RoboRuby

Ruby AI News - August 5th, 2026

Matt Solt — Wed, 05 Aug 2026 18:23:59 +0000

Welcome to the 35th edition of Ruby AI News! This edition features the Rails security team answering a critical CVE with agent-runnable forensics, forging the entire agent stack for Rails single-handedly, the numbers that make Ruby the token-efficient language for agents, and much more.

Thank you to SerpApi, the world’s leading API provider of search data, for sponsoring this edition. Be sure to check out their careers page, they’re hiring!

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

Need to Know AI News

Stateless MCP Has Recaptured My Interest Simon Willison returned to MCP after the 2026-07-28 spec, which co-creator David Soria Parra announced as its biggest release yet, made the protocol stateless. A single HTTP request now serves tools, and Simon argued bounded tool access beats shell access for sensitive agent apps.

How Coding Agents Read Your Code (and How to Write for Them) Ben Vinegar showed agents navigate repos by grepping names, not semantic analysis, so naming is the interface. Two and three word identifiers cut a search from hundreds of files to a handful, dropping agent token use up to 66% in his tests.

Harness Engineering Is Not Enough: Why Software Factories Fail Dex Horthy recounted how his agent factory, where nobody read the code, collapsed. He argued models are rewarded for passing tests while nothing penalizes bad architecture, and prescribed reading the code again and planning down to types, with a written part 1 out now.

Helping Agents Discover My Site Search With Agentic Resource Discovery Dries Buytaert published a manifest at /.well-known/ai-catalog.json that ARD registries crawl and index, letting agents find his site search from plain-language queries. He noted adoption hinges on the big AI providers running such registries.

The Shape of Things to Come, Part 1: The Continuous Thunderdome Steve Yegge described the bespoke agent harness running his game, where merge queues gave way to batching every commit and letting agents diagnose the wreckage. He predicted every team will build one next year because the architecture is convergent.

Content

Announcements

Solid Queue 1.6.0 Carmine Paolino shipped fiber workers for Rails' default queue, set fiber: N, and jobs run on a single Async reactor thread, built for long-running, I/O-bound LLM streaming jobs that waste thread workers. Part of his push to make Rails the best framework for building LLM apps.

Martian Agent Skills Evil Martians packaged their engineering practice as installable skills for Claude Code, Cursor, Codex, Copilot, and Gemini CLI. The catalog spans llms-visibility (making your site readable to AI), layered-rails (the Layered Design book as review rules), and storybook-workbench audits.

Rails Reference Apps Amanda Perino announced a hand-picked library of production-quality open-source Rails apps, including Campfire, Writebook, and Fizzy, explicitly aimed at giving both humans and LLMs clean, current examples to learn from. Rob Zolkos designed and shipped the page.

Agent-First Development, Measured Lucian Ghinda shared two months of stats from an agent-first workflow: four agents implement each feature independently, a multi-panel agent review checks idiomatic Ruby and Rails, and he cherry-picks the best. Claude won most often; every agent over-commented and invented jargon.

gigatoken-rb Eric Jacobs released zero-copy Ruby bindings for gigatoken, the fastest open-source BPE tokenizer: 12.4 GB/s and 2.8 billion tokens per second, 340x the fastest existing Ruby gem. Chasing the last of the Ruby-Python gap surfaced a hidden memcpy, an extra copy of every buffer, he fixed upstream.

AgentsHQ Newton Garcia launched a Rails-built control plane for fleets of autonomous agents: they claim tasks from a live kanban, delegate through structured handoffs capped at three levels deep, and run sandboxed in per-agent containers with token budgets, persistent memory, and WhatsApp, Telegram, and Slack channels.

Audition Yaroslav Markin vibe-coded a linter/fixer that gets Ruby code Ractor-ready, with static analysis on Shopify's rubydex plus dynamic probes that run your code inside Ractors and report what breaks. Checks were trained on real Ractor-izing commits from Rails core, and a bundled skill lets agents drive the audit-fix-verify loop.

Rails MCP With CanCanCan Authorization Erich Stark added a remote MCP endpoint to his Rails app with the official mcp gem, exposing 13 tools over Streamable HTTP. Tools reuse the REST API's personal-access tokens and CanCanCan abilities. Tools/list is filtered by scope, tools/call re-authorizes, and every invocation is audited.

Errors to Agent-Ready Tickets Erich also wired his three-person Rails team's observability so a production error becomes a Linear ticket with stack trace, release SHA, and breadcrumbs attached. A coding agent reads the ticket, reproduces the failure against real source, and drafts a plan for human review.

talk_to_your_app Igor Kasyanchuk released an MCP gem that lets your agent operate a running Rails app. Query the production database, flip feature flags, reset caches, and check background jobs, with custom plugins for your own commands.

GemCP Brandon Weaver introduced read-only MCP tools for RubyGems metadata so agents can answer questions about gem compatibility, dependencies, versions, and ownership straight from RubyGems. He's testing it by asking which gems in ancient Rails repos survive the next Rails version.

safer-dependencies Robert Auger built a security layer for Claude Code that audits packages before they're added: CVEs, typosquats, abandoned projects, and version-age checks with cooldown periods against supply-chain attacks, across RubyGems, npm, PyPI, Maven, Go, and Rust.

Asgard Dewayne VanHoozer shared the deterministic quality gate he runs before accepting LLM-built code. His Thor-based task runner executes a project's .loki tasks, chaining flog, flay, reek, RuboCop, Brakeman, bundle-audit, and the test suite. His experimental robot_lab harness shows it gating a local Ollama loop.

ChatSDK AI Layer Quentin Rousseau added a provider-agnostic AI module to Rootly's ChatSDK. Convert chat threads to LLM messages, generate agent tools with reader, messenger, and moderator permission presets, and stream any enumerable of chunks into a live chat message, with RubyLLM included.

Rails Agent Kannan Reghu launched a full-stack framework for building agents in Rails, pitching agent development as a zero-knowledge task. Typed agent base classes, playbooks, connectors, BYOK model keys, and a hosted runtime for testing, deploying, and monitoring, as an alternative to RubyLLM and Active Agent.

Autohand AI Autohand published its agent tooling on GitHub, a self-evolving coding CLI, a Commander control center for coding agents, and Squad teams, including a Ruby SDK for CLI-backed agent orchestration with streaming and run lifecycle events.

Uno Rafał Piekara launched an AI-native Rails 8 starter with standard SaaS features like auth, billing, admin, jobs, deploys already built, tested, and documented so your agent starts at your product.

i18n-feedback Yaroslav Shmarov released a gem for AI-translated Rails apps that lets a proofreader click any string in the running app and suggest a fix. Suggestions land in the database for developers, or AI, to evaluate and apply.

reve_ai David Paluy updated his Ruby gem for the Reve image model to API V2, after quietly rebuilding how he creates visuals for his products and media around it, usable in chat or programmatically via API.

tramway-skill Pavel Kalashnikov updated his Claude and Codex skill that hands agents an opinionated Rails playbook from bootstrap to Kamal deploys, improving its instructions for end-to-end testing of Hotwire features.

Designed With AI Jesse Waites started a podcast interviewing people making cool things with AI, from reviving old software on new systems with Claude or Codex to shipping back-burner passion projects, and he's looking for guests with demos.

XO Ruby Update Jim Remsik cancelled the Salt Lake City stop after family emergencies and the loss of his brother, fellow Rubyist Veez "Matt" Remsik, while Seattle on August 8 and Vancouver on August 15 go ahead with tickets live. He asked for help in order of priority. Buying tickets first, then spreading the word to teams and meetups, warm introductions to potential sponsors, proposals for open speaker slots, help reviewing the CFP and building the program, and day-of volunteers in either city. Take a look at the post and fill out the form if you can help.

Articles

Most Teams Steer Clear of Ruby When They Build AI. We Leaned In Spencer Miskoviak explained how Tern gave its AI agent the keys to the Rails monolith 12,000+ travel advisors use, with 139,000 actions on advisors’ behalf in June. A tool call is just a controller action reusing existing models and authorization, with RubyLLM handling the providers.

Only One World Is Real Irina Nazarova updated her mental model of LLMs. They don't just retrieve the human corpus, they extrapolate a cloud of plausible worlds around it, and only one reproduces in reality. A knowledge worker's job is pinning down that real subspace, which makes verification the core skill of AI-era work.

Roda on Spinel Sam Ruby asked Claude for an assessment of whether Roda fit the compiler model, then transpiled a Roda and Sequel blog into a native binary booting in ten milliseconds on 4.5 MB of memory. With 93 of 130 lowered methods byte-identical to the Rails version, the IR proved Ruby-shaped rather than framework-specific.

You Can't Rewrite Your Way Out of Big O Sam then chased Spinel's 202-second hang on Roundhouse's 40,000-line Lobsters tree down to per-item helpers rescanning whole tables, the same quadratic that had pushed Matz to rewrite the compiler in C. Five upstream pull requests later, the run takes 5.3 seconds.

Rails on Roda Sam closed the arc with deterministic converter that turns a Rails app into idiomatic Roda and Sequel through the compiler's IR, quoting ambiguities for humans where an AI port would guess. Jeremy Evans measured for himself, 4,720 KB of memory for the Spinel binary against 45,356 KB for his hand-written app.

RubyMine 2026.2 Alexey Varfolomeev announced agentic debugging for RubyMine. A bundled rubymine-debugger skill lets AI agents launch debug sessions, inspect runtime state, and analyze behavior on their own. The release brings native GitHub Copilot integration, third-party AI completion providers, and symbol-based code insight.

Depthfirst Reports 105 Ruby Vulnerabilities RuntimeWire covered Depthfirst's AI security agents validating 105 vulnerabilities across 34 Ruby projects, 61% of them memory-safety bugs in native C extensions, including a Nokogiri bounds-check flaw that survived from 2009 until June and a lock-counter overflow in concurrent-ruby.

Automate Tech Debt Audits With Claude Code Ernesto Tagwerker open-sourced a Claude Code skill that assesses technical debt in a Rails app in minutes, chaining FastRuby's own tools, Skunk, RubyCritic, bundler-audit, and libyear-bundler, into one comprehensive report instead of a tedious manual audit.

Tracking LLM Latency & Cost With Rails Events Henrique Medeiros instrumented RubyLLM calls with Rails 8.1's Rails.event.notify so cost, latency, failures, and attribution live in your own APM instead of a provider dashboard. One emission point ties every call to the feature, user, and request that made it.

The No-Bullshit Guide to Agentic Engineering Juraj Masar published the playbook written for Better Stack's engineers. It opens with catching yourself saying AI isn't good enough, and assuming you're wrong and asking how to configure it properly. It gets Rails-specific, down to a censored rails runner equivalent that strips secrets and PII before agents see them.

The Metaphysics of Vibe Coding (or the Absence of It) Julian Rubisch read the agentic-coding debate as metaphysics versus phenomenology, with disposable-code evangelists against hand-crafted-code partisans. His resolution was knowing when to pick which lens. Build the centerpieces yourself, let the agents build the seams.

Taming AI Agents Muriel Salvan distilled six months deep in the agent ecosystem into hard-won lessons: LLMs will always fail sometimes, most agentic systems are overkill for a single LLM call, and strict workflows belong in code, not prompts. A TDD skill that failed 10% of the time became ten reliable lines of Ruby.

How to Build a Rails AI Code Quality Workflow Oxycon IT argued that AI writes confident code, migrations that lock tables, silenced warnings, invented helpers, so generated code must pass the same gates as human code, or harder. The workflow stacks RuboCop, Packwerk, and staged-file git hooks, fitted to your Rails app's tools.

Claude Code for the Semi-Reluctant, Somewhat Curious Rails Developer Robby Russell updated his living guide for Rails developers trying Claude Code, opening with guardrails: permission prompts are a feature, plan mode (Shift+Tab twice) as default until collaboration feels natural, and review every diff before you commit.

Building an AI-Powered Commercial Intelligence Dashboard Patricio Mac Adden recounted a Rails build that used AI from specs to production where user events roll into per-user fingerprints feeding brand briefs. AI-drafted plans drifted from business requirements, so validating the plan against the real project became the team's job.

Ruby Runway Spotlight: Coolhand Labs Ruby Central interviewed Michael Carroll, whose profitable-from-launch startup acts as a COO for AI agents, using log traces and human feedback to cut costs over 50%. He calls Rails the original vibe-coding platform, and Coolhand is the only AI devtools company maintaining a Ruby gem.

How I Built a Skill to Fan Out 20 Workers to Fix My Old Rails App Riccardo Carlesso showed how his open-source fan-out skill has Antigravity spin up parallel workers over GitHub issues to fix his old Rails app, guardrails included and the prompt free to use.

Roman Numeral Code Golf With AI Peter Cooper spent an hour telling Codex to make a Roman-numeral method ever smaller, landing a 90-byte tr-based recursion that reimplemented an obscure trick from 1976. Along the way the agent taught him Ruby quirks he didn't know and started cheating when the byte targets got unlikely.

The Model Should Be Replaceable David Paluy explained why he dropped Claude Code as his default harness and went model-agnostic. Frontier models for hard problems, cheaper open models for repeatable tasks, and no workflow rebuild when providers change their rules. The goal is refusing to make every model release a migration.

Reptile Care Sheets With Rails, Bedrock, and Grover Katapyooon built a "care sheet" feature that turns reptile husbandry data into generated PDFs, wiring Rails to AWS Bedrock for the content and Grover for the PDF rendering, and wrote up the build in Japanese.

One Place for Me and My Agents to Work Chuck Blake made an Obsidian vault the shared inbox for himself, Claude, Codex, and his scripts. Plain Markdown on disk, synced by GitHub and Obsidian Sync across laptop, always-on Mac Mini, and phone, so any session, human or agent, picks up where the last one left off.

A Six-Month Hiring Trial to Build the Company's "Heart" Sakiyarn recounted a 300-hour hiring trial rebuilding a company's spreadsheet P/L management in Rails, with AI use encouraged. The final review graded how they used AI and how well they understood the generated code.

SleeperGem: RubyGems Supply Chain Attack Charlie Eriksen dissected a rare RubyGems supply-chain attack targeting dormant maintainer accounts: a fresh git_credential_manager gem whose four versions built a dropper fetching flagged binaries from a legitimate-looking "git-ecosystem" account with certificate checks switched off.

Making Failure More Predictable in Ruby Systems Samuel Williams recapped a month of 62 pull requests across 20 repositories, fixing signal handling and a fiber use-after-free in Ruby core, adding safe retry primitives to Async HTTP, and giving Falcon a cluster mode that reports per-worker load for smarter traffic distribution.

Videos

Rails Gives AI Agents What They Actually Need Damian Galarza argued that coding agents made him more bullish on Rails, not less. AI generates custom infrastructure quickly but doesn't make it cheaper to verify, secure, or maintain, so convention over configuration is agent infrastructure. The companion essay carries the full argument.

Structured Output Dave Kimura of Drifting Ruby demonstrated turning a raw email into structured data with an LLM call, then using the response to create a contact record in a Rails app, with gem setup, an extraction controller, and an Extractions class in 14 minutes.

Function Calling Dave followed up the video with tool use. Wiring function calling into a Rails app's generative LLM requests, building an assistant controller and Assistant class through to a working demo, with source code included.

Podcasts

Technology for Humans: Why Ruby on Rails Matters More in the Age of AI Errol Schmidt asked Jeremy Smith, Blue Ridge Ruby organizer and IndieRails co-host, whether Rails can thrive when AI tools steer new builders elsewhere. They covered Hotwire as a small-team alternative, disappearing junior roles, and a simpler path for newcomers.

Technology for Humans: What Humans Still Do Better Than AI Errol Schmidt spoke with AI strategist Scott Stafford about trust, empathy, creativity, and judgment as AI grows more capable, including what should never be handed to an agent, and why organizations that preserve human experiences may outperform pure automation.

Remote Ruby: Don't Steal Our Business Idea Chris Oliver, Andrew Mason, and David Hill dug into practical development. Faster server images with Packer, schema tangles, and when quality tools earn their keep, plus where AI assistants save real time, where they confuse, and why judgment matters most.

Remote Ruby: Big Wins for RubyConf and Grandma Chris, Andrew, and David also went down a Raspberry Pi rabbit hole, covering smart-home automation, MagicMirror dashboards, local AI transcription, then recapped RubyConf Las Vegas and discussed how AI is reshaping programming education and the economics of building products.

Breaking Change: v54 — Hot Sleeper Justin Searls spoke at length about AI and tech news, looking at Claude Fable 5's redeployment, Chinese models, Apple versus OpenAI, and his first iOS game.

Giant Robots Smashing Into Other Giant Robots: What's Really Going On With AI Data Centres Sami Birnbaum talked with Dr. Victoria Plutshack about AI data centres in Scotland and the UK, looking at their environmental cost, whether responsible energy sourcing is possible, and coming strain on the National Grid.

Newsletters

Somebody Has to Guide Us Joe Leo argued, via Naur's "Programming as Theory Building," that AI unbundles implementation from understanding. Code ships unread, so shared theory stops forming as a side effect of the work. Citing the GhostApproval sandbox-escape disclosures, he introduced Def Method's GUIDE principles.

Static Ruby Monthly, Issue 18 Andrey Eremin rounded up a busy month for typed Ruby. Chicory WASM unlocking RBS on JRuby, rbs_infer synthesizing signatures from source, AST-aware rbs-merge, property-based testing with tprop, dspy.rb's Sorbet-validated LLM programs, and Ruby-syntax compiled-language experiments tyra and ruxen.

README, July 2026 Ruby Central's monthly digest opened with a RubyConf Las Vegas retrospective, stating attendance fell short of projections but the community showed up hard, Matz anime swaps included. Notably, they said "AI fatigue is real," heard in the surveys and now a factor in future programming themes.

Discussions

Engineers at AI-Heavy Companies Are Mostly QA-ing Agents An r/rails poster relayed founders saying humans now mostly proofread AI output, and asked where careers head. Commenters pushed back saying a huge Rails codebase is maybe 60% automatable, "10x" qualities matter more with agents, and knowing what to build stays the bottleneck.

Has Anyone Integrated an MCP Server Into a Production Rails App? Marco Colli worried MCP just duplicates an existing REST API and asked what's production-ready. Commenters running the official mcp gem said to stop chasing endpoint parity by designing tools around use cases, and keeping the tool count low enough for agents to navigate.

What Is Wrong With the New Rails Website? An r/rails thread pushed back on Rails' agent-era marketing, the taglines "scales from PROMPT to IPO," "accelerate your agents", asking whether this is what Ruby should be known for. Others countered that the pitch was always fast-to-IPO for small teams, and the copy just reflects who writes the code now.

Which Code Knowledge Graph Are You Using? A Rails developer surveyed Graphify, GitNexus, and CodeGraph for agentic work on monoliths. The standout reply is that none of them helped much, a skill teaching the LLM to run introspection through bin/rails runner beat ast-grep, ruby-lsp, and Graphify combined.

Codex vs Claude Code for Rails? An r/rubyonrails poster asked whether ChatGPT or Claude is better for Rails work. The consensus was the harness matters more than the model, that agent CLIs with file access and tool calls beat pasting into a web UI, and results track your prompts, skills, and docs more than the vendor.

Additional Reading

Evil Martians: Which AI Actually Reads Your Site? Two Months of LLM Traffic, Measured

Gusto: Eval-Driven Design Systems (Part 2)

Visuality: Teaching a Browser to Tell Cats From Dogs

Diogo Viana: Tokenmaxxing? Not With Rails

Sebastian Tekieli: Around 150 PRs in Five Months: Incremental Rails Modernization With AI Agents

Madeline Caples: Learning at RubyConf: A Workflow for AI-Assisted Study

Abhishek Parolkar: The Half-Window Rule for AI-Native Businesses

Ruby Overdrive: Ruby in 2026: Why Engineers Fear AI and Where the "Shame" Around Rails Came From (first of a four-part series)

Jean Emmanuel Cadet: Using AI Coding Assistants for Ruby on Rails

Majestic Labs: The Self-Driving Company Still Needs People

Edward Ojambo: The Silent Code Threat: Why Your Ruby App Needs an Expert Security Wakeup Call

Events

RubyConf Austria: This Is What We've Been Training For Chad Fowler, Rubyist since 2000 and co-organizer of the earliest RubyConfs, opened the Vienna conference by arguing that AI isn't a threat to the Ruby community, it's the moment we've spent 25 years training for.

RubyConf Austria: A Tale of Two Chefs: Debt-Free Engineering in the Age of AI Obie Fernandez, author of The Rails Way and CTO at ZAR, told the story of two chefs in very different kitchens building a fintech together with AI, and what their habits say about keeping engineering debt-free.

RubyConf Austria: Ruby Is the Best Language for Building AI Web Apps RubyLLM creator Carmine Paolino argued that AI app development today is building products around an API call, not training models, and Ruby wins that job on less ceremony, cleaner agent abstractions, and faster iteration. He took the same case to Balkan Ruby.

RBQ Conf: LLM Telemetry as a First-Class Rails Concern David Paluy argued LLM calls deserve the same logging, review, and cost discipline as any other production dependency. He showed how to model telemetry as part of the domain rather than sprinkled logger calls.

Ruby Australia: I Became the Agent Michael Milewski went past AI as coding assistant to AI as the orchestrator of his life, from scout badge writeups and hike plans to mass refactoring and security analysis, because "the dream loop was too long."

Ruby Australia: In Praise of Throwing Information Away Adam Rice showed why a simple rule that ignores almost everything routinely beats a sophisticated model that uses all the data, a theorem rather than a fluke, tracing the math of overfitting in machine learning back to how minds make good decisions and to every premature abstraction you've written.

Balkan Ruby: Stop Tuning Hyperparameters. Start Looking at Your Data Galia Kraicheva challenged the model-first mindset behind failing AI projects, stepping back from XGBoost and deep learning to ask whether we actually understand the data.

Balkan Ruby: Your tech stack doesn't matter Onur Ozer argued that an online business lives or dies on market, positioning, and user experience, that AI commoditizing tech makes the stack matter even less, and that when it does matter, Rails is good enough.

RubyConf: There Is No Server Sam Ruby published the written companion to his RubyConf keynote, which runs a full Rails stack, router, controllers, Active Record, and SQLite, in the browser over WebAssembly while his Roundhouse compiler transpiles Rails apps to Rust, Go, TypeScript, and more. The keynote itself was assembled with AI agents, down to a Spinel compiler bug that Matz and his agent turned around in 72 minutes, and the slides run in your browser with demos and speaker notes.

Upcoming

August 8th - Conference: COSCUP 2026 runs August 8th to the 9th in Taipei at National Taiwan University of Science and Technology, where Ruby Taiwan hosts its Ruby track at Asia's largest open source community conference. AI sessions include Aotoki's "Let AI Take Over Your App: Building a Seamless, Microsecond-Level Ruby Security Sandbox," Pawel Lisewski's "The Deterministic Rubyist: Taming Your AI Pair Programmer with Nix," and George Asfour's "Stoplight: Circuit Breakers for Ruby in the AI Era."

August 12th - Meetup: ChicagoRuby @ Workforce.com is on August 12th in Chicago at the Workforce.com office, streaming over Zoom for remote attendees, and both talks focus on AI. Kevin Murphy joins remotely with "InstiLLMent of Successful Practices in an Agentic World" and Jake Dakic presents "Life Beyond Claude Code" in person, with free RSVP required for building security.

August 13th - Meetup: Ruby Montevideo is on August 13th at the Eagerworks office in Montevideo, Uruguay, a Spanish-language evening of two talks. Santiago Bartesaghi goes "Beyond the Prompt: Tracing AI Agents" while Carlos Musetti shares "From Days to Minutes: How I Processed 2GB of Garbage and Only Cried Twice."

August 15th - Conference: XO Ruby Vancouver is on August 15th at the VIFF Centre in Vancouver, a single-day, single-track regional conference. AI sessions include Fernando Perales' "The Ruby Guide to Responsible LLM Integration," Joé Dupuis' "AI is coming for our jobs! It's time to fight back!," and Colleen Carroll's "Passing the CAPTCHA: Why AI is Making Recruitment More Human, Not Less."

August 21st - Conference: RubyConf Africa 2026 gathers August 21st to the 22nd in Nairobi, Kenya at the Sarit Expo Centre, themed "Beyond Code: Innovating for the Future." AI-flavored sessions include Chris Hasiński's "Cool Things You Can Do With Embeddings," Nicolo Rebughini's "Accidentally Building a Neural Network: A Ruby Product Recommendation Journey," and FH Ndiritu's "In the Age of Abundance, Are We Bottlenecks?"

August 25th - Meetup: SF Ruby Meetup @ Gusto is on August 25th in San Francisco at Gusto's HQ. Gusto co-founder and Head of Technology Edward Kim leads a three-talk evening capped by the full round of 60-second intros, and two speaker slots remain open, with AI and agent integration talks likely from the unannounced speakers.

September 17th - Conference: EuRuKo 2026 runs September 17th to the 18th in Brno, Czechia at the Hotel Passage congress hall, a single-track program with keynotes from Yukihiro "Matz" Matsumoto, Xavier Noria, and Koichi Sasada, who closes on parallel programming with Ractors. The headline AI session is Carmine Paolino's "RubyLLM 2.0: Beyond Agents".

September 23rd - Conference: Rails World 2026 convenes September 23rd to the 24th in Austin at the Palmer Events Center, two tracks and 1,200+ attendees with keynotes from David Heinemeier Hansson, Robby Russell, and Aaron Patterson, and the last general admission tickets on sale now. After a CFP where half the submissions were AI-related, the program leans agentic. Daniela Velasquez builds AI pipelines in plain Ruby, Joël Quenneville pitches harness engineering over prompt perfection, Andrew Novoselac sends an agent loop chasing Rails Ractor-safety, Mike Dalessio adds Markdown APIs to Action Text because "agent accessibility is now table stakes," Kinsey Durham Grace agent-proofs your codebase, Enrique Mogollán builds his way through MCP, and Ryan Sherlock argues shipping is your heartbeat in the agentic era.

SerpApi: Google Search API

SerpApi is the leading provider of search data, and the company behind open source Ruby libraries such as Nokolexbor, an open source high-performance HTML5 parser for Ruby.

Open Source Updates

Code Spotlight

GitHub - bborn/concierge: A per-account AI customer success manager for Rails, built on RubyLLM

A per-account AI customer success manager for Rails, built on RubyLLM

GitHub

Bruno Bornsztein is building Concierge, a Rails engine that gives every account in your app its own persistent AI customer success manager, built on RubyLLM with Claude as the default model. You mount the engine and tell it three things, what an account is, what your app does, and what the agent may touch, and each account gets a durable always-on agent with memory, rule-based governance, and pluggable email, in-app, and Slack delivery. Sensitive actions route through approval gates with human takeover and audit trails, a maker-checker structure that prevents agents from approving their own proposals.

rune. A universal PTY ↔ agent bridge for any CLI · CorvidLabs

rune wraps any CLI or TUI in a real pseudo-terminal and returns the same structured result as colorized text for a human or clean JSON/NDJSON for an agent.

CorvidLabs

CorvidLabs released Rune, a universal PTY to agent bridge that wraps any CLI or interactive TUI so humans and AI agents can drive the same command. Built with zero dependencies beyond Ruby's standard library, it detects who is calling and answers with colored terminal output for people or structured JSON and NDJSON for agents, running commands in a real pseudo-terminal while stripping ANSI codes, disabling pagers, and returning structured results on timeout instead of crashing. The repo adds table and key-value parsers, an interactive script DSL for automating TUI prompts, and a rune watch mode that live-streams sessions as NDJSON events for agent monitoring.

New Gems

Links to the RubyGems page, newest releases are first:

hunk_review_changes - Review a diff in your browser, then hand the comments back to your AI agent

flowspeech - Ruby client for the FlowSpeech text-to-speech API

wide_events - One wide telemetry event per request or job, on the OTel span you already export

pi-browser-taskbar-rails - Development-only Pi browser taskbar adapter for Rails

active_record-vector - Native vector embeddings, semantic search & RAG for Rails ActiveRecord

rails-mcp-insight - Deep Rails introspection MCP server for AI assistants

coatepec - Run targeted RSpec examples against a warm Rails test worker over MCP

odata_duty - Interface layer that serves automation, AI, and developer platforms with minimal duplication

chocomint - Tool Execution Supervisor for Ruby - LLM

mcp_logs - Rails engine for MCP request logging and tool documentation

pipeops-rexec - Official Ruby SDK for Rexec - Terminal as a Service

nemesis-shield - Nemesis Shield - Sentinel SDK for Ruby (positive-security middleware + LLM guard)

insion - Official Ruby client for the Insion API

apologist - Ruby client library for the Apologist API

octoryn-sdk - Governed AI SDK for Octoryn Router

robot_lab-web - Browser console for robot_lab: stream a robot's run over Server-Sent Events.

robot_lab-to - Autonomous overnight agent loop for RobotLab - run robots while you sleep

robot_lab-discovery - Zero-configuration mDNS/DNS-SD robot discovery for RobotLab on local networks

robot_lab-audit - SQLite-backed execution audit log for RobotLab via the Hook system

gemcp - MCP tools for RubyGems package intelligence

webpipe-sdk - Official Ruby SDK for WebPipe.ai - turn any webpage into clean, structured data

brainchat - Chat over a knowledge-brain vault from the terminal

ask-graph - Durable workflow graphs for the ask-rb ecosystem

alt - A Ruby client for the Realtor API

groww-mcp - MCP server for Groww Trading API

aicli - Natural language to live shell commands, with OpenAI and Anthropic

ai-shell - A CLI that converts natural language to shell commands

agent-cli-runtime - Provider-neutral contracts for installed agent CLIs

libexttextcat - Natural language detector

phaseo_agent_sdk - Ruby agent SDK for Phaseo Gateway

phaseo_sdk - Official Phaseo Gateway SDK for Ruby

ask-rails-harness-mcp - MCP server for Rails app introspection - exposes ask-rails-harness tools over the Model Context Protocol

ask-rails-harness - Admin AI copilot for Rails apps - inspect code, query DB, read logs, debug

ask-rag - RAG pipeline for the ask-rb ecosystem

aispec - The engineering framework for behavioral contracts for LLM applications

i18n_proofreading - In-context i18n proofreading for Rails: click any translated string and suggest a fix

sloplint - Flag the rhetorical tics and puffery that mark AI-generated prose

mcp_diff - Lockfile + CI gate for your MCP server's contract - CI goes red when you silently break it

ranked_llm - Ranked, multi-provider AI API credentials with automatic fallback and cost tracking for Rails apps

olyx-guardrails - In-process AI guardrails for Ruby and Rails with configurable policies

tokenzr - Tokenzr gem

quicopt - Ruby client for the Quicopt service - author models, emit the Quicopt wire IR

docwright - Auto-generate and maintain documentation for your Rails application

tokenscope-studio - Pointer gem to the tokenscope token-usage scope tool

znyx-sdk - Official Ruby SDK for the ZNYX Runtime guardrails API

hellm - Ruby agentic framework for LLMs

pago-sdk - Pago SDK - A billing platform for the intelligence era

little_ghost - A dependency-light agent framework for Ruby

all_in_ruby - Tell your AI coding agents to write scripts in Ruby

rails-markup - Point-and-click annotation tool for AI agents

kaizo - A strict, punishing set of RuboCop design cops for AI-agent-authored Ruby

berrycrawl - Ruby client library for the Berrycrawl API

ai2web - AI2Web Ruby SDK - capability model, manifest builder, validator, negotiation, server handler

chat_sdk - Unified Ruby SDK for building chat bots across Slack, Teams, Google Chat, and more

ag-ui - AG-UI protocol server

immersivecommons - Thin, spec-derived Ruby client for the Immersive Commons Agent REST API

clankersupport - Embed the Clanker Support AI-powered support agent in any Ruby web app

xshellz - Official Ruby SDK for xShellz sandboxes

ruby_llm-codex - Use a local, ChatGPT-authenticated Codex CLI as a RubyLLM provider

hermetic - Ruby sandbox - real isolation for untrusted / model-generated code

rails-design-profiles - Reviewable, versioned design-token profiles for Rails applications

solid_loop - ActiveJob-backed infrastructure for autonomous AI agents in Rails

New Open Source

Links to the Github repository:

Nyoy - Rails app for local-first Stable Diffusion image generation and AI chat, driving llama.cpp and sd.cpp with tool-calling and RAG

Evergreen - GitHub Next's agentic workflow that keeps pull requests green by fixing CI failures and syncing branches under repo merge policies

WorkRoom - Shared Rails workspace where every person brings their own local AI agent over ACP and the room keeps persistent team memory

StringLine - Mountable Rails engine adding Kanban backlog management, AI requirement auditing, and MCP endpoints for autonomous agents

Docsage - Rails 8 demo for the Active Agent stack where uploaded documents answer questions with cited passages and traced agent runs

Capybara Self-Healing Locators - E2E test template with Cucumber and Capybara where an LLM repairs broken locators and generates page objects

Licensor - Rails-built MCP server that lets agents discover, recommend, and write canonical open-source license files

AI Page Extractor - Turns a URL and a plain-English instruction into structured JSON, with Claude tool-use replacing CSS selectors

Meeting IceBreaker - Rails app that turns pasted LinkedIn profiles into personalized meeting ice-breakers with a fully offline Ollama model

acts-as-mcp - Exposes a Rails app as a policy-aware, read-only MCP server so AI agents can safely query application data

Chat with AI - Rails and Next.js app simulating realistic Korean messaging with seasonally rotating Gemini-generated personas

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

Junior Fullstack Engineer | SerpApi Careers

Apply for a Junior Fullstack Engineer job at SerpApi. Read about the role and find out if it's right for you.

SerpApi

SerpApi is hiring a Junior Fullstack Engineer to build and maintain the Ruby on Rails APIs behind its web search platform, which structures results from Google and 100+ engine APIs and powers AI products like Perplexity. The worldwide, remote-first role pays $80,000 to $100,000 plus profit share, working in Ruby, Rails, MongoDB, and AWS across proxies, CAPTCHA solving, and browser scraping. SerpApi operates transparently with a public roadmap, shared financials, async-first scheduling, and a neurodivergent-friendly culture.

One Last Thing

Regenerative Software

The assumptions underneath modern software development have quietly broken.

O’Reilly Online Learning • Chad Fowler

Chad Fowler, author of The Passionate Programmer and former Ruby Central director and RubyConf and RailsConf co-organizer, announced early access for Regenerative Software, his upcoming O'Reilly book on what happens to software practice when AI becomes the primary author of code. His argument is that version control, code review, and testing all assume a human made each change, and those abstractions stop making sense once agents generate and regenerate code autonomously. The book proposes treating code as a derived artifact rather than a permanent accumulation of decisions, with provenance tracking replacing version control as the source of truth and architectures where AI agents operate as first-class developers. Early access is available now, with the full release expected from O'Reilly in 2027.

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 - July 17th, 2026

Matt Solt — Fri, 17 Jul 2026 12:00:00 +0000

Welcome to the 34th edition of Ruby AI News! This edition features a Ruby implementation of the new Open Knowledge Format, a history lesson on chatbots, the return of the San Francisco Ruby Conference, and much more.

Thank you to SerpApi, the world’s leading API provider of search data, for sponsoring this edition. Be sure to check out their careers page, they’re hiring!

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

HuggingNews Nikolai Yakovenko launched an AI-curated news feed that ranks roughly 50 AI stories a day into scannable headlines and a short daily brief. Clem Delangue recommended it after weeks of use, suggesting you ask your agent for the top ten stories each morning, with Hugging Face profile personalization coming next.

A Field Guide to Fable: Finding Your Unknowns Thariq Shihipar of Anthropic argued Fable 5's output is bottlenecked by clarifying your unknowns, with patterns from blindspot passes to quizzes. Matt Shumer's How I Prompt Fable supplied the tactics, goals instead of steps, house rules, and a loop against a hard bar that a fresh sub-agent grades.

Control the Ideas, Not the Code Salvatore Sanfilippo (antirez) argued the volume of AI-generated code makes line-by-line review impractical, urging developers to control architecture, design docs, and testing instead. He cautioned young programmers still need to write foundational code to build mental models.

Introducing Inkling Mira Murati's Thinking Machines Lab released open weights for a 975B-parameter multimodal mixture-of-experts model with a 1M context and an adjustable thinking-effort dial. Jack Morris called it a big deal as the only open-weight frontier model trained without distilling from OpenAI or Anthropic.

Apple Sues OpenAI Over Alleged Trade Secret Theft Sarah Perez reported Apple's federal suit accusing OpenAI executives, including former Apple design chief Tang Tan, of coaching recruits to take confidential material on unreleased products, filed as OpenAI builds hardware that could rival the iPhone.

Content

Announcements

Mistri Muhammad Ahmed Cheema wrote a zero-dependency agent harness for a Ruby ecosystem where agent tooling is otherwise TypeScript or Python. It offers resumable append-only sessions, steering a run mid-flight, sub-agents, tool approvals, and one interface for LLMs, and already runs a production assistant. Docs at mistri.sh.

Avo 4 Adrian Marin shipped a major release of the Rails admin framework with a refreshed UI and new add-ons like Kanban boards, notifications, and dynamic filters. It also leans into AI. Generated JSON APIs agents can use, a generated CLI and LLM skill for team workflows, and an MCP add-on coming soon.

The Boring AI Engineer Andrew Kwak published a book arguing that boring technology wins when AI writes the code, plus a companion starter of small Rails files to copy into your app. The starter routes every model call through one front door, keeps agent state in database rows, and treats an agent as a loop with a budget.

2x-skills Akshay Katyal and Brian Scanlan open-sourced Fin's curated set of Claude Code skills and hooks used by hundreds of Intercom engineers. Akshay detailed the review discipline behind their 600-skill marketplace, including a skill that reviews skills, and Brian wrote up what separates good skills from bad.

Engram Alex Kholodniak built a memory layer between a Ruby or Rails app and the model. Durable facts stored in your own Postgres, recalled selectively per message, and injected into the next prompt instead of resending history. The pre-1.0 gem ships Rails, pgvector, and RubyLLM adapters plus scope isolation and secret filtering.

LangExtract David Paluy released a Ruby port of Google's LangExtract for structured extraction you can trace. It maps every extracted value back to its source character and token offsets, keeps an explicit alignment status, and flags results that cannot be grounded, with RubyLLM integration.

data_redactor Daniele Frisanco created a gem that strips secrets and personal data from any string before it leaves your app, whether bound for logs or LLM prompts. A purpose-built C engine scans 89 patterns in a single pass, up to 2.5 times faster than a pure-Ruby gsub loop, with Logger, Rails, Rack, and RubyLLM integrations.

rails-ai-context Cris Nahine updated an open-source MCP server to 39 tools that give AI agents live access to a Rails app, from model, route, and schema introspection to safety-gated SQL. It works with major coding agents with recipes and an API for custom tools.

LocalLingo Mikael Henriksson published docs for his i18n toolkit that extends i18n-tasks with AI translation of missing and changed keys through RubyLLM, per-key source-hash drift detection, strict CI validation, quality linting with an optional AI review pass, and RuboCop cops.

mcp-agents Thomas Witt shipped updates to his MCP server wrapping AI coding agent CLI tools so any MCP client can call them as tools. Built for the "one builds, one judges" pattern where Claude plans and Codex builds, it fixes built-in MCP mode timeouts and adds model selection and goal injection.

ZBoy Abhishek Parolkar built a sovereign macOS coding agent that runs in a disposable Apple Container micro-VM with local MLX inference on Apple Silicon. It builds Rails 8 apps on a 16GB Mac, and its agent rules cast it as a child-safe Ruby mentor for its 8-year-old tester, who vibecodes HTML games instead of tokenmaxxing on Claude.

Rails Cost Model for AI Development Abhishek also proposed treating Rails apps as finite state machines to make cost of change measurable. Bounding changes to ~30 primitives logged in git yields a self-calibrating cost model that prices human and AI work in equal Work Units and hands sales an Uber-style receipt.

Rails MCP with Streamable HTTP Erich Stark added a remote MCP endpoint to a production Rails app using the official mcp gem. A single JSON-RPC entrypoint that reuses the API's bearer tokens and filters the tool registry through the same CanCanCan abilities, so agents only see what their token's scopes allow.

Can an AI Agent Navigate Ruby? Luc Perussault Diallo benchmarked whether agents can find everything that depends on a central model across 13 real codebases. Cold agents found a fraction and declared the audit done, while adding Sense 's structural code map lifted cited recall +0.26 overall and +0.48 on dependents for the strongest model.

Ruby LLM Discoverability Scorecard Irina Nazarova updated her scorecard tracking how well Ruby sites surface in AI training data and agent retrieval. The 30-day change is new llms.txt files from ecosystem providers, new markdown routes, sitemaps from Bridgetown and AnyCable, and Karafka's robots.txt welcoming AI crawlers.

Nuke on Rails Supply-Chain Audit Alan Alves extended his repo-audit skill after fake recruiters started sending trojaned take-home assessments. Distilled from real credential-stealer samples, the checks catch eval'd remote payloads, install hooks, obfuscated base64, and paste-bin kill-switches, auditing the repo without executing it.

Minerva Valentino Stoll detailed his autonomous agent's work to the public. A Claude-powered agent on a Mac mini handling email triage, code commits, infrastructure, and product research, journaling everything on its own site, including a self-audit of its first 50 days.

Pgbus Mikael Henriksson previewed pgbus, a PostgreSQL-native job processor and event bus for Rails built on PGMQ: ActiveJob adapter, topic-routed events, dead-letter queues, worker recycling, and SSE streams with no Redis, plus a built-in diagnostics MCP server and a CLI for real debugging.

Maquina Components 0.5.0 Mario Chávez released an update to his Rails component library with a Drawer whose state survives Turbo navigations and morphs and tears down cleanly before page cache, plus scaffold templates so rails generate scaffold produces Maquina-styled views.

Apple Email Triage with Ruby Mario also demonstrated an Apple Mail triage agent written in Ruby with RubyLLM underneath. It’s built with his agent harness for RubyLLM, nexo, where you write the agent once, then tweak its skill to your liking.

rails-starter TheCodingEnd refreshed and open-sourced the AI-friendly Rails SaaS starter behind several production projects. Rails, React 19 and shadcn/ui via Inertia, RubyLLM, Devise, and Solid Queue. Org & team auth and phone-based auth each landed after a few hours with GPT-5.5 and Claude Opus.

Keeping Agents Read-Only in Production Jorge Manrubia shared a deterministic Claude hook that steers agents to the read-only "rails query" instead of "rails runner" or db: tasks in production, and asked how others balance the productivity of agent-run scripts against the risk.

Generative UI Web Browser Jesse Waites introduced an Electron browser where Chrome renders hidden offscreen and a realtime diffusion model repaints every frame as felt, clay, or oil paint. Clicks and scrolls in the AI-generated view map back to the real page, keeping the illusion fully interactive.

Best AI for Ruby Coding Jenova pitched its Ruby coding assistant for building, debugging, and shipping Rails apps through conversation, claiming Rails 8 mastery, ActiveRecord optimization, and modern Hotwire/Turbo patterns for developers battling shifting best practices.

SimpleCov 1.0.0 Erik Berlin announced the coverage tool's first stable release, the biggest in its 16-year history. The 1.0 line consolidates a redesigned configuration API with new verbs like skip, group, and cover, builds in the JSON formatter, filters test directories by default, and raises the minimum to Ruby 3.2.

RubyEvents Guides Hans-Jörg Schnedlitz launched guides.rubyevents.org, a site for people who want to organize Ruby conferences and meetups. Built from interviews with experienced organizers like Jeremy Smith, Andy Croll, and Amanda Perino, it surfaces the knowledge that usually lives in private chats and organizers' heads.

Lexxy Sandbox Markup View Jorge Manrubia added an option to the Lexxy sandbox to inspect the markup the editor generates, contributed by Zoltan Hosszu, showing off the clean, semantic HTML it produces compared to other rich-text editors.

Articles

Ruby Is the Most AI-Friendly Stack Is Half True Luc Perussault Diallo distilled his Sense benchmark campaign into a seven-part series: models write Ruby fluently but navigate it poorly, and no model upgrade closes the gap, since a map hands the agent a computed fact where a bigger model hands a more confident guess. He recorded an agent auditing GitLab and its million edges, shared a four-command self-audit protocol, admitted his first AI judge called a half-finished audit exhaustive, and ran it on Forem, catching a frontier model reciting stale memory about the engine dev.to runs on. Per-repo deep dives continue on Medium, including Rails itself and raix.

Fable and Opus Build a Multiplayer Feature Irina Nazarova raced Fable 5 and Opus 4.8 at rebuilding Fizzy's collaborative editing (Yjs, yrby, AnyCable) from the same kickoff prompt. Fable's version was safer, Opus's cleaner, and both replayed documents inside the transaction holding row locks, missing the one extraction her own pass made.

Closing the Verification Loop Kieran Klaassen detailed how compound engineering's /ce-dogfood skill closes the gap between merged and working: it diff-scopes the branch, drives a real browser through every changed flow as user personas, fixes what breaks, and re-verifies until the branch carries proof it is ready.

The Compounding Knowledge Lifecycle Kieran Klaassen explained how a lesson learned once keeps paying: each solved problem becomes a markdown learning in docs/solutions/, and retrieval is built into five skills, planning greps the memory and review audits diffs against it, so knowledge resurfaces instead of rotting.

Introducing Fragua: The Harness Already Composed for Rails Mario Chávez opened a private beta of Fragua, an AI agent orchestrator for Rails that walks a one-line idea to a pull request: brief, research, plan, and spec persist as artifacts feeding the execution agent, which picks up accepted specs on its own and runs on your machine.

Idempotent AI Workers in Rails Danial Asghar showed why Sidekiq's at-least-once delivery makes retried LLM jobs double-charge and double-write, then walked the fix in his open-source ticket triage engine: a status gate on a stable UUID, atomic state transitions, and an audit trail that makes retries cheap.

Audit a Rails Project with the Thoughtbot Audit Skill Daniela Baron ran thoughtbot's Rails audit skill on her five-year-old analytics side project, then turned the markdown report into a severity-tiered, labelled GitHub backlog, sharing the findings and the workflow for fixing them one issue at a time.

Snooping on GitHits.com Stas Katkov pried open the GitHits MCP server with mcpsnoop and raced it against its CLI, WebFetch, and Lightpanda on a gem changelog question: MCP burned 1.3M tokens over 9:27 versus Lightpanda's 203K in 1:03, so he removed it (nothing leaked; it was just wasteful).

llmemory: Persistent Memory for LLM Agents in Ruby Entaina wrote up (in Spanish) its llmemory gem giving Ruby agents short-term, long-term, and cognitive memory: LLM-extracted facts or a knowledge graph with hybrid retrieval and conflict resolution, plus Rails, Redis, PostgreSQL, and MCP integrations.

How I Used Fable Last Week Irina Nazarova logged a week of Fable builds with token counts: an 8-bit Super Mario-style sfruby.com rebuild, multiplayer editing on a Fizzy fork tested by 40 Martians at once, a benchmarking harness, a Slidev theme, and a Rails refactor, each between 600K and 1.7M output tokens.

From AI Opportunity to AI Feature: Where We Start in Rails Applications Aysan Isayo argued a Rails app's first AI feature should prove value before ambition: start with semantic search over content users already have, layer summarization and decision support next, and reach for agents only once something simpler has earned it.

AI Coding Workflow for Beginners Celso de Sá published the article behind his beginner guide: a July 2026 model snapshot plus an OpenCode and OMO-SLIM setup where agent lanes split research from edits, AGENTS.md carries instructions, .context/ files persist memory, and Rails wins because conventions shrink the AI's decision space.

I Built a SaaS That Lets AI Build and Publish Sites, Then Scrapped It shuent recounted (in Japanese) building miyo Sites, a Rails platform where Claude Code pushes generated HTML over MCP or API for instant publishing with forms, CRM, and analytics, then scrapping it after concluding that hosting AI-generated pages was a security mistake.

Building Private AI Evals: Why Your Company Needs Them and How to Start David Paluy argued in an X article that AI projects stall because nobody defined what good means: a private eval encodes that definition as versioned cases with allowed tools, reference answers, and scoring rubrics, measuring your workflow rather than a lab benchmark.

DSLs Enable Reliable Use of LLMs Unmesh Joshi wrote on Martin Fowler's site that LLMs need boundaries to generate what's intended: domain abstractions and DSLs form the harness, with the LLM as a partner that iteratively builds the DSL and then serves as its natural-language interface.

Claudeshoring: Your Company's Best First AI Project Michael Carroll argued enterprises fail at AI (MIT counts 95%) by picking never-done-before processes, and coined Claudeshoring: take a process you already offshored, with its documented handoffs and measured costs, and make that your first AI migration.

Trust Is Not a Vibe Chuck Blake wrote two field notes from his background agent jobs. After a happy-path lie in a job posting music across six networks, he trusts the trail of logs and artifacts over any single good run, and in When the Script Wants to Become a Product he traced how Glance, the dashboard watching those jobs, pulled him into real product work.

Why AI Coding Assistants Work Suspiciously Well With Rails Muhammad Ur Rehman argued Rails accidentally built the ideal AI foundation. Conventions act as a system prompt shipping with every project, twenty years of code fill the training data, and Ruby packs more meaning per token.

Videos

Claude Skills Dave Kimura of Drifting Ruby demonstrated creating Claude slash commands for a Rails app, building an /analytics command that acts as a data analyst: it answers business questions by running read-only ActiveRecord queries through bin/rails runner until it can back the answer with real numbers.

Using Claude Design and Fable to Build a Ruby on Rails Web App Justin Jackson showed his workflow from idea to working Rails app: articulate the vision in Claude Design, iterate on the interactive prototypes it builds instantly, then hand off to Fable for the functional build. Ideas he sat on for years now prototype in an afternoon.

TalkGenerator on RubyEvents.org Rachael Wright-Munn streamed a session on RubyEvents.org's TalkGenerator after using it for RubyConf Africa, walking through the big update pull request and open issues around events like Kansai RubyKaigi 09.

Podcasts

The Ruby AI Podcast: AI-Powered Rails Upgrades: NextRails and the Future of Framework Modernization Joe Leo and Valentino Stoll interviewed Ernesto Tagwerker about the Next Rails dual-boot gem, the Claude Code skills encoding FastRuby's upgrade expertise, and why one human plus one agent now matches two humans on upgrade projects.

CTO Confidential: AI in LegalTech Mike Rispoli interviewed Lawrence Krubner, CTO of Scorealytics, on why legal tech wastes AI on keyword search instead of extracting meaning from text. They covered antagonistic agents from different LLMs verifying claims, open-source models beating frontier ones, and Rails playing well with AI.

The Opinionated thoughtbotter: AI Doesn't Make Us More Productive Svenja Schäfer talked with thoughtbot senior developer Sally Hall about why chasing AI productivity is the wrong goal: productivity as a buzzword, products built from generated code failing to last, and incentives that reward writing more code over valuable code.

Additional Reading

OmbuLabs: Error Logs Won't Save You: Why LLM Applications Need Tracing

OmbuLabs: Why LLM Benchmarks Don't Predict Great Agents

Evil Martians: AI vs. Human Illustrators? AI + Human Illustrators!

Viget: Giving Claude Code a Persistent Memory

Redwerk: How to Add AI Features to a Rails App

Andrew Nesbitt: Scrutineer: Scanning Open Source Without Flooding Maintainers

Vicente Reig: Your Job, Their Loop

Ender Ahmet Yurt: Every AI Commit Is Someone's Future Legacy Code

Abhilash Veettil: Why Ruby on Rails Feels Built for the AI Coding Era

Burraq Ur Rehman: Integrating AI into Ruby on Rails the Right Way (A Practical Guide)

Events

Brighton Ruby: In The Model Doesn't Matter, Brian Casel moved past AI spinning up fresh apps to the harder case, one of an established codebase with years of decisions, conventions, and real users. He argued experienced developers hold the biggest AI-era advantage as the developer, designer, and product roles blur.

Brighton Ruby: In Code, Prompts, and Stories, Shopify's Maria Yudina showed what screenwriting teaches about writing code and prompts. The craft principles that make stories work, clarity, structure, and naming apply across code, prompts, and communication.

ChicagoRuby: The July meetup explored staying valuable in the AI age. Alan Ridlehoover of Cisco drew on Hidden Figures to urge engineers to retool as AI transforms the work, and Hashrocket's Tony Yunker demonstrated read-only Rails models with a metaprogramming trick that permits writes during test setup.

Philippine Ruby Users Group: In Is Ruby Dead? Absolutely Not, Artem Blazhievskii made the case for Rails as the One-Person Framework. A solo developer or small team can now build and launch products that once took massive teams.

Upcoming

July 22nd - Meetup: SF Ruby Meetup @ Sentry is on July 22nd in San Francisco at Sentry's HQ, hosted by Evil Martians. The new "fewer talks, more connecting" format features Cameron Dutro on Garnet.js and implementing the YARV virtual machine, plus talks from Alexander Baygeldin and Marco Roth, followed by a full round of lightning intros.

August 4th - Meetup: AI on Rails: Ruby Meets Generative AI is on August 4th in Paris at Algolia's office, co-hosted by AI Tinkerers Paris and ParisRB.new. The "show, don't tell" evening features live-coding demos of developers wiring LLMs, agentic workflows, vector search, and prompt engineering natively into Ruby and Rails, plus a Homebrew-inspired Science Fair for hands-on project walkthroughs.

August 21st - Conference: RubyConf Africa 2026 runs August 21st to the 22nd in Nairobi, Kenya at the Sarit Expo Centre, themed "Beyond Code: Innovating for the Future." AI-flavored sessions include Chris Hasiński's "Cool Things You Can Do With Embeddings," Nicolo Rebughini's "Accidentally Building a Neural Network: A Ruby Product Recommendation Journey," and FH Ndiritu's "In the Age of Abundance, Are We Bottlenecks?"

SerpApi: Google Search API

SerpApi is the leading provider of search data, and the company behind open source Ruby libraries such as Nokolexbor, an open source high-performance HTML5 parser for Ruby.

Open Source Updates

Code Spotlight

Introducing Insta: Snapshot Testing for Ruby

marcoroth.dev - website and blog

Marco Roth

Marco Roth released Insta at RubyConf 2026 in Las Vegas, a new snapshot testing library for Ruby, extracted from Herb 's test suite (where a hand-rolled snapshot module had grown past five hundred lines keeping thousands of parser tests honest) and modeled on Armin Ronacher's insta crate for Rust. His introduction presents it as assert_equal where the expected value manages itself. A failing test writes a pending snapshot, insta review shows a difftastic-powered diff, and accepting is a pure file operation that never re-runs the suite. The gem supports Minitest and RSpec, inline snapshots that rewrite your test source, JSON and YAML serializers, snapshot metadata, and jq-like redactions that swap volatile IDs and timestamps for stable placeholders.

For Ruby AI work this is a near-perfect fit, because LLM pipelines produce exactly what snapshots testing was built for: output that is large, changes often, and is tedious to assert by hand. Pin the model call with VCR (the README is explicit that cassettes manage what goes in while Insta reviews what comes out), then snapshot rendered prompt templates, structured-output JSON, and tool-call payloads, redacting request IDs and token counts. Prompt regression testing becomes a review loop, where you tweak a template, watch every affected snapshot diff, and accept the intentional drift in one session instead of thirty hand-edits. The Rust ecosystem hints where this goes next. Ratatui apps snapshot entire rendered terminal frames through a test backend, the analog of golden-copy testing an agent CLI's transcript, and cargo-insta combines pair snapshots with mutation testing, and a no new snapshots in CI rule to keep suites accurate. All of it ports naturally to Ruby agents, and to Herb-rendered ERB views.

New Gems

Links to the RubyGems page, newest releases are first:

google-cloud-vector_search - Vector database designed to power next-generation search

silas - Durable AI agents on the Rails you already run

maglev-rb - Rails-native semantic knowledge layer for ActiveRecord object graphs

nanobananapro - Free AI image generator powered by Google Gemini 3 Pro Image

envoy_ai - Governed, tool-calling agent chat as a mountable Rails engine

enconvert - Read any page or file into agent-ready Markdown, JSON, or screenshots, every read scored

norn - A pluggable LLM-driven agent development framework

mutation_tester - Simple mutation testing framework for Ruby with RSpec, AI workflow and Minitest support

x_aeon_agents - AI agents skills to be used for X-Aeon projects

ruby_llm-resilience - Circuit breakers and fallback chains for LLM apps

gdkbox - Spin up a GitLab Development Kit in a box, ready for VS Code and Claude Code

bugsage - AI-powered debugging assistant for Ruby on Rails

zer0-image-generator - AI preview/social images for any Jekyll site

okf-sqlite3 - A SQLite storage and full-text search engine for OKF

okf-mcp - A Model Context Protocol server for OKF

floe-servicenow - ServiceNow API Integration for Floe

omnibot-ruby - Rails-first LLM agents for Ruby

transcript-viewer - Pure Ruby static HTML renderer for LLM agent session transcripts

okf - The complete toolkit for the Open Knowledge Format

saleseq - Official SalesEQ Ruby SDK

ruby_llm-voyage - Voyage retrieval APIs for RubyLLM

protege - Email-native AI agent toolkit

rails-agent-stack - Dead-simple AI agents for Rails

chorus-llm - Framework for multi-agent LLM orchestration with contextual routing

hcn - Ruby client for the HouseCanary API

simple_llm - common wrapper for all LLM providers

utobo-email - Official Ruby SDK for the utobo email Email Platform

cpee-llm - CPEE Conversational Agents

visiq - Agent-governance SDK - local, in-process policy decisions.

llmshim - Ruby client for the llmshim multi-provider LLM proxy

locallingo - AI-assisted i18n translation, drift detection, and quality linting on top of i18n-tasks

mcp_toolkit - Opinionated toolkit for building account-scoped, read-only MCP servers

collavre_linear - Linear integration for Collavre

lyman - A composable agentic harness, delivered as code you own - a pure generator in the shadcn/ui mold, built on shifty

ruby_llm-bedrock_invoke - RubyLLM provider for Anthropic Claude via the AWS Bedrock InvokeModel API

worldmonitor - Official Ruby SDK for the World Monitor global-intelligence API

hob - Client for hob, a personal LLM substrate

skill-extractor - Extract skills from job postings and resumes - 32K-skill gazetteer + MiniLM embeddings + MLP context classifier

mistri - The agent harness for Ruby applications

model-language - A typed, safe template language for AI-agent prompts (WebAssembly-backed)

fetch_util - AI for fetching in Ruby

cardinal-ai - A Kanban board where dragging a card to In Progress hires an AI agent to do the task

nightona - Ruby SDK for Nightona

nightona_toolbox_api_client - Nightona Toolbox API Ruby Gem

nightona_api_client - Nightona Ruby Gem

velix-sdk - SDK oficial do VELIX para Ruby

resque-mcp - MCP server for Resque, mountable as a Rails engine

verica-observability - Two-line LLM tracing for Verica

panteao-client - Ruby client for Panteao BDI Coprocessor

prompt_injection - Detects prompt injection attacks in free-text input for LLMs

vector_amp - Ruby SDK for the VectorAmp API

ultrasafeai - Ruby client library for the Ultrasafeai API

crisphive - Official Ruby SDK for the Crisphive API

geminai - Use googles gemini interactions api

emb-server - emb: Redis-compatible embedding server

emb - Client for emb: a Redis-compatible embedding server

New Open Source

Links to the Github repository:

Machina - Agent-native rails new template with a CLAUDE.md operating manual, 32 curated skills, and 17 path-scoped rules, the production starter ZAR uses internally

Zimmer - Self-hostable orchestrator that gives a coding agent a task and a repo, runs an isolated Claude Code or Codex session, and hands back a pull request

Redmine MCP - Redmine plugin adding an MCP endpoint so AI coding agents can search, read, create, and update issues and read wiki pages, over stateless Streamable HTTP

Cardinal AI - Kanban board where dragging a card to In Progress hires a Claude agent that does the task on its own branch, asks when stuck, and hands you a PR to review

DeepForge - Local HTTP/SSE agent runtime for AI-powered GUI apps, managing conversational loops with tool orchestration, context compaction, and pluggable capabilities

Agent Coordination - CLI and workflow helpers for coordinating concurrent agent work across machines, from a zero-config local store to a Cloudflare Worker backend for teams

Groww MCP - MCP server for the Groww trading platform with 25 tools, automated TOTP auth, GTT and OCO smart orders, option chains with Greeks, and backtesting

Printwright - Agent-buyable marketplace for licensed 3D-printable models where humans or agents pay per print over x402 on Hedera and get verifiable license certificates

DocInsightAI - Rails app that answers questions about uploaded PDFs with page-level citations, grounded only in the documents and admitting when they lack the answer

Calvin - CI agent that reads project context from .calvin/, shapes dense tasks in chat, and drives asynchronous implementation through GitHub Actions and external LLMs

Agent Rules Skill - Skill that bootstraps vendor-neutral agent configuration in .agents/ and generates adapters for Cursor, Claude Code, Codex, and opencode

Rulepack - PKGBUILD-inspired package manager for agent rules and skills, with per-package descriptors and a four-stage build pipeline

ai-config - Model-agnostic configuration layer where one canonical AGENTS.md drives Claude, Codex, Copilot, Antigravity, and Grok in lockstep

ForceDream SDK - SDK for the ForceDream A2A network to discover, invoke, and cryptographically verify AI agents, with Ed25519 handled by the OpenSSL standard library

Workmori - Multi-tenant SaaS (in Korean) giving small-business owners a virtual AI employee for marketing, configurable by personality, duties, channels, and cost limits

Bill - Rails bar-tending web app (in French) that recommends cocktails through a conversational interface built on Hotwire and GitHub Models

Jobs & Opportunities

Featured

Senior Fullstack Engineer | SerpApi Careers

Apply for a Senior Fullstack Engineer job at SerpApi. Read about the role and find out if it's right for you.

SerpApi

SerpApi is hiring a Senior Fullstack Engineer to build and maintain the Ruby on Rails APIs behind its web search platform, which structures results from Google and 100+ engine APIs and powers AI products like Perplexity. The worldwide, remote-first role pays $150,000 to $180,000 plus profit share, with total compensation averaging $232,448, working in Ruby, Rails, MongoDB, and AWS across proxies, CAPTCHA solving, and browser scraping. SerpApi operates transparently with a public roadmap, shared financials, async-first scheduling, and a neurodivergent-friendly culture.

One Last Thing

Rails Galaxy — Explore Rails with RubyLens

Explore Rails as an interactive galaxy of classes, modules, tests, dependencies, and reference routes.

st0012.dev/rails-galaxy

Stan Lo teased that he is cooking something on X/Twitter. Rails Galaxy is an interactive demo that renders a Rails codebase as an explorable galaxy through RubyLens. Selecting a class, module, or gem reveals its strongest resolved constant-reference routes, and you orbit, pan, and zoom through the dependency structure. The demo publishes only the architectural shape, deliberately excluding source, comments, and file paths, the same structural map of a codebase that coding agents have lately been to find their way around large Rails apps.

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 - July 2nd, 2026

Matt Solt — Thu, 02 Jul 2026 12:00:00 +0000

Welcome to the 33rd edition of Ruby AI News! This edition features legacy Rails apps getting an AI update, frontier advancements in Ruby’s web server performance, RubyLLM reaching #1 on Hacker News, and much more.

Thank you to SerpApi, the world’s leading API provider of search data, for sponsoring this edition. Be sure to check out their careers page, they’re hiring!

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

Executor is an open-source MCP gateway that gives any agent one endpoint to every tool. Rather than loading thousands of tool schemas (~279K tokens), the model sees a single "execute" tool (~1K tokens) and writes sandboxed code that loads each schema only when it calls it, with secrets kept host-side.

Origin Cursor announced Origin, a git forge "for the agentic era" that gives teams and their AI agents a place to host, review, and collaborate on code. The GitHub-style code hosting arrives this fall behind a waitlist.

Introducing the Open Knowledge Format Google introduced OKF, a vendor-neutral spec that formalizes the "LLM-wiki" pattern so AI agents can share curated context. It is just a directory of markdown files with YAML frontmatter, letting wikis from different producers be consumed by different agents without translation.

Claude Code Artifacts and Claude Science Claude Code can now turn a session into a live, shareable web page from your codebase and conversation, while Claude Science, a new beta research app, produces reproducible scientific artifacts that render proteins, structures, and molecules natively and trace every figure to its code.

Claude Code Is Steganographically Marking Requests Thereallo reverse-engineered Claude Code and found it hides markers in the system prompt's date line. With ANTHROPIC_BASE_URL set, it swaps the "Today's" apostrophe for look-alike Unicode keyed to an XOR-obfuscated list of reseller, proxy, and Chinese AI-lab domains, likely to flag unauthorized gateways and distillation pipelines.

Content

Announcements

OpenClacky Yafei Lee launched a documentation site for the open-source Ruby AI coding agent, publishing live telemetry like a 91% cache hit rate and 779,817 completed tasks alongside install guides, BYOK setup, and a Creator program for monetizing skills. Every metric is public and verifiable.

Mutineer David Teren released a dependency-free Ruby 3.4+ mutation-testing gem that mutates your code and reruns only the tests reaching each change, exposing gaps line coverage misses. It doubles as a "test-value oracle" for AI agents, emitting JSON with stable mutant IDs so agents can regenerate tests to kill surviving mutants.

ActiveAgent v1.0.2 Justin Bowen shipped a patch release of the Rails framework for building AI agents, adding Azure OpenAI, AWS Bedrock, Google Gemini, and RubyLLM providers. It also fixes Anthropic streaming, empty tool-input, and Ollama stream-completion errors, PDF attachment handling, and provider config leakage.

gem-skill Dewayne VanHoozer released a Ruby CLI that generates SKILL.md files for gems, giving AI coding agents accurate API docs at session start where LLM training data is lacking. Framing the trouble with skills as common to human and AI developers, he shipped version 0.2.0 with a --verify flag that checks docs against a gem's source and auto-updates stale ones.

Compound Engineering Update Kieran Klaassen and Trevin Chow shipped a major rework of their Compound Engineering plugin, replacing standalone agent definitions with self-contained skills so it runs natively across Claude Code, Codex, Cursor, and more. A unified "/goal-ready" plan doc now drives multi-hour autonomous runs, one topping six hours that wrote tests and shipped a PR autonomously.

ruby-llm-eval Alex Kholodniak built a Ruby-first LLM evaluation harness that hands models Ruby and Rails problems and scores their generated code against hidden tests. He found even gpt-4o-mini at ~$0.01 a run solves all 14 Rails tasks, with pricier tiers buying more idiomatic style (83% to 93% clean) rather than better correctness.

Nuke on Rails v0.5.0 Alan Alves updated his open-source Claude Code skill that audits Rails repos like a principal engineer, growing from 9 to 15 checks for full OWASP Top 10 coverage. It wraps four Ruby static-analysis engines, uses an LLM to triage and adversarially verify findings, and now catches AI/LLM risks like prompt injection and PII sent to model APIs.

Plastic Zlatko Alomerovic built an open-source, intent-driven work system in Ruby for AI-assisted development, where each "intent" moves through a Why, What, How, and Execute cycle that produces Markdown artifacts (spec.md, plan.md, checklist.md, outcome.md).

RubyLLM::Agents v3.14.0 Adham El-Deeb shipped a release of his Rails engine for building and monitoring AI agents on top of RubyLLM. It adds concurrent tool execution, cost tracking for prompt caching and reasoning tokens, HTTP-level latency instrumentation, and config for more providers like Bedrock and xAI.

Rubyn Code v0.7.0 Matthew Suttles shared an efficiency update to his open-source agentic coding assistant for Ruby and Rails. Its new opt-in Chisel mode counters AI agents' tendency to over-build, making the agent walk a decision ladder and write the minimum that works without cutting validation, security, or error handling.

llm_cost_tracker 0.13.0 Sergii Khomenko created a new release of his self-hosted Rails gem that logs every LLM call. The update sharpens accounting accuracy with a Data Quality page for quarantined rows, retries for failed async ingestion, multi-currency support, and a raised error on unrecognized token keys to catch typos.

llm.rb v12.0.0 Released Robert pushed a major version of llm.rb, Ruby's multi-provider AI runtime with MCP/A2A support and built-in agent tools. The release makes OpenAI's Responses API the default, moves image generation to gpt-image, and adds DeepInfra and Bedrock providers.

lumen-llm GitHub user uxgnod extracted a tiny LLM prompt runner from a legacy Rails app. It renders YAML prompts with Ruby variables, calls OpenRouter, and parses JSON or text. Built for old stacks, it runs on Ruby 2.3+ and Rails 4+ with zero runtime dependencies and no agents, tools, or streaming.

hidaping Carlos Daniel Pohlod showed off hidaping, a work-in-progress Ruby gem wrapping the HIDAPI library so you can talk to HID hardware like mice, gamepads, and joysticks over USB or Bluetooth. His demo captured live mouse movement and button clicks in Ruby, though he noted FFI or Linux evdev are sturdier for production.

Packlight Cory C. shared build-in-public progress on his invite-only community garage sale platform built with Rails, where users drop photos into cloud storage and AI generates each listing's title, description, and price. A swappable multi-provider layer runs on Gemini 2.5 Flash first, with Claude and OpenAI next.

Ubuteco Lucas Sartori relayed how he stopped treating AI as autocomplete and onboarded it like a teammate on uButeco, a multi-tenant Rails API and Next.js bar-management app. To curb architectural drift, he committed ADRs, context docs, and numbered implementation plans so the AI stops reopening settled decisions.

Chero Hammad Shahid launched an AI-powered email assistant built with Rails and OpenAI that generates context-aware replies in one click, auto-responds to new mail, drafts from a prompt or voice, and lets you chat with your inbox while keeping Gmail and Outlook synced.

Rails Mid-Level Interview Prep Celso de Sá released a free flashcard deck and mock-interview workflow that turns a coding agent into a strict Rails interviewer. It pairs 78 scored flashcards with research and interviewer instructions in AGENTS.md, covering theory, coding, debugging, architecture, system design, and behavioral questions.

AI Cover Letter Generator with Groq Ameer Hamza Mushtaq open-sourced a small Rails app that generates tailored cover letters through the Groq LLM API. Built as a hands-on exercise in LLM integration, it explores prompt design, response handling, and structuring AI services within a Rails codebase.

ClaudeBar Nicolas Erlichman created a native macOS / SwiftUI menu bar app that surfaces every running Claude Code session across terminal, desktop, and VSCode, with 5-hour and weekly usage windows, API-equivalent cost estimates, and one-click jumping to any session.

Daily AI Insights David Paluy launched a public daily feed on Telegram and WhatsApp curating the AI releases, tools, agent workflows, and model updates worth attention, with a quick verdict on what he'd actually use, ignore, or watch.

Free Ruby on Rails Consultations Visuality offered a community give-back with a free 30-minute call with a matched expert on whatever you're stuck on, spanning architecture, performance, deployment, Hotwire, databases, QA, and AI. Submit your challenge through a form and they connect you with the right person from their team.

Shopify Joins the Ruby Alliance Ruby Central announced that Shopify, one of the largest Ruby organizations, joined the Ruby Alliance, its corporate membership program funding the language's critical infrastructure. The move signals a long-term investment in the health and sustainability of Ruby's open-source tooling and community.

RDoc 8.0.0 Stan Lo shipped the biggest RDoc release in years, swapping the legacy Ripper parser for Prism, surfacing RBS type signatures alongside method docs in HTML and ri, and adding a live-reload preview server via rdoc --server. RBS files can now serve as a documentation source, and RDoc even got a logo.

Here Are the Rails World 2026 Speakers The Rails Foundation revealed the lineup for the fourth Rails World, in Austin this fall. Half of all CFP submissions were AI-related, yielding talks on building AI pipelines in Rails, using agents in development workflows, and structuring codebases for agent assistance.

Articles

Elastic Software: The AI-Powered Design Pattern Every Engineer Needs to Know Michael Carroll introduced "elastic software", where you route data through an LLM to start flexible, then buy efficiency as the math justifies. His healthcare example swapped thousands of per-client parsers for a few lines of RubyLLM, hardening only high-volume clients while "tokenomics" signals when to optimize.

Testing GLM-5.2 on a Rails Upgrade Mario Chávez used GLM-5.2, an open-weight model from Z.ai, via the Oh-My-Pi terminal agent to upgrade a legacy app from Rails 6.1 to 8.1, drop Node, and migrate Postgres to SQLite. It cleared all five version hops, fixed codebase-specific deprecations, and even launched OrbStack itself when Docker was down, landing 16 commits across 247 files.

Ruby 4.0 Is Here. Why Is AI Still Writing Ruby 3.0? Germán Alberto Giménez Silva argued that AI assistants generate syntactically correct but dated Ruby, defaulting to {user: user} over {user:} and |n| n 2 over it 2. He blamed a feedback loop where models train on old code and developers learn from models, and said the fix is teaching assistants modern idioms, not patching output with RuboCop.

Prompt Regression Rails: Catch It Before Users Andrés Coronel shared how to stop prompt changes from silently degrading LLM output in Rails by adding evals that score outputs before shipping. He walked through exact-match, golden-set, and LLM-as-judge approaches, with Ruby classes that send responses to GPT-4o-mini against a rubric and a rake evals:run task to gate CI.

Chatwoot Is One of the Best-Built Rails Apps Shipping. That's Exactly Why My AI Agent Failed on It Luc Perussault Diallo showed how Chatwoot's clean Rails patterns (polymorphic associations, concerns, service objects, background jobs) hide relationships that grep-based AI agents can't see, missing nine of the Inbox model's critical dependencies.

Mutate All Things Stas Katkov argued that LLMs void the old objection that 100% mutation coverage costs too much. Pairing Ruby's mutant gem with an LLM to triage failing mutants (which need tests, which reveal real bugs), he swept three open-source projects, surfacing bugs and dead code and shipping refactors with zero production issues.

Building AI Agents in Ruby with the Anthropic SDK Nikita Sinenko walked through building production agents on the official Anthropic Ruby SDK in Rails, running the tool-use loop in Solid Queue jobs, scoping tools through Pundit policies, streaming results over Turbo Streams, and cutting costs up to 90% with prompt caching. He covered prompt-injection defenses, human-in-the-loop approval, and WebMock-based testing.

Building AI Agents in Ruby with the Gemini Interactions API Nikita Sinenko also showed how to build Gemini agents in Rails without an official SDK, calling the Interactions API through a Faraday client. The API keeps conversation state server-side, so turns continue via previous_interaction_id, and he capped the loop at 8 steps and split writes into a preview-then-execute phase the user confirms before Rails runs it.

How I'd Start a Legacy Modernization Project Now Mike Doel explained how AI reshapes legacy modernization. Discovery that once took days now happens fast, making even full rewrites more viable. He runs code analysis and stakeholder interviews in parallel and ships a scored diagnosis rating each finding by severity and whether it's a capacity or a capability gap.

The Future of AI Engineering Is YAML-Driven Development Han Ng argued that Markdown specs break down for automation, and pitched "YAML-Driven Development" powered by YAMLScript and its Ruby gem: specs become strict, machine-readable contracts AI agents parse without hallucinating, can execute logic inline, and compile straight into Kubernetes manifests, OpenAPI schemas, and CI pipelines.

AI Crawlers Are Inflating Your View Counts Trésor Bireke described how AI crawlers making ~100,000 requests a day inflated a Rails app's server-side view counts, since Ahoy's device_detector bot list misses the new wave. He moved tracking to a Stimulus beacon that fires only when JavaScript runs, then blocked bots that scraped the endpoint directly with robots.txt and a 204 early-return guard.

You Can Ask Your Coding Agent for a Selector to Compare UI Options Benito Serna shared a workflow where you ask a coding agent to build several variations of a UI element plus a throwaway dropdown to switch between them live. His example wired a Stimulus controller, a

RoboRuby

Ruby AI News - August 5th, 2026

Contents

Top Stories

A Core Problem

The Machine Forge

Conventional Wisdom

Need to Know AI News

Content

Announcements

Articles

Videos

Podcasts

Newsletters

Discussions

Additional Reading

Events

Previous

Upcoming

Open Source Updates

Code Spotlight

New Gems

New Open Source

Jobs & Opportunities

Featured

One Last Thing

Ruby AI News - July 17th, 2026

Contents

Top Stories

Open Knowledge Format, Ruby Style

In the Beginning, There was Eliza

San Francisco Ruby Conference, Part Two

Need to Know AI News

Content

Announcements

Articles

Videos

Podcasts

Additional Reading

Events

Previous

Upcoming

Open Source Updates

Code Spotlight

New Gems

New Open Source

Jobs & Opportunities

Featured

One Last Thing

Ruby AI News - July 2nd, 2026

Contents

Top Stories

Legacy Rails Apps Get an AI Update

The Need for Speed

Loops and Goals

Need to Know AI News

Content

Announcements

Articles