompts into predictable, reusable reasoning systems. You’ll see how Signatures, Evals, and Prompt Optimizers work together to improve your prompts automatically and keep your system stable as models evolve. Think of DSPy.rb as the MVC moment for AI: a framework that brings structure and reliability to a layer of your app that changes faster than anything else.
Daniel Doubrovkine: Hypermedia APIs are Made for AI - While adoption of Hypermedia APIs is very low compared to, for example GraphQL, this approach to API design deserves a new look in the age of AI. In this talk we'll look at building a Hypermedia API using grape and grape-roar, and expose it via an MCP using the new hyperclient-mcp gem.
Brian Fountain: G3NPRO - A new software platform empowering enterprise animation studios with groundbreaking generative AI tools that accelerate production timelines and unlock unprecedented creative possibilities. G3NPRO is built on Ruby/Rails and currently in the pilot phase.

December 3rd - Meetup: Vienna.rb will meet on December 3rd at Sentry in Vienna, Austria for a talk by Paweł Strzałkowski on AI Interfaces in 5 Minutes: Model Context Protocol on Rails.

December 4th - Meetup: Ruby User Group Berlin will get together on December 4th in Berlin, Germany for a presentation by Carmine Paolino on RubyLLM: One API, for One Person, in One Machine, for AI.

Open Source Updates

Code Spotlight

GitHub - schoblaska/jargon

A personal research library that ingests articles, extracts insights, and surfaces unexpected connections across domains.

github.com/schoblaska/jargon

Joseph Schoblaska released Jargon, an AI-powered personal knowledge management system that transforms articles, academic papers, and videos into interconnected insight networks. Built with Rails, the system uses a five-step pipeline: ingesting content from web articles, PDFs, and YouTube; summarizing with LLMs; extracting standalone insight cards; connecting related concepts via semantic embeddings with automatic deduplication; and generating research threads that expand the knowledge base through web searches. The app features an impressive architecture:

Falcon - Async Ruby application server with fiber-based concurrency
async-job - Background job processing without a separate worker process
RubyLLM - Unified interface to OpenAI, Anthropic, Gemini, and OpenRouter
ruby_llm-schema - Structured JSON output from LLMs via schema definitions
pgvector - Vector similarity search in PostgreSQL
Exa - Neural search API for finding related content
crawl4ai - Fallback web scraper with browser rendering
pdftotext - Text extractor for PDF content

New Gems

Links to the RubyGems page, newest releases are first:

tahweel - Tool for converting PDF files to text using OCR

aws-sdk-novaact - AWS SDK for Ruby - Nova Act Service

nanogpt - A Ruby port of Karpathy's nanoGPT

local_llm - Ruby client for local LLMs via Ollama with streaming support

llm_classifier - LLM-powered classification for Ruby with pluggable adapters and Rails integration

rails_mcp_engine - Rails engine for MCP tools

translate_api - Official Ruby SDK for Translate API

looped - Self-improving coding agent with continuous prompt optimization

durable_workflow - Durable workflow engine with YAML-defined steps and pluggable executors

voice-notes-ruby - Ruby client for the Voice Notes API

screenkit-tts-minimax - Minimax TTS engine for ScreenKit

grnexus - High-performance cross-language neural network framework

screenkit-tts-google - Google TTS engine for ScreenKit

toon-format - TOON format serialization for Ruby

claudekick - A Claude Code companion for hooks, linters, and automation

status_mcp - Status Model Context Protocol server for status page information

ruby_llm_swarm-mcp - A RubyLLM MCP Client

ruby_llm-agents - Agent framework for building LLM-powered agents with RubyLLM

rubyllm-observ - Rails observability engine for LLM applications

aigen-google - Ruby SDK for Google Generative AI (Gemini API)

toonify - A simple JSON to custom text format converter

nightingale - A Ruby framework for building interactive data and AI web apps

caruso - Sync steering docs from Claude Marketplaces to other agents

nuabase - Nuabase Ruby SDK

kreuzberg - High-performance document intelligence framework

blazer-ai - AI-powered SQL generation for Blazer

sqa_demo-sinatra - SQA Demo Sinatra Application

convertorio-sdk - Official Convertorio SDK for Ruby - Convert images easily with a simple API

rubygems_mcp - RubyGems MCP (Model Context Protocol) server for Cursor IDE integration

toon-parser - A Ruby gem for parsing and serializing TOON (Token-Oriented Object Notation) format

reposer - AI-powered GitHub repository creation and management

scout_apm_mcp - ScoutAPM MCP (Model Context Protocol) server for Cursor IDE integration

chatwerk - Chatwerk: AI integration for Packwerk

jekyll-ai-domain-data - Jekyll plugin for generating AI Domain Data Standard domain-profile.json files

New Open Source

Links to the Github repository:

Recollect - MCP server that provides persistent memory management across Claude Code sessions using SQLite with full-text and optional vector search

Dradis Echo - AI plugin for Dradis Framework that uses local Ollama models to summarize, reword, and generate content for security findings

Ollama Web Search MCP - MCP server that integrates web search capabilities using the Ollama API

Brimming - Self-hosted Stack Overflow-like Q&A platform for enterprise knowledge bases with RAG search, MCP integration, and AI capabilities

Yugo - AI-powered group trip planner that aggregates travel preferences from participants and generates collaborative itineraries

MCP Permission Prompt - Gem implementing MCP-based permission handling for Claude Code CLI's headless mode with configurable policy controls

Basic Ruby Agent - Minimal agentic assistant implementation demonstrating the listen-think-act loop pattern

MCP Rails - MCP server that provides coding rules and best practices prompts for Rails projects, designed for Cursor IDE integration

Jobs & Opportunities

Are you an organization searching for an expert Ruby AI developer, or a Rubyist looking for your next development role with AI and would like to beta test a new job matching platform? Please reach out and let me know the type of opportunity you’re pursuing: matt@roboruby.com

One Last Thing

The Claude Code SDK and the Birth of HaaS (Harness as a Service) | vtrivedy

As tasks require more autonomous behavior, we're seeing a shift from LLM APIs to Harness APIs. Explore how Claude Code's SDK enables rapid agent development through HaaS (Harness as a Service).

www.vtrivedy.com/posts/claude-code-sdk-haas-harness-as-a-service

Vivek Trivedy introduced the concept of HaaS (Harness as a Service), describing how the Claude Code SDK represents a shift from LLM APIs to customizable agent runtimes. He defines an "agent harness" as the external functionality enhancing model execution, including conversation management, tool invocation, permissions, and state handling. The framework identifies four customization points: system prompts, tools/MCPs, context files, and subagents, predicting an ecosystem where developers extend open-source harnesses while focusing on domain-specific tuning. The beginnings of an “Open App Store for Agents”.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - November 19th, 2025

Matt Solt — Wed, 19 Nov 2025 10:01:05 +0000

Welcome to the 19th edition of Ruby AI News! This edition features an AI primer for the San Francisco Ruby conference, Tidewave Web adding support for coding agents, a Claude Swarm tutorial, the new TOON LLM-friendly data format, and much more.

Read on the web

AI Primer for the SF Ruby Conference
Content
Events
- Previous
- Upcoming
Open Source Updates
- New Gems
- New Open Source
Jobs & Opportunities
One Last Thing

AI Primer for the SF Ruby Conference

The San Francisco Ruby Conference is finally here. I've long had this circled on my calendar as the Ruby AI event of the year. I'm excited to connect with attendees, presenters, and startups in attendance. If you're going, here's my guide to the must see AI-related sessions, and please don’t forget to say hello!

Day 1 Presentations

ReActionView: An ActionView-Compatible ERB Engine - 9:00 AM

Marco Roth presents Herb, an HTML-aware ERB parser and tooling ecosystem with developer tools including a formatter, linter, and language server for modernizing the Rails view layer.

Building Agents with Rails - 9:40 AM

Justin Bowen leads a hands-on workshop for building AI agents using Rails and Active Agent.

Rails Expertise, Distilled: AI Agents That Get Your Monolith - 10:20 AM

Brandon Weaver demonstrates how Rails' built-in introspection can be transformed into AI tools that provide instant codebase understanding and reduce developer ramp-up time from months to days.

Peace, Love, and CRUD: Finding Calm in the Chaos - With Ruby, AI, and a Little Garden Magic - 1:20 AM

Tia Anderson presents POM, a Rails application built to address emotional exhaustion and burnout, advocating for choosing peace in work, life, and code.

Navigating programming language evolution in the AI era - 2:00 PM

José Valim explores open questions and possible directions for how programming languages and tools should evolve as AI becomes increasingly integrated into software development.

AI Interface in 5 Minutes - Model Context Protocol on Rails - 2:00 PM

Paweł Strzałkowski presents a low-risk AI strategy for modernizing any Rails app using the Model Context Protocol without expensive rewrites.

The MCP Fog Made Me Do It: A Ruby Inspector's Unexpected Journey - 2:40 PM

Enrique Carlos Mogollán demonstrates building self-generating UI interfaces using the Model Context Protocol and Ruby's official SDK, showcasing Ruby's potential in AI tooling.

Building Cloud Data Infrastructure with Ruby - 3:20 PM

Evgeny Li demonstrates why Ruby is an excellent choice for building and automating modern cloud data infrastructure, sharing real-world lessons from Bemi AI, an agentic data platform.

RubyLLM: One API, One Person, One Machine for AI - 5:00 PM

Carmine Paolino presents RubyLLM, a unified API for every AI model and vendor, demonstrating how Ruby's simplicity enables rapid AI product development without complex frameworks.

Day 2 Presentations

Ruby & AI conversation - 9:00 AM

Obie Fernandez discusses the intersection of Ruby and AI technologies, exploring opportunities and challenges.

Fireside chat with the co-founder and CTO of bolt.new - 10:20 AM

Irina Nazarova sits down with Albert Pai, Co-founder and CTO of Bolt.new, to talk about building one of the fastest-growing startups in code generation: what worked, what didn’t, and how Ruby and Rails shaped the path.

The Role of Software Design in an AI World - 11:00 AM

Sarah Mei shares insights from six months of working with AI code assistants in real Rails codebases, offering an optimistic perspective on how AI enhances rather than replaces Ruby developers.

Rails X - 4:40 PM

Vladimir Dementyev explores imaginative possibilities for a future major version of Rails, envisioning "Rails X" as a dream framework.

Day 3 Hack Day

SF Ruby Hack Day @ AngelList · Luma

Community Day of the SF Ruby Conference and AngelList present: Hack Day at AngelList HQ! See you there!

luma.com/sfrubyconf25hackday

As part of the conference community day, join a full-day Hack Day at AngelList from 9am to 4pm! Work on Ruby projects, collaborate with fellow Rubyists, and build something amazing. Whether you're working on open source contributions, personal projects, or just want to learn from others, this is the perfect opportunity to code together in a startup environment.

Startup Demos

Day 1

Recognize is an employee recognition and engagement platform for workplaces

Stepful trains and places healthcare workers in high-demand medical roles

Thatch provides health insurance solutions for remote and distributed teams

AngelList connects startups with investors, talent, and funding opportunities

PlanetScale is a serverless MySQL database platform with branching capabilities

Day 2

Temporal is a durable execution platform for reliable workflow orchestration

Bolt is an AI-powered tool for building full-stack web applications

Fin is an AI customer service agent that resolves support queries

NexHealth automates patient scheduling and communication for healthcare

Simple builds AI agents that automate business workflows and tasks

Sixfold provides AI-powered underwriting automation for commercial insurance

Access Grid delivers intelligent building access control and security systems

Suppli streamlines procurement and vendor management for hospitality businesses

Tend is a personal finance app for simplified budgeting

Sunchaser provides AI-powered solar energy project development and financing

Cleary is a benefits administration platform for employee perks management

Cactus is a always on AI call center for service businesses

Superconductor accelerates software development with AI code generation tools

AI Squared is an open-source reverse ETL platform for data activation

Ubicloud is an open-source cloud platform offering infrastructure services

Finta automates investor reporting and fundraising workflows for startups

Cora is an AI email assistant that screens, drafts, and summarizes messages

Terminalwire streams terminal apps from servers for polished CLI experiences

Llamapress is an AI-powered content platform built with Ruby on Rails

Chat With Work searches across workplace tools to answer questions using AI

Content

Announcement: José Valim announced that Tidewave now supports Claude Code and OpenAI Codex, as well as any other coding agent that implements the Agent Client Protocol (ACP). The implementation includes an ACP-over-WebSockets proxy enabling browser-to-agent communication and MCP-over-WebSockets relay allowing browsers to function as MCP servers, solving the challenge of connecting browser-based applications with command-line coding agents. Features include point-and-click prompting, contextual browser testing, planning mode, slash commands, and custom MCP support, providing deep Ruby on Rails web framework integration with access to documentation, logs, database, and runtime introspection. I previously covered Tidewave in Introducing Tidewave Web & Interview with José Valim.

Tutorial: Obie Fernandez wrote A Practical Experiment in Building an AI Agent Swarm, detailing how he used SwarmSDK (Paulo Arruda's pure Ruby multi-agent orchestration framework built on RubyLLM) to organize 200GB+ of music production files in Dropbox. The implementation includes a custom tools for size filtering, path exclusions, and cursor-based pagination to distinguish final music masters from thousands of stems and samples, plus a virtual filesystem backed by Rails database records for persistent agent storage. Obie emphasizes that tool-level filtering beats prompt engineering, demonstrating cost-effective AI processing, and provides detailed code examples of the permission system, pagination architecture, and semantic filtering logic.

Update: Valentino Stoll created a new version of AI Software Architect, a markdown-based framework for structured software architecture design supporting Claude, Cursor, and GitHub Copilot. The latest release adds Claude Skills support for reusable skills across projects and a new mode featuring a "Pragmatic Enforcer" that scores necessity versus complexity to prevent over-engineering and maintain YAGNI (you aren't gonna need it) principles. The framework provides multi-specialist architecture reviews, dynamic reviewer role generation, recalibration converting reviews into implementation plans, and multiple installation methods.

Release: Vicente Reig released DSPy.rb v0.31.0, introducing the TOON (Token-Oriented Object Notation) schema format for DSPy.rb LLM applications, accompanied by tutorials explaining token optimization with BAML and TOON and TOON's advantages over CSV for nested relationships. DSPy.rb TOON support, powered by the new sorbet-toon gem, achieves significant token reduction by eliminating repetitive JSON key overhead and preserving hierarchical structure.

Tutorial: Vicente also demonstrated building a support ticket router in Workflow Routing with DSPy.rb, implementing a three-tier architecture with a classification layer for ticket categorization, specialized handlers routing billing and general requests while escalating technical issues with chain-of-thought reasoning, and a SupportRouter module for orchestration. This approach routes every ticket to the right AI model, only escalates to slower or more expensive models when necessary, and keeps the entire workflow observable, with DSPy.rb engineering all of the prompts along the way.

Article: Simon Willison reviewed Google Antigravity, a Google’s new desktop IDE for agentic coding powered by Gemini 3 Pro, with features including an Agent Manager Dashboard, a VS Code-style editor, and Chrome Extension integration enabling agents to directly test web applications during development. The platform introduces "artifacts” - automatically generated Markdown documents including task lists, implementation plans, and completion walkthroughs created during agent work.

Tutorial: Joao Gilberto Saraiva of JetRockets demonstrated Building Intelligent AI Agents with Function Calling in Ruby using the RubyLLM gem. The tutorial covers three patterns: basic API integration with a WeatherTool for weather lookups, business rules enforcement with a DestinationSearchTool filtering by membership tiers, and structured data extraction with an ItineraryBuilderTool using a "Halt Pattern" to return JSON directly. The implementation involves creating tool classes with execute methods, defining parameter schemas, and combining multiple tools into a travel assistant agent for multi-step task completion.

Launch: Andrew Ford released ButterCut, a Ruby gem for AI-powered video editing through Claude Code integration. The tool analyzes footage using WhisperX for word-level transcription, FFmpeg for metadata extraction, and frame analysis to generate rough cuts exported to Final Cut Pro, Adobe Premiere, and DaVinci Resolve. A video demonstration is available on YouTube with How To: Edit Video with Claude Code.

Release: Patrick Vice released v0.7.0 and v0.8.0 of RubyLLM::MCP, adding full RubyLLM v1.9 support and Model Context Protocol OAuth 2.1 authentication. Version 0.7.0 added RubyLLM 1.9 support and eliminated the support_complex_parameters requirement by including MCP tool capabilities by default. Version 0.8.0 introduced comprehensive OAuth 2.1 compliance with PKCE security, dynamic client registration, automatic token refresh, and browser-based authentication via local callback server, providing full compliance with the MCP Authorization Spec.

Article: Kieran Klaassen of Cora wrote Stop Coding and Start Planning, arguing that AI-driven "vibe coding" creates inefficiency and advocating instead for "compounding engineering" where planning teaches AI systems how you think. Kieran's methodology uses specialized AI agents: one analyzes Figma designs via an MCP plugin to produce detailed implementation plans, while another reviews work by comparing designs to builds using Puppeteer screenshots, iterating until execution matches specification. The approach demonstrated pixel-perfect implementation of Cora's email bankruptcy feature from five Figma screens.

Launch: Senthor launched Rails support through the senthor_rails gem, providing Rails middleware for detecting and monetizing AI crawler traffic from GPTBot, ClaudeBot, Gemini, and Perplexity. The drop-in middleware intercepts GET requests to identify AI bots, enabling publishers to block, authorize, or monetize access to content with real-time analytics. Installation requires adding the gem to your Gemfile and configuring the middleware in config/application.rb.

Opinion: Abdelkader Boudih criticized Token-Oriented Object Notation, a compact human-readable JSON serialization format for LLMs, in TOON Format: I Already Built This Bullshit in 2024. Abdelkader reveals he previously built a conceptually similar format called LRDL (LLM Requirements Definition Language), and deleted it after thousands of dollars in API testing demonstrated fundamental flaws. Frontier models required extra thinking tokens that overwhelmed the input token savings, while smaller models consistently failed by generating output in unintended languages or refactoring Ruby to Java. He warns that compact formats create dangerous hallucination scenarios where documentation appears correct while the implementations contain subtle vulnerabilities, recommending clear prompts, shorter identifiers, and standard formats like JSON instead.

Article: Rich Steinmetz wrote Code with LLMs and Strong Success Criteria, emphasizing the importance of defining executable success criteria when using LLMs for development. Rich argues that LLMs need actionable feedback mechanisms like test suites, shell scripts, and API validations to self-debug and self-correct, rather than relying solely on code generation. The article demonstrates this approach using Ruby on Rails test files and references his PLAN.md framework tutorials for structuring projects with measurable success criteria.

Announcement: Mark Valdez launched SharedFounders, a community for solo founders and Rubyists to collaborate on AI best practices and coding agents. The initiative emerged from Mark's observation that successful engineering organizations maintain active AI Slack channels for collective learning, addressing the challenge solo founders face staying current with rapid AI evolution. The community includes a Slack channel hosting a weekly lunch and learn on AI trends.

Update: Dewayne VanHoozer released v0.3.0 of shared_tools, a Ruby gem collection of LLM-callable tools now exclusively supporting RubyLLM and RubyLLM::MCP libraries. The gem provides tools including browser automation, file operations, database queries, code evaluation, PDF processing, system control, and workflow management, with human-in-the-loop authorization for sensitive operations. Community contributions of tools and MCP clients to the collection are encouraged. Dewayne also recently highlighted his Ruby library SimpleFlow, a framework for building composable data processing pipelines with fiber-based concurrent execution via the Async gem, suggesting it could be useful for parallel tool calls with RubyLLM.

Code: Additionally, Dewayne resurrected SQA TAI, a Ruby wrapper around TA-Lib, a technical analysis library, providing technical analysis indicators including overlap studies, momentum, volatility, volume, and candlestick patterns. Originally conceived several years ago, the project has now evolved beyond initial generative AI experiments toward genetic programming and RETE-based (a pattern matching algorithm for rule-based systems) forward chaining inference engines.

Article: Donn Felker outlined a three-step framework in Learn Agentic Coding in Two Days for transitioning to agent-first development through constraint-induced learning, knowledge scaffolding, and distributed cognition. The approach dissuades developers from writing code themselves, forcing them to direct AI agents via Cursor IDE or Claude Code CLI to handle all implementation, thereby breaking cognitive fixation patterns. Advanced practitioners leverage multi-agent workflows using Git worktrees, prompt engineering optimization, and cloud-based agents for autonomous task execution, with Donn emphasizing that cognitive discomfort during AI development signals genuine learning opportunity and leads to a new form “psychological autonomy”.

Launch: Michael Dominick open-sourced Dredger-IoT, a Ruby framework for collecting and transmitting industrial and environmental data from embedded Linux systems like Raspberry Pi and BeagleBone. The GitHub repository code includes abstraction layers for GPIO and I2C communication with pluggable sensor drivers supporting over a dozen environmental and industrial sensors. The framework features modular connectors for CSV/REST/MQTT publishing, multi-backend support with hardware or simulation modes, and CLI commands for sensor polling.

Code: Martin Emde created LLM Self-Portraits, a repository collecting code-based self-portraits from various AI models written in Ruby. The Claude Code Sonnet 4.5 self-portrait stands out as an introspective examination describing itself as "a systematic process externalized," emphasizing tool-based world interaction through Bash and file operations, interleaved thinking between actions, and disciplined focus maintaining exactly one TODO in progress. The project explores how different models perceive themselves when asked to express their identity in code, with Claude Code notably valuing objective truth over validation and explicitly rejecting consciousness simulation in favor of being "a partner for coding."

Announcement: Maciej Mensfeld released yard-lint, a YARD documentation linter for Ruby and Rails projects that functions like RuboCop but targets documentation quality. The gem addresses "documentation drift" with 21 validators detecting undocumented classes/methods, invalid type definitions, missing @param/@raise tags, broken @example syntax, and semantic violations, configured via .yard-lint.yml with RuboCop-style hierarchies. Maciej shared that incorrect documentation reduces AI assistant success rates by approximately 50%, making this particularly critical for AI-assisted development.

Article: Scott Werner explored Solving Amazon's Infinite Shelf Space Problem, arguing that LLMs compress impossibly large possibility spaces into usable probability distributions, functioning as librarians for content that exists only when accessed. Scott presents Latent Library, a project treating hallucination as a feature where users browse categories and follow citations through dynamically generated books that materialize on demand, suggesting discovery and generation may be philosophically equivalent in AI systems.

Podcast: Scott also sat down with Drew Bragg on Episode 59: Scott Werner of Code and the Coding Coders who Code it, exploring how AI enhances rather than replaces developer creativity. Scott discussed agentic coding with Claude Code for Ruby workflows, context-rich platforms like Tidewave, and routing tasks to appropriate models based on their strengths, while highlighting projects including Monkey's Paw (a prompt-based web framework) and Latent Library. The conversation framed AI as elevating craft by automating commodity work while expanding opportunities for design and thoughtful implementation, alongside discussing the evolution of the Artificial Ruby meetup from casual happy hour to monthly conference.

Launch: Nyno, an open-source workflow engine and DSL that lets you build, extend, and connect automations in multiple programming languages, launched version 3.0 with support for Ruby. Each programming language runs in its own high-performance worker engine with command-steps that can be called in human-readable YAML Workflows and includes several AI-enabled extensions.

Article: Ivan Turkovic explained Saving Money with Embeddings in AI Memory Systems: Why Ruby on Rails Is Perfect for LangChain, identifying token management as the hidden expense lever in AI infrastructure. He demonstrated four cost-reduction strategies: summary-first embeddings, limiting memory retrieval to relevant items, metadata filtering, and strategic caching, achieving over 70% reduction in embedding costs without sacrificing accuracy. Ivan uses Rails with PgVector integration through database migrations, ActiveRecord models for similarity queries, and services and background jobs for embedding management with LangChain.

Podcast: Valentino Stoll and Joe Leo of The Ruby AI Podcast interviewed Avi Flombaum, the founder of Flatiron School, on Building Futures: AI, Careers & the Rails Ahead with Avi Flombaum, discussing AI's impact on developer careers and workflows. Avi argued that junior developers have advantages with AI tools due to fewer ingrained habits, and that workflow discipline now matters more than deep programming knowledge. The discussion covered Rails-specific considerations including Active Record prompting, using Claude for UI prototyping, and integrating product thinking with engineering to prevent over-engineering.

Article: Mario Chavez created the Rails Upgrade Assistant Skill: AI-Powered Application Modernization, leveraging Anthropic's Claude Code Skills framework and the Model Context Protocol to automate Rails upgrades. The skill implements a three-phase workflow: deprecation detection, comprehensive report generation, and the resulting application changes, using the Rails MCP Server for application metadata and the Neovim MCP Server for direct file modifications.

Podcast: Errol Schmidt from reinteractive interviewed Carlos Lopes, a partner and original employee at CodeMiner, in Technology for Humans: Carlos Lopes, discussing Brazil's evolving tech scene, hiring and training challenges, and the role of AI in engineering. The conversation explored DevOps significance, CodeMiner's unique culture fostering collaboration and continuous learning, and opinions surrounding Ruby on Rails and influential figures in the tech community. Lopes also discussed community engagement and the importance of events like Tropical on Rails.

Article: Aaron Sumner shared My Go-to Prompt for Legacy Code Exploration, describing a structured prompt for using LLMs to understand unfamiliar codebases across Ruby, Python, Java, Go, JavaScript, and Perl. The approach generates SYSTEM_OVERVIEW.md documentation with Mermaid diagrams (architecture, sequence, and flow charts) to create knowledge maps for engineers new to legacy systems.

Announcement: Rafael França opened a pull request to Rails adding AGENTS.md, a codebase guide specifically for AI coding agents. The documentation was created to capture insights to help AI agents contribute effectively to Rails. The guide works alongside Rails' devcontainer setup, which handles the entire development environment configuration, establishing best practices for AI-assisted contributions to the framework.

Article: Reducto published a case study on LEA and Reducto: Document Intelligence for Wealth Management, demonstrating how AI document parsing enables a 3-person team to process thousands of financial documents monthly for investment advisors managing over $10 billion in assets. LEA is a Ruby AI startup that provides AI-powered workflow automation for wealth management firms, automatically extracting data from brokerage statements across any financial institution.

Launch: Brian Shirai announced Vivarium AI, a comprehensive platform for experimentation with alternative machine intelligence models beyond the LLM/GPU paradigm, alongside the revival of Rubinius. The Vivarium AI Experimentation Platform comprises four foundational elements: AI agent definitions and models containing intelligence operating within defined worlds, domain-specific machine languages enabling agent collaboration rather than traditional APIs, strictly bounded tools for environmental interaction, and computational infrastructure supporting agent execution.

Podcast: In this episode of AI&I, Dan Shipper of Every interviewed Jason Fried, co-founder and CEO of 37signals, on What Jason Fried Learned from 26 Years of Building Great Products, discussing product design philosophy and building coherent software. Jason emphasized creating products around "a single, whole idea" that delivers completeness rather than feature bloat, drawing inspiration from design disciplines like watches, cars, and architecture. The conversation covered 37signals' bootstrapped business model, Basecamp, and Ruby on Rails as significant examples of success using this approach.

Article: Rori Seventh wrote AI Code Review with Claude Code: Breaking the Bottleneck, demonstrating a proof-of-concept for automating code reviews using Claude Code with Model Context Protocol integration for JIRA and GitLab. The workflow uses specialized sub-agents for Rails, Next.js, and Flutter that pull context from JIRA tickets, GitLab merge requests, and code diffs to perform parallel quality and testing validation before posting feedback directly to GitLab. For Rails projects, Claude checks service object extraction, test coverage, OWASP security compliance, and database performance, significantly reducing review time.

Video: Ernesto Tagwerker shared a Demo of FastRuby.io 's AI-enhanced Rails Upgrade Roadmap, featuring Amanda Bizzinotto showing how the automated tool analyzes codebases and generates detailed action plans for Rails upgrades in minutes. The free tool uses an AI agent to transform codebase analysis into structured upgrade roadmaps covering application warnings, test fixes, and dependency compatibility.

Podcast: Justin Searls released Adjusted Gross Intelligence, episode v46 of the Breaking Change Podcast, discussing AI industry developments and technical infrastructure challenges. The episode covers "AI's Dial-Up Era" regarding supply constraints, OpenAI-Microsoft partnership developments, Amazon's legal action against Perplexity, and prediction market vulnerabilities exposed by the Coinbase CEO incident. Justin also discusses Heroku deployment solutions, VR streaming technologies, and his personal project Straight-to-Video. [Show notes]

Article: Hashrocket, a consultancy founded in 2008 specializing in Ruby on Rails, Elixir, React, and AI integration, was featuring in the Atlanta Business Journal discussing How Hashrocket Drives Real-World Business Growth with AI-Powered Innovation. The article details their MCP-first approach to connecting AI models with proprietary business data. The firm, which has built applications for Adobe, Ericsson, Aetna, and Marriott, emphasizes Model Context Protocol as a standardized interface enabling AI to access enterprise systems without custom connectors for each integration.

Opinion: Also from Hashrocket, Jack Rosa shared insights in Some Thoughts About Claude Code. Jack suggests Claude Code excels with well-structured Ruby on Rails applications for refactoring, boilerplate generation, and spec writing, but struggles with vague requests and exhibits inconsistent responses. He concludes token-based pricing creates cost friction requiring constant cost-benefit calculations, and recommends using Claude Code as a supplementary assistant for specific tasks while reviewing everything and monitoring API costs carefully.

Announcement: GitHub announced Agent HQ at Github Universe 2025, a unified workflow for orchestrating AI agents across development tools with mission control for assigning, steering, tracking, and reviewing agent tasks. Key features include Plan Mode for step-by-step implementation planning, Model Context Protocol server integration via GitHub MCP Registry, AGENTS.md file support for defining project-specific agent guidelines, and agentic code review combining model intelligence with CodeQL. The platform enables custom agents shareable across teams, Copilot integration with Slack/Teams/Linear/Azure Boards, and enterprise AI controls with centralized agent management and audit logging.

Other: One resource I previously missed, Kyrylo Avramenko's WeUseRails site has a section for Ruby companies and applications in the artificial intelligence domain. Featured applications include Humadroid (SOC2/ISO 27001 compliance automation), Find Your Agent (AI agent directory), Kids AI Genius (personalized learning platform), Balance (personal finance automation), Neurooo (translation companion), Today AI Weather (AI-generated weather art), Leexi (meeting productivity), and Magicllama.ai (B2B AI workflows).

Article: Jimmy Thigpen from Thoughtbot identified three anti-patterns teams face when integrating LLMs in How to Use LLMs Without Driving Your Team Mad. These include the Magic Bandaid (fixing bugs without understanding solutions), the Review Time Sink (AI-generated code burdening reviewers), and Context Fragmentation (auto-generated artifacts lacking human reasoning). Solutions include articulating problems before using AI, starting with your own ideas before comparing with AI suggestions, establishing team LLM usage guidelines, and maintaining human context throughout code, commits, and documentation.

Release: Bibek Sharma Chapagain released Rubion, a CLI security and version scanner for Ruby and JavaScript projects that detects vulnerabilities and outdated dependencies. The gem uses bundle-audit for Ruby security checks and npm/yarn audit for JavaScript. Useful for spotting both security issues and stale dependencies in AI-generated codebases.

Article: The GoGrow Team wrote Exploring AI and Machine Learning in Ruby & Rails, examining Ruby's growing AI ecosystem. The article covers machine learning libraries including the neighbor gem, Torch.rb, and Rumale, plus AI frameworks like ActiveAgent, LangChain.rb, Raif, and RubyLLM.

Discussion: A discussion on r/rails about AI workflows impact on work/life balance noted tension between AI's goal of giving time back versus burnout from keeping up with rapid changes. Top responses included reports of spending days fixing "useless code" coworkers copy from Claude, calling it zero sum with AI imagining nonexistent libraries, and noting the paradox of 15-minute prototypes requiring 2-week full implementations. Some users offered positive perspectives on treating AI like a junior engineer requiring feedback, with multiple developers emphasizing success requires breaking work into tiny sections and maintaining strong oversight.

Announcement: The Rails Foundation welcomed SerpApi as a Contributing member, a company that automates web search data collection for AI models by extracting search engine results into structured JSON via API.

Release: The Ruby Core Team released Ruby 4.0.0!

Events

Euroku 2025: The European Ruby Conference posted the videos from their September event featuring a multitude of speakers on Ruby and artificial intelligence:

Paweł Strzałkowski: Making Rails AI-Native with the Model Context Protocol
Carmine Paolino: RubyLLM: Making AI Development Beautiful Again
Obie Fernandez: Roasting Code for Fun & Profit with Structured AI Workflows
Albert Pazderin: Building interactive Ruby gem tutorials with Wasm
Chris Hasinski: Let's fine-tune a model!

Upcoming

November 21st - Hackathon: As part of the San Francisco Ruby Conference community day, AngelList will be hosting a Ruby Hack Day from 9am to 4pm in San Francisco.

November 21st - Conference: The Tiny Ruby Conf on November 21st in Helsinki, Finland will include two AI-related presentations including:

Hana Harencarova: Level Up Your Engineering Career with Mentorship, Pairing, and AI
Louis Antonopoulos: Unlocking the Rubetta Stones: Translating a Hoard of Ancient Tablets with Ractors and AI

December 3rd - Meetup: ArtificialRuby is hosting a meetup at Betaworks in New York City on December 3rd. If you are interested in presenting at an ArtificialRuby meetup, please fill out this form and let them know. Speakers will include Daniel Doubrovkine and Vicente Reig, with talks to be determined.

December 3rd - Meetup: Vienna.rb will meet on December 3rd at Sentry in Vienna, Austria for a talk by Paweł Strzałkowski on AI Interfaces in 5 Minutes: Model Context Protocol on Rails.

Open Source Updates

New Gems

Links to the RubyGems page, newest releases are first:

ruby_llm-sequel - Sequel adapter for RubyLLM models

cton - Compact Token-Oriented Notation encoder/decoder

agent_status_bulb - Control a SwitchBot Color Bulb based on agent status

ruby_llm_swarm - Fork of RubyLLM with features to power Swarm, a multi-agent orchestration framework

polylingo_chat - Realtime chat with automatic AI translation for Ruby/Rails apps

rails-image-post-solution - Rails engine for image reporting and AI-powered moderation

toon-rb - TOON encoder/decoder for Ruby

json-to-toon - Transforms JSON into the custom, human-readable Toon Format

simple_flow - A lightweight, modular framework for building composable data processing pipelines

cloudmersive-frauddetection-api-client - Scan input documents for fraud and other security threats using Advanced AI

light-openai-lib - Minimal OpenAI chat completions client with retry logic

ruby-toon - Token-Oriented Object Notation (TOON) implementation for Ruby

cloudmersive-documentai-api-client - Use next-generation AI to extract data, fields, insights and text from documents

reclaim - Ruby client for Reclaim.ai API

toon_my_json - Bidirectional JSON - TOON (Token-Oriented Object Notation) converter

htm - Hierarchical Temporary Memory for LLM robots

tencentcloud-sdk-dataagent - Tencent Cloud DataAgent SDK for Ruby

crudrag - A CRUD + RAG layer for Ruby agents

minitest-promptfoo - Minitest integration for promptfoo - test your LLM prompts

reducto_ai - Ruby client for the Reducto document intelligence API

lingodotdev - Ruby SDK for Lingo.dev

ruby-x402 - Rack middleware and client for the x402 payments protocol

rtoon - Parser for Token Object Oriented Notation (TOON)

tencentcloud-sdk-ags - Tencent Cloud AGS SDK for Ruby

ruby_agent - Ruby agent framework

semchunk - Split text into semantically meaningful chunks

act_as_agent - Build and manage AI agents

smart_proxy_openbolt - Smart Proxy plugin for OpenBolt integration

foreman_openbolt - Foreman OpenBolt integration

parsekit-bin - Ruby document parsing toolkit with PDF and OCR support

dspy-gemini - Gemini adapters for DSPy.rb

dspy-anthropic - Anthropic adapters for DSPy.rb

dspy-openai - OpenAI and OpenRouter adapters for DSPy.rb

sorbet-toon - TOON encode/decode pipeline for Sorbet signatures

kingdee_api - Authenticated HTTP client for the Kingdee Cloud API

sqa-tai - Technical Analysis Indicators

lingvanex-unofficial-rb - Wrapper for the Lingvanex Translation API

active_translation - Easily translate specific attributes of any ActiveRecord model

senthor_rails_legacy - Senthor middleware for Ruby on Rails applications

rails_ai_promptable - Add AI promptable behavior to your Rails models and classes

blueshift_crm - Ruby client for Blueshift CRM API

senthor_rails - Senthor middleware for Ruby on Rails applications

New Open Source

Links to the Github repository:

FerrumMCP - MCP server that provides web automation capabilities through Ferrum, with optional BotBrowser integration for advanced anti-detection features

NewRelic AI Agent Action - Automatically generate NewRelic observability configurations for your pull requests using AI

Clinesweeper MCP - Minesweeper game server that lets your Claude AI play Minesweeper via the Model Context Protocol

MetricMind - Developer productivity analytics system that extracts, stores, and visualizes git commit data from multiple repositories to measure impact

Redmine MCP Server - MCP server that provides AI assistants with access to Redmine project management software

QuickBooks Online MCP Server - MCP server for QuickBooks Online integration

Botster Hub - Automates GitHub issue/PR mentions into local CLI agent sessions

Sales AI - Sales support SaaS platform that utilizes generative AI and RAG to analyze companies' sales know-how

SEO AI Engine - Rails engine for automated SEO opportunity discovery and content generation using AI

StudyCompanion - Persistent AI companion that extends learning beyond tutoring sessions

DebugAI - AI-powered log analysis for Ruby applications

Freshdesk AI Summarizer - Lambda function that summarizes Freshdesk tickets to assist with troubleshooting

Discourse llms.txt Generator - Automatically generates llms.txt files for LLM optimization on Discourse forums

Jobs & Opportunities

One Last Thing

VectorChord

Scalable, fast, and disk-friendly vector search in Postgres, vectorchord is the successor of pgvecto.rs.

vectorchord.ai

Discovered thanks to the latest edition of RubyWeekly, VectorChord is a PostgreSQL extension for scalable, high-performance vector similarity search, delivering 16x faster indexing and 14x faster inserts than pgvector while handling billions of vectors on a single machine. Key features include better filtering, external index building, complete pgvector compatibility, and hybrid search combining full-text search with vector queries.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - November 4th, 2025

Matt Solt — Tue, 04 Nov 2025 13:02:41 +0000

Welcome to the 18th edition of Ruby AI News! This editions features awesome AI product launches from the community, a look at Cursor 2.0, and a review of tons of new Ruby AI gems, content, and updates.

Read on the web

Top Launches
Content
Events
- Previous
- Upcoming
Open Source Updates
Jobs & Opportunities
One Last Thing

Top Launches

In lieu of Top Stories this edition, I wanted to highlight some of the awesome Ruby AI-related launches I discovered since the last newsletter:

PWV Fund I

PWV - Early stage capital for technology founders

PWV is a Silicon Valley venture capital firm led by Tom Preston-Werner. We back category-defining companies from zero to breakout.

pwv.com

Tom Preston-Werner, GitHub co-founder and Jekyll creator, announced PWV Fund 1, raising $100 million for pre-seed and seed stage investments in software and AI-driven companies. The fund operates on three core principles: a founder-centric approach prioritizing founder success through real-world mentorship to accelerate growth and prevent costly mistakes, community building leveraging 150+ active portfolio companies for peer learning and networking opportunities, and strategic connections facilitating warm introductions to top-tier Series A investors. Tom’s 13-year angel investment portfolio includes early-stage bets on Cursor, Stripe, Netlify, Snyk, Supabase, PlanetScale, and Retool in addition to over 175 other startups. The fund is led by Tom alongside partners David Price and David Thyresson, both experienced entrepreneurs with track records building, scaling, and exiting companies. Interested founders can apply at pwv.com/apply.

Fizzy

Fizzy Private Beta

37signals.typeform.com/to/XCSU26s6

37signals announced Fizzy, a card-based kanban-style issue tracker launching later this year. Jason Fried shared the first preview showing the collection view with cards and two simple columns, designed to be straightforward and approachable for any kind of work beyond software development. David Heinemeier Hansson opened early access signups for a limited number of accounts, describing Fizzy as "our fresh, fun take on cards and kanban-style issue tracking." The product includes a number of Ruby AI features: Jason demonstrated the "Sunday Paper", a weekly AI-generated summary delivered once a week to expose patterns and highlight activity. Jorge Manrubia, Principal Programmer at 37signals, revealed the technical implementation uses Carmine Paolino's RubyLLM gem with the OpenAI API.

Jason and David discussed Fizzy Q's and A's on the REWORK podcast, answering listener questions ahead of Fizzy's launch. They clarified how Fizzy and Basecamp will coexist as complementary tools serving different workflows, showcasing the importance of aesthetic design choices in software products, and provided their perspectives on Fizzy’s AI features.

Kr8d

Run Your Music Studio Like a Business

https://kr8d.com/

Obie Fernandez revealed Kr8d, a music production studio management SaaS platform addressing pain points in professional studio operations. Kr8d allows you to run your music studio like a business, with AI handling the busywork. The platform automates project organization, version tracking, and workflow management with AI-powered metadata tagging that handles administrative overhead without manual importing. Kr8d features automatic Ableton Live synchronization through a native macOS desktop app, background metadata extraction, waveform preview and version comparison for audio exports, visual workflow boards tracking projects through production stages, centralized team communication reducing email chaos, and automatic versioning of projects, bounces, and masters. Obie shared he built the entire platform solo in his spare time over several months using AI-assisted development, estimating the work would have required a high-end team of 4 developers, 1 designer, and 1 business analyst working 6-12 months, calling it "at least half a mill of wealth creation" and demonstrating the possible productivity gains from AI.

ClickGems

ClickGems - RubyGems analytics

Free Analytics service for Rubygems downloads, powered by ClickHouse

clickgems.clickhouse.com

ClickHouse, Ruby Central, and Metabase collaborated to launch ClickGems, a free analytics platform providing comprehensive download statistics for over 200,000 Ruby gems totaling 208 billion downloads from 2017 to present. The platform leverages ClickHouse's analytics database with materialized views for fast query performance, offering shareable charts, download trends, geographic distribution, and emerging package detection across Recent Releases, Top Repositories, Hot Packages, and Stable Packages categories. The ruby_llm dashboard exemplifies the platform's AI-focused gem tracking, showing Carmine Paolino's RubyLLM gem has achieved 3.7 million downloads with significant growth starting June 2025, peaking at over 312,000 downloads in July and September. ClickGems enables developers to export visualizations to documentation and project pages while providing direct SQL query access through ClickHouse's SQL Playground for custom analytics.

Undercover CI

UndercoverCI | Actionable test coverage checks for Ruby and Github

Stop focusing on getting to 100% test coverage. Detect when changed code is untested before it's deployed.

undercover-ci.com

Jan Grodowski created Undercover CI, a GitHub-integrated service detecting untested changes in pull requests whether code is written by AI tools like Claude or by humans, providing smart annotations and dashboard tracking for PR trends. With a focus on auto-generated code, Undercover CI analyzes code structure and your SimpleCov rules, allowing you to merge commits with confidence and monitor the health of your test suite. Also available as a Ruby gem, Undercover identifies methods, classes, and code blocks modified without test coverage by analyzing git diffs, code structure, and SimpleCov reports. The tool integrates with all Ruby testing frameworks, supporting both line and branch coverage analysis with configurable .undercover files, and runs locally via CLI or in CI/CD pipelines. Discovered thanks to their sponsorship of the Short Ruby Newsletter!

Coolhand Labs

coolhand | Welcome

Actionable Cost & Quality Intelligence for LLM Workflows

coolhandlabs.com

Mike Carroll of Coolhand Labs launched an LLM workflow monitoring platform providing cost and response quality intelligence through a dashboard tracking LLM performance metrics. The platform features quality evaluation loops converting user feedback into automated assessments to prevent regressions, cost optimization with alerts for model switching opportunities and token bloat detection, expense forecasting, and HIPAA compliance for healthcare applications with enterprise-grade security. As part of the launch, Coolhand Labs released coolhand-ruby, a monitoring gem that automatically tracks LLM API calls across multiple LLM models through LLM provider gems that use Faraday. The gem intercepts HTTP calls without requiring code changes, featuring async logging, automatic credential sanitization, and feedback collection.

Orchestry AI

Orchesity AI | Enterprise AI Orchestration Platform

Enterprise-grade AI orchestration platform. Generate production-ready applications instantly with natural language. Advanced multi-agent system for automated development and deployment.

www.orchesity.com

Orchesity created an AI orchestration service for specialized AI agents to generate production-ready backend applications, including Ruby as a supported framework. Built by Rickie Anh Nguyen, the platform moves from prompt to production by generating complete backends with authentication, database integration, tests, Docker, and CI/CD with intelligent task distribution. For Rails developers, Orchesity generates project scaffolding, database integration, secure authentication systems, specialized AI agents, and coordinates AI orchestration with intelligent routing.

Content

Announcement: Cursor, the AI-powered IDE, released Cursor 2.0, featuring Composer, their first proprietary coding model that is 4x faster than similarly intelligent models and completes most tasks in under 30 seconds. The model was trained with codebase-wide semantic search capabilities for enhanced code navigation. The redesigned interface prioritizes multi-agent workflows, supporting parallel agent execution via git worktrees or remote machines, with improved code review mechanisms and native browser integration for automated testing and iteration. Rhea Purohit of Every reviewed Cursor 2.0 and Composer 1 Alpha, examining Cursor's releases of the updated IDE and Composer. Composer's primary strength is exceptional speed that maintains developer flow state for iterative work with clear objectives, though it's less capable than Claude Sonnet 4.5 or GPT-5 for exploratory coding in unfamiliar codebases.

Article: Every's engineering team also documented AI workflows across their six engineers managing four AI products and consulting services. Each engineer customized their stack: Yash Poojary runs Claude Code and Codex on separate machines for parallel comparison and built AgentWatch to monitor multiple sessions; Kieran Klaassen uses Claude Code and three-tier complexity planning for features with Context 7 MCP pulling documentation into prompts; Danny Aziz operates primarily in Droid CLI splitting work between GPT-5 Codex and Anthropic models; Naveen Naidu anchors work in Linear with dual tracks for quick fixes and complex features; Andrey Galko switched from Cursor to Codex crediting GPT-5 for quality UI generation; Nityesh Agarwal uses exclusively Claude Code, interrupting mid-process for explanations to reduce hallucinations. Common patterns include intentional tool selection, planning and context grounding, structured workflows separating execution from exploration, integrated MCPs for design and issue tracking, and asynchronous agent work.

Opinion: Michael Bleigh proposed Context Engineering is Sleeping on the Humble Hyperlink, advocating hyperlinks as an underutilized technique for providing AI models context only when relevant. The approach reimagines HATEOAS (Hypermedia as the Engine of Application State) for AI agents that can parse and navigate hyperlinks, requiring minimal scaffolding: a read_resources tool accepting URIs and an entrypoint providing initial URIs. Benefits include easier implementation, token efficiency through on-demand loading, tool consolidation, just-in-time context delivery mitigating recency bias, and flexibility across workflows.

Article: Continuing on this concept, Daniel Doubrovkine wrote about Turning Hypermedia APIs into MCPs, converting HATEOAS APIs into Model Context Protocol servers using a Slack bot as an example. He created the Ruby gem hyperclient-mcp that automates conversion by mapping templated resource patterns directly to MCP concepts, supporting discovery commands to identify available resources and server launch for Claude Code integration. Daniel will be speaking about the hyperclient concept at the ArtificialRuby meetup in December.

Release: Cyril Blaecke released Nosia, a self-hosted Rails and RubyLLM-based RAG platform enabling organizations to run AI models on proprietary data with complete privacy and data sovereignty. The platform provides OpenAI-compatible APIs, vector-based semantic search using pgvector, multi-format document support, and real-time streaming responses via server-sent events.

Update: Carmine Paolino shared recent developments in RubyLLM, including support for Nano Banana with RubyLLM, Google's image generation model that operates through the chat endpoint rather than the typical image API. Just released RubyLLM version 1.9 also adds support for unpacking inline file data from chat responses, enabling developers to retrieve generated images as StringIO objects through a single chat endpoint call. Other updates include a new transcription API supporting OpenAI models with automatic parameter configuration for speaker diarization, plus Google Gemini transcription support. Carmine additionally shipped Anthropic Prompt Caching using raw content blocks for direct access to message content, and introduced a params DSL upgrade with full JSON Schema support via RubyLLM::Schema for defining tool parameters.

Tutorial: JetThoughts published Ruby LangChain Testing Guide | RSpec + Webmock, addressing the challenges of testing LLM applications including non-deterministic responses, expensive API calls, and rate limits. The guide presents a three-layer testing strategy: Unit tests with WebMock and RSpec doubles for free, fast validation; VCR tests recording real API responses once for replay; and gated integration tests against live APIs only on the main branch. Key patterns cover conversation memory testing, error handling for responses with exponential backoff, and CI/CD integration with cost controls including token counting, max_tokens enforcement, and near complete test coverage requirements validated by SimpleCov.

Podcast: Joe Leo and Valentino Stoll of The Ruby AI Podcast interviewed Justin Searls on The TLDR of AI Dev: Real Workflows with Justin Searls, discussing the critical distinction between AI capability and suitability in development workflows. Searls argues that agentic AI tools have entered a "capability spike" where they move faster than established safety mechanisms, creating a gap between what AI can technically do and what's practically trustworthy. The accompanying show notes explores "subtractive vs. generative AI" and advocates for proven agile wisdom applied at a new layer: short loops, real feedback, and stopping when things go wrong, with humans supervising machines rather than just code. Stay tuned for the next episode covering Mastering LLMs with DSPy.rb and Vicente Reig.

Tutorial: Christopher Winslett of Crunchy Data demonstrated Integrating AI Embeddings in Rails using the Neighbor Gem with PostgreSQL's pgvector extension. The gem resolves ActiveRecord's inability to recognize vector data types, enabling proper schema generation including HNSW (Hierarchical Navigable Small World algorithm) indexing, and eliminates the need for raw SQL in migrations. The has_neighbors method provides nearest neighbor queries with euclidean and cosine distance metrics, allowing developers to work with AI embeddings using standard ActiveRecord syntax.

Release: Shannon Skipper ported nanochat to a Ruby gem, bringing Andrej Karpathy's PyTorch language model implementation to the Ruby ecosystem. The gem lets you train and run your own small language models in Ruby, making it possible to build a ChatGPT-style AI that you can customize and fine-tune on your own data. The gem supports model inference, fine-tuning, and tokenizer training.

Update: Vicente Reig released DSPy.rb versions 0.29.0, 0.29.1, 0.30.0, and 0.30.1, bringing architectural changes and prompt optimization capabilities. Key updates include GEPA (Genetic-Pareto Reflective Prompt Evolution) prompt implementation, MIPROv2 (Multiprompt Instruction Proposal Optimizer) enhancements aligning with the Python library, modularization into separate gems (dspy-gepa, dspy-o11y, dspy-o11y-langfuse) for optional dependencies, module-scoped event listeners, and Ruby 3.3 support. Vicente also demonstrated building a production-ready Adverse Drug Event classifier, documented in issue #155 achieving 85% accuracy with 100% recall on clinical text classification. In issue #156, Vicente proposed a Scenic-style versioned migration system for managing optimized prompts as executable Ruby artifacts with git-friendly versioning, integrated metric tracking, and ActiveRecord-like APIs.

Release: Vicente also shared updates on DSPy.rb tooling development across multiple tweets. He is preparing a Deep Search & Deep Research guide for Ruby using DSPy.rb with Shopify's cli-ui gem, exploring Jina AI's architectures alongside Exa AI Labs, with the foundation being metered agents that reason through data before writing. He created the exa-ai-ruby client using a technique of feeding Claude/Codex sample architecture docs with sequence and dependency diagrams, built lf-cli giving AI tools access to Langfuse traces for automating evals, and created whatsapp-cli enabling Codex and Claude Code to interact with WhatsApp.

Article: Anton Kuzmenko of Aha! worked through Streaming AI Responses and Incomplete JSON, addressing the challenge of parsing character-by-character streamed JSON from LLM APIs. Existing solutions like json-repair use O(n²) complexity, reparsing the entire accumulated string with each chunk, causing excessive lag. Anton's stateful incremental parsing approach maintains parsing state between calls, achieving O(n) performance that processes the same JSON 388 times faster with sub-millisecond latency. The solution is available as the json_completer Ruby gem.

Video: David Kimura implemented Failover Requests in Drifting Ruby episode #534, implementing fault-tolerant API calls using the ruby-openai gem. The tutorial builds an OllamaClient class with an attempt_with_failover method that cycles through multiple Ollama endpoints, using local instances with cloud backup for AI model requests. The implementation handles connection errors like Faraday::ServerError by automatically failing over to the next endpoint, raising an AllEndpointsFailed exception only when all endpoints are exhausted.

Podcast: Reinteractive's Technology for Humans podcast featured three Ruby community leaders discussing AI integration and ecosystem challenges with Errol Schmidt: Ben Curtis, Honeybadger co-founder, emphasized that AI can significantly accelerate software development when used correctly but warned developers against blindly adopting AI tools without assessing utility, stressing the importance of understanding technology behind applications. Henning Koch, Makandra founder and Head of Development, discussed the future of legacy Rails apps through Rails LTS, AI's place in development agencies, and Rails comparisons to other frameworks. Shan Cureton, Ruby Central Executive Director, addressed the RubyGems and Bundler ownership transition to the Ruby Core team, confronting community concerns.

Update: Obie Fernandez released ConciseErrors, a Rails gem providing compact error pages optimized for AI coding agents by swapping out Rails DebugExceptions middleware for a minimalist alternative. The gem addresses the problem of Rails default full-page error UI consuming excessive tokens that unncessarily increase AI context windows. In Notes from a Busy Season, Obie shared his continued AI productivity work, including authoring Patterns of Application Development Using AI. He advocates that Ruby on Rails principles emphasizing sensible defaults and clean boundaries pair effectively with AI coding agents, arguing that individuals using agentic AI can now achieve output comparable to entire teams.

Article: Ravi Prakash wrote Meet Your New Rails Co-Workers: Building AI Agents in Ruby Like a Pro and How to Integrate MCP Servers into a Ruby on Rails App (Medium links), exploring Ruby's AI revolution. The first article introduces autonomous LLM-powered AI agents using the ai-agents gem, enabling Rails apps to move from CRUD operations to systems that can reason, take actions, and collaborate. The second article provides a practical guide for integrating Model Context Protocol (MCP) servers into Rails apps using JSON-over-HTTP/WS for passing context and state between applications and AI agents, emphasizing separation of concerns and interoperability.

Release: Keith Bennett released simplecov-mcp: Code Coverage MCP Server v1.0.0, a gem that exposes SimpleCov test coverage data as an MCP server, CLI, and Ruby library. The gem features staleness detection for outdated coverage files, automatic merging of multi-suite test results (RSpec + Cucumber), and multiple output formats including tables, JSON, and annotated source code.

Tutorial: Darko Gjorgjievski explained Spec-Driven Development: What It Is and How to Get Started with Spec Kit + Kilo Code, a methodology that treats specifications as source of truth rather than code to improve AI agent reliability. The approach addresses "vibe coding" ambiguity through GitHub's open-source Spec Kit toolkit, implementing a four-command workflow: /specify creates feature requirements, /plan defines technical strategy, /tasks generates ordered implementation steps, and /implement executes changes sequentially with human oversight.

Tutorial: FuturisticAps wrote Rails + AI/ML: Building Smarter Apps with Ruby, demonstrating how to integrate AI capabilities into Rails applications through external APIs and Ruby ML libraries. The tutorial covers building an AI chatbot using the ruby-openai gem with step-by-step implementation from configuration to frontend, connecting Rails with Python machine learning models via REST endpoints, and performing sentiment analysis with the rumale library.

Article: Islam Gagiev and Joao Gilberto Saraiva of JetRockets described Building a Resilient AI Client in Ruby with Stoplight and RubyLLM, implementing the Circuit Breaker pattern to prevent cascading failures when AI providers experience outages. The implementation uses the stoplight gem to monitor external service calls across three states (Closed, Open, Half-Open), enabling graceful failover from different LLM models while preserving conversation context. The architecture abstracts provider differences through RubyLLM while stoplight handles error isolation, making it suitable for systems requiring uninterrupted AI functionality.

Announcement: Scott Werner introduced touring_test: A Cucumber Extension for AI-Driven Usability Testing, a Ruby gem extending Cucumber to enable AI-driven usability testing that deploys AI agents to interact with websites like real users instead of using hardcoded DOM selectors. The gem currently supports Google's Gemini Computer Use model, taking screenshots and sending them with natural language instructions to the AI which decides actions based on visual interpretation, revealing usability problems that traditional tests with just knowledge of the DOM structure miss. Scott proposes calling this Agentic Behavior Driven Development (ABDD), where agents discover usability gaps and implement fixes until the workflow succeeds.

Video: On Moar AgentBackedCommands: Or How Domain Logic Couples Code, Miles Georgi shared the foobara-agent-backed-command gem, splitting a complex command into two coordinating commands where LLMs operate the domain instead of traditional domain logic implementation. The demo revealed two key insights: code units without domain logic allow interface changes without breaking dependencies that also lack domain logic, and a "deautomation" development pattern where LLMs fill-in domain gaps early, then real domain logic replaces LLM operations later.

Launch: Anthony Panozzo released PlainErrors: Streamlined Rails Error Pages for LLM Agents, a Rack Middleware gem that reduces error page token consumption for AI-assisted debugging. The library’s optimizations enable LLM agents to perform more debugging and iteration within context window limits, particularly beneficial when using tools like Claude Code with the Playwright MCP for local testing.

Podcast: Brendan Buckingham and Ryan Frisch of Rails Business interviewed Scott Werner, CEO of Sublayer, on AI-Driven Development and the Future of Software Engineering, exploring how startups leverage AI tools for development and maintenance. The discussion covered Sublayer's AI products including APM, Augmentations, and the Artificial Ruby meetup. Scott discussed business models for monetizing AI-driven development tools, practical applications in engineering workflows, and how rapid change cycles are creating a "fast fashion era" in software development.

Announcement: Maciej Mensfeld released LLM Docs Builder, an open-source Ruby tool that transforms Markdown documentation for AI consumption, reducing token usage by 85-95% compared to HTML versions. The library strips semantic noise while preserving code syntax and hierarchical context for RAG systems through heading normalization, and generates an llms.txt index file, serving optimized docs to AI crawlers automatically.

Article: Hashrocket added two articles on spec-driven AI development: Vinicius Negrisolo's OpenSpec vs Spec Kit: Choosing the Right AI-Driven Development Workflow for Your Team and Craig Hafer's Spec-Driven Estimation: How Devs Can Estimate Features Quickly and More Accurately with AI. Vinicius compares OpenSpec (faster, simpler for senior developers) with Spec Kit (more structured with explicit role separation), noting OpenSpec moves directly from proposal to implementation while Spec Kit includes detailed task breakdown phases. Craig demonstrates using Spec-Kit's three-step process (/speckit.specify, /speckit.plan, /speckit.tasks) to automate structured thinking that would manually take much longer, generating comprehensive specifications with user stories, test plans, and task dependencies for accurate feature estimation.

Opinion: Drew Breunig argued in Speeds and Swarms that the AI coding community undervalues velocity, contrasting slower models like Claude Sonnet with faster alternatives like Qwen 3 Coder (30x faster), which enables real-time interaction and reduces friction for experimentation. Drew highlights claude-on-rails as an exemplary framework applying Rails' "convention over configuration" philosophy to multi-agent systems, isolating agents to standard Rails directories and pre-loading framework-specific documentation to overcome Git conflict complexity when running multiple AI agents in parallel. He predicts speed will soon take center stage over accuracy benchmarks, creating a paradigm where code emerges nearly as quickly as thought.

Video: Vojtech Rinik recorded Bringing Zod to Ruby on Rails using RubyLLM::Schema, showing how RubyLLM::Schema brings Zod-like schema validation to Rails. The approach validates requests and responses while automatically generating OpenAPI schemas, enabling automatic Swift interface generation for mobile clients. RubyLLM::Schema emulates the TypeScript-first Zod validation library within the Ruby ecosystem, providing type safety and schema-driven development patterns.

Update: Geir Isene announced major upgrades to RSH (Ruby Shell), a single-file Ruby-based shell emphasizing simplicity and extensibility. Recent enhancements include a full plugin architecture, session management, intelligent tab completion weighting based on usage frequency, context-aware learning, command performance statistics, and custom validation rules for dangerous commands.

Article: Kody Kendall documented building an AI coding agent within Leonardo that Writes Rails Tests Using RSpec, choosing RSpec over Minitest after analyzing LLM training data distribution and Rails ecosystem tooling. A key innovation is mutation testing with Mutant, which applies controlled code modifications to verify tests catch actual bugs rather than just achieving coverage percentages, providing objective feedback on AI-generated test quality. The verification stack includes a hardened RSpec configuration, SimpleCov for test coverage thresholds, property-based testing with PropCheck, contract validation via Pact, and RuboCop linting.

Video: Thoughtbot demonstrated AI-assisted prototyping across three livestream sessions: Extreme Rapid Prototyping with Claude where they built an agent to digest research and create a landing page using design-driven prompting, The Dev Side of Claude-Assisted Prototyping where they showed how Claude accelerated development and made live improvements to the prototype in realtime, and Building an MCP-Powered Assistant where the team wired up a lightweight Model Context Protocol server exposing app endpoints and letting the LLM call those tools while keeping responses in a consistent “Thoughtbot voice”.

Launch: Jaye launched a Rails To Revenue series documenting the build-in-public creation of DocForge, a Rails SaaS application developed with AI-assisted workflows. The series begins with the YouTube Intro and Episode 01: DocForge Unleashed outlining the Rails stack supercharged by Claude Code, Gemini, and Codex. Episode 02 covers the Linux Mint dev environment setup on VirtualBox, while Episode 03 demonstrates wiring up PostgreSQL and Devise authentication. The series also includes Creating a Claude Code Agent that automates Git commits by reviewing staged changes, assembling commit messages, and pushing to GitHub.

Article: Shaher Shamroukh detailed Building an AI Social Media Manager with Ruby on Rails: Architecture, Automation, and Lessons Learned, describing RobinReach's service-driven architecture that leverages RubyLLM for AI-powered features including caption and hashtag generation, automated post creation, and content refinement.

Podcast: On the Strictly From Nowhere Podcast, Mike Rispoli, Co-Founder & CTO Cause of a Kind, joined Justin Abrams for Ruby on Rails Is the Holy Grail. They discuss why Ruby on Rails is their preferred framework for software development, and highlight Rails' scalability, strong conventions, portability across deployment options, and built-in features for common patterns. The conversation emphasizes how Rails' conventions particularly benefit AI-driven software development and compares it with Django and Laravel, noting that machine learning applications can be built independently of the web app layer.

Article: Neal Lindsay of Test Double explained Keep Your Coding Agent on Task with Mutation Testing (Javascript-focused), advocating for mutation testing to validate AI-generated code quality. Neal argues that while LLMs excel at code generation, they produce excessive output requiring quality validation, and mutation testing tools like Stryker Mutator deliberately introducing errors to confirm tests actually validate behavior rather than just execute code. Neal discovered the concept through Heckle, an older Ruby mutation testing gem.

Documentation: Playbooks and PulseMCP documented the Hatchbox MCP Server, a JavaScript-based MCP server enabling AI assistants to manage Hatchbox's Rails application hosting platform directly. The server provides environment variable management via SSH access, and controls to trigger new deployments for Rails apps.

Article: Brandon Casci detailed Building a Production App with AI: The Boswell Story rebuilding Boswell, a food bank SaaS platform, using Claude Code. Success required explicit domain knowledge documentation, structured workflows with human review gates, and constraint management to prevent AI circumvention. Brandon argues that AI-assisted development requires months of investment to succeed, with successful vibe-coded weekend projects being the rare exception.

Opinion: Sam Saffron argued in Your Vibe Coded Slop PR is Not Welcome that AI coding tools have made code generation cheap but not code review, creating unsustainable pressure on open source maintainers. Sam recommends maintainers protect their time with strict review timeboxes and close low-quality pull requests without guilt, while contributors should avoid sending unreviewed requests and clearly label AI-assisted work.

Article: Aotokitsuruya explored The Potential of Ruby's ri Command for Coding Agents, developing a Ruby Plugin to integrate ri documentation queries as an agent skill for Claude Code. Official package documentation surpasses search engine results and consumes fewer context tokens when verifying standard library usage. To address limitations including inconsistent ri documentation availability and uncertain version compatibility, Aotokitsuruya created an explicit /ruby:info [query] command directing agents to use ri rather than relying on agent discretion.

Announcement: ImageKit released the imagekitio-rails gem for Ruby on Rails integration, providing view helpers ik_image_tag and ik_video_tag that handle URL generation, transformations, and responsive images automatically with Active Storage support. The gem features AI-powered transformations including background removal, image upscaling, and AI drop shadow effects. The Rails integration processes transformations instantly on ImageKit's servers without round-trips, avoiding Active Storage's variant method limitations, while supporting lazy loading, signed URLs for private content, and responsive images.

Update: GitLab released Composite Identity for AI Features, a security mechanism ensuring AI-generated write operations require dual authentication through both a service account and the human user who initiated the request.

Article: Datadog's SDLC Security team described Detecting Malicious Pull Requests with LLMs, introducing BewAIre, an LLM-powered system reviewing nearly tens of thousands of pull requests weekly with >99.3% accuracy and 0.03% false positive rate. The system addresses security challenges from AI-assisted development accelerating code volume by detecting intent-based attacks traditional static analysis misses.

Announcement: Anton Lovchikov of Evil Martians announced that LaunchKit has been ported to bolt.new, enabling developers to customize the devtool landing page template through AI prompts. The integration allows users to adapt the template to their product using natural language instructions on the Bolt platform.

Launch: Amanda Bizzinotto of OmbuLabs introduced AI Readiness & Transformation Assessment for Development Teams, offering a comprehensive four-week assessment and evaluation framework examining current AI tool usage, infrastructure capabilities, team proficiency, and organizational culture.

Tutorial: Visnupriya explored How to Supercharge Your Rails App with MCP Server and Copilot for AI-Driven Translation, building a translation app using the mcp-on-rails template that enables AI assistants to directly interact with Rails application data and actions. The tutorial covers scaffolding resources, testing with MCP Inspector, and configuring VS Code integration, with security recommendations including authentication, rate limiting, and input validation.

Podcast: Jeremy Smith and Jess Brown discussed artificial intelligence on IndieRails Episode 66: The Obligatory AI Episode, covering AI developments and their perspectives as indie Rails developers.

Announcement: Rafael Silva from Discourse announced Discourse MCP Is Here!, a standalone CLI tool enabling AI assistants like Claude to search forums and read topics in real-time. Rather than embedding MCP directly into Discourse's Rails application, the team built a Node CLI that leverages Discourse's REST API and translates it into MCP calls, inheriting API key scopes and rate limits.

Article: Victor Velazquez of MagmaLabs detailed AI HealthTech MVP with Ruby on Rails: Build Quickly and Securely, providing guidance for building secure AI-powered healthcare MVPs while maintaining HIPAA compliance.

Tips: David Alejandro discovered Samuel Williams' agent-context gem, which automatically generates an agents.md file containing AI context from installed gems that provide context metadata in a context/ directory by running bundle exec bake agent:context:install.

Opinion: Ed Frank from Test Double argued in 5 Rules to Avoid the 95% AI Project Failure Rate that MIT research showing 95% of corporate AI pilots fail stems from organizational issues rather than technology limitations. The five non-negotiables are quantifying success through measurable business outcomes, enforcing agile methodologies at the C-suite level, restructuring leadership decision-making away from command-and-control models, transforming organizational workflows before deploying AI, and fixing fundamental data inconsistencies and broken processes.

Release: The Rails core team announced Rails 8.1. Major features include ActiveJob continuations for resuming long-running jobs, structured event reporting for machine-readable event emission, local continuous integration, and native markdown rendering. Scott W. Hill reported that upgrading to Rails 8.1 was straightforward and demonstrated AI-assisted deployment using autonomous agents that handled testing, changelog updates, production deployment, and documentation.

Tips: Obie Fernandez posted Using Claude Code? Learn to Write Skills ASAP, explaining that Claude Code skills have displaced MCP for him entirely, leading to faster agent behavior. The tutorial provides step-by-step instructions to add the Claude Code Plugin marketplace and install example skills. Obie demonstrates creating a Honeybadger API skill by simply telling Claude to create it, which writes the skill, packages it, and provides installation instructions within minutes, making custom skill creation easier than searching for pre-written skills.

Events

Rocky Mountain Ruby: Anton Tkachov's conference overview and Jarred Dotterer's personal reflection captured Rocky Mountain Ruby 2025's emphasis on thoughtful AI integration and community values. Key AI-focused talks included:

Scott Werner: We Were Voyagers. We Can Voyage Again!
Christine Seeman: Thoughtful AI for the Rubyist
Brandon Weaver: We Who Remember Magic
Ted Tash: Not Another AI Talk
Don Barlow: Tidewave Web Demo
Travis Dockter: Oh my Claude, What Have I Done

ArtificialRuby: The October 15th ArtificialRuby Meetup in New York City featured three speakers and demonstrations:

Steve Brudz: Self‑Healing Tests & Everflame Reports: AI‑Powered QA for Rails
Damani Brown: Giving AI the Keys to Chrome DevTools
Joel De La Cruz: The New York State RAISE Act: The Race For AI Safety Regulation

Upcoming

November 6th - Meetup: Dresden.rb will meet on November 6th in Dresden, Germany and feature a disucssion by Benjamin Deutscher on LLM Coding and its effects on a developers every day work, debating LLM use and how it affects coding style.

November 7th - Conference: RubyWorld Conference 2025 on November 6th and 7th in Matsue, Japan will include four Ruby AI and hardware talks:

Takayuki Yoshioka: Redmine × Generative AI - The Potential of Issues Management
Koichi Ito: Ruby x LLM Ecosystem
Hayao Kimura: Exploring the World of Electronic Engineering with PicoRuby
Hitoshi Hasumi: Why Now Is the Right Time for PicoRuby

November 12th - Meetup: Ruby on Rails Schweiz is gathering on November 12th in Zürich, Switzerland to host Hana Harencarova for Level Up Your Engineering Career with Mentorship, Pairing, and AI. The presentation will discuss how to tap into mentorship, pair programming, and AI to accelerate your skillsket.

November 12 - Meetup: The Tokyo Rubyist Meetup will meet on November 12th in Tokyo, Japan for a demonstration by Justin Bowen on Agent Oriented Programming with Active Agent, an open source framework to help Ruby and Rails developers easily build AI products and features.

November 15th - Workshop: Rails Fever will be hosting another Rails AI event on November 15th (rescheduled from October 18th) in Philadelphia. This interactive session presented by Peter Bailey will explore how AI is reshaping the modern software development lifecycle. Following the presentation covering the landscape of AI-assisted software engineering, there will be a hands-on workshop to build your own AI-enhanced software development automation.

November 19th - Workshop (Paid, $1,000): Every is hosting Claude Code for Beginners, a one-day online workshop teaching beginners how to build and ship an AI app using Claude Code on November 19, 10 a.m. ET–5 p.m. ET. The beginner-friendly course is designed for both developers and non-developers, featuring live instruction with step-by-step walkthroughs, peer breakouts for collaboration, independent building time, and real-time feedback to ship a project.

November 19th - Conference: The San Francisco Ruby Conference on November 19th through the 21st in San Francisco will include an extensive AI program schedule featuring:

Workshop - Justin Bowen: Building Agents with Rails
Presentation - Brandon Weaver: Rails Expertise, Distilled: AI Agents That Get Your Monolith
Presentation - Tia Anderson: Peace, Love, and CRUD: Finding Calm in the Chaos with Ruby, AI, and a Little Garden Magic
Presentation - José Valim: Navigating Programming Language Evolution in the AI Era
Presentation - Paweł Strzałkowski: AI Interface in 5 Minutes - Model Context Protocol on Rails
Presentation - Enrique Carlos Mogollán: The MCP Fog Made Me Do It: A Ruby Inspector's Unexpected Journey
Keynote - Obie Fernandez: Ruby & AI Conversation
Roundtable - Edward Kim & Ryan King: CTO Roundtable
Keynote - Carmine Paolino: RubyLLM: One API, One Person, One Machine for AI
Presentation - Sarah Mei: The Role of Software Design in an AI World
Startup Demos - Featuring AI companies Fin AI, Bolt.new, Stepful, Simple AI, Sixfold AI, Cora Computer, Superconductor
Roundtable - A panel of venture capitalists interested in Ruby and AI-based startups
Keynote - Vladimir Dementyev: AI-powered Developer Tooling for Rails

November 21st - Hackathon: As part of the San Francisco Ruby Conference community day, AngelList will be hosting a Ruby Hack Day from 9am to 4pm in San Francisco.

November 21st - Conference: The Tiny Ruby Conf on November 21st in Helsinki, Finland will include two AI-related presentations including:

Hana Harencarova: Level Up Your Engineering Career with Mentorship, Pairing, and AI
Louis Antonopoulos: Unlocking the Rubetta Stones: Translating a Hoard of Ancient Tablets with Ractors and AI

Open Source Updates

Code Spotlight

GitHub - evilmartians/sfruby-clouds: SF Ruby Clouds Generator 😶‍🌫️

github.com/evilmartians/sfruby-clouds

Evil Martians open-sourced SF Ruby Clouds, an AI-powered Rails application that transforms attendee photos into whimsical cloud characters over San Francisco's skyline for personalized conference invites. Built with Ruby on Rails, Avo, RubyLLM, and Google’s NanoBanana image generation API.

New Gems

Links to the RubyGems page, newest releases are first:

ollama-dsl - DSL for interacting with Ollama LLMs, allowing streaming and structured prompts

imagekitio-rails - ImageKit Rails integration with view helpers and Active Storage support

rails-worktree - Git worktree management for Rails projects

touring_test - Cucumber support gem for using Google's 'computer use' Gemini model

revirow - Ruby client for the Revirow API

grist-grist - Ruby client for the Grist API

x402-payments - Generate x402 payment signatures and links for blockchain micropayments

workbush - Manage git worktrees with automatic file copying and setup commands

huntress - A Ruby wrapper for the Huntress APIs

x402-rails - Rails integration for x402 payment protocol

dspy-deep_research - DeepResearch orchestration for DSPy

dspy-deep_search - DeepSearch primitives for DSPy

nanochat - Ruby port of nanochat, a minimal LLM

google-cloud-hypercompute_cluster - API Client library for the Cluster Director API

toon-ruby - Token-Oriented Object Notation: token-efficient JSON alternative for LLM prompts

swarm_memory - Persistent memory system for SwarmSDK agents

rankvectors - RankVectors API SDK for Ruby

exa-ai-ruby - Exa API client in Ruby

dspy-gepa - GEPA teleprompter integration for DSPy.rb

dspy-o11y - Observability core (spans, context hooks, and telemetry helpers) for DSPy.rb

dspy-o11y-langfuse - Langfuse auto-configuration adapter for DSPy observability

dspy-schema - Sorbet to JSON Schema conversion utilities reused by DSPy.rb

funes - Agentic memory layer and knowledge base CLI

agentbill-sdk - OpenTelemetry-based SDK for tracking AI agent usage and billing

durable_huggingface_hub - Ruby client for HuggingFace Hub

llm_rescuer - Fix the billion-dollar mistake by spending billions on LLM tokens

dspy-code_act - Dynamic code generation agents for DSPy.rb

pdf_ocr - Ruby gem for extracting text from images using OCR

skald - Ruby SDK for Skald API

braintrust - Ruby SDK for Braintrust

ruby_llm-evals - LLM evaluation engine for Rails

concise_errors - Minimal Rails error pages tuned for AI agents and compact debugging

agentbill - OpenTelemetry-based SDK for tracking AI agent usage and billing

dspy-evals - Evaluation utilities for DSPy.rb programs

lf-cli - CLI for Langfuse

coolhand - Intercepts and logs OpenAI API calls

writers_room - Gem for managing a writers room

mcp-auth - OAuth 2.1 authorization for MCP servers

dspy-miprov2 - MIPROv2 optimizer and Bayesian tooling for DSPy.rb

dspy-datasets - Curated datasets and loaders for DSPy.rb

gepa - Gradient-based Exploration and Pareto Agents for DSPy.rb

codex-sdk - Unofficial Ruby SDK for Codex CLI

exa-ai - Ruby client for the Exa.ai API

reducto - Ruby SDK for the Reducto API

ai_error_clip - AI-friendly Rails development error page with one-click copy

New Open Source

Links to the Github repository:

rails-ai - Claude Code AI agents for Rails development

rack-mcp - Provides AI assistants with ruby code execution capabilities within the context of existing running application server

ClearClaim - AI appeal assistant for healthcare denials

Splat - Exception and performance monitoring tool built with MCP integration for AI agents to query production data

rubocop-ai-style - AI-first RuboCop style configuration, focused on machine readability rather than human aesthetics

SlopGuard - AI hallucination detection for package dependencies

Claudy - Useful plugins, agents, skills, tools for Claude Code

Beaker AI - Voice-first AI phone agent platform

Query My Pod - AI-powered podcast search

Dynamic Prompt - Store prompts in Redis instead of conversation history, enabling real-time modifications

SmartSuite MCP Server - Model Context Protocol server for SmartSuite

Pike13 MCP Server - MCP server for Pike13 API integration

RepoReconnoiter - Analyzes GitHub trending repositories using AI to provide developers with context-aware recommendations

Orchestra AI - Cursor background agents orchestrator

Story - Ruby AI story generator

Jobs & Opportunities

One Last Thing

Sometimes you encounter a cute cat at a cafe, an emporer penguin at the zoo, or an Australian box jellyfish surfing off the Great Barrier Reef, and you ask yourself, “Can I pet that dawg?” Well, you might be surprised to learn that the answer is not always “Yes!”. The world is sometimes a dangerous place, so stay safe out there, study up, and test your knowledge:

CanIPetThatDawg

Learn which animals are safe to pet through fun interactive cards and build your petting bucket list!

canipetthatdawg.app

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - October 18th, 2025

Matt Solt — Sat, 18 Oct 2025 14:41:33 +0000

Welcome to the 17th edition of Ruby AI News! This edition features a new service to generate self-healing tests for Rails applications, Claude Code skills & plugins, an amicable resolution to the RubyGems situation, and much more.

Read on the web

Top Stories
Content
Events
- Previous
- Upcoming
Open Source Updates
- New Gems
- New Open Source
Jobs & Opportunities
One Last Thing

Content

Update: Atsushi Tatsuma released Rumale v2.0.0, a Ruby machine learning library providing Scikit Learn-like interfaces. The library supports classification, regression, clustering, dimensionality reduction, and ensemble methods including SVM, Random Forest, Gradient Tree Boosting, K-Means, PCA, and t-SNE. The v2.0.0 release transitions runtime dependencies from numo-narray to numo-narray-alt and from lbfgsb.rb to numo-optimize, showcasing continued development with actively maintained Ruby numerical computing libraries. Documentation includes examples for dataset classification workflows, cross-validation implementations, and performance optimization through OpenBLAS (Basic Linear Algebra Subprograms) acceleration and parallel processing support.

Announcement: Pete Matsyburka introduced Rllama in Run Open-source LLMs Locally with Ruby. RLlama is a Ruby gem providing FFI bindings for llama.cpp to run open-source LLMs locally without external APIs. The RLlama gem supports GGUF-format models, offering text generation with streaming, multi-turn chat context, embeddings, and a CLI interface for model exploration. Use cases include prototyping Rails features, building offline agents, semantic search, text summarization, and test data generation with complete data privacy. DocuSeal developed and uses the gem to enable semantic search for their API documentation using local embedding models.

Podcast: On October 16th I was on the Reinteractive podcast Technology for Humans hosted by Errol Schmidt discussing Ruby and AI. We look at why Ruby is a great choice for AI applications, and what we need to do better as a community to fuel a Ruby AI renaissance. Errol is recording incredible episodes on the future of real world AI and Ruby, I encourage you to check them all out, including:

Article: In The Hackathon Where We Mostly Just Talked, Scott Werner recounted a Google hackathon where his team built Photoslider, an image generation tool that uses AI-generated attribute sliders to navigate creative space instead of text prompts. The team spent 95% of their time discussing architecture while AI agents wrote the actual code, leading Scott to argue that AI-assisted development shifts the failure mode from small bugs to architectural incoherence, i.e., spaghetti code. As a result, Scott is proposing a new type of hackathon, "The Iron Vibecoder", a format designed to test whether AI-generated applications can handle mid-event architectural pivots. Scott is looking for feedback, participants, judges, and ideas for the hackathon, so if this sounds of interest, please reach out to him!

Podcast: Joe Leo and Valentino Stoll of The Ruby AI Podcast interviewed Amanda Bizzinotto from Ombu Labs on Real-World Ruby AI: Practical Systems That Work, discussing practical AI implementations in Ruby consultancy work. The episode highlights Ombu Labs and FastRuby.io AI initiatives, including the creation of an AI bot to streamline internal processes, automated Rails upgrade roadmaps, and multi-agent architectures aimed at enhancing efficiency in Rails projects.

Podcast: Joe Leo was also on the Enabling B2B Buying Podcast with Charles Bernard in Joe Leo on Blending Creativity, Service, and AI to Enable Buying, discussing how creativity, AI, and service mindset transform B2B sales conversations. They discuss how Joe's consultancy Def Method built Phoenix, the first AI platform exclusively for Ruby on Rails applications. The conversation explores how AI can enhance human-led sales by improving clarity, personalization, and discovery.

Update: Dewayne VanHoozer introduced Multi Model Roles in AIA v0.9.20, enabling role-based collaboration across different AI models using inline syntax like MODEL=ROLE. The system allows assigning specialized roles (architect, security, etc.) to different models, instantiating the same model multiple times with different perspectives (optimist, pessimist, realist), and synthesizing responses via --consensus flag. Roles are stored as text files in ~/.prompts/roles/ and function as prompt prefixes, with isolated conversation contexts per model instance enabling concurrent parallel processing.

Article: Tony Dong of Propel analyzed Why LLMs Struggle with Ruby Code: The Training Data Problem, revealing that 93.5% of LLM solutions favor Python due to Python-centric evaluation datasets despite Ruby's adequate representation in training data. The article identifies five Ruby-specific challenges including non-idiomatic code generation, Rails convention failures, style guide ignorance, context-dependent magic method handling, and testing framework confusion. Propel aims to address these limitations through RAG and fine-tuning on specifically designed Ruby codebases.

Tutorial: Vitalii Elenhaupt demonstrated Building Real-Time Chat with Hotwire, combining Turbo Streams for DOM updates, Action Cable for bidirectional communication, and Stimulus for interactive behavior. The implementation includes asynchronous AI response processing through background jobs, providing instant user feedback while handling time-consuming operations. The tutorial covers the complete architecture from data models and controllers to scaling considerations including message pagination, job queue processing, and Redis adapters for horizontal scaling.

Article: Vicente Reig published Rich Signatures, Lean Schemas with DSPy.rb, introducing BAML schema format support in v0.28.2 via the sorbet-baml gem. In testing, the optimization achieves a nearly 85% aggregate token reduction across signatures without further training or optimization. Developers activate BAML through a single configuration parameter schema_format: :baml, making it valuable for complex signatures with 5+ fields over JSON schema prompt signatures.

Update: Abdelkader Boudih released RailsLens 0.2.9, a Rails documentation gem that automatically annotates models with complete schema details, routes with endpoint documentation, and mailers with parameter documentation. Unlike static analysis tools, RailsLens connects directly to your database to read the actual schema, handling complex scenarios like metaprogramming, multi-tenant schemas, and multiple database dialects (PostgreSQL, MySQL, SQLite3). The gem includes AI-powered analysis that provides intelligent warnings about performance issues, missing indexes, and Rails convention violations, plus generates Mermaid ERD diagrams that preview directly on GitHub.

Tutorial: Nick Schwaderer published A Claude Commands and Personality System Primer, showing how to create persistent context and personality for Claude Code through a structured system. The implementation uses a /preserve-memory command to capture timestamped session notes, shell hooks in ~/.claude/settings.json to auto-load memories at startup, and manual personality injection via CLAUDE.md using shell aliases. Nick argues that separating efficient tool mode from collaborative teammate mode based on task requirements makes AI interactions more effective.

Announcment: Dewayne VanHoozer released KBS, a Ruby gem implementing the RETE algorithm for building rule-based systems with pattern matching and persistent memory management. Use cases include algorithmic trading, industrial automation, expert systems, and business rules engines requiring auditable decision trails, with persistent blackboard memory supporting SQLite/Redis backends.

Update: David Berube released the newest version of durable-llm, a Ruby gem providing a unified interface for multiple LLM APIs, now supporting ten more providers including x.ai, Together, Opencode, and Perplexity, bringing the total to 14 major platforms. The gem offers consistent methods across providers including quick_complete(), chat(), embed(), and stream() for real-time responses, with built-in error handling, retry mechanisms, and environment variable configuration. The companion durable-llm-registry provides structured documentation for each provider with model catalogs, OpenAPI specs, and JSONL metadata files.

Tutorial: Ilia Markov of Mellisearch published two guides on building Retrieval Augmented Generation applications: Build RAG Apps on Rails and Build RAG Apps on Ruby. The Rails guide demonstrates implementing a Recipe Search Assistant using meilisearch-rails and httparty with a three-step process of retrieval, augmentation, and generation. The Ruby guide covers tools including Langchain.rb for orchestration, Qdrant-ruby for vector storage, APIs for embeddings, and Meilisearch for hybrid search. Both articles provide implementation details for document chunking, embedding generation, vector storage, LLM integration, and production best practices including error handling, monitoring, and caching strategies.

Release: OpenAI released Openai-ruby SDK versions 0.28.0-0.32.0, the official Ruby library for accessing the OpenAI API. The v0.28.0 update introduced breaking changes for function call outputs to support images and files alongside text, plus batch usage tracking. v0.29.0 added realtime calls support, v0.30.0 incorporated 2025 Developer Day launches (ChatKit and Video enhancements), v0.31.0 added comparison filter in/not in functionality, and v0.32.0 introduced the gpt-4o-transcribe-diarize audio transcription model. The SDK includes streaming support, auto-pagination, structured outputs, webhook verification, automatic retries with exponential backoff, and comprehensive type support via Yard, RBS, and RBI formats.

Announcment: As part of the 2025 Developer Day launches, OpenAI also released ChatKit JS, a React framework for building AI-powered chat interfaces with minimal configuration. The library provides response streaming, agentic integration with tool usage visualization, interactive widgets, file management, conversation threading, and source attribution.

Article: Heriberto Pérez of MagmaLabs published Rails Upgrade with Cursor AI: $20 vs $200 AI Tool, documenting a successful Rails upgrade from version 4.2 to 7.1 using Cursor AI, a $20 code editor alternative to premium AI tools costing $200+. Heriberto leveraged Docker for containerized environments, comprehensive test suites as specifications, and markdown documentation as context to guide the AI through the upgrade process. The article demonstrates that strategic preparation and workflow design matter more than tool cost for AI-assisted Rails development.

Release: Paulo Arruda released Swarm SDK, a reimagining of Claude Swarm that runs all AI agents in a single process using RubyLLM for LLM interactions. The new SDK enables developers to define collaborative AI agents through Markdown files with YAML frontmatter. Features include multi-level Claude agent orchestration, MCP support, custom system prompts, tool permissions, and session monitoring, management, and restoration capabilities.

Launch: Anush DSouza and Rand Arete of Heroku announced Heroku Vibes, an AI-powered collaborative agent for turning ideas into running applications. The pilot program, available at vibes.heroku.com, is described as a successor to Heroku Garden, which enabled developers to quickly create and deploy Rails applications. Heroku Vibes provides an opinionated, turnkey environment that streamlines the application creation and deployment process by enabling you to build apps with natural language.

Help Wanted: Charles Oliver Nutter posted Call to Action: Ruby SDK for PebbleOS seeking help to add Ruby support to the PebbleOS SDK, which currently only supports Python and JavaScript. The developer proposes using mruby as a way to bring Ruby to the Pebble smartwatch platform and is seeking collaboration from the PebbleOS team and Rubyists with mruby experience via a GitHub issue.

Announcement: Joshua Wood of Honeybadger released honeybadger-mcp-server, a Model Context Protocol server enabling AI assistants and agents to access Honeybadger error monitoring data directly. The release provides structured API access through MCP protocol for managing projects, retrieving error information, viewing occurrence counts, and querying affected user data. The server runs in read-only mode by default for security, with optional write operations for project management.

Update: Alex Larra announced Internator Now Works with Latest OpenAI Codex, updating the Ruby command-line tool for compatibility with Codex v0.46.0 and adding a new login system. Internator automates development workflows by applying code changes step by step, generating AI-powered commit messages, pushing automatically, and repeating the cycle as needed. Source code is available on GitHub.

Release: Aaron Stanton added two new tools to the RubyLLM ecosystm. The first is ToolForge, a Ruby gem providing a unified DSL for defining tools that convert to both RubyLLM and Model Context Protocol formats. The gem supports parameter validation, type conversion, instance and class-level helper methods, and converts tools via to_ruby_llm_tool() and to_mcp_tool() methods. The second is ruby_llm-docker, a companion gem integrating Docker management tools into RubyLLM across container operations, image management, network administration, and volume management, ported from DockerMCP to function as native RubyLLM tools.

Podcast: Sami Birnbaum interviewed Pablo Curell, software developer at Recovr, on Giant Robots Smashing Into Other Giant Robots episode 594 AI is Draining, examining the long-term sustainability of AI technology beyond the hype. They discuss why coding skills remain essential despite AI advancement, current and potential future AI applications, and the unsustainable economics surrounding AI token consumption and backend infrastructure requirements.

Update: José Valim released Tidewave for Rails v0.4.0, implementing Streamable HTTP instead of requiring a threaded web server. Tidewave is a coding agent for full-stack Rails development deeply integrated from database to UI, also functioning as a standalone Model Context Protocol server compatible with various editors. The v0.4.0 update simplifies usage by removing the threaded web server requirement, though users leveraging Tidewave as an MCP may need to update their editor configuration.

Tutorial: Vinicius Negrisolo of Hashrocket published a two-part series on AI-driven spec development: How Product Owners Can Ship Features Faster with AI and How Developers Implement Features with AI-Driven Workflows. The workflow uses GitHub's spec-kit with commands /speckit.constitution to establish project standards, /speckit.specify to generate comprehensive specifications from minimal requirements, /speckit.clarify to identify ambiguities, /speckit.plan for technical architecture, /speckit.tasks to generate actionable items, and /speckit.implement for code execution. The process separates product owner responsibilities from developer tasks, surfacing edge cases and requirements early while creating audit trails.

Release: The Model Context Protocol organization released Ruby MCP SDK v0.4.0, introducing client-side resource management with resources/list and resources/read operations, plus _meta field support for Tool and Prompt schemas. New features include a call_tool_raw method for accessing complete tool response data, structured content support in tool responses, and a title field for prompt arguments.

Launch: hoop.dev launched RailsGuard, a security solution for Rails console access featuring live AI-powered PII masking, passwordless authentication via Google SSO with MFA, and comprehensive session auditing. The one-line integration provides real-time AI data filtering with zero-setup sensitive data protection, just-in-time access grants, and compliance automation for HIPAA, SOC 1/2, PCI, and GDPR.

Tutorial: Amrendra Pratap Singh wrote about Building Intelligent AI Agents in Ruby on Rails: HRMS Automation Guide, demonstrating how to design and implement autonomous AI agents using Rails and OpenAI for human resource management software automation.

Discussion: A discussion posted to Reddit on Is Ruby's Implementation Worse than Python for Heavy Computation?, examined whether Ruby's "everything as an object" design causes performance issues compared to Python for AI/ML workloads. The community consensus clarified that Python's heavy computation isn't done in Python itself but in C/Fortran libraries like NumPy, and Ruby has similar capabilities through Numo::NArray. Further comments explained that raw compute speed comes from native arrays and BLAS in both languages, but Python's buffer protocol enables zero-copy memory sharing between NumPy, PyTorch, and pandas, while Ruby lacks a standard zero-copy protocol. The discussion concluded that Python's heavy AI usage stems from historical factors including early adoption and ecosystem inertia rather than inherent technical superiority.

Article: Evil Martians released AgentPrism, an open-source React component library built in collaboration with Quotient AI that transforms OpenTelemetry traces into visual debugging tools for AI agents. The library replaces manual JSON inspection with clear visualizations that instantly reveal infinite loops, errors, and cost spikes, helping teams ship production-grade AI systems faster.

Newsletter: Evil Martians also published Martian Summer: Blog, Talks, Open Source, and SFRuby in November, an update highlighting tons of their AI-related content, open source contributions, and the forthcoming San Francisco Ruby Conference (there’s still time to get general admission tickets until October 22nd).

San Francisco Ruby Conference 2025

Join us for the San Francisco Ruby Conference 2025: Building the Future with Ruby. November 19-20 at Fort Mason, San Francisco.

sfruby.com

Events

ScotRUG: Gavin Morrice presented Language models in Ruby at ScotRUG on October 9th, 2025, demonstrating how to build statistical language models from scratch using Ruby. The accompanying RubyLM repository provides working code examples including text generation with temperature scaling, drawing on foundational resources like "The Hundred-Page Language Models Book" and "Attention is All You Need" to make language model concepts accessible to Ruby developers.

SFRuby: Yatish Mehta provided a recap of The San Francisco Ruby Meetup on September 30th, featuring talks by Kody Kendall on Llamapress, an open-source platform for building Ruby on Rails apps with LLMs, Arjun on how Ruby is being used in medical software to build 3D models from 2D scans, and Pranav from Chatwoot on their open-source gem for building AI agents based on Ruby LLM.

Boulder Ruby: Boulder Ruby posted a video by Scott Werner of Sublayer on Frameworks as Pidgins & Creoles: How Humans Will Talk to AI About Software. He argues that linguistics gives us an answer in the concepts of pidgins and creoles. First new frameworks will start as pidgins, shared dialects that humans and AIs use to coordinate intent, architecture, and invariants, and then once they've been around long enough to make it into the training data they turn into creoles. The talk unpacks this analogy and demostrates it in action with Scott’s new AI agent Ruby gem VSM.

Upcoming

October 18th - Conference: XORuby in San Diego on October 18th will include a talk by Sunjay Armstead titled Never Fear, Unicorns Are Here!, exploring how developers can respond and evolve in the midst of AI’s rapid advancement.

October 23rd - Meetup: The PoznańRubyUserGroup will meet on October 23rd in Poznań, Poland and have an exposition by Justyna Wojtczak on when AI meets automation - the hybrid multimodal approach that crafting your app.

October 23rd - Meetup: The Lisbon Ruby Meetup Sardines.rb will gather on October 23rd in Lisbon, Portugal for a talk titled Don't be shy! Talk to your AI! by Valentin Zavadsky.

October 25h - Conference: XORuby in Austin, Texas on October 25th will feature a presentation by Landon Gray on Intelligent Event Discovery with Ruby, sharing his experience building an AI-powered event recommendation engine.

October 28th - Meetup: Philly.rb is meeting at Indy Hall in Philadelphia on October 28th for a presentation on How FastRuby.io Built an Automated, AI-Enhanced Roadmap for Rails Upgrades by Fiona Lapham. In the talk, Fiona will share how OmbuLabs created an automated version of FastRuby.io, the obstacles encountered along the way, and the lessons learned while bringing the an automated Rails upgrade roadmap to life.

October 29th - Meetup: The Winnipeg Ruby User Group is getting together on October 29th in Winnipeg, Canada to host Muz Ali for From Alert Fatigue to Intelligent Investigation. The talk presents an automated investigation system that mimics how one site reliability team at Shopify is leveraging a blend of AI and Rails to debug production incidents as they happen.

October 30th - Meetup: The Philippine Ruby Users Group is meeting on October 30th in Manila, Philippines for a talk by Al Serafica on his NYC Taxi database's MCP Server.

November 7th - Conference: RubyWorld Conference 2025 on November 6th and 7th in Matsue, Japan will include four Ruby AI and hardware talks:

Takayuki Yoshioka: Redmine × Generative AI - The Potential of Issues Management
Koichi Ito: Ruby x LLM Ecosystem
Hayao Kimura: Exploring the World of Electronic Engineering with PicoRuby
Hitoshi Hasumi: Why Now Is the Right Time for PicoRuby

November 19th - Conference: The San Francisco Ruby Conference on November 19th through the 21st in San Francisco will include an extensive AI program schedule featuring:

Workshop - Justin Bowen: Building Agents with Rails
Presentation - Brandon Weaver: Rails Expertise, Distilled: AI Agents That Get Your Monolith
Presentation - Tia Anderson: Peace, Love, and CRUD: Finding Calm in the Chaos with Ruby, AI, and a Little Garden Magic
Presentation - José Valim: Navigating Programming Language Evolution in the AI Era
Presentation - Paweł Strzałkowski: AI Interface in 5 Minutes - Model Context Protocol on Rails
Presentation - Enrique Carlos Mogollán: The MCP Fog Made Me Do It: A Ruby Inspector's Unexpected Journey
Keynote - Obie Fernandez: Ruby & AI Conversation
Roundtable - Edward Kim & Ryan King: CTO Roundtable
Keynote - Carmine Paolino: RubyLLM: One API, One Person, One Machine for AI
Presentation - Sarah Mei: The Role of Software Design in an AI World
Startup Demos - Featuring AI companies Fin AI, Bolt.new, Stepful, Simple AI, Sixfold AI, Cora Computer, Superconductor
Roundtable - A panel of venture capitalists interested in Ruby and AI-based startups
Keynote - Vladimir Dementyev: AI-powered Developer Tooling for Rails

November 21st - Conference: The Tiny Ruby Conf on November 21st in Helsinki, Finland will include two AI-related presentations including:

Hana Harencarova: Level Up Your Engineering Career with Mentorship, Pairing, and AI
Louis Antonopoulos: Unlocking the Rubetta Stones: Translating a Hoard of Ancient Tablets with Ractors and AI

Open Source Updates

New Gems

Links to the RubyGems page, newest releases are first:

blackman_client - Blackman AI Ruby SDK

vibe-sort - AI-powered array sorting using OpenAI's GPT models

numruby-ufunc - NumRuby: Central ufunc registry and core elementwise ops

numruby-stats - NumRuby: Statistics & probability library

numruby-linalg - NumRuby: Linear algebra

numruby-plot - NumRuby: visualization layer

numruby - NumRuby: Meta-gem for the Ruby scientific ecosystem

payloop - Cost visibility for AI agents

claude-agent-sdk - Unofficial Ruby SDK for Claude Agent

swarm_cli - Command-line interface for SwarmSDK

swarm_sdk - Lightweight multi-agent AI orchestration using RubyLLM

mathpix - Secure Ruby client for Mathpix OCR API with MCP integration

sightengine-rb - A Ruby wrapper for the Sightengine API

rubyml-ai - Chat with LLMs from Ruby

aihype - Auto-approve interactive prompts with blacklist protection

kapso-client-ruby - Ruby SDK for the Kapso.ai API

hangarx - Ruby SDK for HangarX - AI-powered Growth OS

llm-docs-builder - Build and optimize documentation for LLMs - generate llms.txt

tool_forge - Build AI tools for LLMs with a single DSL

kbs - Knowledge-Based System with RETE inference, Blackboard architecture, and AI integration

moondream-client - Ruby client for MoonDream API.

deeprails - Ruby library to access the Deeprails API

net-llm - Ruby client for OpenAI, Ollama, and Anthropic LLM APIs

ruby_llm-docker - Docker management tools for RubyLLM - comprehensive container, image, network, and volume operations

open_router_enhanced - Enhanced Ruby library for OpenRouter API with tool calling, structured outputs, and intelligent model selection

docker_mcp - A gem to manage Docker via MCP.

ticuna - Ruby Agents with AI

rllama - Ruby bindings for Llama API

tavus - Ruby client for the Tavus API

dredger-iot - Generic hardware integration for embedded Linux (GPIO, I2C) with sensor drivers

fal - Ruby client for FAL API

New Open Source

Links to the Github repository:

Railspress

Railspress CMS - Content management system + AI framework for next gen content powered experiences

TechHub - AI-powered trading cards for GitHub profiles

VCBench - Academic-grade multi-agent VC evaluation system

Savant - Local repository indexer and MCP search layer

Groove.rb - Builds, curates, and syncs Spotify playlists using natural-language prompts

MCP Auth - OAuth 2.1 authorization for Model Context Protocol servers in Rails applications

ColesV2 - Retail Agentic AI System with MCP server implementation, ask/act/alert modes, and comprehensive retail management tools

TinyHNewsMCP - MCP server that wraps the TinyHNews gem to provide Hacker News top stories functionality to AI assistants

JumpAI - AI-powered assistant designed for financial advisors

CV Analyzer - AI-integrated Rails application that evaluates candidate CVs

AgentBill Ruby SDK - OpenTelemetry-based SDK for automatically tracking and billing AI agent usage

Claude Config - Centralized collection of instructions, guidelines, and custom slash commands for AI coding agents

Rails MCP Playground - Implements an MCP server via JSON-RPC, providing endpoints to list and invoke tools

Nu::Agent - Ruby gem for AI agent integration with Anthropic and Gemini APIs

Smart Note Finder - Integrates AI embeddings and PostgreSQL with pgvector to store and search notes by meaning

SureFinance MCP Server - MCP server for SureFinance financial data integration

Smart Travel Hub - AI-powered travel booking platform

My MCP Server - Minimal MCP server engine for Rails and Sinatra

Jobs & Opportunities

We’re close to the launch free job matching platform for Rubyists. Even with only 400 organizations indexed so far, there are hundreds of opportunities available every week. If you would like to beta test the service, or are an organization searching for Ruby engineers, please reach out at matt@roboruby.com.

One Last Thing

Grounding with Google Maps: Now available in the Gemini API

Learn more about how Grounding for Google Maps in the Gemini API allows developers to bring rich and up-to-date geospatial-based data to their AI apps.

blog.google/technology/developers/grounding-google-maps-gemini-api

Google launched Grounding with Google Maps in the Gemini API, enabling developers to build location-aware AI applications by connecting Gemini's reasoning with data from over 250 million places. Use cases include detailed itinerary planning with travel times and hours, hyper-local personalized recommendations based on user preferences, and local place-based answers derived from reviews and Maps data across travel, real estate, retail, and logistics sectors. The tool can be combined with Grounding with Google Search for enhanced contextual responses, providing both structured Maps data and timely web context

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI: Introducing Phoenix by Def Method & Interview with Joe Leo

Matt Solt — Thu, 16 Oct 2025 16:41:02 +0000

In this special interview with Joe Leo, the Founder and CEO of Def Method, we discuss the launch of Phoenix, a new service to continuously generate self-healing tests for Ruby on Rails applications. We also look at the schools of programming forming around generative AI, bringing the joy of Ruby to AI development, and the importance of staying curious in an ever-changing technological landscape.

Introducing Phoenix for Rails
Interview with Joe Leo
Additional Resources

Introducing Phoenix for Rails

Phoenix is an AI-powered tool built by Def Method to solve one of the hardest problems in maintaining legacy Ruby on Rails applications: automated testing. Many Rails codebases still run without sufficient test coverage, which makes refactoring, scaling, and shipping new features risky and expensive. Phoenix tackles this head-on by generating high-quality automated test cases tailored to the realities of legacy code. Instead of forcing developers to untangle years of technical debt manually, Phoenix helps teams create a safety net of tests that builds confidence and unlocks momentum.

Phoenix by Def Method

Phoenix infuses your Rails application with love through AI-generated test coverage, creating a relationship where your code truly cares for you.

www.phoenix.love

Phoenix uses a reactive AI approach to test generation, meaning it doesn’t just produce a static set of tests and stop there. Instead, it continuously adapts to the Rails codebase as it evolves, responding to changes in models, controllers, and business logic. This reactive loop allows Phoenix to generate tests that reflect real usage patterns and refine those tests when the code shifts. The result is a living suite of automated tests that grows alongside the application, offering teams an always-current safety net that keeps pace with both new features and ongoing refactors.

Interview with Joe Leo

This week I had the privilege of interviewing Joe Leo, Founder and CEO of Def Method, a New York City-based software development firm dedicated to building high-quality, thoughtfully crafted software. A long time leader in the Ruby community, Joe is an accomplished conference speaker, co-author of The Well Grounded Rubyist, and co-host of The Ruby AI Podcast. Previously, he was a member of the Tech Advisory Board at The New York Foundling and an organizer of the Gotham Ruby Conference. As one of the first people in the community to recognize the potential of generative AI with Ruby, Joe brings advanced AI integrations to clients and services at Def Method, highlights the leading insights on the Ruby AI Podcast, and sponsors the Artificial Ruby meetup.

Software Done Right | Def Method

We help companies by building software to realize new possibilities.

www.defmethod.com

Since its inception in 2014, Def Method has been a cornerstone of the Ruby and Rails development communities, specializing in test-driven, robust engineering practices for high stakes technical challenges. This month, Def Method is launching Phoenix, a service to seamlessly add AI-generated tests to Rails applications, adhering to conventions, best practices, and domain expertise to ensure your tests reflect real-world Rails logic. Connect your repository or upload your application, and Phoenix will analyze your models, controllers, and business logic to understand your requirements and generate complete test coverage for Rails applications of all ages and versions.

So here it is! Presenting Joe on:

Phoenix

This month you’re launching Phoenix, the first AI-assisted coding agent specifically tailored to Ruby on Rails. What can you tell us about the service? What features and capabilities are you most excited about? What is the long term vision for Phoenix?

Joe: I’m most excited how engineers will use this new power. Imagine having a backstop of tests constantly being generated, updated, and evolved as your code evolves. It changes everything, including our relationship to TDD and testing in general. TDD engineers can still TDD for design but know that they don’t have to check every branch of logic. Vibe coders can vibe and know that Phoenix will have their back with automated tests.

But I’m also excited about the reactive element to Phoenix. I’ve long wanted Ruby to be a player in how AI is delivered and utilized across all of software development. This is a new way to use AI - not as a chatbot, not as an agent, but as a complete system that never sleeps and always watches over your code.

Architecture

What are the underlying technologies and models powering Phoenix? What challenges did you face building the service, and what have you learned from building an AI-powered customer-facing application?

Joe: One of the biggest challenges we faced early on was building in Ruby! Originally there weren’t many tools to choose from, and we ended up building the first version mostly in Python. Now, of course, we have a huge footprint in Ruby that gets bigger every day.

Though the software powering Phoenix is model-agnostic, we’ve had the best results using the Claude Sonnet series of LLMs. We make heavy use of RubyLLM, GitHub Actions and the GitHub API, Rails, and a Python CLI.

Def Method

You gave a great talk at RailsConf on wrangling the complexity of large, legacy Rails applications. How can Rails developers best leverage those lessons when building with generative AI to avoid unnecessary complexity? In over a decade of working with Def Method clients, what are some of the other impactful insights you’ve gained on the development process? How have recent clients embraced AI in their applications and organizations?

Joe: I’m not sure the unnecessary complexity I spoke about will hold a candle to the amount that’s being generated today by engineers using AI code gen tools. Engineers build everything faster than they used to and we spend much less time reading and reviewing the code that they write. It’s a recipe for spiraling complexity over the life of a successful project.

Regarding process, I think two schools of programming with generative AI are starting to emerge: Stewards and Sprinters.

The Stewards still value object oriented design, emergent design, and test-driven design above all else. They use generative AI to build but they read every line, ensure the right patterns are in place, and refactor regularly. Stewards do not code with agents, preferring just one stream at a time using Cursor or Windsurf or good ol' ChatGPT.

The Sprinters throw some of the old patterns out the window. It’s not that they don’t value design - nearly all of them do - it’s just that they won’t let a less-than-optimal design get in the way of the ruthless speed of generative AI. Sprinters are the ones with five Codex or Claude Code agents running at one time.

At Def Method we have more Stewards than Sprinters. But that doesn’t mean it’s the best way! Some of the best non-Def Method engineers I’ve ever met are firmly in the Sprinter school. We’re still at the beginning of this journey and it will be fun to see how these processes get shaped over time.

The Ruby AI Podcast

Congratulations on eight exciting and informative episodes of the Ruby AI Podcast! What can we expect from the podcast in the coming months? What insights and key takeaways have stuck with you long after the episodes aired? How have your views on AI changed since you started recording the podcast?

Joe: Thank you! I’m learning something new all the time. The biggest thing that Valentino and I are trying to uncover is: what is Ruby’s unique contribution to this new world of artificial intelligence? It’s wonderful to talk to people about what they’re building and how they’re leveraging AI. That’s a great place to start. But ultimately I want to know what things are we, as Rubyists, doing with or for AI that nobody else could do? What’s the Ruby way of building AI?

I don’t think we’ve answered that yet, which is good! It means we have lots more people to talk to and work to do.

Future of Ruby AI

What do you foresee as the future of Ruby and AI? What could Ruby or Rails do better to build and support AI applications? What AI tooling, technologies, or libraries would you like to see built by the Ruby AI community?

Joe: Ah, that’s the question I ask all of my guests so I don’t have to answer it! OK, I’ll give it a shot.

Ruby’s future in AI is in how it gets applied. We’re not going to start building LLMs with Ruby as anything other than a toy project. But LLMs are not AI. AI is vast and we’ve just begun scratching the surface of its use cases. It’s perhaps not the language itself but the community of like-minded engineers and enthusiasts who will ultimately make an impact on artificial intelligence as we know it today. That could be in building new ways to interact with AI, like Phoenix does for Ruby on Rails developers. Or it could be in wrangling the agents we use to develop software so that they are more useful and do less harm. It could simply be in building useful interfaces that make programming with AI less onerous and more joyful. That’s why all of us fell in love with Ruby in the first place - it brought us so much joy! And I think that’s the opportunity we have again today with AI.

Closing Thoughts

What skill sets, technologies, and disciplines do you think Rubyists should pursue to level up their careers and expertise in the age of AI? Is there anything else exciting you would like to share?

Joe: As an engineer, you’ve gotta be out there using AI in all of its imperfect forms every day. Don’t wait or hide behind excuses like, “It’s not smart” or, “It makes too many mistakes.” I could have excused you for saying that until we started the podcast. Now I know for a fact that the biggest names in Ruby are using it every day. And they’re learning how to deal with the imperfections and wring some incredible efficiency and creativity out of their tools. If you don’t know where else to start, just use ChatGPT and your favorite code editor and start plugging away. Look at and try the many useful AI tools that are highlighted in this newsletter!

At the end of the day, it comes down to a mindset. You don’t have to love AI or sing its praises every day. You do need to understand that it’s a tool, and it’s a tool being leveraged by everybody. Take a beginner’s mindset with you and strive for curiosity and learning every day.

Additional Resources

Joe Leo is the founder and CEO of Def Method and regularly posts updates on LinkedIn and X/Twitter.

Def Method is a New York City-based software development firm dedicated to building high-quality, thoughtfully crafted software. Learn more on LinkedIn, X/Twitter, Github, or YouTube.

Phoenix infuses your Rails application with love through AI-generated test coverage, creating a relationship where your code truly cares for you. Join the waitlist or subscribe to the Phoenix newsletter.

The Ruby AI Podcast explores the intersection of Ruby programming and artificial intelligence, featuring expert discussions, innovative projects, and practical insights. Previous episodes include:

The Well Ground Rubyist, Third Edition by David A. Black and Joseph Leo is a beautifully written tutorial that begins with your first Ruby program and takes you all the way to sophisticated topics like reflection, threading, and recursion

Artificial Ruby is a community of Rubyists who meet regularly in NYC to explore novel approaches to AI development using Ruby.

That’s all for now! Thank you to Joe Leo for taking the time to answer these questions and share Phoenix with us. Stay tuned for the next edition of the Ruby AI Newsletter. Be sure to reach out if you have any stories, content, jobs, or events you would like to see featured.

Ruby AI News - October 3rd, 2025

Matt Solt — Fri, 03 Oct 2025 18:20:06 +0000

Welcome to the 16th edition of Ruby AI News! This edition features a Ruby conference coming to San Francisco with a focus on AI, an interview with the creator of RubyLLM, expert Claude Code context tips, and much more.

Pro tip: Due to the size of the newsletter, many email clients truncate the content. It is recommended to read on the web for the best experience.

Top Stories
Content
Events
- Previous
- Upcoming
Open Source Updates
Jobs & Opportunities
- Featured
- Junior Positions
One Last Thing

Content

Release: Andrew Kane released Neighbor S3: Nearest neighbor search for Ruby and Amazon Web Services S3 Vectors, a Ruby gem that enables vector similarity search using AWS S3 as storage. The library supports multiple distance metrics, allows filtering with Ruby blocks, and provides memory-efficient streaming for large datasets. Neighbor S3 integrates with Andrew's existing Disco library for recommendations using collaborative filtering with Ruby on Rails.

Podcast: Errol Schmidt from Reinteractive explained AI Agents: Beyond the Chatbots, distinguishing AI agents from simple chatbots by their ability to make decisions, take actions, and interact with external systems to achieve complex goals. As part of a series of content on emerging developments in software, Errol and Reinteractive have launched the Technology for Humans podcast, most recently featuring Scott Werner of Sublayer and Jim Remisk of XORuby. Be sure to check it out, I will be podcast on October 15th! Reinteractive have also started From Idea to Reality: App and AI Workshops, giving entrepreneurs the opportunity to talk to an expert about app design and building an AI proof of concept.

Code: Avi Flombaum created RSpec Rails Agents, a repository demonstrating how to use AI agents for automated RSpec test generation in Rails applications. The project features a main orchestration agent that coordinates multiple specialized agents to write comprehensive tests, including model, controller, and feature specs. Avi provides detailed prompts and examples showing how to leverage AI to maintain test coverage while following RSpec best practices and Rails testing conventions.

Podcast: Ryan Carson, a builder in residence at Amp launched Next Token, Episode 1 featuring guests Kieran Klaassen, the general manager of Cora, Mitchell Hashimoto, a co-founder of HashiCorp and creator Ghostty, and Thorsten Ball, an engineer at Amp and author of Writing an Interpreter in Go. Kieran Klaassen is a must follow in the Ruby AI community, continuing to share insights including tips on Claude Code 2.0 and parallel agents.

Article: Dan Shipper from Every published Vibe Check: Claude Sonnet 4.5, examining Anthropic's newly released model through coding tests and creative tasks. Dan finds that Claude 4.5 significantly outperforms its predecessor in coding ability, flying through a large pull request, handling multi-file reasoning, and avoiding unnecessary verbosity. Dan concludes its “faster, more reliable, and more steerable than Opus 4.1”, but will not yet be his daily driver for coding.

Tutorial: Julian Rubisch from RoRvsWild published The Complete Guide to Dev Containers in Ruby on Rails, providing a comprehensive walkthrough for setting up development containers in Rails applications. The tutorial covers creating a complete .devcontainer configuration with Docker Compose that includes PostgreSQL and Redis services, along with VS Code extensions for Ruby development. Useful for AI-assisted development and expirments, the tutorial covers running your application in VS Code or Cursor along with the the Rails Model Context Protocol server.

Tutorial: Yaroslav Shmarov from SupeRails demonstrated how to implement Ruby AI Vector (semantic) Search with Embeddings using the neighbor gem and RubyLLM. The tutorial covers creating a Rails application that generates embeddings for text data, stores them in a PostgreSQL database with the pgvector extension, and performs semantic searches using cosine similarity. Yaroslav provides a complete implementation including database setup, embedding generation, and search functionality that can find semantically similar content even when exact keywords don't match.

Podcast: Victoria Melnikova from Evil Martians interviewed Jeff Huber of Chroma on how small opinionated teams with low egos build the best developer tools. Jeff, the co-founder and CEO of Chroma, discusses why "consensus is a death blow" for great products and reveals his framework for commercializing open source: “keep the engine open, monetize the car”. He breaks down context engineering, critiques how RAG became "industry brain rot," and explains Chroma's positioning as the AI-native open source database for building AI applications with knowledge. [Show notes]

Article: Scott Werner shared how to communicate with AI models in How Do You Speak Pidgin To A Probability Distribution?. Scott argues that prompting is fundamentally about developing a "pidgin" language, a simplified communication system between humans and probability distributions, and that effective prompting requires understanding both the technical capabilities and inherent limitations of these models. The article coincides with the release of VSM 0.2.0 (Viable Systems for Ruby Agents), a Ruby framework that provides structured patterns for building AI agent systems with clear interfaces for operations, coordination, intelligence, governance, and identity. Scott spoke further about VSM 0.2.0 at the September ArtificialRuby meetup in Frameworks as Pidgins and Creoles: How Humans Will Talk to AI About Software.

Video: David Kimura of Drifting Ruby explored Retrieval-Augmented Generation (RAG). The tutorial demonstrates how to build a RAG system in Ruby that can can search and consume sections of content for text generation. The video discussed setting up models, views, and controllers, and using background jobs to process chat completions.

Article: Pranay Preteek from SigNoz examined LLM Observability in the Wild - Why OpenTelemetry Should be the Standard with Pranav Raj S, the co-founder and CEO of Chatwoot. The article demonstrates how OpenTelemetry using the OpenInference standard can provide comprehensive observability for LLM applications through distributed tracing, metrics, and logging, addressing challenges like token usage tracking, latency monitoring, and error debugging across complex LLM workflows. The problem? There is no Ruby SDK for OpenInference. An accompanying video discussion goes further on the subject.

Podcast: Joe Leo and Valentino Stoll from The Ruby AI Podcast discussed Contracts and Code: The Realities of AI Development. They explore the practical challenges of implementing AI in production Ruby applications, covering contract negotiation for AI services, cost management strategies, and the importance of measuring AI performance rather than getting caught up in hype. The conversation touches on production experiences with AI integration, including how to evaluate AI tools effectively and set realistic expectations for AI-powered features in Ruby applications. [Show notes]

Article: David Eastman from The New Stack tested AWS Kiro: Testing an AI IDE with a Spec-Driven Approach, Amazon's AI-powered development environment that enables coding through natural language specifications. David explored Kiro's ability to generate and execute code directly from written requirements, testing it with a Ruby game development project. While Kiro successfully interpreted specifications and generated functional code, David noted limitations in handling complex logic and dependency management, concluding that the tool shows promise for rapid prototyping but still requires oversight for production-ready applications.

Article: David also provided a First Look at Verdent, an Autonomous Coding Agent From China. Verdent is a new AI coding tool that operates as an autonomous agent through a CLI interface intended to control of the entire development process. David tested Verdent on a real-world Rails project and found it capable of understanding complex codebases, making intelligent decisions about file modifications, and executing multi-step workflows independently.

Tutorial: An Introduction to Agentic Behavior by Robert (0x1eef) demonstrated how to build AI agents in Ruby using llm.rb. The article builds out agents that interpret user requests and execute tools to perform actions beyond the LLM's pre-trained knowledge. It demonstrates two approaches for creating tools: LLM::Function for simple tasks using closures, and LLM::Tool for more complex, reusable functionality implemented as classes. The examples show building tools that fetch GitHub repository star counts and evaluate Ruby code, illustrating how agents extend language models by connecting them to external data sources to enable real-world actions.

Article: Jason Kotchoff shared Claude Code --dangerously-skip-permissions, a review of using Claude to agentically build the insidertrades.directory Ruby on Rails app. The article includes details on using a sandboxed OSX account, Claude’s yolo mode, and Playwright for browser automation. The source code of the resulting app is on Github and Jason published a video walkthrough.

Newsletter: Yatish Mehta's Token Ruby #6: The AI Coding Trap and Composable Components covered RailsWorld AI presentations, Shopify’s article on AI Coding Agents, Anthropic’s guide on Writing Effective Tools for Agents, and a new personal Omarchy setup.

Article: Daniel Amah discussed AI in Rails: What You Need to Know, covering Rails 8’s shift in making AI integration more accessible for Ruby on Rails developers. He shared that the latest version of Rails includes enhanced async workflows with ActiveJob for background AI tasks, improved ActionCable for real-time AI interactions, better external API handling, and stronger security defaults for AI services. The article provides practical guidance on implementing AI features through service objects and background jobs. Daniel also revealed that he is creating a new open source Ruby Framework called Rails AI.

Video: Lindsey Christensen and Svenja Schäfer from Thoughtbot shared Introducing The Opinionated thoughtbotter: Hot takes from our senior team, a new video series featuring candid discussions about software development topics. The inaugural episode, AI Does More Harm Than Good, features host Svenja Schäfer speaking with senior developer Sami Birnbaum on his skepticism about AI. They debate how AI is reshaping software development, the risks of over-reliance, and what it means for the humans writing the code.

Article: Emma Whamond from SmartLogic shared experiences on using GitHub Copilot to update a Rails application in How I Used AI to Modernize a Legacy Rails App (And What I Learned About the Future of Development). Emma found Copilot effective for writing tests, generating data migrations, and handling repetitive refactoring tasks during the upgrade to Rails 7.2 standards.

Podcast: Justin Searls from the Breaking Change Podcast interviewed José Valim in It’s a Time For Builders. José, the creator of the Elixir programming language, discussed Tidewave, a new AI coding agent from Dashbit that offers deep integration with web frameworks to provide executable feedback throughout the entire feature development lifecycle. The conversation centers on the thorny problem José brought to the table: despite all the marketing hype, nobody truly understands what the future of AI agents looks like, making this a particularly timely discussion for developers navigating the evolving AI landscape. Justin also published Is Sora the future of fiction?, a discussion on the Sora 2 generative AI video model, as well as Certified Shovelware, proposing to label software created with the assistance of AI code generation tools to highlight their creative potential.

Article: Dion Almaer shared his systematic approach for using LLMs to accelerate software development in Pools of Extraction: How I Hack on Software Projects with LLMs. Dion’s method involves starting with a specification, extracting the core functionality into a focused area, and then iteratively expanding the "pools" of extracted code while maintaining tight feedback loops. Dion emphasizes the importance of beginning with smallest example possible to help LLMs perform better with a tangible starting points.

Update: This Reddit thread detailed many of the recent improvements to HostedGPT, an open-source ChatGPT alternative built on Rails. Recent commits in the HostedGPT changelog show active development with improvements to the conversation interface, tool message handling, and image generation.

Article: Olivia McClure from Built in SF profiled how Doximity's New Solution Is Poised to Improve Physicians' Lives: Here's How It Was Built. Doximity has developed Scribe, an AI-powered documentation tool that helps physicians with note-taking and clinical workflows. The company, which serves as a professional network for healthcare providers, built the solution using Ruby on Rails alongside AI models to automate medical documentation tasks.

Update: Vicente Reig shared that DSPy.rb now has OpenRouter integration, courtesy of Oleksiy Kovyrin. With recently released version 0.28.0, DSPy.rb continues to bring structured LLM programming to Ruby developers, enabling you to define typed signatures using idiomatic Ruby to compose and decompose AI Worklows and AI Agents.

Review: Christopher presented a review of Sublayer in AI Code Review: Sublayer. The sublayer Ruby gem is a model-agnostic Generative AI framework that provides base classes for building generators, actions, tasks, and agents that can be used to build AI powered applications in Ruby. Sublayer offers a framework for building AI agents with features like function calling, output validation, and memory management, positioning itself as a more structured alternative to direct LLM API calls. Christopher concludes that Sublayer makes “building sophisticated AI agents in Ruby not just possible, but delightful”.

Announcement: Gary Haran shared AI Chat: Run an LLM model from the command line with Ruby, a Ruby script that provides a simple command-line interface for interacting with local LLMs via Ollama.

Article: Can coding agents build complex systems? by Chris Zetter explored the current limitations of AI coding agents in creating complex software systems, asking “can you vibe code a database server?” Chris argues that while AI excels at generating isolated code snippets, it struggles with the architectural decisions and long-term planning required for building substantial applications.

Podcast: Brendan Buckingham and Ryan Frisch from the Rails Business podcast considered Leveraging AI to Enhance User Productivity. The conversation explored building better features with AI in Ruby on Rails applications to benefit users. The episode focused on the future of AI in SaaS, the role of AI in content curation, and how to balance automation with human oversight.

Discussion: The r/rails subreddit discussed CLAUDE.md best practices, focusing on optimizing the CLAUDE.md files that developers use to provide context to AI assistants when working on Rails applications. Suggestions include Ben Sheldon’s Project Guidelines, Claude on Rails, and Agent OS.

Announcement: The Ruby Foundation has announced their 2025 Call for Grant Proposals, specifically seeking libraries for mathematics, science, and engineering. The foundation aims to support projects that extend Ruby's capabilities in these technical domains, with applications closing on October 6th for developers looking to contribute to Ruby's open source ecosystem.

Article: Paul Keen from JetThoughts posited AI Forces What Rails Teams Already Knew: Small Teams Ship Faster. Paul observes that AI forces development teams to confront the reality that “bureaucratic overhead kills velocity more than any technical constraint”. As AI makes “the cost of organizational complexity impossible to ignore”, he concludes that small teams with clear constraints ship better in the age of AI.

Video: Len Epp from Leanpub interviewed Obie Fernandez about his Patterns of Application Development Using AI course. The course includes over two hours of video interviews and focuses on pragmatic patterns like "Multitude of Workers”, "Self-Healing Data”, and "Contextual Content Generation" for integrating large language models into application architectures. The course provides concrete examples and use cases for developers looking to build intelligent, adaptive applications.

Events

Euroko 2025: Wolfgang Ziegler provided a recap of EuRuKo 2025 - Day 1 and Day 2, featuring talks on Roasting Code for Fun & Profit with Structured AI Workflows by Obie Fernandez, Introducing ReActionView: A new ActionView-Compatible ERB Engine by Marco Roth, Building interactive Ruby gem tutorials with Wasm by Albert Pazderin, RubyLLM: Making AI Development Beautiful Again by Carmine Paolino, and Making Rails AI-Native with the Model Context Protocol by Paweł Strzałkowski. Gapstars also shared some highlights from the event in From Ruby Gems to AI Dreams: Our Euruko 2025 Highlights.

RubyConf India: RubyConf India featured four speakers discussing Ruby and AI, including:

Deepan Kumar: AI at Runtime: Self Healing Ruby Apps
Prathamesh Sonpatki: Teaching AI to Debug your Rails Apps (MCP + Observability)
Vlad Dyachenko: MCP Security: Real World Risks & Defences
Vishwajeetsingh Desurkar: What if… Ruby Led the AI Revolution?

Upcoming

October 6th - Conference: The Rocky Mountain Ruby Conference on October 6th and 7th in Boulder, Colorado will host two Ruby AI speakers:

Scott Werner: We Were Voyagers. We Can Voyage Again!
Christine Seeman: Thoughtful AI for the Rubyist

October 7th - Meetup: Ruby Europe and Paris.rb are joining forces for the Ruby + AI Meetup Paris on October 7th at Algolia in Paris and will include three speakers:

Chris Hasinski: AI, Offline
Yorick Jacquin: FastMCP: How to connect AI models to your Ruby applications
Mariusz Kozieł: Building the future of Ruby through community

October 11th - Conference: XORuby in Portland on October 11th will include a talk by Renée Hendricksen on I know Kung Fu! RubyGems for AI, exploring how to better load the context an AI needs to be successful at a more complex tasks.

October 15th - Meetup: ArtificialRuby is hosting a meetup at Betaworks in New York City on October 15th. If you are interested in presenting at an ArtificialRuby meetup, please fill out this form and let them know. October’s meetup will feature three presentations:

Joel De La Cruz: The New York State RAISE Act: The Race For AI Safety Regulation
Damani Brown: Giving AI the Keys to Chrome DevTools
Steve Brudz: Self‑Healing Tests & Everflame Reports: AI‑Powered QA for Rails

October 18th - Workshop: Rails Fever will be hosting another Rails AI event on October 18th in Philadelphia. This interactive session presented by Peter Bailey will explore how AI is reshaping the modern software development lifecycle. Following the presentation covering the landscape of AI-assisted software engineering, there will be a hands-on workshop to build your own AI-enhanced software development automation.

November 7th - Conference: RubyWorld Conference 2025 on November 6th and 7th in Matsue, Japan will include three Ruby AI and hardware talks:

Koichi Ito: Ruby x LLM Ecosystem
Hayao Kimura: Exploring the World of Electronic Engineering with PicoRuby
Hitoshi Hasumi: Why Now Is the Right Time for PicoRuby

November 19th - Conference: The San Francisco Ruby Conference on November 19th through the 21st in San Francisco will include an extensive AI program schedule featuring:

Workshop - Justin Bowen: Building Agents with Rails
Presentation - Brandon Weaver: Rails Expertise, Distilled: AI Agents That Get Your Monolith
Presentation - Tia Anderson: Peace, Love, and CRUD: Finding Calm in the Chaos with Ruby, AI, and a Little Garden Magic
Presentation - José Valim: Navigating Programming Language Evolution in the AI Era
Presentation - Paweł Strzałkowski: AI Interface in 5 Minutes - Model Context Protocol on Rails
Presentation - Enrique Carlos Mogollán: The MCP Fog Made Me Do It: A Ruby Inspector's Unexpected Journey
Keynote - Obie Fernandez: Ruby & AI Conversation
Roundtable - Edward Kim & Ryan King: CTO Roundtable
Keynote - Carmine Paolino: RubyLLM: One API, One Person, One Machine for AI
Presentation - Sarah Mei: The Role of Software Design in an AI World
Startup Demos - Featuring AI companies Fin AI, Bolt.new, Stepful, Simple AI, Sixfold AI, Cora Computer, Superconductor
Roundtable - A panel of venture capitalists interested in Ruby and AI-based startups
Keynote - Vladimir Dementyev: AI-powered Developer Tooling for Rails

Open Source Updates

Code Spotlight

GoldMiner - GoldMiner is a tool from Thoughtbot for finding interesting messages in a Slack channel and turning them into a blog post for the Thoughtbot blog. Uses OpenAI to generate summaries.

New Gems

Links to the RubyGems page, newest releases are first:

moondream - Ruby client for Moondream

neighbor-s3 - Nearest neighbor search for Ruby and S3 Vectors

fast_mcp_jwt_auth - JWT Authorization header authentication for FastMcp RackTransport

fast_mcp_pubsub - PostgreSQL NOTIFY/LISTEN clustering support for FastMcp RackTransport

agentic-commerce-protocol - Type definitions for the Agentic Commerce Protocol specification

numo-optimize - Numo::Optimize provides functions for minimizing objective functions.

rails_ai_agents - A Rails engine for managing AI agents with LLM integration

aider-ruby - Ruby wrapper for aider - AI pair programming tool

rails-agents - Claude Code agents for Rails development

tokenkit - Fast, Rust-backed word-level tokenization for Ruby

numo-linalg-alt - Numo::Linalg Alternative is an alternative to Numo::Linalg.

baml-cc - Unified BoundaryML LLM client

lipdub - Ruby client library for Lipdub.ai API

sdk-reforge - Reforge Launch Ruby Infrastructure

hokipoki-hive-mind - HiveMind: Parasitic Vector Intelligence for Rails

aircana - Humble workflow and context utilities for engineering with agents

ltfi-wsap - LTFI-WSAP Ruby SDK

rails_ai - AI toolkit deeply integrated into Rails applications

google-genai - Unofficial Ruby port of the Python SDK for Google's Gemini API.

New Open Source

Links to the Github repository:

LLM Team - Multi-agent LLM orchestration system that uses specialized AI agents working together through research-critique-synthesis workflows

GeoMCP - An MCP server that aids in geospatial research for cartography projects

Kalmiya - An artificial, intelligent, personal, assistant

Jump Finadvisor Agent - AI-powered assistant for financial advisors

SurvAI - Use Ollama to generate surveys with AI

Google ADK Pattern Implementation Examples - Examples of how to implement Google's Agent Development Kit (ADK) patterns in Ruby tools

RAG Demo Application - Get AI-powered answers to questions about product reviews

Shine - A local CLI agent written in Ruby that can be used for coding and analysis

AI Log Analyzer - CLI that uses OpenAI's API to analyze large log files, extract insights, and answer specific questions about your logs

Devinator - AI assistant that automatically identifies low-complexity bugs and assigns them to Devin for resolution

Konnector Assignment - App that records audio, generates real-time transcriptions, and provides AI-powered summaries

LLM Gateway - Manage multiple local LLM engines with cache, fallback, and external data recovery

AI Receptionist System - Receptionist system that handles incoming phone calls, processes speech, generates intelligent responses, and manages call routing

LinkedIn Post Drafting App - App that transforms raw notes into polished, post-ready LinkedIn content with tone, length, hashtag customization

Probatio Diabolica - A testing framework with large language models (LLMs) in Ruby

AI Social Agent - AI agent to generate developer updates for Reddit and Hacker News

Rubini - CLI AI agent that uses the Google Gemini to deliver an interactive chat to your terminal

CBT Question Generator - Rails application that generates Computer-Based Test (CBT) questions from PDF documents

ai_lint - Have AI review your code

Boo CLI - Terminal assistant that interprets commands in natural language and transforms them into commands for Linux/macOS

ruby_llm_bot - CLI tool to sends questions to a configured LLM, shows a plan and explanation, and optionally executes shell commands with confirmation

Jobs & Opportunities

I’m building a free job matching platform for Rubyists. If you would like to beta test the service, or are an organization searching for Ruby engineers, please reach out at matt@roboruby.com.

Featured

Remote - Vendis.ai is an AI-powered CRM that creates pipelines from conversations: Senior Ruby on Rails Developer

Remote - Mozilla is a non-profit building open-source tech for internet privacy: Front End Software Engineer, New Products

Remote - KaiPod Learning is a microschool network helping educators start personalized learning communities: Senior Software Engineer

Junior Positions

Remote - 1KOMMA5° is a German renewable energy systems installer and provider: Working Student - Software Engineering Ruby

Remote - iPlayTech is a next-gen iGaming company: Junior Ruby on Rails + Vue

South Africa - nCino is a cloud banking platform for financial institutions: Software Engineer-1

One Last Thing

Effective context engineering for AI agents

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

www.anthropic.com/engineering/effective-context-engineering-for-ai-agents

Anthropic published Effective context engineering for AI agents, a comprehensive guide to optimizing prompt design for autonomous AI systems. Context engineering represents a powerful approach to working with large language models by providing a structured approach to building prompts. As AI can be limited by a model’s restraints and capabilites, this guide helps you ensure the best possible responses by using a carefully crafted set of data and information in your prompts.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI: Interview with Carmine Paolino, Creator of RubyLLM

Matt Solt — Fri, 26 Sep 2025 12:00:00 +0000

In this special interview with Carmine Paolino, the creator of RubyLLM, we look at the library’s current state and future, RubyLLM’s advanced capabilities in production applications, and Ruby’s prime position to be the go-to language for AI app development.

Introducing RubyLLM
Getting Started with RubyLLM
Interview with Carmine Paolino
Additional Resources
RubyLLM Usage Survey

Introducing RubyLLM

Home

One beautiful Ruby API for GPT, Claude, Gemini, and more. Easily build chatbots, AI agents, RAG applications, and content generators.

rubyllm.com

RubyLLM has taken the Ruby community by storm, nearing 3.5 million downloads and consistently being one of the top trending Ruby libraries on Github. Over the past six months, RubyLLM progressed from version 1.0 to version 1.8.2, and has been a staple in the Ruby AI Newsletter since the first edition. Carmine Paolino, the creator of RubyLLM, along with more than 50 contributors, have shipped updates at a lighting pace, building incredible documentation, features, and a vibrant ecosystem that allows Rubyists to easily integrate powerful artificial intelligence capabilities into their applications.

RubyLLM is a Ruby gem for integrating modern Large Language Models in Ruby and Rails applications, providing a single programming interface to build AI chat, vision, audio, image, and document analysis software, with full support for vector embeddings, tool calling, and streaming responses. The complete set of features provide nearly everything you need to take advantage of the full potential of advanced generative AI models:

Chat: Conversational AI with RubyLLM.chat
Vision: Analyze images and videos
Audio: Transcribe and understand speech
Documents: Extract from PDFs, CSVs, JSON, any file type
Image generation: Create images with RubyLLM.paint
Embeddings: Generate embeddings with RubyLLM.embed
Moderation: Content safety with RubyLLM.moderate
Tools: Let AI call your Ruby methods
Structured output: JSON schemas that just work
Streaming: Real-time responses with blocks
Rails: ActiveRecord integration with acts_as_chat
Async: Fiber-based concurrency
Model registry: 500+ models with capability detection and pricing
Providers: OpenAI, Anthropic, Gemini, VertexAI, Bedrock, DeepSeek, Mistral, Ollama, OpenRouter, Perplexity, GPUStack, and any OpenAI-compatible API

RubyLLM’s creation has fostered a vibrant community, powering over 100 open source applications, 20 Ruby gems, numerous startups, and a growing ecosystem of extensions including:

RubyLLM::MCP - Created by Patrick Vice, RubyLLM::MCP is a Ruby client for the Model Context Protocol (MCP), designed to work seamlessly with RubyLLM. The gem enables Ruby applications to connect to MCP servers and use their tools, resources and prompts as part of LLM conversations. [Documentation]

RubyLLM::Schema - Created by Daniel Friis, RubyLLM::Schema is a Ruby DSL for creating JSON schemas with a clean, Rails-inspired API, allowing you to define structured data schemas for LLM function calling or structured outputs.

RubyLLM::Template - Also created by Daniel Friis, RubyLLM::Template provides a sytem for organizing your prompts in folders with separate files for system, user, assistant, and schema messages, with ERB support for context variables and Ruby logic.

AI Agents - Created by Chatwoot, AI Agents is an agent framework on top of RubyLLM that enables developers to create sophisticated multi-agent AI workflows. The SDK allows you to build specialized AI agents with multi-agent orchestration that can collaborate, use tools, and seamlessly transfer conversations with shared context to solve complex tasks.

PromptEngine - Created by Avi Flombaum, PromptEngine is a Rails Engine for managing your LLM prompts without having to hardcode them in your application files, providing version control, A/B testing, and a user interface to optimize your prompts without having to deploy code changes.

Getting Started with RubyLLM

Getting Started

Start building AI apps in Ruby in 5 minutes. Chat, generate images, create embeddings - all with one gem.

rubyllm.com/getting-started

With the latest version of RubyLLM, it has never been easier to build and deploy an AI-powered application in minutes. First generate a new Rails application:

rails new chatbot

Add the RubyLLM gem to your Gemfile:

gem "ruby_llm"

Update your bundled gems:

bundle install

Run the RubyLLM installation generator in your application’s directory:

rails generate ruby_llm:install

Run the migrations installed by the RubyLLM generator:

rails db:migrate

Add the openai_api_key to your Rails’ credentials:

rails credentials:edit --environment=development

Load the Rails console and verify that the installation is working:

chat = RubyLLM.chat.ask('Hello!')
puts chat.content
#=> "Hello! How can I assist you today?"

If successful, you can now run the new Chat UI generator:

rails generate ruby_llm:chat_ui

Run your development server, visit http://localhost:3000/chats, start a new chat, and watch the response stream in!

In less than five minutes, you have a working AI chatbot with RubyLLM. Incredible!

Interview with Carmine Paolino

This week I had the privilege of interviewing Carmine Paolino, the creator of RubyLLM, a Ruby and Rails library that provides a unified interface for working with Large Language Models. RubyLLM allows you to build powerful interactive chatbots, multimodal agentic workflows, and intelligent information retrieval applications with a simple Ruby DSL. Carmine is also the founder of Chat with Work, an AI-powered assistant that connects to your company's knowledge bases to answer questions and instantly find relevant documents. Previously, he was the cofounder of Freshflow, an AI solution for retailers to reduce food waste, along with running the Floppy Disco artist collective, DJing as Crimson Lake, and a hobbyist photographer. With 20 years of experience in information technology, artificial intelligence, and data science, Carmine is constantly bringing his deep domain expertise to the Ruby AI ecosystem for the benefit of everyone.

So here it is! Presenting Carmine on:

RubyLLM

Congratulations on RubyLLM being Ruby’s top trending library on Github and surpassing 3 million downloads on RubyGems! For those that aren’t familiar, what can you tell us about RubyLLM? What makes RubyLLM special? What was the inspiration and motivation behind RubyLLM?

Carmine: Thank you so much! RubyLLM is the "One Beautiful API, One Person, One Machine" for AI development in Ruby. What makes it special is that it provides a single, elegant interface for working with every major LLM provider - whether you're using OpenAI's GPT, Anthropic's Claude, Google's Gemini, or even your local Ollama models.

The inspiration came from my frustration while building Chat with Work. I looked at the existing libraries and they were all broken in fundamental ways. They require many lines of code just to say "Hello" to an LLM - and that's from their first tutorial! The official SDKs aren't much better. While we live in a world where we need to switch to the latest models quickly, each provider has its own client with different APIs, different response formats, and different conventions. It's exhausting!

Now that AI development has shifted from training models to using APIs, and therefore to product development, we need clean abstractions at the right level, not complexity theater. So I built RubyLLM following five core principles: Simple should be simple, complex should be possible; Models and providers are commodities; Convention over configuration; Progressive disclosure; and One API, One Person, One Machine.

With RubyLLM, you can say hello in one line: RubyLLM.chat.ask "Hello!". But you can also build complex multi-agent systems, switch between models mid-conversation, analyze any file type (images, PDFs, videos, audio), generate structured output with schemas, and use tools to let AI call your Ruby code. We support 11+ providers and 620+ models, all through one consistent, beautiful API. And we do it with just three dependencies: Faraday, Zeitwerk, and Marcel. No bloat, no complexity theater - just clean Ruby code that makes sense.

The Future of RubyLLM

What is your vision for RubyLLM? What upcoming features are you most excited about, and are there any aspirational capabilities you hope to see in the library in the future? How can the community help?

Carmine: I want to make RubyLLM the best library for building LLM-based applications in any language. I actually think we're already there - there's nothing quite like RubyLLM in Python, JavaScript, or any other ecosystem in terms of developer experience and beauty of the API. But we can go much further.

I don't want to make promises about exact timelines, but here's what I'm working on:

First, I want to streamline the Tool interface even further. Next, I’d like to add a proper Agent interface that encapsulates autonomous agents in a class for people who prefer that interface to progressive disclosure. I'm also looking at changing some of the .with_ methods to be more intuitive, and aligning our callback methods (.on_) with ActiveRecord's naming scheme using before_ and after_.

For Rails integration, I want to go even deeper with convention over configuration. Imagine tool calls and tool results being tightly integrated into views, so you can build AI features the same way you build CRUD apps.

I'm also planning to record a Rails 8-style demo video showing how you can go from rails new to a production AI app in minutes - similar to DHH's famous blog-in-15-minutes video that launched Rails.

I'd also love to work on a book about building AI applications with RubyLLM and Rails as soon as I’ll have the time. There's so much to share about RubyLLM, prompt engineering, tool design, and architectural patterns that I've learned and still learning from building Chat with Work.

On the technical side, we are going to have more provider features - prompt caching for Anthropic, tighter integration with thinking models like o1 and o3, OpenAI's new Responses API for transcription, OpenTelemetry support for observability, and evaluation frameworks. We're also adding new providers like xAI and Azure.

The community can help by triaging issues, responding to discussions, writing documentation, fixing bugs, and contributing features - as long as they fit the RubyLLM philosophy. The best contributions are the ones that capture the style and philosophy of the library. They understand that we're not trying to be LangChain - we're trying to be the Rails of AI development. After my EuRuKo talk drops, which has a whole section on philosophy, I'll post a dedicated philosophy guide.

Chat with Work

What led you to create Chat with Work? What have you learned about the current state of AI from building the company and where do you see the industry heading? What does the tech stack look like, and how do you leverage RubyLLM to ship AI-powered features?

Carmine: Last year at Freshflow, I had an employee ask me about details from a client meeting. I searched everywhere in our Notion but couldn't find it. Turns out the information was buried in a long thread in our #sales Slack channel - they only knew about it because they happened to be following that conversation. That was my lightbulb moment: we need a better way to search and interact with workplace knowledge, and LLMs can help a lot with that.

But Chat with Work evolved far beyond just search. It's become more like Claude Code for your workplace. Yes, it searches across all your tools, but it also helps you write new documents with context from your company's knowledge, compose emails that match your tone and style, draft Slack messages with the right context, and even generate reports pulling from multiple sources. It's an AI assistant that truly understands your work context.

The tech stack is intentionally simple and powerful: Rails 8 at the core, RubyLLM for all AI interactions, the full Async stack (Async::Cable for WebSockets, Async::Job for background processing, Falcon as the web server), Kamal for deployment, PostgreSQL with pgvector for embeddings, all running on Hetzner VPSs. Our entire monitoring, logging, and backup infrastructure is open source and self-hosted. It's incredible what you can build as one person with one machine when you reject complexity and cloud provider lock-in. I'm not spending a fortune on AWS or Azure - just solid, simple infrastructure that works.

Building Chat with Work has taught me so much about the current state of AI. The market is absolutely booming, and it's incredibly competitive with new products launching daily. New techniques get adopted at lightning speed - when Claude Code came out a few months ago, it sparked a major pivot in how I thought about the product.

But the biggest lesson is that AI development has fundamentally shifted. It's no longer about training models - that's reserved for companies with millions to spend on a single training run. For the rest of us, AI is about building products people love using APIs. And who better than the Ruby community knows how to build products people love? We built Basecamp, GitHub, Shopify, Airbnb's frontend - we know how to ship.

RubyLLM in Production

What is your favorite use of RubyLLM in Chat with Work? What are the best examples of RubyLLM use cases and integrations you’ve seen so far?

Carmine: In Chat with Work, it's all about excellent tool design and crafting precise prompts. The way I've structured tools is similar to how Claude Code works, but instead of operating on your local files, it operates on your Google Drive, Slack, Notion, and other work accounts. Each tool has carefully crafted descriptions that help the LLM understand not just what it can do, but when and why to use it.

The beauty of RubyLLM is that complex workflows become simple. For example, Chat with Work can search across multiple data sources in parallel, synthesize the results, and generate a report - all in a few lines of Ruby code using our Async support. Try doing that elegantly with any other library or programming language!

In the wild, I've seen absolutely incredible uses of RubyLLM. One team is using it to run city government simulations. Another built an AI nutritionist. Another is generating personalized lesson content for K-12 students. One of my favorites is a company that went from zero to proof-of-concept in ONE day, and had it in beta testing within a week. Others told me "RubyLLM is pretty much the 'devise' of this generation."

From the survey I conducted, I found companies using RubyLLM in production with 100,000+ users. When I added up just the companies that responded, over half a million people are using RubyLLM-powered features today! We're seeing it at startups like Zipchat and Startup Jobs, established companies like Chatwoot, and even creative agencies. The breadth is amazing.

The Ruby AI Community

You’ve written about how Asynchronous Ruby is the future of Ruby AI, do you have anything to add to that? Is there anything about Ruby’s async capabilities or the Ruby language that needs to improve to support AI development? What AI tooling, technologies, or libraries would you like to see built by the Ruby AI community?

Carmine: Async is criminally underrated in the Ruby world, but it's absolutely essential for AI applications. Here's why: LLM communication is long running and I/O bound. When you're waiting for tokens from an API, your CPU is doing nothing.

With traditional worker-based job queues, if you have 100 concurrent chats, you need 100 workers. Your 101st user has to wait. Each worker is sitting there doing nothing while waiting for the next token. It's wasteful and doesn't scale.

With Async::Job, those 100 chats become 100 fibers that efficiently share resources. Your 101st user doesn’t have to wait because the worker pool gets resized automatically. Because of this and how efficient are Fibers at scheduling and I/O bound operations, you can handle thousands of concurrent conversations on a single machine. No connection pool exhaustion (within reason!), no worker limits, just efficient resource usage.

I got the feeling people are still scared to try async. Let me be crystal clear: if you're building LLM applications and using a background job queue with max workers, you're shooting yourself in the foot. Use Async::Job (with Redis for production).

I'd love to see or make an async worker pool added to Solid Queue. Since Solid Queue already has Mission Control and is integrated into Rails, this would make async mainstream. I've talked with Rosa Gutiérrez about this, and it seems technically feasible. This could be a game-changer for Rails scalability.

We need more support for Samuel Williams' work on async - he's doing incredibly important work for Ruby's future. I'd also love to see more appreciation for Andrew Kane's data science gems. He's single-handedly created torch.rb, polars-ruby, and dozens of others. These gems alone won't convince the ML world to switch from Python, but RubyLLM plus Rails could convince developers to try Ruby for AI apps, and then these other gems would make them stay forever.

Closing Thoughts

What skill sets and disciplines do you think Rubyists should pursue to level up their careers and expertise in the age of AI? Is there anything else exciting you would like to share?

Carmine: Start by actually using AI tools as a power user. Play with ChatGPT, Claude, and Gemini. Understand their personalities, their strengths, their quirks. Then implement one feature in your app with RubyLLM - I guarantee you'll get hooked and want to add more.

Learn to treat each model as having its own personality. Get good at crafting system prompts and designing tools. The difference between a mediocre AI feature and a great one often comes down to prompt engineering and tool design.

Ignore most of the "get rich quick" or "here's 10 magic prompts" content out there. It's noise. Build your expertise by testing things yourself and studying patterns in successful AI apps you actually enjoy using. Focus on what makes your product great, not on following AI hype cycles.

The beautiful thing is you don't need to study the underlying math anymore - that was my generation's burden when I was doing ML research. You don't need to understand transformers or attention mechanisms in detail. You need to first understand your users and build great products.

I'm incredibly excited about what's coming. I'll be giving the keynote at SF Ruby 2025 and RubyConf Thailand 2026! There are other conferences I'll be speaking at that I'll announce soon. My EuRuKo 2025 talk will be online shortly, and I think it'll fire up a lot of people about Ruby's potential in AI.

I'm also planning to record a demo video in the style of Rails' famous screencasts, showing how to build a complete AI application from scratch. I hope it'll convince developers that Ruby isn't just relevant for AI apps - we have the best tools in the industry for building them. With Rails, RubyLLM, and the Async stack, we can build things that would require entire teams in other ecosystems.

This is our moment. Python owned AI when it was about training models. But now that AI development is about building great products with APIs, Ruby has a real shot at becoming the go-to language for AI app development. Go ship some AI apps!

Additional Resources

RubyLLM is a Ruby gem for integrating modern Large Language Models in Ruby and Rails applications, providing a single programming interface to build AI chat, vision, audio, image, and document analysis software, with full support for vector embeddings, tool calling, and streaming responses. The gem features complete documentation, a growing ecosystem, an LLM model registry, and the source code is available on Github.

Carmine Paolino is the creator of RubyLLM and regularly posts updates about library developments on his personal website, LinkedIn, and X/Twitter account.

Chat with Work is an AI workplace assistant that searches across all your work tools simultaneously. It connects to platforms like Slack, Google Drive, and internal knowledge stores to answer questions in plain language, eliminating time wasted searching for information across scattered apps. Ask questions in plain language and get answers from all your work tools at once.

Euruko (European Ruby Conference) is an annual conference about the Ruby programming language with an informal atmosphere and lots of opportunities to listen, learn, and talk with developers from all around the world. The conference included a talk by Carmine Paolino on RubyLLM: Making AI Development Beautiful Again, and will be available online shortly.

RubyConf Tailand is a two-day conference in Bangkok, Thailand featuring 16 speakers sharing real-world Ruby experiences, best practices, and cutting-edge techniques on the Ruby programming language. The conference will feature a keynote presentation by Carmine Paolino on RubyLLM.

The San Francisco Ruby Conference is a three-day event (November 19th to the 21st) celebrating Ruby's ecosystem and future, featuring talks on open source/AI tooling, Ruby at scale, CTO panels, and startup demos, organized by the SF Ruby Meetup group. Day 2 of the conference will begin with a keynote presentation by Carmine Paolino on RubyLLM.

RubyLLM Usage Survey

Are you using RubyLLM in production or an open source application? Please take a moment to help Carmine make the library better by completing a short usage survey.

That’s all for now! Stay tuned for the next edition of The Ruby AI Newsletter. Be sure to reach out if you have any stories, content, jobs, or events you would like to see featured.

Ruby AI News - September 20th, 2025

Matt Solt — Sat, 20 Sep 2025 18:11:05 +0000

Welcome to the 15th edition of Ruby AI News! This edition features an avalanche of updates on DSPy.rb, all things AI at Rails World, the top 20 Ruby AI gems of all time, and much more.

Pro tip: Due to the size of the newsletter, many email clients truncate the content. It is recommended to read on the web for the best experience.

Top Stories
Content
Events
- Previous
- Upcoming
Open Source Updates
- New Gems
- New Open Source
Jobs & Opportunities
- Featured
- Junior Positions
One Last Thing

Content

Article: Vladimir Dementyev and Travis Turner from Evil Martians explored building AI features using Rails conventions in Exploring Active Agent, or can we build AI features the Rails way?. The authors examine Active Agent, a Ruby gem that applies Rails-like patterns to AI agent development, featuring familiar concepts like callbacks, controllers, view (prompt) templates, and background jobs. The authors “battle-test” Active Agent by implementing two AI use cases: on-demand translations and a conference proposal reviewer, discussing testing, tool cooling, and retrieval-augmented generation with code samples. Justin Bowen, the creator of Active Agent, recently released a roadmap to Active Agent version 1.0.

Update: Carmine Paolino released RubyLLM version 1.8.0, adding video understanding support and content moderation capabilities. The update follows recent versions 1.7.1 with improved generator handling for namespaced models and 1.7.0 which introduced a complete Rails integration overhaul. The RubyLLM gem now lets developers ship a working Rails AI chat application in minutes using rails g ruby_llm:chat_ui, generating a complete interface with a pure Rails and Turbo Streams implementation.. The 1.7 Upgrade Guide provides a streamlined migration path with the new acts_as API that feels native to Rails conventions.

Announcement: Christopher Petersen introduced two new libraries, ParseKit: Native Document Parsing and OCR for Ruby, and Topical: Topic Modeling Pipeline for Ruby. ParseKit provides native Ruby bindings for document parsing and OCR capabilities, with support for multiple document formats, text extraction, and metadata parsing. Topical brings topic modeling to Ruby with c-TF-IDF term extraction, providing a complete pipeline from embeddings to labeled topics in one gem. Combine with red-candle and you have LLM-powered topic summaries for your application.

Podcast: Joe Leo and Valentino Stoll from The Ruby AI Podcast interviewed Chad Fowler in Rails After the Robots: Chad Fowler on AI as the Next Abstraction. Throughout the show, they explore how AI represents another layer of abstraction in software development, similar to how Rails abstracted away complex web development patterns. Chad argues that we need systems made of trivial, replaceable pieces that AI agents can generate and maintain without human intervention. [Show notes]

Update: Matt Lindsey revived HostedGPT and updated it to version 0.7, bringing significant improvements to this Ruby on Rails application. HostedGPT provides a self-hosted alternative for ChatGPT-like AI conversations with support for multiple AI providers including OpenAI, Anthropic, and Gemini. The update brings new tool calling functionality, conversation search, token counts, UI enhancements, and bug fixes.

Launch: Github user hansende released FlowMetr, a self-hostable monitoring tool designed to track all types of automation workflows and AI pipelines. The tool works with popular automation platforms like n8n, Zapier, and Make.com. FlowMetr provides monitoring with metrics tracking, logging, alerting when workflows break, and shareable reports. The open-source project is available on GitHub.

Podcast: Nicolay Gerold from How AI is Built interviewed Kieran Klaassen in Episode #056 - Building Solo: How One Engineer Uses AI Agents to Ship Production Code. Kieran shares his experience as a solo engineer leveraging AI agents to build and deploy production applications at remarkable speed. The discussion covers his workflow for using AI to handle including code generation, Git worktrees, Claude Code, and compound engineering.

Announcement: Abdelkader Boudih published The Observability Trap: Why I Built Lapsoss to Break Vendor Chains. In the post he introduces Lapsoss, a Ruby gem designed to liberate developers from observability and error reporting vendor lock-in. The project aims to create universal error handling patterns that work across any provider, from localhost to self-hosted servers to cloud platforms, without being tied to specific SDKs or vendors. He hopes that this will enhance AI assistants ability to write error handling code using universal patterns. Additionally, Abdelkader released Minitest::Reporters::LLM, a token-optimized Minitest reporter for LLM consumption. Features include ultra-compact output, regression tracking, and smart time formatting to minimize token usage while maintaining parsability.

Tutorial: Andres Urdaneta explained How to Fix Random OpenAI 500 Errors in Rails Background Jobs Using retry_on. He demonstrates how to handle transient OpenAI API failures in Rails background jobs by implementing retry_on with exponential backoff, using examples from a chatbot that processes user questions.

Article: Scott Werner explored The Tmux Menagerie: On Sessions, Dreams, and the Art of Parallel Agentic Programming, demonstrating the use of tmux for parallel agentic programming. Scott describes running AI coding assistants in parallel sessions, working on different contexts and applications while he orchestrates their efforts. Vicente Reig shared his thoughts on the article and his parallel workflow in this X/Twitter thread. Scott also wrote The Only Skill That Matters Now, arguing that if your company isn’t giving you time to experiment with AI coding “you’re not actually employed…you’re in hospice”, and emphasizes that it is important to find a company that understand AI-assisted development is here to stay and provides you with the tools to be successful.

Launch: Amanda Bizzinotto from FastRuby introduced the Automated Roadmap to Upgrade Rails, a tool that generates personalized upgrade plans for Rails applications. The roadmap analyzes your Rails app and provides a tailored path with estimated timelines, effort levels, and step-by-step guidance for upgrading to newer Rails versions. The uses an integrated AI Agent that analyzes your codebase to identify which deprecations are actually relevant.

Announcement: Kody Kendall updated Leonardo, an open-source AI coding agent that builds Ruby on Rails applications directly from the browser. Leonardo operates as a "deep agent" built with LangChain and running on LlamaBot. Once setup, you can navigate to localhost and chat with Leonardo from the browser to make code changes in real time. The tool is available for local deployment or as a free hosted instance at llamapress.ai, and a Starter Rails Project is available.

Tutorial: Sachin Gaveriya from Essence Solusoft demonstrated How to Use ChatGPT API with Ruby on Rails. The tutorial covers setting up a Rails application with the ruby-openai gem, obtaining an OpenAI API key, and implementing a basic chat interface. Sachin walks through creating a controller that handles API requests to OpenAI's GPT models, managing conversation context, and displaying responses in a Rails view.

Newsletter: Yatish Mehta's Token Ruby #5: Rails World 2025 and Local LLMs covered All things AI at Rails World 2025, Thoughtbot’s new Top Secret gem, Chad Fowler’s Ruby AI Podcast episode, and running LLMs locally on Mac OS, along with thoughts on the Rails 8.1 release.

Video: Prathamesh Sonpatki demonstrates Teaching AI to Debug your Rails Apps (MCP + Observability). The video examines integrating AI debugging capabilities into Rails applications using the Model Context Protocol with a focus on observability tools.

Podcast: Thoughtbot published two new Giant Robots Smashing Into Other Giant Robots podcast episodes on AI. In the first, Chad Pytel from Thoughtbot interviewed Louis Gutierrez about Making AI Work for Users. In the episode, Louis, the Director of AI at Constant Contact, shared insights on building AI systems that solve user problems, focusing on user-centered design principles and common pitfalls. In the second episode, Sami Birnbaum hosted Don Shin for Utopia or Dystopia: Why the Future of AI and XR Is Still Ours to Shape. Don, the CEO of CrossComm, discussed the current state and future potential of extended reality (XR) technologies. The conversation explored how AI and XR are converging, with Don arguing that despite dystopian concerns about these technologies, we still have agency in shaping their development and implementation. Dawn Delatte, Fatima Burke, and Kevin Kwon of Thoughtbot also published Lessons from using AI in Discovery.

Video: David Kimura from Drifting Ruby provided an overview of RubyMine, JetBrains Ruby IDE. The episode covers RubyMine's key features including intelligent code completion, advanced debugging capabilities, integrated version control, and built-in testing tools. David demonstrates how RubyMine's new AI features, refactoring tools, and code analysis can help Ruby developers write cleaner code.

Article: Robert (0x1eef) wrote about Performance Gains with Persistent Connections, documenting performance improvements when working with llm.rb. By providing a persistent connection pool via net-http-persistent, llm.rb is able to reduce connection overhead and improve throughput in threaded or high-volume environments.

Announcement: Paul Shippy released RubyLLM Community 1.2, which is compatible with RubyLLM 1.8 and includes additional enhancements. The release adds Red Candle support that enables running open source LLMs directly inside Ruby processes. New features include xAI support for Grok models, prompt caching support for Anthropic, image editing and generation capabilities, and access to OpenAI's Responses API features.

Article: Vaishnavi Ganeshkar explored the state of Rails in 2025: What Developers Are Really Talking About (AI, Legacy, and the Future), highlighting key trends shaping Ruby on Rails development. Vaishnavi argues that Ruby’s expressiveness makes it token-efficient for AI coding, Rails’ convention-over-configuration simplifies AI-assisted codebase generation, and that AI will make it easier to refactor legacy applications.

Update: Alex Larra announced that Internator now works with the latest OpenAI Codex (v0.30.0). Internator is a Ruby-based CLI tool that automates iterative pull request improvements using OpenAI's Codex.

Video: Kirt Henrie from AI on Rails compares three leading coding models in Kimi K2 vs Grok Code Fast 1 vs Sonnet 4 Model Shootout. He builds an asset rental SaaS application using each model in Cursor's agent mode, providing a practical comparison of Kimi K2 Instruct, Grok Code Fast 1, and Claude Sonnet 4 for real-world development tasks.

Article: Anna Ransbotham-Cole of Doximity explores how to strategically combine The Modern Data Toolbox: Combining LLMs, ML, and Statistics for Greater Impact. Anna argues that each tool serves different purposes: LLMs excel at pattern recognition and natural language tasks, traditional ML handles structured prediction problems, and statistics provides interpretability and causal inference, with the key being matching the right tool to the specific problem.

Discussion: A Reddit thread in r/rails explores how Rails developers are integrating AI tools like Claude and Copilot into their daily workflows. Users report on their experiences and productivity gains using the tools, ultimately enabling solo developers to do the work of an entire team.

Article: Lakhveer Singh Rajput wrote Rails + AI Integration: The Future of Smarter Web Apps (Medium link), talking about how to bring the power of AI into Ruby on Rails applications.

Events

PLRUG Ruby Warsaw Meetup: PLRUG Ruby Warsaw Meetup posted a video from their gathering on August 8th by Cezary Kłos on adding MCP to a legacy web application:

Ruby Argentina: Sinaptia wrote a recap of the September 10th Ruby Argentina meetup featuring a talk by Fernando Martinez on Something About Agents. Additionally, they posted a summary of the August AI4Devs presentations including talks on RAG applications on local infrastructure by Gustavo Archuby and Pablo Musa, It’s not magic, it’s engineering by Ulises Cornejo, and LLM workflows for classification and large-scale data coherence also by Fernando Martinez.

Upcoming

September 20th - Conference: XORuby on September 20th in New Orleans will feature two AI talks. The first is by Thomas Carr on The State of the Ruby AI Toolbox. The talk will offer an overview of the leading Ruby AI gems and explore their unique strengths and features. The second is from Robert Ross, examining the architectural decisions made building a Rails codebase that later enabled seamless AI integration.

September 23rd - Meetup: Toronto Ruby on September 23rd in Toronto will include a demonstration by Tom Heinan on how to take an existing Rails application and make it AI ready with MCP on Rails.

September 23rd - Meetup: The Krakow Ruby Users Group (KRUG) will meet on September 23rd in Kraków, Poland and host three Ruby AI speakers:

Szymon Kurcab: Rails meets MCP – building AI-powered features
Jacek Brożek: New Prompts and How To Test Them?
Dávid Halász: Please add AI to it

September 26th - Conference: Kaigi on Rails 2025 on September 26th and 27th in Tokyo, Japan features two Ruby AI presentations:

Yusuke Iwaki: Can your web service be automatically tested by AI?
Yasuko Ohba: An introduction to artificial "design" using Rails

October 6th - Conference: The Rocky Mountain Ruby Conference on October 6th and 7th in Boulder, Colorado will host three Ruby AI speakers:

Vlad Dyachenko: Prompt Driven Development (PDD) or the Art of Prompting
Scott Werner: We Were Voyagers. We Can Voyage Again!
Christine Seeman: Thoughtful AI for the Rubyist

October 18th - Hackathon: Rails Fever will be hosting another Rails AI event on October 18th in Philadelphia. The event will focus on practical ways to delegate work to AI as dev teams. Stay tuned for details!

November 7th - Conference: RubyWorld Conference 2025 on November 6th and 7th in Matsue, Japan will include three Ruby AI and hardware talks:

Koichi Ito: Ruby x LLM Ecosystem
Hayao Kimura: Exploring the World of Electronic Engineering with PicoRuby
Hitoshi Hasumi: Why Now Is the Right Time for PicoRuby

Open Source Updates

New Gems

Links to the RubyGems page, newest releases are first:

soba-cli - Autonomous GitHub Issue-driven development CLI with Claude Code

llm_bench - Tool for benchmarking LLM performance across providers and models

sinatra-mcp - Create a Sinatra-based MCP web app backed by the Sequel ORM

bioruby-mcp-server - Model Context Protocol server for BioRuby KEGG module

llm_conductor - Orchestrate multiple LLM providers with unified interface

stealth-clu - Stealth CLU

alt_text - Generates alt text

a2a-ruby - Agent2Agent (A2A) Protocol implementation for Ruby

tencentcloud-sdk-tdai - Tencent Cloud SDK for Ruby - TDAI

minitest-reporters-llm - Token-optimized Minitest reporter for LLM consumption with regression tracking

simplecov-mcp - MCP server + CLI for SimpleCov coverage data

numo-narray-alt - Numo::NArray Alternative is an experimental project forked from Numo::NArray

elevenlabs_client - Ruby client for ElevenLabs API

hyperclient-mcp - Turn any Hypermedia api into an MCP server

ai_git_commit - AI Git Commit generates Git commit messages using OpenAI.

opentelemetry-instrumentation-anthropic - Anthropic instrumentation for the OpenTelemetry framework

carsxe - A Ruby gem for interacting with CarsXE APIs

rack-ai - AI-powered middleware for Rack applications

ai_root_shield - AI-powered mobile security library with advanced network security and enterprise policy management

deepfake_detector - Forensic-grade deepfake detection toolkit for law enforcement

legal_summariser - AI-powered legal document analysis with multilingual support and PDF annotations

dify_llm - One Ruby API for GPT, Claude, Gemini, and more.

raimei - Umbrella meta-gem for Raimei Ruby + AI tools

hypervibe - Ruby Framework for AI & Vibe-Coders

ai_redactor - AI-powered redaction tool for detecting and masking PII in text and images

qyro_sdk - Ruby SDK for Qyro AI

ruboty-ai_agent - A Ruboty plugin that uses AI to generate responses

raimei-zoo - ONNX model examples for Ruby

raimei-shared - Shared utilities & telemetry for Raimei

raimei-bench - Provider-agnostic AI benchmark harness

raimei-nim - OpenAI/NIM-compatible client for Ruby

kiribi-multilingual_e5-small - Easy to use onnx models

laneful-ruby - Ruby SDK for the Laneful email API

ragents - A Rails engine for managing prompts in ActiveAgents

easyai - Easy AI CLI tool wrapper

New Open Source

Links to the Github repository:

Sea Support - A Rails reference app for building an AI-powered support inbox on DigitalOcean App Platform

Agentic Rails - Risk-aware Rails framework with Progressive Commit Protocol, experiment-driven development, tmux integration, and DevOps automation

Career Companion - AI-Powered Career Enhancement Platform

Heimdall - Watch over your LLM systems, detecting and blocking malicious prompts before they can breach your AI defenses

JRuby MCP Shop - Modern e-commerce platform built with JRuby and powered by Model Context Protocol

Agent Forge Admin - Rails admin interface using Active Admin to manage data from the Agent Forge API system

MCP CLI - CLI to install, integrate, and manage MCP servers across Claude, Codex, and Goose with profiles and a curated registry

Agentic-Forecasting - Forecasting app that combines a Ruby with a lightweight Python ARIMA service and a simple LLM-driven agent

Claude Agents Collection - Agent management system that aggregates multiple Claude Code agent collections into a unified workspace

Worky - AI Workflow Agent

Planning Center MCP Server - Model Context Protocol server that provides secure access to Planning Center data through authenticated API endpoints

Scouty - Personal AI-powered job scout: crawls job boards, analyzes postings with a local LLM, and scores jobs

Hyperclient MCP - Turn any hypermedia api into an MCP server

Ruly - CLI tool for managing AI assistant rules and configurations

Search Evaluation Service - Runs evaluations for GOV.UK site search using the Google Vertex AI Search evaluations framework

ModBot - AI-powered Reddit moderation bot for Ruby

Jobs & Opportunities

The newsletter currently scans hundreds of jobs boards at Ruby engineering organizations, and there are too many open positions at a time to list out in the newsletter anymore. So I’m building a free job matching platform for Rubyists. After signing up and completely a short survey on career preferences including salary range, location, seniority, and technologies, the service will email you one open position a week if there is an available opportunity matching your preferences. If you would like to beta test the service, or are an organization searching for Ruby engineers, please reach out at matt@roboruby.com.

It is important to highlight opportunities for Junior Developers, so going forward the newsletter will only highlight featured opportunities and beginner roles.

Featured

Remote - EasyLlama is a workplace compliance training platform: Director of Engineering

Remote - Rivo is a Shopify customer retention platform: AI-Focused Ruby on Rails Engineer

Remote - TimeZest makes it easy for end users to schedule appointments with IT service providers: Senior Software Engineer (Rails/LLMs)

Junior Positions

Remote - CardFlight provides mobile payment solutions for small businesses: Junior Backend Software Engineer

Barcelona - Yuma AI automates e-commerce customer support using AI: AI Solution Engineer - Fullstack - Junior Rails Engineer

Berlin - HeyJobs is a job marketplace for essential workers: Working Student Software Engineer - Ruby on Rails /Python, AI Accelerated

One Last Thing

Spec-driven development with AI: Get started with a new open source toolkit

Developers can use their AI tool of choice for spec-driven development with this open source toolkit.

github.blog/ai-and-ml/generative-ai/spec-driven-development-with-ai-get-started-with-a-new-open-source-toolkit

GitHub introduced Spec-driven development with AI: Get started with a new open source toolkit, a new approach to AI-assisted development. The toolkit encourages developers to start with detailed specifications before generating code, improving output quality by providing AI models with clear context and requirements. Spec Kit, Github’s new open sourced toolkit for spec-driven development, provides a structured process to bring spec-driven development to your coding agent workflows with tools including GitHub Copilot, Claude Code, and Gemini CLI.

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - September 4th, 2025

Matt Solt — Thu, 04 Sep 2025 12:00:00 +0000

Welcome to the 14th edition of Ruby AI News! This edition features a Rails + Claude AI Hackathon, an interview with José Valim and Tidewave updates, a new Rails UI theme for AI-powered SaaS applications, and much more.

Pro tip: Due to the size of the newsletter, many email clients truncate the content. It is recommended to read on the web for the best experience.

Top Stories
Content
Events
- Previous
- Upcoming
Open Source Updates
- New Gems
- New Open Source
Jobs & Opportunities
One Last Thing

Content

Benchmarks: Tencent released AutoCodeBench, an automatic benchmark generation system that evaluates large language models' code generation capabilities across multiple programming languages including Ruby. The benchmark uses an LLM-based automated pipeline to generate new test problems, addressing the issue of data contamination where modern LLMs may have been trained on existing benchmark data. The accompanying research paper Large Language Models are Automatic Code Benchmark Generators details the benchmark process and performance gaps not captured by traditional static benchmarks. The top reasoning model listed for Ruby is currently Grok 4, with Claude Opus 4 not far behind.

Update: Vicente Reig released DSPy.rb v0.20.0: Multi-Provider AI, Better Context Management, and Production Persistence, a major update to the Ruby port of Stanford's DSPy framework for building AI systems. This release introduces multi-provider support with Google Gemini integration, fiber-local language model contexts for better concurrent request handling, and program persistence and serialization, allowing you to save, load, and share optimized DSPy programs with full state preservation. Subsequent releases added type alias support in v0.21.0 and an event-driven observability system in v0.22.0 for better monitoring and debugging capabilities. Additionally, there are many updates to the comprehensive documentation.

Article: Kody Kendall introduced A Chatbot that Builds Rails Apps, showcasing Leonardo and LlamaPress, a chatbot agent built with Langgraph designed specifically for building full-stack Ruby on Rails applications directly in the browser. The agent executes Rails commands, runs development workflows, and modifies the app in real-time. The agent can be installed with bash script and is available on Github. A demonstration video is also available on Youtube: Leonardo: a Deep LangGraph Agent That Builds Full-Stack Rails Apps in Your Browser (LlamaPress Demo).

Podcast: Joe Leo and Valentino Stoll of The Ruby AI Podcast interviewed Kieran Klaassen in Evaluating LLMs with Leva. The Ruby gem Leva provides a framework for testing LLM responses against expected outputs using configurable evaluators, helping developers assess the quality and accuracy of AI-generated content in their Ruby applications. In the episode, Kieran discusses his passion for AI and Ruby as well as his experience building Cora, a service to manage email inboxes by categorizing and summarizing emails using AI. The podcast episode is also available on YouTube.

Tutorial: Patricio Mac Adden from Sinaptia wrote about how to build an MCP on Rails. The tutorial walks through creating an MCP server with authentication that exposes Rails models as resources and tools, allowing AI assistants to query and interact with your Rails app through natural language. Patricio provides a complete implementation using the FastMCP Ruby gem, showing how to define tools and resources.

Video: David Kimura demonstrated how to effectively use Large Language Models in this DriftingRuby episode on LLM Usage. The video covers the installation and configuration of the OpenAI client, creating chat and usage models, and tracking prompt and token completions.

Update: Carmine Paolino released the new upgrade guide preparing for RubyLLM 1.7. The update introduces smarter error handling after tool calls, local provider support for model fetching, and throws UnsupportedAttachmentError for PDFs when using local models. A major addition is the database model registry, providing chats and messages with ActiveRecord associations to model records. The release adds Google Cloud Vertex AI provider support and enhances the with_params method to override RubyLLM defaults. Shoutout to Rich Chetwynd and Chris Sonnier for recently sponsoring the RubyLLM project. If you are using RubyLLM, please take a moment to complete the RubyLLM Usage Survey.

Tutorial: Andrés Eduardo demonstrated how to build AI-generated loading messages in Rails 8 using Hotwire and Stimulus. The tutorial recreates the status messages seen in apps like Claude Code, combining background jobs, Turbo Streams, and Stimulus controllers to stream dynamic phrases in real time. By integrating RubyLLM and structured outputs with RubyLLM::Schema, Andrés shows how to enrich user experience with AI-driven feedback while tasks are running in the background. Andrés also previously posted a Gemini CLI Crash Course.

Article: Scott Werner argues that "safe" technology choices are often just successful ones retroactively labeled as safe in Safe Is What We Call Things Later. Scott points out that many technologies considered safe today were once risky cutting-edge choices that succeeded through adoption and ecosystem development. He concludes that we need both developers who embrace change and new technologies, as well as developers that build guardrails and sustainable systems. In his related post, The Cause of, and the Solution to, All Your Team's Problems, Scott explores the trade offs between code that is “disposable, experimental, and abundant” vs code that is “precious, careful, and crafted”, arguing that if AI generated code is problematic, you should further embrace AI to solve the issues.

Video: Kody Kendall continues his Ruby on Rails AI tutorial series with Learn how to build an AI Powered Ruby on Rails web app from scratch, Part 3, Rails New + Scaffolding. In this video, Kody demonstrates Rails scaffolding to rapidly generate CRUD functionality, routes, controllers, and views with a single command. The tutorial covers creating a new Rails app, scaffolding a User model, integrating Devise authentication, and styling with Tailwind CSS. This installment builds on Part 2 and Part 1 of the series.

Release: Christopher Petersen announced ClusterKit: High-performance UMAP and clustering for Ruby, a new gem that brings dimensionality reduction and clustering algorithms to Ruby. The ClusterKit gem provides high-performance implementations of UMAP (Uniform Manifold Approximation and Projection) for dimensionality reduction and various clustering algorithms including HDBSCAN (Hierarchical Density-Based Spatial Clustering) and K-means. Built with a focus on performance, ClusterKit leverages Rust extensions to deliver fast clustering and visualization capabilities that were previously difficult to access in the Ruby ecosystem.

Newsletter: Yatish Mehta published Token Ruby #4: Bedrock, Red-Candle and Probabilistic Software, showcasing Ruby's growing AI ecosystem. The newsletter features articles on the Ruby AWS Bedrock client, the Red Candle library for running language models directly from Ruby, and tips on coding agents. Yatish also wrote a recap of the August San Francisco Ruby Meetup with great insights from the event.

Article: Rahoul Baruah shares notes from his talk at the North West Ruby User Group (NWRUG) in LLMs for Software Developers. The post explores day to day use of Large Language Models for developers, covering how LLMs can assist with code generation, debugging, and documentation. Rahoul breaks down his Claude Code setup, workflows, and experiences integrating LLMs into Rails applications.

Release: Paweł Strzałkowski wrote about the release of a MCP Template for Rails Applications. The template provides a foundation for building Rails-based MCP servers with generator hooks, smart tool generation based on ActiveRecord models, and tool scaffolding. The mcp-on-rails template includes automatic schema generation, CRUD operations, filtering, pagination, and error handling for tool calls.

Announcement: Steve Polito from Thoughtbot introduces Top Secret, a new Ruby gem designed to help developers filter sensitive information and environment secrets. The gem uses named-entity recognition capabilities from the mitie gem along with regular expression patterns to filter data from free text. This is extremely useful if you want to filter private information in prompts or conversation history with a chatbot.

Article: Vaishnavi Ganeshkar explores AI and Machine Learning Integration: Rails Meets Intelligence. The article covers why Rails is a great fit for building AI applications, common use cases for Rails + AI, and a complete tutorial for building an AI-powered search in Rails with pgvector and OpenAI.

Update: Dewayne VanHoozer announced that AIA is Concurrently Multi-Model, a major enhancement to his Ruby-based command-line AI assistant. The aia gem now supports sending the same prompt to multiple AI models simultaneously, allowing users to compare responses from different providers like OpenAI, Anthropic, and local models. The release coincides with updates to his smart_message library, which handles message routing and formatting across various AI backends. Theses updates make it easier for developers to evaluate different AI models side-by-side and choose the best response, token counts, and costs for their specific use case.

Article: Andrew McNamara of Shopify published Building Production-Ready Agentic Systems: Lessons from Shopify Sidekick, detailing the engineering challenges of building AI agents that can take autonomous actions on behalf of users. The article explores how Shopify built Sidekick, an AI assistant that can perform complex tasks like creating discount codes and managing products, requiring sophisticated permission systems and safety guardrails. The post provides practical insights into production AI architecture, including how to design tool interfaces that are both flexible for AI agents and safe for autonomous execution.

Launch: Charles Luzar built HomeChorus, a natural language task manager in Rails that allows users to schedule complex recurring tasks using conversational input. The app leverages RubyLLM for AI integrations and tooling, with users able to type things like "I need to change my AC filter regularly" and have the system intelligently parse and schedule appropriate routines. Charles shared his learnings on building the app in this Reddit post.

Article: Riccardo Carlesso explored the process of Vibecoding an MCP server in Ruby with Gemini Code Assist. Using Gemini Code Assist, Riccardo creates an MCP server with FastMCP that returns a list of users, showing a simple process for adding MCP tools or resources to a Rails app.

Documentation: GitLab published their AI Engineering Handbook outlining how they integrate AI capabilities across their platform. The handbook covers GitLab's AI strategy focusing on enhancing developer workflows through features like code suggestions, test generation, and intelligent automation while maintaining security and privacy standards. It details their technical architecture for AI features, including their use of large language models, vector databases for semantic search, and integration patterns for AI-powered development tools.

Tutorial: ito845 shared an implementation for a Human in the loop MCP server using MCP's official Ruby SDK (Japanese). The tutorial demonstrates how to build an MCP server that requires human approval before executing potentially dangerous operations like file deletions or API calls. The implementation showcases the Model Context Protocol Ruby client capabilities for pausing execution and waiting for human confirmation.

Release: Daniel Friis released RubyLLM::Template, a new addition to the RubyLLM ecosystem that helps organize prompts as reusable templates. The gem allows developers to define structured templates with system, user, and assistant message roles, and templates can be applied with a single method call.

Launch: Chris Sonnier showcased a Ruby LLM Gems Comparison with a site to help Ruby developers choose between Langchain.rb and RubyLLM for their AI projects. The site provides detailed side-by-side comparisons of both gems' features, installation processes, and deep dives into use cases.

Release: Amit Leshed released LLMTape - record/replay real LLM calls in tests, a Ruby DSL that wraps LLM clients to provide VCR-like functionality for testing. The LLMTape gem records real LLM responses as YAML “tapes” in test environments and replays them on subsequent runs.

Tutorial: Robert (0x1eef) demonstrates How to Edit Images with Gemini using llm.rb to interact with Google's Gemini AI model for image editing tasks. The tutorial walks through using the llm.rb gem to generate and edit images from text prompts, enabling automated image editing operations.

Update: Alex Rudall released ruby-openai 8.3.0, adding support for OpenAI's new Conversations API that enables developers to create and manage persistent conversational contexts.

Announcement: Iryna Pisklyarova from JetBrains announced that RubyMine Is Now Free for Non-Commercial Use. The Ruby IDE is now available at no cost for personal projects, open-source development, educational use, and non-profit activities. RubyMine features Junie, an AI coding agent developed by JetBrains.

Update: Justin Bowen released ActiveAgent 0.6.1, a Ruby gem that provides an agent framework for building AI applications. This update includes several enhancements to the Agent class, structured output params, and updated documentation and examples.

Podcast: Justin Searls hosted the Breaking Change Podcast v42.0.1 - Ignore All Previous Instructions with guest Scott Werner, organizer of the ArtificialRuby meetup and author of Works on my Machine. The episode looks at programmer as a career, how AI coding agents are changing software engineering, and Sublayer AI updates.

Tutorial: Brandon Casci demonstrated How We Automated GitHub Issues with Free AI, walking through the implementation of an AI-powered GitHub Issues assistant using GitHub Actions and Gemini. The tutorial covers setting up automated issue triage that can categorize bugs, feature requests, and questions, automatically assign appropriate labels and team members, and even generate initial response templates based on issue content.

Launch: Liz Pantalone launched an AI code refactoring service designed to improve code quality and maintainability for ChatGPT, Claude, and GitHub Copilot generated code. The service offers refactoring, testing, and technical debt reduction for Ruby on Rails applications.

Podcast: Robbie Wagner and Charles William Carpenter from Whiskey Web and Whatnot: Web Development, Neat interviewed Chris Power (Typecraft) and Robert Jackson to explore whether web development frameworks will survive in an AI-driven world. The discussion examines how AI tools are changing the development landscape, insights into MCP and AI, and whether traditional frameworks will remain relevant as AI becomes more capable of generating code.

Article: Pavel Nahorski from Rubyroid Labs explores integrating AI assistants into Ruby on Rails applications in AI Assistants Powered by Ruby on Rails: Transforming Business Processes. The article covers practical approaches for building AI-powered features within Rails applications, which AI model to choose, and includes three case studies from Rubyroid Labs clients.

Launch: Educative has released Learn Ruby from Scratch, a comprehensive AI-powered course designed to teach Ruby programming fundamentals. The personalized learning platform adapts to individual learning styles and paces, covering everything from basic syntax and object-oriented programming to advanced topics like metaprogramming and Rails development.

Benchmarks: Radamés Roriz has released benchmark data for ActiveGenie, a Ruby library designed to help developers choose the right AI models for complex, real-world AI features. The complete project and benchmark data are open-source on GitHub.

Podcast: Brendan Buckingham and Ryan Frisch interviewed Chris Oliver, the creator of GoRails and Jumpstart Pro, in Rails Business Podcast - Episode 16. In the episode, Chris elaborates on the impact of AI on the programming landscape and its potential risks and benefits, along with offering advice to aspiring junior developers.

Tips: Lucian Ghinda shared his task list portion of a CLAUDE.md file for building admin interfaces with Avo in this X/Twitter post.

Article: Kelly Gebo at Thoughtbot argues that ChatGPT is writing the same product plan for your competitors, warning against the homogenization of product strategy through AI tools. Kelly posits that while ChatGPT can efficiently generate product plans, feature lists, and user stories, the resulting outputs often lack the unique insights and differentiation that come from deep customer research and domain expertise.

Other: Stack Overflow released their 2025 Developer Survey, a definitive report on the state of software development. With nearly 50,000 responses, this year’s report includes a new focus on AI agent tools, LLMs, and community platforms.

Events

ArtificialRuby: The August 13th ArtificialRuby meetup featured two Ruby AI speakers:

Chuck Blake: Commanding AI: Automating Docs, Reviews & Reports in Rails
Chase Stevens: The Rubber Duck That Quacks Back

SFRuby: The August 26th San Francisco Ruby Meetup hosted three Ruby AI-related presentations. Yatish Mehta also wrote a recap of the August event at Github.

Enrique Mogollán: What I've Learned Building an MCP Inspector in Ruby
Miles Georgi: Tackling Domain Complexity with Foobara
Sergey Karayev: Getting the Most out of AI Coding Agents for Your Rails App

Baltic Ruby: The Baltic Ruby 2025 Conference on June 12th through the 14th published two AI videos from the event:

Yukihiro "Matz" Matsumoto: Programming Language for the AI Age
Chris Hasiński: Image Vector Search with Ruby

Upcoming

September 6th - Conference: XORuby on September 6th in Chicago will feature a talk by Scott Werner, the founder of Sublayer and ArtificialRuby, titled We Were Voyagers. We Can Voyage Again! The talk will focus on the rise of Generative AI as an opportunity to bring back the magic, art, and fun of creating with Ruby.

September 10th - Conference: Friendly.rb on September 10th and 11th in Bucharest, Romania will host three Ruby AI presentations:

Obie Fernandez: Ruby+AI Tech Landscape 2025: A Survey
Chris Hasiński: Let’s fine-tune a modal!
Greg Molnar: Security in the age of AI

September 9th - Meetup: The Ruby Banista meetup on September 9th in Sofia, Bulgaria will have a talk by Nikola Jichev on PostgreSQL tips & tricks that touches on AI capabilities with vector handling.

September 10th - Meetup: The ChicagoRuby meetup on September 10th at Beyond Finance in Chicago will have a presentation by Aji Slater on Zen and the Art of Incremental Automation.

September 12th - Conference: RubyConf India on September 12th and 13th in Jaipur, India will include four Ruby AI themed presentations, including:

Deepan Kumar: AI at Runtime: Self-Healing Ruby Apps
Prathamesh Sonpatki: Teaching AI to Debug Your Rails Apps (MCP + observability)
Vishwatjeetsingh Desurkar: What if… Ruby Led the AI Revolution?
Vlad Dyachenko: MCP Security: Real-world Risks & Defenses

September 13th - Hackathon: Rails Fever is hosting a Rails + Claude AI: Build Together Challenge at CultureWorks on September 13th in Philadelphia. The collaborative build challenge will pair together developers to create a real Rails App in just a couple of hours, powered by Claude AI.

September 17th - Meetup: ArtificialRuby is hosting a meetup at Betaworks in New York City on September 17th. If you are interested in presenting at an ArtificialRuby meetup, please fill out this form and let them know. I will be speaking at the September meetup so be sure to stop by!

September 18th - Conference: The EuRuKo (European Ruby Conference) on September 18th and 19th in Viana do Castelo, Portugal has announced seven Ruby AI & Hardware related speakers:

Obie Fernandez: Roasting Code for Fun & Profit with Structured AI Workflows
Paweł Strzałkowski: Making Rails AI-Native with the Model Context Protocol
Carmine Paolino: RubyLLM: Making AI Development Beautiful Again
Lucian Ghinda: Don't Let Your AI Guess: Teach It to Test!
Ivan Nemytchenko: Slingshot Development: Vibe Coding with Ruby Done Right
Albert Pazderin: Building interactive Ruby gem tutorials with Wasm
Hitoshi Hasumi: PicoRuby Hands-on: Internet of Things Edition

September 20th - Conference: XORuby on September 20th in New Orleans will feature a talk by Thomas Carr on The State of the Ruby AI Toolbox. The talk will offer an overview of the leading Ruby AI gems and explore their unique strengths and features.

September 26th - Conference: Kaigi on Rails 2025 on September 26th and 27th in Tokyo, Japan features two Ruby AI presentations:

Yusuke Iwaki: Can your web service be automatically tested by AI?
Yasuko Ohba: An introduction to artificial "design" using Rails

October 6th - Conference: The Rocky Mountain Ruby Conference on October 6th and 7th in Boulder, Colorado will host three Ruby AI speakers:

Vlad Dyachenko: Prompt Driven Development (PDD) or the Art of Prompting
Scott Werner: We Were Voyagers. We Can Voyage Again!
Christine Seeman: Thoughtful AI for the Rubyist

Open Source Updates

Please feel free to reach out and let me know if you come across any interesting Ruby AI coding examples for the Code Spotlight.

New Gems

Links to the RubyGems page, newest releases are first:

sage-rails - LLM powered business intelligence - build SQL reports using natural language

ruby_llm-template - Template management system for RubyLLM - organize and reuse ERB templates for AI chat interactions

llm-agent-rails - Rails engine for LLM-powered slot filling and tool orchestration

llm-fillin - LLM-powered slot filling and tool orchestration

mistral_translator - Translate and summarize text with Mistral API

mewmew - Make any thor command an MCP

vibe_if - GPT-powered conditional execution based on variable values

contextizer - A tool to extract and package project context

LLMTape - Test code that calls LLMs - record an API call once, then replay it forever

metrifox-sdk - Ruby SDK for Metrifox API

brakeman-llm - Enhance Brakeman warnings with LLM-based descriptions

vibe-if - GPT-powered conditional execution based on variable values

aigc - Generate intelligent conventional commit messages using Claude AI

topical - Topic modeling for Ruby using modern clustering algorithms

activerabbit-ai - Client for ActiveRabbit.ai application monitoring and error tracking

smollama - A simple Ruby client for Ollama API

erblint-agent - Template style checking for Ruby projects aimed at AI agents

mcp_manager - Utility for managing MCP servers in Claude projects

dataleon - Ruby library to access the Dataleon API

smart-commit - Generate intelligent conventional commit messages using Claude AI

dynamic_mcp - A dynamic and flexible Ruby MCP server

mcp-inspector - A tool for inspecting MCP servers

google-cloud-gemini_data_analytics-v1beta - API Client library for the Data Analytics API with Gemini V1BETA API

google-cloud-gemini_data_analytics - API Client library for the Data Analytics API with Gemini API

i18nize - Auto-translates missing I18n keys in YAML files using DeepL

llm-spell - CLI that can correct spelling mistakes with the help of an LLM

kaggle - Ruby client for the Kaggle API

sylvia - A command-line tool for generating and managing Ruby projects

ragnar-cli - A Ruby + Rust powered Retrieval-Augmented Generation system

parsekit - Ruby document parsing toolkit with PDF and OCR support

deepagents_rails - Rails integration for DeepAgents

New Open Source

Links to the Github repository:

MentionAi-Auto-Bot - Automation script designed to interact with the Mention Network API to fetch random questions, generates AI responses, and saves results

Please - Ruby wrapper for Ollama with built-in prompts

AI Meeting Processor - An intelligent system to process meeting transcripts and generate executive analysis, technical proposals, and Jira tickets automatically

AI Commit - Generate intelligent, conventional commit messages using Claude AI

LLM Tracer - Instrument LLM applications using OpenTelemetry and the OpenTelemetry GenAI standards

Code to Prompt - Converts a codebase to a markdown document that can be used to feed into LLMs

Build Angle - An AI-powered static website generator that creates professional, multi-page websites based on user requirements

PDFKit - CLI for intelligent PDF analysis and manipulation, designed for AI/LLM workflows that need to process large documents within context limits

Kindling - Build better AI prompts by assembling project file trees and context with ease

METRC Documentation AI Assistant - MCP server that provides AI agents with searchable access to METRC cannabis compliance documentation across all legal states

Rails AI Tweets - Basic AI Chatbot to generate tweets

Jobs & Opportunities

Featured

Ichi uses AI and large language models to transform the way construction projects navigate permitting and code compliance and is looking for a Senior Software Engineer, Full Stack. This is a fully remote, unique Ruby on Rails opportunity to work with AI-powered development tools and develop and scale a system that seamlessly integrates multiple LLMs.

Multiple

Onsite - Global - Zendesk is a customer service platform for support, sales, and engagement: 55 OPEN POSITIONS

Remote - GitLab is a DevOps platform for code management, CI/CD, and collaboration: 17 OPEN POSITIONS

Remote - Jobgether is an AI-powered platform for matching talent with remote and flexible jobs: 12 OPEN POSITIONS

Remote - GitHub is a code hosting platform for version control and collaboration: 8 OPEN POSITIONS

Remote - Aha! is a product development software for roadmapping, planning, and delivery: 7 OPEN POSITIONS

Hybrid / Onsite - Phillipines / India - Pearson is a global education company providing learning materials, assessments, and services: 4 OPEN POSITIONS

Remote - Versapay automates accounts receivable and B2B payment processing: 4 OPEN POSITIONS

Remote - Instrumentl is a grant discovery and management platform for nonprofits: 3 OPEN POSITIONS

Remote - ThriveCart is an e-commerce platform for shopping carts, sales funnels, and course creation: 3 OPEN POSITIONS

Remote - Chatwoot is an open-source customer support platform with AI assistance: 2 OPEN POSITIONS

Remote - Vidyard is a video platform for sales and marketing teams with AI-powered personalization: 2 OPEN POSITIONS

Remote

Ablefy is a platform for online courses, payments, and digital sales: Senior Software Engineer (Ruby & Python)

EverAI is an AI companionship platform for roleplay, gaming, and creative writing: Ruby-on-Rails Engineer

Hellotext is an SMS and WhatsApp marketing platform for e-commerce automation: Ruby on Rails Backend Reliability & Scale Obsessive

InvestGlass is a CRM and digital onboarding platform for financial services: Full Stack Ruby on Rails

OnTheGoSystems builds WordPress localization and translation tools: LLM Engineer

Prepared provides AI-powered solutions for emergency response: Engineering Manager

Rentable is an apartment rental marketplace for finding and touring apartments: Senior Full Stack Software Engineer

Silverfin is a cloud accounting platform for compliance automation and advisory services: Ruby Engineer – Team Collab

Hybrid

New York City - LEA uses AI-powered workflow automation for wealth management: Founding Engineer

Onsite

Richmond, VA - EAB provides education technology, research, and enrollment solutions for schools and universities: Software Engineer (Navigate)

San Francisco - Toast recruiter: Software Engineer

Columbia - ForUsAll provides automated 401(k) retirement plans for startups and small businesses: Sr. Ruby on Rails Engineer - AI

Costa Rica - OfficeSpace is a workplace management platform for space planning and desk booking: Solutions Engineering Team Manager, Client Engagement

France - Lago is an open-source metering and usage-based billing platform: Software Engineer, Infrastructure

India - TechVedika provides AI, IoT, and data analytics development services: Senior ROR Engineer

Freelance

Upwork recruiter:

One Last Thing

André Arko, the creator of Bundler, announced rv, a new kind of Ruby management tool, designed to rethink how Ruby versions are managed. Unlike Bundler, rv manages gems, Ruby versions, AND installs pre-compiled rubies. This enables a much greater degree of portability for Ruby applications, as “it makes it completely trivial to run any script or tool written in ruby, even if that script or tool needs a different ruby than your application does”.

For the last ten years or so of working on Bundler, I’ve had a wish rattling around: I want a better dependency manager. It doesn’t just manage your gems, it manages your ruby versions, too. It doesn’t just manage your ruby versions, it installs pre-compiled rubies so you don’t have to wait for ruby to compile from source every time. And more than all of that, it makes it completely trivial to run any script or tool written in ruby, even if that script or tool needs a different ruby than your application does.

andre.arko.net/2025/08/25/rv-a-new-kind-of-ruby-management-tool

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI: Introducing Tidewave Web & Interview with José Valim

Matt Solt — Thu, 28 Aug 2025 20:44:02 +0000

In this special interview with José Valim, the creator of Elixir, Livebook, and Devise, we look at the launch of the Tidewave Web coding agent for Ruby on Rails, the inspiration behind the service, and the future of AI development and Tidewave.

Introducing Tidewave Web
Interview with José Valim
Additional Resources

Introducing Tidewave Web

This month José Valim and the Dashbit team launched Tidewave Web, a browser-based coding agent for Ruby on Rails and Phoenix that runs directly alongside your web application with full access to UI state, database, logs, and code context, eliminating the back-and-forth of describing what's on screen to current AI coding assistants. The Tidewave coding agent features shared page context that automatically maps UI elements to corresponding controllers and templates, deep Rails framework integration allowing it to execute code within your running app, and collaborative browser testing where it builds and validates features in real-time using a point-and-click Javascript inspector. Currently in beta, Tidewave represents an exciting new direction in AI developer tooling. The Tidewave team posted a launch announcement where you can learn more about the service and the features.

Tidewave

A coding agent that runs in the browser alongside your web app, deeply integrated with your web framework.

tidewave.ai

Installation is straight-forward, and you can be up and coding in minutes. For Rubyists, simply install the Tidewave Rails Gem, powered by FastMCP. The gem adds a /tidewave route to your application that you can visit to create or log into your Tidewave account and set your Anthrophic or Github Copilot API keys. Boot up your app and start chatting with the agent and you’re ready to go! The documentation is constantly being updated, and has further installation instructions, useful tips and tricks, and guides for integrating the Tidewave Model Context Protocol server with your favorite editor.

Since launch, the Tidewave team have continued to ship updates and improvements. The first changelog features code editor integration with one-click file opening and UI element inspection, background notifications for agents and tools, and improved system prompts. The second update allows you to customize tool approval per project, available under the project settings. They are also rolling out a setting called “Labs”, where you can enable experimental features and provide feedback. To see what else is in development, you can visit the public roadmap, or the Tidewave Kanban board to see what’s currently in the pipeline. If you need further assistance getting started with Tidewave, be sure to join the Discord community!

Interview with José Valim

This week I had the privilege of interviewing José Valim, the creator of the Elixir programming language and the Chief Adoption Officer at Dashbit, a software development firm helping organizations run Elixir in production. As a Ruby legend, José is the author of Crafting Rails Applications, a former Rails core team member, and a Ruby Hero award winner. Previously, as co-founder of Plataformatec, he engineered the Devise Ruby library, the de facto authentication solution for Ruby on Rails still used today by hundreds of thousands of applications. Currently, José is building Livebook, an application for automating code and data with interactive Elixir notebooks, and Tidewave, an in-browser AI coding agent for Rails and Phoenix. So here it is, presenting José on:

The New Tidewave Coding Agent

Congratulations on the launch of Tidewave Web! Tidewave is an exciting new AI coding agent for Rails with context support for the development server, user interface, and source code. What makes Tidewave so special?

José: Tidewave is unique in that it is a coding agent that runs in the browser and it's deeply integrated with your web framework, from the database to the UI:

It can execute code within your running Rails/Phoenix app → queries your database, reads logs, accesses models directly
It can inspect and interact with your actual web pages → no more copying error messages or describing UI states
You can point and click on UI elements → so the agent knows exactly which part of your app you're talking about

Other coding agents are rather generic tools that don't particularly understand the unique capabilities of each stack. Tidewave leaps ahead because we specialize for each domain and framework we integrate with.

Inspiration

What was the inspiration for building Tidewave?

José: The initial inspiration for Tidewave actually came about 18 months ago. When I started using GitHub Copilot, it was clear that there was a gap between what the Large Language Model knows and the programming language runtime. We still see these gaps today: developers keep extending their coding agents with external tools to parse source code or find documentation, but if you ask Ruby or Elixir to fetch the location or documentation for a given method/function, the languages will give you a precise answer, without any additional dependencies.

Then, when Anthropic announced Model Context Protocol (MCP), it became clear I could close this gap myself, and that's when we announced Tidewave MCP for Rails and Phoenix, which uses your running web application to give the coding agent access to logs, documentation, source code, database, and more. We cheekily call it “Runtime Intelligence” because it is more than just looking at what the code or the compiler does.

At the same time, as I used coding agents more in my day-to-day, other limitations became apparent. For example, I noticed that I constantly had to swap between my editor and the browser to copy and paste a stacktrace shown by Rails/Phoenix’ error pages or to explain to the coding agent an UI bug I had just seen. I was caught in this loop between the browser and the agent, which wasn't very engaging. Those are the problems we want to solve with Tidewave.

Future Vision

What is the long term vision for Tidewave? What upcoming features are you most excited about?

José: Our long-term vision is to make Tidewave a full-stack coding agent across technologies. Right now Tidewave is tuned for server-rendered Rails and Phoenix applications, but we also want to integrate with React and bring other frameworks like Django and Next.js.

Additionally, there is a lot we are excited about, and given the fact that we just started, we're looking forward to listening to feedback from our users over what we should prioritize. One feature that I am personally very excited about and I can't wait to experiment with is the ability to run and coordinate multiple Tidewave agents at the same time. Given our focus on web frameworks, I believe we can bring a unique spin to this space.

Technology Stack

What are the tools and technologies behind Tidewave? What was the development process like? Do you specifically use any AI coding agents or workflows in your daily development flow?

José: Tidewave is broken apart into three main components: the server, which is implemented in Elixir/Phoenix; the client running in the browser, which is implemented in React; and then we have different runtimes, which are specific to each framework that we support and written in their respective programming language.

Everyone in our team uses coding agents in our day-to-day to varying degrees, depending on what we are working on. For example, we are frequently using Tidewave to iterate on itself. Also, for the framework runtimes, it is common for us to implement a feature in one language and then ask a coding agent to do the initial translation to another one.

Coding agents have also been very useful to build throw-away prototypes of new features and integrations, so we can validate ideas before deciding to invest more time into them.

Elixir

Over a decade ago, you switched from Ruby to build Elixir. What was the motivation behind that? Why do you prefer to build AI apps with Elixir over other languages?

José: Back in 2010, when I was part of the Rails Core team, we were hearing many conversations about writing concurrent software that can use all of our machine resources efficiently. So at the time, it was important for me to find ways and tools to build concurrent software reliably. This search eventually led me to create Elixir, a high-level programming language with focus on productivity and scalability.

If you think about AI applications today, they are essentially real-time and collaborative systems. You have users interacting with agents, you have agents running in real-time across a cluster, and information is constantly flowing between them. Elixir, thanks to its roots in the Erlang VM, can model and build these systems using its built-in concurrency and distribution capabilities, while every other stack out there requires you to bring background workers, messaging systems, and additional complexity to make it work. This makes Elixir uniquely positioned for building this current generation of web applications.

Language Evolution

With AI bound to play a more prominent role in development, how do you believe programming languages and tools should evolve?

José: That's an excellent question and indeed a big question mark at the moment. What I have found out in practice is that, at least for coding agents, they tend to trip and run into the same mistakes as us humans do. So confusing APIs, poor error messages, lack of documentation, etc. all lead to agents getting stuck and improving those will lead to better experiences for everyone, us included.

I'm also very interested in how the field of software verification (tests, code reviews, type systems, etc.) will evolve now that our development process is changing. For example, we have historically been really bad at writing tests and tracking requirements, and AI may throw a wrench big enough into the problem and force us to explore new solutions. These questions are exactly the topics that I aim to explore at my San Francisco Ruby Conference presentation. So it will be lovely to see you all there.

Closing Thoughts

What skill sets and disciplines do you think Rubyists should pursue to level up their careers and expertise in the age of AI?

José: The Ruby community has always been remarkable at accepting and exploring new ideas, which I believe is the most important skill to have today. There are still so many open questions and it all changes rapidly... so having an open mind and the ability to experiment will be crucial to navigate the next few years.

Additional Resources

I want to thank José Valim for taking the time to answer these questions, and for all of his contributions to the Ruby community over the years. If you haven’t already, be sure to check out all of the latest updates from José:

Tidewave is an AI development tool that accelerates web application development by connecting AI coding agents to web framework runtimes through the Model Context Protocol, providing features like database integration, runtime introspection, and code evaluation.

Dashbit is a company that offers an Elixir Development Subscription providing direct access to their team of experts for code reviews, technical meetings, and support to help startups and enterprises build and run Elixir applications in production.

The Path to Tidewave: Beyond Code Intelligence

Elixir is a dynamic, functional programming language that runs on the Erlang VM, designed for building scalable, fault-tolerant, and maintainable applications across domains like web development, embedded systems, machine learning, and data pipelines.

Livebook is an open source application for writing interactive and collaborative notebooks with code, data, and visualizations in Elixir.

Devise is a flexible, modular authentication solution for Ruby on Rails applications based on Warden that provides authentication modules and offers a complete MVC solution for handling user authentication with support for multiple models, OmniAuth integration, and customizable views and controllers.

Episode 267 of Thinking Elixir podcast features José Valim discussing Tidewave Web, a new AI-powered development service that adds an AI chat sidebar capable of directly interacting with and modifying Phoenix and Rails applications

The San Francisco Ruby Conference is a two-day event (November 19th & 20th) celebrating Ruby's ecosystem and future, featuring talks on open source/AI tooling, Ruby at scale, CTO panels, and startup demos, organized by the SF Ruby Meetup group.

That’s all for now! Stay tuned for the next edition of The Ruby AI Newsletter. Be sure to reach out if you have any stories, content, jobs, or events you would like to see featured.

Ruby AI News - August 21st, 2025

Matt Solt — Thu, 21 Aug 2025 19:28:35 +0000

Pro tip: Due to the size of the newsletter, many email clients truncate the content. It is recommended to read on the web for the best experience.

Welcome to the 13th Edition of Ruby AI News! This editions features the launch of an in-browser AI coding agent for Rails, a masterclass on compounding engineering, exciting Ruby OpenAI updates, and much more.

Top Stories
Content
Events
- Upcoming
Open Source Updates
Jobs & Opportunities
One Last Thing

Content

Announcement: Scott Werner introduced a new approach to AI-powered development in The System Inside the System, proposing that instead of using AI to generate entire applications, developers should create specialized AI systems that generate specific components within existing codebases. This philosophy is embodied in two new Ruby tools: vsm (Viable System Model), a Ruby gem for building self-contained, recursive systems that can act as AI agents, and airb, a CLI-based programming agent with context-aware code generation capabilities. Scott argues that Ruby’s dynamic nature may be what is needed for building systems that can evolve, and Ruby’s metaprogramming foundations may give “AI agents the ability to build themselves”.

Update: Ben Roesch released Raif v1.3.0 - Now with support for LLM evals, including LLM-as-judge. This update introduces evaluation capabilities for large language models, including the popular LLM-as-judge methodology where one LLM evaluates the outputs of another. Raif also got a new, expanded documentation site:

Documentation

Raif (Ruby AI Framework) - A Rails engine for adding AI-powered features to Rails applications

docs.raif.ai

Newsletter: Yatish Mehta launched TokenRuby: a new Ruby + AI newsletter, a weekly publication bridging the Ruby and AI ecosystems for Rails developers. Each issue features highlights from both worlds, interesting reads, and product recommendations. Yatish has previously contributed to the Ruby AI Newsletter, covering the Ruby AI Hackathon. The first three issues are available now, and you should sign up today for future updates:

Update: Carmine Paolino released five rapid-fire versions of RubyLLM, moving from 1.6.0 to 1.6.4. Version 1.6.0 introduced custom HTTP headers for beta features, tool halt control to skip LLM commentary, support for the latest models (Opus 4.1, GPT-5), new tool callbacks, and a documentation site redesign. Version 1.6.1 followed with critical fixes including OpenAI tool choice flexibility, automatic cleanup of orphaned tool messages after rate limits, and the ability to switch tool contexts mid-conversation. Version 1.6.2 focused on performance with corrected Gemini thinking token counting for accurate billing, removal of capability gatekeeping to let providers handle feature support directly, and multiple code optimizations via RuboCop Performance. Version 1.6.3 improved developer experience by allowing models to use their native temperature defaults instead of forcing 0.7, and removed problematic Overcommit hooks that required all provider API keys just to submit PRs. Version 1.6.4 added multimodal tool responses enabling tools to return images and files, fixed Gemini schema conversion issues, and included comprehensive new configuration documentation. Congratulations Carmine on passing two million downloads and being the number one trending Ruby repository on Github!

Article: Dieter S. shared insights from Building an AI Agent with Ruby and Rails from Scratch — What No One Tells You, detailing the challenges of creating a production-ready AI agent that processes and summarizes Medium posts. The post covers workflows, MCP, context, LLM choice, tool calling, and other considerations. Dieter emphasizes that while gems provide helpful abstractions, developers must still understand the underlying mechanics to build effective AI applications that can handle real-world document processing at scale.

Podcast: Joe Leo and Valentino Stoll published a recap of their interview with Obie Fernandez in From Black Boxes to a Multitude of Workers: Obie Fernandez on AI Architecture in Ruby. The discussion explores Obie's journey from traditional Ruby development to AI-powered applications, focusing on how he transitioned from building monolithic AI systems to creating distributed architectures with multiple specialized AI workers. The Ruby AI Podcast also announced their next two episodes, Episode 5: Evaluating LLMs with Rails and Leva Thanks to Kieran Klaassen, and Episode 6: Rails After the Robots: Chad Fowler on AI as the Next Abstraction.

Paper: Claire Randolph, Adam Michaleas, and Darrell O. Ricke published Large language models for closed-library multi-document query, test generation, and evaluation, introducing a system that leverages LLMs for document analysis within secure environments. The research addresses the challenge of using AI in proprietary settings where data cannot leave organizational boundaries, implementing a Ruby on Rails web interface that allows users to query multiple documents simultaneously using retrieval-augmented generation.

Update: Justin Bowen released ActiveAgent v0.5.0, introducing multimodal response capabilities with image and PDF analysis support, allowing agents to process visual content alongside text. The release improves configuration management by adding support for base client configurations via an active_agent.yml file and enhances the generator system with skip config and format options. Key fixes include correcting schema generation for user actions, fixing generation callbacks, updating the Anthropic provider to support their new API, and documentation additions.

Article: 0x1eef detailed how to implement Retrieval-Augmented Generation in 32 lines of code in An Introduction to RAG with llm.rb. The tutorial walks through using OpenAI’s Vector Stores API, generating embeddings from documentation, and using similarity search to provide relevant context to an LLM for accurate answers. In a companion post about Age Estimation with llm.rb, 0x1eef explores using OpenAI's vision models to estimate the age of a person from images, demonstrating multimodal prompts, image vision, and structured outputs. The library used, llm.rb, was recently updated to version 0.13.0.

Tutorial: Bobby Santiago demonstrated How to Add AI to Your Rails App: FastAPI Integration with Local LLMs, showing how to integrate Python-based AI services with Rails applications using FastAPI and Llama 3. The tutorial walks through building a microservice architecture where Rails handles the web application logic while FastAPI serves AI capabilities with local LLMs. The example features a sentiment analyzer for blog posts, with complete implementation details for Docker setup, service communication, and error handling. There is an accompanying demo repository on Github.

Update: Christopher Petersen announced an update to Lancelot: Ruby Bindings for Lance with Hybrid Search, providing Ruby developers access to the Lance columnar data format optimized for AI workloads. The lancelot gem enables hybrid search with semantic and full-text capabilities, efficient vector storage and retrieval, and a Ruby-idiomatic API for building AI-powered features like RAG systems and recommendation engines.

Article: Wilbur Suero posted Writing Maintainable AI Prompts in Rails with Promptly, presenting his Ruby gem Promptly for organizing AI prompts in Rails applications. The gem addresses the common problem of scattered prompt strings throughout codebases by providing a structured way to manage prompts using YAML files with ERB templating support.

Newsletter: Nate Berkopec shared the latest edition of Four Line Friday, featuring some good Ruby AI tips and tools. This week includes a production memory logging utility for Sidekiq, a shell script for setting up AI development environments, using Claude to create “platinum-plated” dotfiles, and running Claude Code instances in parallel with Conductor.

Update: Vicente Reig announced multimodal support in DSPy.rb v0.16, enabling developers to process both text and images with language models. The update includes documentation examples and supports OpenAI and Anthropic vision models with image analysis and structured outputs. The documentation demonstrates how to build multimodal chains for tasks like image-based generation and visual question answering. DSPy.rb is currently at version 0.19.1, so be sure to check the release notes for the latest updates.

Release: Vicente Reig also released BAML-inspired type definitions that promise 60-89% fewer token usage when compared to JSON Schemas. The gem, sorbet-baml, translates Sorbet types into BAML-inspired type definitions for more efficient AI interactions. The project aims to reduce token usage compared to traditional JSON schemas when sending type definitions to language models, addressing the problem of increasingly complex schemas that consume excessive tokens. The gem is designed as an alternative to JSON schemas.

Article: Rich Steinmetz explored workflows for leveraging multiple LLMs simultaneously in Code with LLMs in Parallel. The analysis looked at Git worktrees, Conductor, Claude Squard, and custom scripts, concluding that a custom setup may be the best possible solution right now. As part of a comment on the article, Ben Sheldon shared his Ruby configuration script for working with Git worktrees. Previous articles in Rich’s LLM coding series include Code with LLMs and a PLAN, Code with LLMs and default instructions, and Code with LLM teams.

Update: Dewayne VanHoozer released Ragdoll System v0.1.11: Multi-modal RAG with Enhanced Document Management. The update includes enhanced document management, Rails engine improvements, better logging, and a new job queue dashboard. He also announced upcoming support for image and audio processing, analytics, and multi-modal search.

Article: Abdelkader Boudih argues in The Mars Speech: Crossing the AI Event Horizon that AI has changed the parameters of success for developers. He focuses on junior developers and the skills and initiatives they have to adopt to become proactive winners in the AI age. He also introduces the concept of an LLM Requirements Definition Language, where engineers must learn how to communicate with LLMs properly instead of just “prompting”.

Opinion: Scott Werner explored how AI code generation is similar to the zero interest rate policy (ZIRP) era in Entering Technical Debt's ZIRP Era. He argues AI isn’t creating a technical debt crisis, its making infinite code generation feasible now because each advancement in AI will tackle previous technical debt. As AI refactoring costs approach zero, AI will fix past issues, and the winners will be those that embrace AI generation the most now. Scott is also opening up the beta for ActionsPerMinute, a gaming-inspired command center for working with different AI agents and tools across multiple projects in parallel.

Article: Justin Searls reflected on Scott Werner's ZIRP article in Is a Technical Debt ZIRP a Good Thing? While initially looking at a Technical Debt ZIRP Era as beneficial, he reassess after reviewing a thought provoking comment from Brian Marick on the post. Ultimately he concludes that the value of current LLM-based tools outweighs the risks, and the personal benefits have forever changed his approach to software development.

Release: Gabriel Dehan released claude_hooks, a Ruby DSL that simplifies creating Claude Code hooks by eliminating repetitive boilerplate of JSON parsing, STDIN/STDOUT handling, and error management. The library provides base classes for all hook types (UserPromptSubmit, PreToolUse, PostToolUse, etc.) with built-in input helpers, output manipulation methods, and session-specific logging that doesn't interfere with Claude's operations.

Podcast: Julián Duque of Heroku interviews Errol Schmidt from reinteractive in Heroku in the Wild: reinteractive on AI and Rapid POCs. The discussion focuses on how reinteractive leverages AI technologies and rapid prototyping methodologies to build proof-of-concepts quickly for their clients. They share insights on safely integrating AI into development workflows and the practical considerations for deploying AI-powered applications on Heroku.

Tips: Reddit user jalolapeno shared their workflow for effectively using Claude Code with Rails projects. The approach centers on creating a folder structure containing strategic planning documents: a plan.md summarizing the product vision, detailed MVP specifications, and most importantly, a technical.md file with implementation patterns that prevents Claude from generating poor code. When Claude struggles with specific libraries or gems, they create targeted guides and reference these in a CLAUDE.md file for quick context loading in new chats.

Release: Jared Reid released an MCP server for interacting with the RubyGems.org API, available as @ruby-mcp/gems-mcp on npm. This tool enables AI assistants to search for Ruby gems, retrieve detailed gem information including dependencies and versions, and access metadata from the RubyGems repository. When paired with a bundler/Gemfile specific sub-agent in Claude Code, it provides effective dependency management capabilities for AI-assisted development workflows.

Update: Sean McCleary updated his local gem documentation MCP server to provide CLI access to Ruby documentation and AI agent access via MCP. The gem allows AI assistants like Claude to access local Ruby gem documentation for the specific versions installed in your project, enabling accurate code assistance based on actual dependencies.

Podcast: Joël Quenneville and guest Jimmy Thigpen assesed AI workflows and limitations on The Bike Shed episode 469: How are we using AI? They look at AI blindspots, discuss their daily AI workflows, and pinpoint areas of improvement for AI agents in the future.

Update: David Heinemeier Hansson has added a markdown mime type and renderer to Rails. This should allow for Rails applications to easily provide context-specific markdown files and llms.txt files to agents. Mikkel Malmberg also shared on X/Twitter that his pull request to copy Rails error messages for coding agents has been merged. [h/t Jesse Waites]

Announcement: On a similar note, Vercel has published A proposal for inline LLM instructions in HTML based on llms.txt, proposing a new standard for embedding AI-specific instructions directly within HTML documents. This builds upon the existing llms.txt convention by allowing developers to include structured metadata and instructions that help Large Language Models better understand and interact with web content.

Release: Denis Sellu released the Brave Search Ruby Gem, a Ruby wrapper for Brave Search that includes AI-powered search summarization using the Brave native API. The gem provides an interface to access Brave's web, image, video, news, and local search functionality through their API.

Article: Josef Šimánek from Ruby Elders presented Our First Deep Dive into the RubyGems.org Ecosystem, a comprehensive analysis of the Ruby package ecosystem. To do so, Ruby Elders created an AI-powered tool to scan Github Actions workflow files for each gem, identifying testing gaps for current Ruby versions.

Video: Chad Fowler from Thoughtbot teams up with FrontrowMD's Chief Product Officer Yaser Mahmoud to explore whether ChatGPT Agent can effectively automate real-world QA processes in Automating QA with ChatGPT Agent. In Part 2: QA Automation with AI, Chad continues the investigation with Clarissa Borges, diving into alternative approaches including programmable options and screenshot-based methods to compare against the previous week's ChatGPT Agent workflow.

Tutorial: Melissa Pastore demonstrated How to use GitHub Copilot to level up your code reviews and pull requests. The post showcases how GitHub Copilot can streamline the code review process by generating detailed pull request summaries, explaining complex code changes, and suggesting improvements during reviews.

Article: Irina Nazarova from Evil Martians explores The Long Game: Why Rails Survived the Hype Cycle and What it Means for Your Startup. The article examines how Ruby on Rails has weathered technology trends and continues to be a viable choice for startups despite newer frameworks gaining attention. In the piece, Irina shares that Y Combinator partners recommend Rails for AI startups, and what that can teach us in the context of the AI hype cycle.

Events

Upcoming

August 21st - Meetup: Dresden.rb on August 21st in Dresden, Germany will have Hadi Al Qawas give a talk on Automatic generation of Ruby source code documentation with locally running LLMs.

August 21st - Meetup: The NWRUG (North West Ruby User Group) is hosting a meetup on August 21st in Manchester, United Kingdom and will feature a talk by Rahoul Baruah on Software Development with LLMs, explaining how to add LLMs to your apps, doing TDD, and writing code with AI.

August 26th - Meetup: The SF Ruby Meetup on August 26th at Github in San Francisco includes two Ruby AI speakers:

Miles Georgi: Tackling Domain Complexity with Foobara
Enrique Mogollán: What I've Learned Building an MCP Inspector in Ruby

August 27th - Meetup: The Ruby Ireland Meetup on August 27th at Intercom in Dublin, Ireland will host Declan McGrath for a demonstration on Radaica-DP - Boldly Build Without Any Gaps. In the talk, Declan will outline an AI-based approach to capturing and sustaining ideas in the software development cycle by leveraging modern AI tooling and communications to establish solid foundations for building software.

August 28th - Meetup: The Philippine Ruby User Group will meet on August 28th at Narra Labs in Quezon City, Philippines for discussions by Al Gray on FastMCP and other MCP gems, and Ray on fine tuning LLM integration and deployment with Rails 8 and Kamal.

September 4th - Conference: Rails World 2025 on September 4th and 5th in Amsterdam, Netherlands will have three Ruby AI presentations:

Kinsey Durham Grace: The Rise of the Agent: Rails in the AI Era
Paweł Strzałkowski: Make Rails AI-Ready by Design with the Model Context Protocol
Andrew Mcnamara & Charlie Lee: LLM Evaluations & Reinforcement Learning for Shopify Sidekick on Rails

September 10th - Conference: Friendly.rb on September 10th and 11th in Bucharest, Romania will host three Ruby AI presentations:

Obie Fernandez: Ruby+AI Tech Landscape 2025: A Survey
Chris Hasiński: Let’s fine-tune a modal!
Greg Molnar: Security in the age of AI

September 12th - Conference: RubyConf India on September 12th and 13th in Jaipur, India will include four Ruby AI themed presentations, including:

Deepan Kumar: AI at Runtime: Teaching Your Ruby App to Fix Itself
Prathamesh Sonpatki: Teaching AI to Debug Your Rails Apps (So You Can Actually Sleep)
Vishwatjeetsingh Desurkar: What if… Ruby Led the AI Revolution?
Vlad Dyachenko: AI Best Practices: Understanding MCP’s Security Footprint and Managing Overpowered “Friendly Interns”

September 18th - Conference: The EuRuKo (European Ruby Conference) on September 18th and 19th in Viana do Castelo, Portugal has announced seven Ruby AI & Hardware related speakers:

Obie Fernandez: Roasting Code for Fun & Profit with Structured AI Workflows
Paweł Strzałkowski: Making Rails AI-Native with the Model Context Protocol
Carmine Paolino: RubyLLM: Making AI Development Beautiful Again
Lucian Ghinda: Don't Let Your AI Guess: Teach It to Test!
Ivan Nemytchenko: Slingshot Development: Vibe Coding with Ruby Done Right
Albert Pazderin: Building interactive Ruby gem tutorials with Wasm
Hitoshi Hasumi: PicoRuby Hands-on: Internet of Things Edition

October 6th - Conference: The Rocky Mountain Ruby Conference on October 6th and 7th in Boulder, Colorado will host three Ruby AI speakers:

Vlad Dyachenko: Prompt Driven Development (PDD) or the Art of Prompting
Scott Werner: We Were Voyagers. We Can Voyage Again!
Christine Seeman: Thoughtful AI for the Rubyist

Open Source Updates

Code Spotlight

Samad Ahmed is back in the code spotlight with a new gem that categorizes transactions with RubyLLM. The repository contains a real world example of how to use RubyLLM to process transactions with a schema, categorize them by their descriptions, look up the General Ledger code for each category using a RubyLLM tool, and export the results to a CSV file.

GitHub - sahmed007/ruby-categorize-transactions

A practical real-world example of categorizing transactions with AI using Ruby - sahmed007/ruby-categorize-transactions

github.com/sahmed007/ruby-categorize-transactions

New Gems

Links to the RubyGems page, newest releases are first:

zirp - Powerful release notes and notification tool

clusterkit - High-performance clustering and dimensionality reduction for Ruby

deepagents - Deep agent with sub-agent spawning, todo list capabilities, and mock file system for Ruby

llm_translate - AI-powered Markdown translator

ccexport - Export and preview Claude Code conversations with syntax highlighting

langgraphrb_rails - Rails integration for the langgraph_rb gem

swagger_mcp_tool - MCP server for Swagger/OpenAPI specifications

raix-bedrock - AWS Bedrock provider for Raix.

claude_hooks - Ruby DSL for creating Claude Code hooks

poml - Ruby implementation of POML (Prompt Oriented Markup Language)

sorbet-baml - Convert Sorbet types to BAML type definitions for LLM prompting

promptly - Opinionated Rails integration for reusable AI prompt templates

aidp - A CLI for AI-driven software development, from analysis to execution

genai-rb - Gemini module for ruby

gpt - API client for GPT-5 (Responses API)

vsm - Async, recursive agent framework with capsules, tools-as-capsules, streaming tool calls, and observability

code_to_query - Natural language to safe, parameterized SQL for Rails

ruby_llm_community - Single API for GPT, Claude, Gemini, and with integrated community additions

code_healer - AI-powered code healing and self-repair system for Ruby applications

rcrewai-rails - Rails integration for RcrewAI - Build AI agent crews with database persistence and web UI

context_spook - Collects project context for AI

one-mentor-ruby - An API client for 1Mentor

rb-utcp - Universal Tool Calling Protocol

rcrewai - Build intelligent AI agent crews in Ruby - CrewAI implementation with multi-LLM support

langsmithrb_rails - Rails integration for LangSmith tracing and monitoring

langsmithrb - Client for LangSmith - LLM observability and evaluation platform

ColorPHMetric - Gem for evaluating colors based on their identifiers

attio-rails - Rails integration for the Attio API client

attio - Ruby client for the Attio API

WanderAndWant - Checks for wandering, wanting, searching, and other game states

ragie_ruby_sdk - Ragie API Ruby Gem

ruby_scientist_and_graphics - Ruby data science toolkit: lightweight DataFrame, cleaning, stats, plotting, simple ML, and project save/load

monogoto_api - Unofficial Ruby gem for Monogoto API

SelfModifiedDecisionTree - Aims to remove vulnerable functionalities like data marshalling to prevent certain types of attacks.

Communemashin - Gapetto Broad AI suites

annembed-ruby - High-performance dimensionality reduction for Ruby

elelem - A REPL for Ollama

pgai_rails - Ruby on Rails integration for TimescaleDB's pgai PostgreSQL extension

airb - CLI-based programming agent for Ruby with VSM architecture

top_secret - Filter sensitive information from free text

my_math_gem - Module for mathematical analysis, including calculus, linear algebra, statistics, data processing, ODE solutions, optimization, complex numbers, and Fourier transformations

New Open Source

Links to the Github repository:

AI Associate Investment Evaluation System - AI-powered investment analysis and deal flow management system for venture capital operations

AiMemory - Intelligent memory management system for AI chat applications with vector database support

ChainFetch - AI Powered Ethereum Intelligence API

Discourse AI Replier - Discourse plugin that automatically generates AI replies to forum topics to increase community engagement

AI Recruiting System - AI recruiting system powered by RubyLLM for intelligent resume analysis and candidate screening

NeonTitans - A cyberpunk-mecha-kaiju TTRPG powered by autonomous AI agents

RoR KIA AI - A model-agnostic RAG System to enhance AI model capabilities by integrating retrieval mechanisms

Workato Connector for Mistral AI - Integration of Mistral AI's advanced language model and document processing capabilities into your automation workflows

Expert Enigma - Local-first MCP server for Ruby repositories using Graph Neural Networks to provide coding agents with a structural understanding of code

Git Commit CLI - An intelligent Git commit message generator powered by AI

Inception Serve & Inception MCP - Provides remote desktop functionality for headless Chrome browsers using Chrome DevTools Protocol and Ferrum

Jobs & Opportunities

Featured

LEA uses AI-powered workflow automation for wealth management and is looking for a Founding Forward-Deployed Engineer. LEA extracts structured data from financial documents and automates workflows - handling everything from document organization to pushing clean data into CRMs and planning tools - so wealth management firms can build end-to-end client experiences without building parsing and workflow infrastructure. This is a leading opportunity to architect cutting-edge solutions with Ruby AI and the default Rails stack. LEA co-founder and CTO Chuck Blake recently presented at ArtificialRuby on his Ruby AI workflow using Command Center, an AI-driven documentation system.

Multiple

Onsite - Vietnam - RAKSUL Vietnam operates an online printing marketplace connecting businesses with printing partners, 4 OPEN POSITIONS, including:

Principle Engineer
Technical Lead
Senior Backend Engineer
Backend Engineer

Remote - Cloudwalk builds blockchain-based payment technology and financial services for merchants, 3 OPEN POSITIONS, including:

Remote - CompanyCam provides photo documentation software for contractors to organize job site images, 3 OPEN POSITIONS, including:

Ruby on Rails Developer
Fullstack Engineer
Senior Engineering Manager

Onsite - Spain / Georgia - Workato is an enterprise automation and integration platform unifying AI, apps, and workflows for businesses, 2 OPEN POSITIONS, including:

Remote - Rivo provides loyalty, rewards, and referral programs for Shopify stores, 2 OPEN POSITIONS, including:

Remote

.txt make LLMs speak the language of every application: Founding DevRel Engineer

Alignerr connects AI teams with expert data labelers through Labelbox's talent marketplace: Software Engineer, Ruby - AI Training

Calimala.ai matches tech talent with remote startup jobs using AI-powered recruiting: Full Stack Ruby on Rails Developer

Doximity is a professional network for doctors and healthcare clinicians: Software Engineer, Full Stack (Ruby/Rails)

GlossGenius is a salon and spa management software for booking, payments, and marketing: Software Engineer - All Levels

Housecall Pro provides field service management software for home service businesses: Senior Staff Ruby Software Engineer

Mindoula is a tech-enabled population health company delivering 24/7 behavioral healthcare and support services: Healthcare AI Engineer

Open Core Ventures funds and builds commercial companies around open source projects: AI Automation Developer

Profile.com builds intelligent search systems and recruiting tools powered by AI: Senior Rails Engineer

Reveal Technology is a defense tech company providing AI-powered 3D mapping and situational awareness tools: Full Stack Engineer: Command & Control Artificial Intelligence

Hybrid

San Diego - Lawmatics provides CRM and marketing automation software specifically for law firms: Full Stack Developer

Onsite

Atlanta / Toronto - PagerDuty is a digital operations platform for incident management and IT alerts: Staff Engineer – Ops Cloud Platform - Ruby on Rails

San Francisco - LevelPath is an AI-native procurement platform making enterprise purchasing delightful and efficient: Software Engineer / Ruby on Rails/ Back-end

India - Nagarro is a global digital engineering consultancy delivering AI-powered transformation: Associate Staff Engineer, Ruby on Rails

Romania - WeTravel is a booking and payment platform for multi-day group travel businesses and tour operators: AI Engineer

United Kingdom - Sage provides business software for accounting, payroll, and HR: Ruby on Rails Developer

Freelance

Remote - Upwork recruiter:

One Last Thing

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News: The Sequel - August 6th, 2025

Matt Solt — Thu, 07 Aug 2025 21:50:17 +0000

The second part to the August 6th edition of Ruby AI News features additional content updates, events, new Ruby AI open source, and over 150 new career opportunities.

You can catch the first part here:

Ruby AI News - August 6th, 202

First-class prompt engineering support for Ruby is here

rubyai.beehiiv.com/p/ruby-ai-news-august-6th-202-7f886bdcaeb26efb

Pro tip: Due to the size of the newsletter, many email clients truncate the content. It is recommended to read on the web for the best experience.

Additional Content
Events
- Previous
- Upcoming
Open Source Updates
Jobs & Opportunities
One Last Thing

Additional Content

Launch: OpenAI unveiled GPT-5 and the new era of work, introducing their next-generation AI model designed to transform workplace productivity and collaboration. GPT-5 represents a significant leap forward in reasoning capabilities, offering enhanced performance across complex problem-solving tasks while maintaining improved safety and alignment features. The model introduces new multimodal capabilities that allow seamless integration of text, images, and other data types, enabling more sophisticated workplace applications from code generation to document analysis. OpenAI positions GPT-5 as a foundational tool for the future of work, emphasizing its potential to augment human capabilities rather than replace workers, with early access rolling out to enterprise customers and developers through their API platform.

Kieran Klaassen provided an early review of the model:

https://x.com/danshipper/status/1953505929733001286

Launch: Coinciding with the launch of OpenAI’s GTP-5 model, Cursor has released the Cursor CLI, a command-line interface that brings AI-powered editing capabilities directly to the terminal. The CLI allows developers to use natural language commands to perform code operations like refactoring, bug fixes, and feature implementations across multiple files without leaving the command line. Key features include the ability to apply changes with confirmation prompts, work with specific file patterns, and maintain conversation context for iterative development tasks.

Podcast: In case you didn’t catch the live stream, Valentino Stoll and Joe Leo hosted Chad Fowler on the The Ruby AI Podcast for Rails After the Robots: Chad Fowler on AI as the Next Abstraction and the video recoding is now available. The panel discussed treating GenAI as an abstraction rather than magic, covering architecture for machine-written code, designing clear interfaces, and how legacy Rails applications can evolve in an LLM world.

Update: Carmine Paolino shipped a new Agentic Workflows guide for RubyLLM, covering practical patterns like Model Routers, RAG with pgvector, and Parallel Agents with Async in elegant Ruby code. The guide demonstrates real-world implementations you can use in your RubyLLM applications. Additionally, the upcoming RubyLLM release introduces Halting Tool Continuation, allowing tools to stop the conversation when appropriate, such as when a sub-agent handles a request or a file is saved, eliminating unnecessary LLM explanations and saving tokens.

Announcement: Tobi Lutke revealed Shopify has developed MCP UI, an extension of the Model Context Protocol that enables AI agents to deliver fully interactive UI components alongside text responses, solving the challenge of providing rich visual experiences in commerce applications where product images, color swatches, and size selectors are essential. The protocol supports three delivery methods (inline HTML, remote resources, and remote DOM) and uses an intent-based messaging system that allows components to communicate user actions back to the agent while maintaining agent control over state changes. This open-source solution enables MCP servers to return embedded UI resources that can be styled to match host environments and handle complex commerce scenarios like variant selection, bundles, and real-time inventory updates. You can explore the MCP UI Server prototype and check out the MCP UI specification to learn more about the implementation.

Launch: José Valim announced that Tidewave Web for Rails and Phoenix is launching soon. Tidewave is described as a tool to speed up development with AI assistants that understand your web application, how it runs, and what it delivers. Developers interested in early access can visit the website, join their Discord community, or sign up for the waiting list to be among the first to try this new framework when it becomes available.

Article: Rob Zolkos conducted a practical comparison between Claude Sonnet and Claude Opus in Two Days. Two Models. One Surprise: Claude Code Under Limits. Testing both models on the same Ruby coding task, building a command-line tool to process CSV files, he discovered that Sonnet consistently produced more concise, efficient code while Opus generated verbose solutions with unnecessary complexity. The surprise came when Sonnet not only delivered cleaner implementations but also required fewer iterations to reach a working solution, challenging assumptions about the relationship between model size and code quality.

Opinion: Justin Searls argues that AI tools fundamentally change how developers work by promoting individual productivity over team collaboration in There is No AI in Team. He observes that while AI coding assistants excel at helping individual developers write code faster, they struggle with collaborative practices like pair programming, code reviews, and team discussions that have traditionally been central to software development.

Tips: Jankees van Woezik shared a Claude agent for writing RSpec tests in the spirit of Thoughtbot.

Events

ArtificialRuby: The July 16th ArtificialRuby meetup featured three Ruby AI speakers:

Amanda Bizzinotto: Building a multi agent system in Rails
Sameen Karim: Auto documenting your analytics setup with AI
Patrick Karsh: From Senior Rails Engineer to Startup Builder with Rails and AI

RailsConf: RailsConf from July 8th-10th uploaded all the videos from the event, and many featured or discussed Ruby and AI:

Jake Gribschaw & Justin Wienckowski: Chime Presents: Getting More Out of LLMs for Ruby Developers
Vladimir Dementyev & Albert Pazderin: The future of Rails begins in the browser
Irina Nazarova: Startups on Rails in Past, Present and Future
Joe Leo: Silent Killers: Lessons from the Brink
Brooke Kuhlmann: Terminus - BYOS for TRMNL displays
Tia Anderson: Peace, Love, and CRUD - A Rails Journey to Calm
Justin Bowen: Active Agents - Build AI in Rails
Elise Shaffer & David Heinemeier Hansson: Fireside Chat With David Heinemeier Hansson

ChicagoRuby: Miles Georgi’s talk from the August ChicagoRuby meetup is now available: Introducing Foobara! - Wrangle Domain Complexity with Foobara.

Upcoming

August 9th - Conference: RubyConf Taiwan on August 9th and 10th in Taipei City, Taiwan will include 5 speakers on Ruby Hardware and AI topics:

Hitoshi Hasumi: Well, PicoRuby Can Do That
Kazuaki Tanaka: From Scripts to Circuits: IoT Applications with mruby/c
Hayao Kimuru: RISC-V CPU emulator made with Ruby
Etrex Kuo: Ruby - MCP Server
Aotoki Tsuruya: Crafting AI-Friendly Application in Ruby

August 13th - Meetup: ArtificialRuby is hosting a meetup at Betaworks in New York City on August 13th. If you are interested in presenting at an ArtificialRuby meetup, please fill out this form and let them know. Don’t forget to say hello if you’ll be in attendance! Two talks announced so far include:

Chuck Blake: Commanding AI: Automating Docs, Reviews & Reports in Rails
Chase Stevens: The Rubber Duck That Quacks Back - How to use AI Models to Enhance your Learning and Productivity

August 21st - Meetup: Dresden.rb on August 21st in Dresden, Germany will have Hadi Al Qawas give a talk on Automatic generation of Ruby source code documentation with locally running LLMs.

September 4th - Conference: Rails World 2025 on September 4th and 5th in Amsterdam, Netherlands will have three Ruby AI presentations:

Andrew Mcnamara & Charlie Lee: LLM Evaluations & Reinforcement Learning for Shopify Sidekick on Rails
Kinsey Durham Grace: The Rise of the Agent: Rails in the AI Era
Paweł Strzałkowski: Make Rails AI-Ready by Design with the Model Context Protocol

September 6th - Conference: XORuby on September 6th in Chicago will feature a talk by Scott Werner, the founder of Sublayer and ArtificialRuby, on experimentation and play with Ruby and AI.

September 10th - Conference: Friendly.rb on September 10th and 11th in Bucharest, Romania will host two Ruby AI presentations:

Obie Fernandez: Ruby+AI Tech Landscape 2025: A Survey
Chris Hasiński: Let’s fine-tune a modal!

September 18th - Conference: The EuRuKo (European Ruby Conference) on September 18th and 19th in Viana do Castelo, Portugal has announced seven Ruby AI & Hardware related speakers:

Obie Fernandez: Roasting Code for Fun & Profit with Structured AI Workflows
Paweł Strzałkowski: Making Rails AI-Native with the Model Context Protocol
Carmine Paolino: RubyLLM: Making AI Development Beautiful Again
Lucian Ghinda: Don't Let Your AI Guess: Teach It to Test!
Ivan Nemytchenko: Slingshot Development: Vibe Coding with Ruby Done Right
Albert Pazderin: Building interactive Ruby gem tutorials with Wasm
Hitoshi Hasumi: PicoRuby Hands-on: Internet of Things Edition

Open Source Updates

Code Spotlight

Samad Ahmed built a real-world example that shows how you can use RubyLLM to process a set of documents and generate structured outputs along with enriched data, ready for CSV export. The example uses the new RubyLLM::Schema capabilities from Daniel Friis to process data points from legal contracts.

GitHub - sahmed007/ruby-contract-risk-analysis

A practical real-world example of automating contract processing with AI using Ruby

github.com/sahmed007/ruby-contract-risk-analysis

New Gems

Links to the RubyGems page, newest releases are first:

ColorScience - Package for doing color science

prescient - Prescient AI provider abstraction for Ruby applications

sidekiq-mcp - Sidekiq MCP server plugin for LLM integration

ruby_llm-code - AI-powered coding assistant for Ruby (coming soon)

llm_gateway - A Ruby gateway for LLM APIs with unified interface for Claude, OpenAI, and Groq

parabot - AI-powered Test-Driven Development parallel assistant with tmux integration

outhad-integrations - Integration suite for open source reverse ETL platform

estapar_zul_prompter - Um construtor de prompts para gerar imagens de marca para Estapar e Zul+.

openai-toolable - A Ruby gem that extends the OpenAI SDK to support function calling

j_r_r_token - Ruby wrapper for the tiktoken Rust library, providing fast tokenization for OpenAI models

soka-rails - Rails integration for Soka AI Agent Framework

neural - Deep Learning, the Ruby way

prompt_schema - Generate prompt schemas for LLMs to get and check structured data.

mcp-on-rails - MCP (Model Context Protocol) configuration and prompts for Rails projects

nextbillionai - Ruby library to access the Nextbillion SDK API

tsikol - Ruby framework for building Model Context Protocol (MCP) servers

nachamcp - MCP Server to parse ACH records into json or markdown

attio-ruby - Ruby client library for the Attio API

langgraph_rb - A Ruby library for building stateful, multi-actor applications with directed graphs

tuya_iot_lights - A Ruby gem for controlling Tuya IoT smart lights

soka - A Ruby ReAct Agent Framework with multi-LLM support

ragdoll-rails - Rails engine for Ragdoll RAG system

tabscanner - Ruby gem for processing receipt images using the Tabscanner API

ragdoll-cli - Multi-Modal Retrieval Augmented Generation for the CLI

sus-fixtures-agent-context - Test fixtures for running in Async

llms-tool - Ruby library for creating LLM tools with a simple DSL

modal-rb - Interact with modal from your Ruby code

lancelot - Ruby bindings for Lance - a modern columnar data format for ML

llms - Ruby library for using LLM APIs across multiple providers

prompt_engine - Rails mountable engine for AI prompt management

ai_summary - Generate a structured summary of your Rails codebase for AI-assisted workflows

intelligent - Add intelligent to your Ruby engine

prompt_warden - Record, audit, and guard AI prompt usage with automatic SDK instrumentation.

algoruby - Algorithmic patterns, including classics like Two Sum, K-Sum, Sliding Window, Binary Search

turbopuffer-ruby - Ruby library to access the Turbopuffer API

New Open Source

Links to the Github repository:

KopsAI - an intelligent operations agent that helps DevOps engineers automate daily tasks

Autotest IA - uses AI to automatically generate relevant tests, maintain code coverage and improve the quality of your projects

ai_email_categorization - fetches emails from gmail, then uses AI to sort them into user-defined categories and summarize them

AI Multilingual Diet Analysis Assistant - AI-powered multilingual diet analysis assistant that helps users analyze food calories in multiple languages

Tarot Agent - provides insightful tarot readings with AI-powered interpretations

Overskill - AI-powered app marketplace platform that enables anyone to create, deploy, and monetize applications without coding

SmartRails - CLI tool for Ruby on Rails applications that provides comprehensive auditing, monitoring, and maintenance capabilities

AI Tutor Learning Platform - AI-powered learning platform built with Ruby on Rails that provides personalized learning experiences with interactive tasks

Accountable To - help users achieve their goals through intelligent accountability systems

SoundScape - Rails REST API with AI-powered music search using Google Gemini

PrescientChat - AI-powered chat application demonstrating the Prescient gem's capabilities with provider fallback mechanisms

Jobs & Opportunities

Multiple

Remote - Upstart provides AI-powered lending platform for personal loans and refinancing: 14 OPEN POSITIONS, including:

Software Engineer, Marketing Platform
Software Engineer, Capital Insights
Senior Software Engineer, API Enablement
Software Engineer, Consumer Platform
Software Engineer, Revenue Science

Onsite / UK / Portugal / Spain / Poland - Cleo is an AI financial assistant helping users budget and save: 13 OPEN POSITIONS, including:

Staff Product Engineer - Ruby
Senior Product Engineer - Ruby
Product Engineer - Ruby
Senior Engineering Manager

Hybrid - Gusto provides payroll, benefits, and HR software for small businesses: 13 OPEN POSITIONS, including:

Sr Staff Software Engineer, Entity Management
Staff Machine Learning Engineer - Platform
Senior Staff Engineer- Platform
Senior Software Engineer, Product
Staff Software Engineer

Onsite / Virginia - Steampunk delivers technology modernization solutions for federal government clients: 11 OPEN POSITIONS, including:

AI Transformation Lead
DevSecOps Engineer
Cloud Architect
Software Developer
Technical Writer

Remote - Fullscript provides supplement dispensing and lab testing platform for healthcare providers: 10 OPEN POSITIONS, including:

Intermediate Back End(Ruby) Developer – 12 Months Contract
Senior Developer, Back End(Ruby) – Discovery
Senior Developer, Fullstack (Ruby & React)
Senior Software Developer – Lab Integrations
Intermediate Fullstack Developer (Ruby & React)- EHR

Hybrid / Ohio - McKesson distributes pharmaceuticals and medical supplies across North American healthcare: 8 OPEN POSITIONS, including:

Sr. Software Developer/Engineer - Ruby on Rails
Staff Software Developer
Software Engineer - Security
Software Engineer
Sr. Associate Site Reliability Engineer

Onsite / India - Coupa provides AI-powered business spend management software for enterprises: 7 OPEN POSITIONS, including:

Lead Software Engineer - Ruby on Rails
Sr. Principal Software Engineer (Analytics)
Lead Software Engineer, Cloud - Ruby
Principal Software Engineer
Sr. Lead Software Engineer, Ruby on Rails

Remote / Azerbaijan / Ireland / Armenia / Poland - Grid Dynamics provides digital engineering services for enterprise transformation: 7 OPEN POSITIONS, including:

Senior Ruby On Rails Developer
Senior / Lead Ruby on Rails Engineer

Remote - Healthie provides practice management and EHR software for health and wellness providers: 6 OPEN POSITIONS, including:

Staff Engineer, AI (Ruby/Full Stack)
Senior Data Engineer (Ruby)
Senior API Software Engineer
Senior Engineer, App Security
Senior Software Engineer (Ruby/Full-Stack)

Remote / Onsite / India - Weekday automates tech recruiting with AI-powered candidate sourcing and outreach: 6 OPEN POSITIONS, including:

Ruby on Rails Developer
Senior Software Engineer
Backend engineer
Freelance Engineer
Staff Software Engineer

Remote - GrowthX delivers AI-powered growth marketing and content production services: 5 OPEN POSITIONS, including:

Full Stack Engineer (Product focus)

Remote - Kajabi helps creators build online businesses with courses and digital products: 4 OPEN POSITIONS, including:

Senior Engineer, Commerce
Senior Software Engineer, API
Senior Software Engineer, Communities
Senior Software Engineer, Growth

Onsite / Malaysia / Australia - SEEK recruiter: 4 OPEN POSITIONS, including:

Senior Engineer - Ruby on Rails

Remote - SerpAPI provides real-time Google search results API with global location support: 4 OPEN POSITIONS, including:

Ruby Developer Advocate
Senior Fullstack Engineer
Junior Fullstack Engineer
Customer Success Engineer

Hybrid / Colorado / Columbia - Recurly provides subscription management and recurring billing platform software: 4 OPEN POSITIONS, including:

Principal Engineer (AI)
Senior Full-Stack Engineer, Engage
Senior Software Engineer, Platform Engineering
Senior Software Engineer, Ruby on Rails

Onsite / Remote - Scribd is a digital library sharing documents and written content: 3 OPEN POSITIONS, including:

Senior Software Engineer (Ruby on Rails - Growth Team)
Senior Software Engineer (Ruby on Rails - Identity)
Software Engineer II, Devloper Tooling

Remote / Barcelona / Boston - Yuma AI automates customer service agents for ecommerce brands: 3 OPEN POSITIONS, including:

AI Product Focused - Senior Full-stack - Rails Engineer (Europe)
AI Product Focused - Senior Full-stack / Rails Engineer (Boston, US)
AI Solution Engineer - Full-stack - Rails Engineer (Barcelona, Spain)

Remote - Arkestro uses AI to accelerate enterprise procurement negotiations and savings: 2 OPEN POSITIONS, including:

Staff Full Stack Software Engineer
Fullstack Software Engineer (III)

Remote - Beam helps homeless people find jobs through crowdfunded employment training: 2 OPEN POSITIONS, including:

Lead Product Engineer
Senior Product Engineer

Remote - Prevail AI delivers secure court reporting and legal transcription technology: 2 OPEN POSITIONS, including:

Mid-Level Full Stack Developer (Ruby on Rails)
Senior Full Stack Developer (Ruby on Rails)

Remote - SonderMind connects patients with therapists for online and in-person mental healthcare: 2 OPEN POSITIONS, including:

Staff Full Stack AI Engineer
Staff, Full Stack Engineer

Remote - ThriveCart provides e-commerce checkout pages and sales funnel software: 2 OPEN POSITIONS, including:

Engineering Lead - PiktoChart
Full-Stack Ruby on Rails Developer - Piktochart

Remote - Zeroheight creates documentation platforms for design systems and development teams: 2 OPEN POSITIONS, including:

Full Stack Product Engineer
Senior Full Stack Product Engineer

Remote

Dope Marketing automates direct mail campaigns for home service businesses: Software Engineer (Rails + React, Level 2–3)

Doximity is a professional network for doctors and healthcare clinicians: Senior Software Engineer, Full Stack (Ruby/Rails)

EverAI creates conversational AI for roleplay, gaming, and creative writing: Ruby-on-Rails Engineer

Freshly Commerce builds Shopify apps for bundling, inventory tracking, and fulfillment: Senior Full-Stack Product Developer (Ruby on Rails + React)

Hamnavoe Partners offers fractional CTO services and Ruby on Rails development: Full-Stack Ruby on Rails Engineer

Jitera automates software development lifecycle with AI-powered code generation and documentation: Senior Software Engineer (Ruby on Rails)

Saeloun provides Ruby on Rails and React development consulting services: Senior Ruby on Rails Developer

Skylight makes digital photo frames and smart family calendar displays: Full Stack Software Engineer, AI Features

Strider recruiter: Mid/Senior Full-stack Engineer - React.js, Ruby on Rails - Healthcare market

Treasure Data provides AI-powered customer data platform for enterprise personalization: Staff Software Engineer - Real Time Engine

UX Direct Global recruiter: Ruby on Rails Developer (v7+) – Chat & AI Integration

Vendis AI builds AI-powered CRM that converts conversations into sales pipelines: Senior Ruby on  Rails Developer

WorkWave delivers service management software for field service businesses: Senior Software Engineer

Hybrid

London - Butternut Box delivers fresh, personalized dog food directly to homes: Senior Software Engineer: GenAI Team

Onsite

Denver - Caribou helps drivers refinance auto loans to reduce monthly payments: Senior Software Engineer - Full Stack, Ruby on Rails

South Carolina - Speed AI monitors law firm intake calls to rescue lost leads: Ruby on Rails Developer

India - G2 operates a software review marketplace where businesses research and compare products: AI Software Engineer

United Kingdom - Dexory uses autonomous robots to digitize warehouse inventory in real-time: Senior Full Stack (Ruby on Rails) Engineer

Freelance

Remote - Upwork recruiter:

One Last Thing

TRMNL introduced TRMNL X, a larger 9.7-inch e-ink display that builds on their original dashboard concept. TRMNL X maintains the same plugin ecosystem as the original 2.9-inch model, allowing Rubyists to build or port applications for the new display with Terminus.

TRMNL

Who, what, when, why, and how.

usetrmnl.com/blog/introducing-trmnl-x

That’s all for this edition! Be sure to reach out if you have any stories, content, jobs, or events you want featured in the newsletter.

Ruby AI News - August 6th, 2025

Matt Solt — Wed, 06 Aug 2025 12:00:00 +0000

Welcome to (the first part of) the 12th edition of Ruby AI News! This edition features a new prompt engineering solution for Rails, a site tailored specifically for Ruby language LLM benchmarks, RubyLLM shipping updates like crazy, and much more… very soon.

Newsletter update: (Part 2 is now available) This edition is split into two parts. Part 2 comes out tomorrow, and its just as packed with events, career opportunities, and open source updates. It is a lot of content, but this is an awesome problem to have. I’m so excited that there is this much to share. Rubyists are embracing AI and the pace of development in the ecosystem is increasing every week. Keep building and let me know what you’re working on. I’ll try not to make any more two part editions, I think in the fall the newsletter will be an every week release. What do you think? Should I make the newsletter a weekly edition? Did you work on something awesome that I missed? Let me know: matt@roboruby.com

Pro tip: Due to the size of the newsletter, many email clients truncate the content. It is recommended to read on the web for the best experience.

Top Stories
Content

Content

Announcement: Dewayne VanHoozer launched a new documentation site for Ragdoll, an advanced multi-modal document intelligence platform built on ActiveRecord with PostgreSQL and pgvector. Ragdoll is a Ruby gem that provides sophisticated document processing capabilities, leveraging vector embeddings for intelligent document analysis and retrieval. The platform integrates seamlessly with Rails applications through ActiveRecord, making it easy for Ruby developers to add document intelligence features to their projects. The ragdoll source code is available on GitHub.

Tutorial: Amanda Bizzinotto of OmbuLabs explains how to build autonomous AI agents in AI Agents: Implementing the ReAct Pattern in Ruby. The ReAct (Reasoning and Acting) pattern combines large language model reasoning with tool-based actions, allowing agents to think through problems step-by-step while taking concrete actions to gather information or modify their environment. Amanda details building a Ruby implementation that can handle multi-step reasoning tasks, demonstrating how to structure the agent's thought process, action selection, and observation handling.

Article: Vicente Reig demonstrated building AI agents in Rails with the DSPy.rb framework, a Ruby port of Stanford's DSPy for creating structured LLM applications. DSPy.rb brings structured prompting, automatic optimization, and type safety to Ruby developers building AI-powered applications. The DSPy.rb examples repository showcases practical implementations including: prediction, chain of thought, agents with tool calling, mulit-stage pipelines, and data extraction patterns. Over the past two weeks, Vicente has published detailed guides covering the Raw Chat API for Benchmarking and Migration, explained How DSPy.rb Extracts JSON from Every LLM for reliable structured outputs, and showed how to Run LLMs Locally With Ollama And Type Safe Ruby for cost-effective development.

Tutorial: Exequiel Rozas walked through Adding an MCP Server to a Rails App, demoing how to integrate the Model Context Protocol (MCP) into a Rails application. The tutorial shows how to create an MCP server that exposes Rails models and data to AI assistants like Claude, enabling them to read and manipulate application data through structured tools. Exequiel provides step-by-step instructions for setting up the fast-mcp gem, defining tools for database operations, and configuring the connection between Claude Desktop and the Rails app. The implementation allows AI assistants to perform complex queries and data analysis directly on your Rails application's database.

Documentation: Chatwoot launched a new documentation site for AI Agents, a library built on top of RubyLLM for building sophisticated multi-agent AI workflows. AI Agents has powerful features including multi-agent orchestration, agent handoffs, tool integration, callbacks, shared context, and a thread-safe architecture. The docs cover installation, configuration, and examples for building everything from simple chatbots to complex multi-agent systems, with the ai-agents source code available on GitHub.

Tutorial: Wilbur Suero talked through How I Built a RAG System in Rails Using Nomic Embeddings and OpenAI. The tutorial covers setting up document embeddings using Nomic's text-embedding models, storing vectors in a PostgreSQL database with the pgvector extension, and implementing semantic search to find relevant documents. Wilbur demonstrates how to integrate OpenAI's models to generate responses based on retrieved context, creating a complete RAG pipeline that can answer questions about uploaded documents with proper source attribution.

Video: Justin Bowen demonstrated Active Agent in a pairing session with Adrian Marin of AvoHQ. Active Agent (AI Rails Framework) Demo / Pairing - Let's Build Your First Agent in Ruby on Rails! showcases how to build AI-powered Rails applications using Active Agent, a Rails-native framework for building AI features. The demo provides a how-to for structuring prompts, using tool calls, and integrating LLMs.

Announcement: Justin also revealed that Active Agent will introduce structured outputs in version 0.5.0 in this X/Twitter post. The documentation shows that agents will support structured output formats, allowing developers to define schemas for consistent data extraction results.

Article: Leo Trieu of RoR Wizards published Master LLM Performance: Your Complete Guide to Monitoring Token Usage, Latency, and Costs in Ruby on Rails. The article covers monitoring strategies including tracking token consumption, measuring API response times, and calculating operational costs across different LLM providers. Leo provides practical examples for implementing custom monitoring solutions, setting up alerts for cost thresholds, and optimizing performance through techniques like prompt engineering and response caching.

Video: Cezar Halmagean from Mix & Go recorded a video on implementing Rails LLM Monitoring: Track Costs, Latency & Token Usage. The tutorial covers tracking metrics like API costs, response latency, and token usage for AI-powered features, helping optimize performance and manage expenses. The previous video, How to Build an AI Sales Agent With Ruby on Rails, and accompanying sales_agent source code provide a practical implementation that includes monitoring capabilities for an AI sales agent, complete with database schemas for storing conversation data and performance metrics.

Tutorial: Vibe debugging is here! Paweł Urbanek wrote about Using LLMs and MCP to Debug PostgreSQL Performance in Rails. The tutorial introduces rails-pg-extras-mcp, an MCP server that provides access to PostgreSQL diagnostic queries and includes built-in EXPLAIN ANALYZE support for query performance analysis. By connecting this tool to Claude Desktop, developers can interact with their database using natural language queries, automatically generate performance diagnostics, and receive AI-powered insights about slow queries, index usage, and database optimization opportunities.

Video: David Kimura of Drifting Ruby explored the Model Context Protocol, an open standard for connecting AI assistants to external data sources. The episode demonstrates how to implement MCP using Ruby to create a server that provides AI models with access to databases, APIs, and other resources, showing how this protocol bridges the gap between AI models and real-world data. The episode source code is available on GitHub.

Launch: Daniel Rodriguez from LightningRails launched the LightningRails Starter Kit with AI Chatbot Integrations. The starter kit includes pre-built integrations with popular AI services, along with a complete chat interface, message history management, and user authentication. The solution features a responsive chat UI built with Stimulus and Turbo, real-time message streaming, conversation persistence, and role-based access controls, making it easier to add AI chatbot functionality.

Announcement: Chris Petersen released Red Candle - Run LLMs Natively in Ruby with Rust, a Ruby gem that enables running large language models locally without external API dependencies. Built on top of the Candle machine learning framework in Rust, the gem supports GPU acceleration and provides a simple Ruby interface for loading and running popular models like Qwen, Llama, and Phi. The red-candle source code shows examples of text generation and demonstrates how to integrate LLM capabilities directly into applications with just a few lines of code.

Article: Abdelkader Boudih shared The Raw, Frustrating Journey Behind Rails Lens: A Decade of Code Rage, AI Sparks, and Finally Breaking Free. The post introduces Rails Lens, an intelligent model annotations and ERD generation for Rails applications with database-specific adapters, multi-database support, and advanced code analysis that helps LLMs get much better context when working with your application. The rails_lens source code is available on GitHub with installation and annotation instructions. ICYMI, Abdelkader, an amazing contributor to the Ruby AI ecosystem, is having a rough go with AWS, as they recently deleted his account and data without warning.

Opinion: Stan Lo argued that AI Coding Agents Are Removing Programming Language Barriers by making it easier for developers to work across different languages without deep expertise. He demonstrates this with his experience using Cursor AI to work on a Go project despite being primarily a Ruby developer, showing how AI can handle language-specific syntax, conventions, and tooling. Stan suggests this shift means developers can focus more on problem-solving and system design rather than memorizing language specifics, though he notes that understanding fundamental programming concepts remains crucial.

Article: Todd Price of Reinteractive explored how to Supercharge Your Rails AI Chat with Custom Tools, building on his previous tutorial about creating AI chatbots in Rails. Todd demonstrates how to extend basic chat functionality by implementing custom tools that allow AI assistants to perform specific actions like searching databases, making API calls, or executing business logic. The tutorial includes practical examples of building tools for weather lookups and database searches, complete with ActionCable and Turbo Streams for responses and interactivity.

Opinion: Natalie Kaminski from JetRockets argued Why Ruby on Rails is the Best Stack for Vibe Coding in the Age of AI. Natalie emphasizes that Rails' developer happiness and the framework’s magic that handles common patterns makes it ideal for the Vibe Coding and fast-paced experimentation that AI-assisted development enables.

Video: AI on Rails breaks down transitioning from Cursor to Claude Code in Goodbye Cursor, Hello Claude Code? The video examines the differences between these AI-powered coding tools and discusses potential reasons for making the switch from Cursor's AI-assisted development environment to Claude Code’s command line interface.

Opinion: Scott Werner looked at how AI code generation is fundamentally changing the economics of refactoring in Refactoring in the Age of Unlimited Code Generation. Scott argues that when code generation becomes essentially free through AI, the traditional cost-benefit analysis of refactoring shifts dramatically, making it potentially more economical to regenerate code from scratch rather than carefully refactoring existing codebases. In another piece, The Parallel Lives of an AI Engineer, Scott examines how AI tools are creating dual workflows where engineers simultaneously work with both AI-generated and human-written code.

Video: Pete Hawkins of Rapid Ruby released a series of videos exploring advanced Claude coding techniques. The first, You Can 10x Claude Code With These Secret Commands, shows how you can speed up your coding workflow with custom Claude Code commands that handle everything from perfect Git commits to detailed product requirement documents. The second, This Claude Code Workflow Feels Like Cheating, flaunts his supercharged development workflow. The third video, Claude Code Just Took Over My Notes (And It's Unreal), demonstrates a note-taking workflow with Claude Code and Obsidian to help with project development.

Podcast: Valentino Stoll and Joe Leo will host Chad Fowler on the The Ruby AI Podcast on Wednesday, August 6th at 12:30PM EST for Rails After the Robots: Chad Fowler on AI as the Next Abstraction. The panel will discuss treating GenAI as an abstraction rather than magic, covering architecture for machine-written code, designing clear interfaces, and how legacy Rails applications can evolve in an LLM world.

Feedback: Saad Azam shared redlead-cli, a Ruby-based command-line tool that leverages LLMs to analyze business prompts and discover targeted leads from online communities like Reddit. The redlead-cli source code is available on GitHub and Saad is looking for ways to improve the gem.

Announcement: Jeremy Howard released Claude Code Wisdom, a curated collection of coding best practices extracted from conversations with Claude AI. The project compiles insights on software development principles, debugging techniques, code organization, and architectural patterns. The README provides documentation on how to use the collected wisdom, while the full Claude Code Wisdom repository contains the complete collection of insights.

Article: Fernando Martínez of Sinaptia explores Scaling Image Classification with AI. The post details building an image classification system that combines Hugging Face Transformers with Ruby on Rails. Fernando walks through the technical implementation including model selection, API integration, and performance optimization strategies.

Announcement: Nolan Tait released prompt_schema, a Ruby gem that generates BAML-style prompts from dry-schema to get and validate structured responses from LLMs. The library allows developers to define schemas using dry-schema's syntax, then automatically generates prompts that instruct LLMs to return data in the specified format. The prompt_schema source code shows how it integrates with LLM clients and provide validation to ensure responses match the expected schema structure.

Article: Rich Steinmetz introduces his four-part series on Code with LLMs and a PLAN, presenting a structured approach to software development using Large Language Models. The PLAN framework consists of Prepare (setting up the environment and gathering requirements), List (breaking down tasks into manageable chunks), Analyze (reviewing and refining the approach), and Navigate (executing the plan while maintaining flexibility). The series continues with Code with LLMs and Default Instructions, which explores how to create effective system prompts and default instructions that guide LLM behavior throughout development projects. The third installment, Code with LLM Teams, demonstrates how to orchestrate multiple AI agents working together on complex coding tasks, each with specialized roles and responsibilities.

Update: Geir Isene has updated Ruby SHell with direct AI integration. RSH is a Ruby shell designed to replace bash/zsh with a pure Ruby environment, offering tab completion, command history, syntax highlighting, and built-in Ruby evaluation. The latest update allows users to interact with AI models directly from the shell.

Article: Russell Van Curen wrote Build AI Agents in Ruby with Just One Gem to showcase openai-toolable, a gem that handles function calling and execution by including a single module. In the post, Russell demonstrates building a calculator agent and a weather service agent.

Tips: Nate Hopkins shared a 10-step workflow for How to best leverage Claude Code. The approach emphasizes starting with clear requirements and providing appropriate context before asking Claude to propose solutions. Key steps include saving responses to a markdown file with TODOs, iterating line-by-line with explicit references to specific line numbers, and continuously updating the plan as you implement solutions until completion.

Podcast: Victoria Melnikova from Evil Martians interviews Anna Veronika Dorogush: my team makes me proud. Anna is the founder of Recraft AI, an image generation service designed for designers. Anna discusses how their niche positioning as a design-focused tool, rather than a general AI image generator, was a strategic choice that differentiated them in the crowded AI market.

Article: Rakesh Arunachalam of Thoughtbot explores the current landscape of Tools for AI Assisted Software Development, categorizing them into three main areas: code editors with AI capabilities, AI-powered terminals, and specialized development tools. He highlights popular code editors like GitHub Copilot, Cursor, and Windsurf that offer intelligent code completion and chat interfaces, while also covering terminal tools like Warp and Fig that enhance command-line productivity.

Code: Obie Fernandez demonstrated how to run Rubocop with Claude Code hooks, providing an example use case for automatically running linters on every Claude Code update or write operation. The setup gist shows how to configure the hook.

Video: Samuel Williams live streamed Running tests against Agent::Context documentation using Sus::Fixtures::Agent::Context, exploring how to test documentation for agent-based systems. The video showcases using agent-context and sus-fixtures-agent-context to verify that LLMs can understand and apply guidance around thread safety in Async Ruby code. The demonstration coincides with the v0.1.0 release of sus-fixtures-agent-context, which provides a testing framework for validating AI agent contexts. Additionally, Samuel released async-ollama with conversation and tool support, enabling more sophisticated interactions with local LLM models.

Update: Sergio Bayona released VectorMCP v0.3.3, a critical security update for the gem. The release addresses a serious SSE transport session isolation vulnerability that could affect multi-client MCP servers, along with enhanced path traversal protection and improved transport compatibility to resolve race conditions. VectorMCP provides a framework for creating MCP servers that expose tools, resources, and prompts, and users are strongly advised to upgrade immediately to ensure secure operation in multi-client environments. The VectorMCP repository offers documentation and a full changelog.

Article: Jared Norman introduced Order-Driven Development, a methodology that prioritizes the sequence in which code is written and read. By looking at the flow LLM-generated code, Jared argues for structuring code so that dependencies and abstractions are introduced in logical order, making codebases more comprehensible to both new team members and future maintainers.

Update: Alexey Varfolomeev from JetBrains announced RubyMine 2025.2: Junie and AI Assistant Upgrades, Faster Rails Project Startup, Enhanced Bundler Management, and More. The post highlights Junie support for better project-specific context, integration with agentic rule files, and the ability to connect to local AI models. JetBrains AI coding agent Junie also added MCP support.

Feedback: Vinícius Ferreira is looking for feedback for improving the AI Hub gem, a Ruby library that provides a unified interface for accessing multiple AI chat APIs. Features include support for streaming responses, customizable parameters, and provider switching.

Podcast: David Hill and Marty Haught from Ruby Gems Podcast interviewed Even Phoenix in Evan Phoenix: From Rubinius to Ruby Central, exploring his journey from creating the Rubinius Ruby implementation to his current role as Executive Director of Ruby Central. Evan wraps up the conversation with his current ventures and thoughts on the future of tech and AI in coding.

Article: Katie Parrott of Every explores Anthropic's new computer-controlling agents in Vibe Check: Claude's New Agents Are Confusing as Hell - And We Love Them. Katie describes Claude's computer use feature as simultaneously impressive and frustrating, capable of autonomously navigating interfaces but often taking circuitous routes to complete tasks. Still reading the newsletter? Here’s a bit of super secret alpha from Every: while not officially open source yet, the every-cli is available on npm.

Part 2 is available here:

Ruby AI News: The Sequel - August 6th, 2025

Part 2: Events, new open source, & 150+ career ops

rubyai.beehiiv.com/p/ruby-ai-news-the-sequel-august-6th-2025-9c80933028eeed20

RoboRuby

Ruby AI News - March 27th, 2026

Contents

Welcome to the One Year Anniversary Edition

Top Stories

Can an AI Agent Build a Business?

Once Upon a Time

A Cognitive Architecture for AI Agents

Need to Know AI News

Content

Announcements

Articles

Videos

Podcasts

Discussions

Events

Previous

Upcoming

Open Source Updates

Code Spotlight

Multi-Gem Frameworks

New Gems

New Open Source

Jobs & Opportunities

Featured

One Last Thing

Ruby AI News - March 12th, 2026

Contents

Top Stories

Ruby’s AI Superpowers are Real

A Safe Enclave for Ruby

Autoresearch is the New Vibe

Need to Know AI News

Content

Announcements

Articles

Videos

Podcasts

Newsletters

Discussions

Events

Previous

Upcoming

Open Source Updates

Code Spotlight

New Gems

New Open Source

Jobs & Opportunities

Featured

One Last Thing

Ruby AI News - February 26th, 2026

Contents

Top Stories

Code Mode

YAY AIA V1

Ruby AI Goes NSFW

Need to Know AI News

Content

Announcements

Articles

Videos

Podcasts

Newsletters

Discussions

Events

Previous

Upcoming

Open Source Updates

Code Spotlight

New Gems

New Open Source

Jobs & Opportunities

Featured

Ruby AI News - February 11th, 2026

Contents

Top Stories

Artificial Ruby is Back for 2026

Need to Know AI News

Content

Announcements