👋 Howdy, GTM Engineer!

Did you catch the big drop?

Clay is officially one of the first apps in the ChatGPT Appstore.

Sellers, Recruiters, Marketers, VCs, and other individual users can now create their own workflows without having to build or go into a Clay table.

There are some limitations and not all prompts work, so I’ve put together a list of 15 prompts to get you started.

Try them in ChatGPT

Happy automating.

Alex

👇️ 15 Prompts for Clay in ChatGPT

Prompts: Simple Contact Research

@Clay find the mobile number of [NAME] who works at [COMPANY]

@Clay find the work email of [NAME] who works at [COMPANY]

@Clay find the LinkedIn profiles of these emails: [EMAIL 1], [EMAIL 2], etc.

• Ex, copy email addresses from your Google Cal to do some quick research before a call

@Clay find the [DEPARTMENT] leaders at [COMPANY] and find the last podcast that they have been on.

Prompts: Finding People w/ Specific Criteria

@Clay find [TITLES] at [COMPANY] who have joined in the last 6 months. Tell me what company they are coming from

@Clay find everyone in the [DEPARTMENT] who work at [COMPANY] who are located in [CITY]

👉️ Great to use if you are putting together an event and need to source people quickly.

 @Clay find all of the [TITLE] that work at the following companies: [COMPANY 1], [COMPANY 2], [COMPANY 3], etc.

@Clay find the [FOUNDERS] who work at [COMPANY] and tell me how many years experience they have in [FIELD]

👉️ Great for VCs to do rapid due diligence on Founders or their team of engineers.

@Clay find everyone that works in [DEPARTMENT] at [COMPANY] and tell me how long they have been at the company & how many promotions they’ve received

👉️ Great for recruiters to spot rising talent

Prompts: Company Research

@Clay show me [COMPANY]’s hiring trends, tech stack, and new product announcements.

@Clay research hiring trends at [COMPANY]. What roles are they hiring and where are they hiring those roles? Write a summary of their expansion plans based on this research.

@Clay research and compare the hiring trends of [COMPANY 1] and [COMPANY 2]. Summarize conclusions about what their focused on comparatively.

👉️ Great for competitive/comparative research

Prompts: Account Plan

@Clay research all [DEPARTMENT] leadership at [COMPANY]. Then research the company and create an account plan with the the people, initiatives, an strategies to break into [COMPANY] selling [YOUR COMPANY]

Example Account Plan:

Example Account Plan generated by Clay + ChatGPT

Prompts: Personalizing Outreach + Emails Generation

@Clay find and research the [TITLE] at [COMPANY]. Research the company’s growth initiatives. Then draft a personalized email introducing [YOUR COMPANY] and tie the pitch to the research gathered. The email should have a strong hook and call out an immediate growth initiative to impact.

@Clay draft an email referencing [COMPANY]’s [TITLE] recent interviews and their AI spend in 120 words or less.

Multi Toolchain Prompting

This is where things are gonna get event more interesting…

Step 1: Find data in Clay

Step 2: Use that data in another tool that you call in the same ChatGPT conversation.

Here’s an example:

I searched for Databrick’s sales leadership and then asked ChatGPT image generation to create an org chart of those people.

Granted, this isn’t perfect… but we’re getting there!

Stay tuned for more!

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AI that calls the Real World

👋 Howdy, GTM Engineer!

I attended one of the best AI in GTM events in NYC last night led by Chris Balestras.

GTM leaders from Clay, Cursor, Kleiner Perkins, and Sensei shared how they evaluate startups to determine:

1. Likelihood of breakout success

2. How much the Founder values / focuses on their sales org

3. How the product will fair long term in the market

Check out the strategies shared in my latest LinkedIn post and check out Chris’ newsletter: GTMBA

This week I’m sharing a workflow that gathers data in a way that Clay cannot…

A voice agent that makes calls, has a conversation, and gathers intelligence to programmatically bring back across hundreds or thousands of SMBs.

This is useful for gathering pricing details that Medspas or other similar local businesses may not share on their website, but that you can only get from calling.

Happy Automating!

— Alex Lindahl, GTM Engineer at Clay

GEAR: Building a Voice Agent that Actually Calls for You

GEAR - ‘GTM Engineers Accelerating Revenue’ is Claymation’s series that highlights GTM Engineers and creative workflows & automations they’re building for modern GTM. Reply to this email if you’re interested and tell me a bit about what you’ve cooked up.

This week: Ashish Datta, Partner at SetFive Consulting

🎯 Objective: Unlocking "Offline" Pricing Data at Scale

We live in a digital-first world, yet a massive amount of high-value competitive intelligence—specifically pricing in industries like aesthetics and healthcare—remains locked behind a phone line.

Medspas frequently withhold pricing from their websites for several reasons:

• Dynamic Pricing: Rates fluctuate based on inventory or seasonality.

• Sales Psychology: They want to convert a caller, not just inform a browser.

• Competitive Opacity: Keeping rivals in the dark.

Traditionally, gathering this data requires a BDR to sit on a phone for hours, navigating IVR trees and manually transcribing numbers. This is unscalable.

The Solution: An automated voice agent workflow that sources targets via Clay, calls them using OpenAI Realtime API, navigates phone trees, and extracts structured pricing data back into Clay or a database.

⚙ The Tech Stack

• Source: Clay (Google Maps Integration)

• Telephony: Twilio (Media Streams API)

• Intelligence: OpenAI Realtime API (Voice-to-Voice)

• Orchestration: Setfive (Custom infrastructure)

👇 The Step-by-Step Build

Step 1: Building the "Hit List" in Clay

Before you can dial, you need verified targets. We needed to find Medspas in specific high-volume metros—Boston, Dallas, and Miami—to test the system.

Instead of buying stale lists or scraping manually, we used Clay’s Find Local Businesses source (powered by Google Maps).

1. Input: Categories (Medspa, Aesthetics, Laser Clinic) + Location (Boston, Dallas, Miami).

2. Enrichment: Clay instantly pulled the Business Name, Formatted Phone Number, and Website.

3. Export: We generated a clean CSV of verified local businesses in seconds, ready to be fed into our dialing infrastructure. Clay took what used to be a day of manual research and turned it into a 5-minute workflow.

Google Maps in Clay

Step 2: eliminating Latency with OpenAI Realtime API

OpenAI Realtime API Voice 2 Voice

The biggest hurdle in AI voice agents has historically been latency. The old stack looked like this: Speech-to-Text -> LLM Processing -> Text-to-Speech. This resulted in awkward pauses that immediately signaled to the recipient that they were talking to a bot.

We leveraged the OpenAI Realtime API to solve this. Because it handles native audio-to-audio processing, we achieved:

• Human-level Latency: No awkward waiting periods.

• Interruptibility: The AI stops talking instantly if the human interjects, just like a real conversation.

• Function Calling: Triggering backend actions mid-call.

Step 3: Bridging the Audio via Twilio

To get the AI on the actual telephone network, we utilized Twilio Media Streams. This allows us to pipe the raw audio stream directly from the phone call into OpenAI.

The architecture ensures that the Medspa receptionist hears a responsive potential customer, capable of handling unexpected conversational pivots, rather than a rigid script.

Step 4: The "Press 1" Problem (DTMF Simulation)

A major friction point in calling local businesses is the Interactive Voice Response (IVR) system (e.g.,"Press 1 for appointments"). These systems listen for Dual-Tone Multi-Frequency (DTMF) signals, not voice commands.

We built a layer on top of Twilio’s callback architecture that allows our AI Agent to:

1. Listen to the menu options.

2. Decide which path leads to a human (e.g.,"Front Desk" or "Appointments").

3. Simulate the physical button press (DTMF tone) to bypass the menu and connect the call.

Step 5: Converting Chatter to JSON

Getting a human on the line is only half the battle. The goal is data extraction.

Using system prompts designed for structured output, the AI engages in natural conversation to uncover pricing (e.g.,"How much is a first-time Botox unit?"). Even if the pricing is mentioned casually or amidst small talk, the system captures it.

The Output: The agent takes the free-flowing conversation and returns clean, structured data (JSON) containing pricing, availability, and specific conditions (first-time customer deals, minimums, etc.) that can be piped back into your CRM or database.

Step 6: Handling the "No Answer" Scenario

Small businesses are busy. Often, they don’t pick up. To ensure high success rates without harassing the business with repeated calls, we implemented a full communication cycle loop:

• Voicemail Detection: The AI recognizes when it has hit an inbox.

• Message Drop: It leaves a natural, context-aware message requesting the specific information needed.

• Inbound Handling: When the business calls back, the system picks up and seamlessly resumes the objective to gather the data.

💡 You can also send this data back to Clay via a Webhook so that you can perform further analysis, enrichment, or data transformation on the data collected.

🚀 Results & Demo

By combining Clay's ability to instantly map local markets with OpenAI's conversational speed, we transformed a manual, high-friction research task into a scalable GTM engine.

Want to hear it in action?

Listen to the Demo at voice2data.setfive.com

If you're interested in implementing voice-based data gathering for your GTM motion, reach out to Ashish: contact@setfive.com

New in GTM Tech: Chainlit

Chainlit.io

Chainlit is a framework for building your own AI applications that look and feel like ChatGPT. It’s being used by teams at Google, NVIDIA, Microsoft and smaller companies like BuzzFeed & Backmarket.

A customer showed me their app in action and it was pretty slick! It’s like they made their own ChatGPT-style app for their sales team. It’s growing in popularity and has over 50,000 monthly developers building on it.

Chainlit.io

GTM Engineer Jobs of the Week

Primary Ventures - Associates for GTM Engineering Team

Primary, a leading seed stage VC firm in New York, is hiring 2 new Associates for their GTM team. Primary’s GTM team works side by side with early stage founders to help them build GTM systems and workflows, run growth experiments, and drive pipeline and revenue.   This role is great for an early career SDR, Sales, or GTM professional that would love the exposure to a VC firm and to hone their growth skills. In this role you will learn pipeline building tools and techniques as well as technical skills.  You must be based in NYC as we are 3-4 days per week in office.  Contact Gelman@primary.vc to apply.

Harness - GTM Engineer

• Comp: Unknown

• Location: Bengaluru, India

• Company: Just raised $240M Series E round of financing. Company providers developer tooling platform for DevOps and Automation to help engineering teams ship code faster

Scarlet / Jack & Jill - GTM Engineer

• Comp: Unknown

• Location: London, UK

• Company: Jack & Jill AI is a recruitment platform that utilizes specialized AI personas to connect job seekers with employment opportunities and assist companies in hiring talent more efficiently. The service features Jack, who acts as a career coach and recruiter for candidates, and Jill, who sources and screens candidates for employers at a fraction of the cost of traditional agencies.

IronCircle - GTM Engineer

• Comp: $120k - $140k OTE

• Location: Columbia, MD

• Company: Jack & Jill AI is a recruitment platform that utilizes specialized AI personas to connect job seekers with employment opportunities and assist companies in hiring talent more efficiently. The service features Jack, who acts as a career coach and recruiter for candidates, and Jill, who sources and screens candidates for employers at a fraction of the cost of traditional agencies.

Goblins - Head of Growth Engineering

• Comp: ~$150k to $250k Base + Equity

• Location: Brooklyn, NY (will pay for relocation)

• Company: Goblins is building the AI tutor students actually treat like a friend (2x MoM growth, 82% retention, 4x viral coefficient). Backed by the Gates Foundation, we are supply-constrained—closing massive school districts in 6 weeks vs the industry standard of 18 months. We need a Head of Growth Eng to pour gasoline on the fire—using code, not ads, to engineer the automated systems that will scale us to 1 Million Students.

What I’m Reading: System of Record vs. System of Action

a16z Big Ideas for 2026

But also:

Long Live Systems of Record

Systems of Record are Dead. Long Live Systems of Record. Every few weeks I see some version of the same claim: “The new system of record is the agent,” or “Workflows swallow systems of record,” or “Data is the system of record, apps are just thin views.” There is a grain of truth in each of those, but I think it is also easy to over-rotate and accidentally throw out the thing enterprises still need most, which is not a “system of record” as much as a reliable source of truth.

cloudedjudgement.substack.com/p/clouded-judgement-121225-long-live

System of Action — Part 1: Hero Tools | Tidemark

In vertical SaaS, the next battleground is the system of action—where AI doesn’t just help run the business, it does the work. The winner gets the user, the workflow, and the economics.

www.tidemarkcap.com/post/the-race-to-become-the-system-of-action

Data Teams Aren’t Dying. They’re Finally Becoming What We Hoped They’d Be.

AI is making data teams smaller, sharper, and harder to fake your way into

hanson377.substack.com/p/data-teams-arent-dying-theyre-finally?triedRedirect=true

Bonus: State of GTM Engineering Report

I’m putting together the first State of GTM Engineering report with my friends Garrett Wolfe Author of Garrett’s Growth Substack and Maja Voje, Author or The GTM Strategist.

AI-native CRM

“When I first opened Attio, I instantly got the feeling this was the next generation of CRM.”
— Margaret Shen, Head of GTM at Modal

Attio is the AI-native CRM for modern teams. With automatic enrichment, call intelligence, AI agents, flexible workflows and more, Attio works for any business and only takes minutes to set up.

Join industry leaders like Granola, Taskrabbit, Flatfile and more.

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Hey, GTM Engineers! 

Welcome to the 2nd Edition of GEAR - GTM Engineers Accelerating Revenue.

GEAR highlights the best workflows, ideas, & creative plays from the community. This week’s GEAR is from Diana Marcela Gonzalez, a Sr. Product Growth Manager at RevPartners - a Clay Partner and HubSpot Elite Partner.

This guide walks through how to use Clay + HubSpot to build a system that:

1. Prioritizes the right ICP, warm accounts + people

2. Eliminates the vast majority of grunt work for BDRs

3. Provides prospecting guidance to BDRs in HubSpot

   1. Ice breaker summary

   2. Pain point summary

   3. ‘Poke the bear’ summary

4. Gives BDRs time back to reinvest into prospecting

Prospecting isn’t broken, it’s just under engineered.

Today, there are too many tools, too many tabs, too much context switching, too many tasks, and too much time wasted chasing scraps of data instead of actually talking to people. 

It’s not their fault.

The system is under-engineered and relies on outdated playbooks.

This is how you can build a better prospecting system with HubSpot + Clay.

Happy Automating!

Alex

P.s. give me a shout if you have a killer workflow you’d like to share!

‼️ Problem

Buyers are changing how they buy, and we (GMTEs) must adjust how we help our teams go to market.

Buyers have changed their purchasing habits:

• They’re even more informed (hello, ChatGPT)

• Better briefed with the real tea from peers & community convos

• Expect a more tailored experience because that’s what the best companies are doing.

Getting to a conversation is harder. There’s a greater expectation of due diligence. BDRs + AEs need to come in prepared to tailor. 

Juggling all these steps between systems just KILLS productivity.

The result is outreach that feels cold and rushed. And buyers can tell when they’re just another name on a list.

🎯 Objective

Take away the grunt work. Codify the best practices from the best reps. Build an automated pipeline that delivers what BDRs need to stay focused on prospecting.

⚙️ Enter ‘Assisted Prospecting’ with Clay + HubSpot

That’s where assisted prospecting comes in. It cuts out the busy work, shows you the right signals, and makes it clear who to reach out to, why they matter, and when to do it. 

Imagine a world where…

1. Prospecting teams are being fed a list of companies and contacts that are already interacting with your brand. 

2. The lists are coming through fully enriched, signals are flowing through, and prospecting content snippets and tips are readily available to the prospecting team. 

3. These data points are used to prioritized lists for the prospecting team based on timed relevance. 

4. Best of all, it’s readily available within HubSpot (where the BDRs work) - powered by Clay. 

 🪜 7 Steps to setup Clay + HubSpot:

Step 1: Build lists based on signals

Create the Clay tables that constantly source prospects from 1st and 3rd party sources. A few examples below. 

• Warm Interactions: 

  • Website visitors

  • LinkedIn followers or interactions

  • LinkedIn post interactions

  • Product Sign Ups (for PLG motions)

• Cold Intent:

  • New hires

  • Job changes

  • Lookalikes

  • Funding rounds

‼️ Don’t shy away from building lists out of custom signals.

AI Prompts: Uncovering Unique Ideal Customer Signals with Clay

A 3-step guide to finding unique ideal customer signals using Clay's custom signals, transforming GTM strategy with precision targeting and data-driven insights.

www.claymation.io/p/prompt-finding-ideal-customer-signals-for-clay-custom-signals

Step 2: Layer enrichments & AI categorization

Every single company or contact sourced goes through firmographic, demographic and technographic enrichment (if needed). 

This information is then leveraged through Claygents that: 

• Pre-qualify for ICP: Does this company meet my minimum requirements of a good-fit prospect?

• Pre-qualify for Buyer Persona: Is this a person of interest for my buying cycle? If not, let’s source more relevant titles. 

Once pre-qualified, Clay validates emails, updates roles, and fills in missing details like phone numbers or other company info. 

Only pre-qualified prospects make it into HubSpot.

Step 3: Automate account research & outreach prompts

Source any and all information your prospecting team is currently researching manually.

Use a Claygent to analyze buyer persona, paint points, etc and provide custom prospecting snippets for your team. We recommend these three: 

• Ice breaker summary: brings in context about the prospect and ties it to the product/service of interest. 

• Pain point summary: leverages the context of the prospect’s role and LinkedIn headline + company to weave in the pain point tied to the product/service. 

• Poke the bear: question to be used at the end of an outreach email in order to spark a conversation.

AI Prompts: Competitive Research & GTM Signals

Discover 2 advanced DeepResearch prompts for competitive analysis: Uncover strategic insights, compare enterprise tech solutions, and develop custom market signals.

www.claymation.io/p/ai-prompts-competitive-research-signals-using-deepresearch-clay

You’ll map these to fields in HubSpot so they show up:

Step 4: Prioritize orospects to route to XDRs

Not every account deserves the same attention. Casual website visitor does not = high-intent buyer. Layers of AI will help us filter.

First, enrichment fills in the basics: firmographics, demographics, and the right contacts so reps can multi-thread. Then scoring weighs intent signals like funding rounds, job postings, tech stack changes, or spikes in site visits.

With that data in place, accounts fall into clear tiers:

• Tier 1: High-intent, worth personalized, high-touch outreach.
  

• Tier 2: Warm, managed with light automation plus rep follow-up.
  

• Tier 3 - 4: Lower priority, monitored or nurtured by marketing until signals strengthen.

Step 5:  Send data to HubSpot + fill custom cards

Create new “Custom Cards” within HubSpot to make the information available at the Company & Contact level. 

Company Prospecting Card should include: 

• Company Firmographics

• Relevant Signals

• Relevant Contacts 

• Previous Sales Processes

• Previous Outreach & Activity

Contact Custom Cards include: 

• Contact Demographics

• Relevant Signals 

• Prospecting Tips

Step 6: Create a repeatable prospecting process

Having a specific guideline for XDRs to follow or, at least reference, is underrated. Build the process right into HubSpot through: 

• Target Accounts, leveraging tiers. 

• Task assignment when new priority prospects are assigned.

• Step-by-Step guides and recommendations for outreach.

Step 7: Pro tip - allow XDRs to request automated enrichments via HubSpot.

Whether it is a new event list that was uploaded into HubSpot or the renegade account that needs to be enriched - XDRs need a way to be able to do so. And now you can allow them to, directly from HubSpot, triggering a Clay table. 

We call this…On demand enrichment.

You can do this to request: 

• Company firmographics

• Contact demographics

• Contact email & phone number

• Account research & outreach prompts

 🚀 GTM Engineering in Venture Capital

Give me a shout if you’re a VC and thinking about adding GTM Engineering into your offering / platform team. I’m working on something here in NYC that could help you.

🔥 Hot GTM Engineer jobs this week

Your gal to follow is Natalie Ho on LinkedIn. She’s in CX but also working on Clay’s Talent Network where we help match talent to companies looking to hire a GTM Engineer.

These are the hot ones this week that she’s posted about:

👉 GTM Engineer - Miro
Location: Austin
🔗 https://lnkd.in/eekZiuWF

👉 GTM Systems Engineer - OpenAI
Location: NYC, SF
🔗 https://lnkd.in/eNrXeyjc

👉 GTM Engineer - G2
Location: Remote
🔗 https://lnkd.in/er5iQzYu

👉 GTM Engineer - Pendo.io
Location: SF, NYC, Raleigh
🔗 https://lnkd.in/eR5Cpk3d

👉 GTM Engineer - Verkada
Location: San Mateo, CA
🔗 https://lnkd.in/eisAmrVx

👉 GTM Engineer - Atlan
Location: Remote (U.S.)
🔗 https://lnkd.in/eWYiSxUJ

Hey, GTM Engineers!

Did you know you can connect over 500 apps to ChatGPT? Say what!

This week’s guide shows you how to set it up in less than 5 minutes.

Go from using ChatGPT for research to orchestrating actions across different tools to get actually get things done. For example:

Sure you can build Clay + n8n workflows, but that takes time and is probably over complicating for many ad hoc needs. There’s also infinite use cases and workflows.

The newsletter dives into:

• What is an MCP?

• GEAR Technology Spotlight: Rube.app

• GTME Guide: How to Connect 500 Apps in < 5 Minutes

• 5 GTM Engineering Resources

• Fastest Growing Companies hiring GTM Engineers

Happy automating,

Alex

🎯 What is an MCP?

MCP stands for Model Context Protocol.

I love the description and analogy from Nir Diamant’s Substack post (check it out if you want to go into more technical detail):

MCPs are getting added to almost all software. I was hoping my LinkedIn petition to Gong got more traction.

MCP is how Rube.app will help us connect all of those apps to ChatGPT.

Think of it as a unified MCP.

1 MCP connection gets you 500+

⚙️ GEAR Spotlight: Rube.app

Rube is developed by Composio who raised a $25M Series A to build Agents that evolve and learn over time. You can read more about Lightspeed’s investment here: Building the Backbone of Agent Intelligence.

Composio’s platform has already attracted 100,000 developers.

Composio’s Mission

The use cases and tools that you can chain together and access within a chat window become endless.

My hunch is that Clay will evolve in this way:

1. Data marketplace

2. Agent marketplace

3. MCP marketplace

Example MCP Connectors

🪜 The Step by Step

Step 1: Signup to Rube.app

Step 2: Enable Developer Mode in ChatGPT + Create Connector

Enabling Dev Mode in ChatGPT

Step 3: Copy 👇️ 

https://rube.app/mcp

Step 4: Add New Connector in ChatGPT

Go to:

1. Settings

2. Connectors

3. Create

Creating the Connector + Adding MCP URL

Step 5: Add Connectors in the Rube Marketplace

Step 6: Start ChatGPT and use Rube in Dev Mode

📌 GTM Engineer Job Opening of the Week

James Hunsberger, Head of GTM Engineering & Technology, announced Miro is hiring their first GTM Engineer.

Apply here: https://www.linkedin.com/jobs/view/4303420837

Miro’s 1st GTM Engineer

📖 GTM Engineering Resources

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Yash Yekriwal was the 1st GTM Engineer at Clay (now Head of Education) and is one of the reasons I’m here and writing this newsletter. He has a must read newsletter “Know Your Growth”. This is his latest post:

The Evolution of Go-To-Market Engineering

What is GTM engineering + when and how to hire a GTME.

knowyourgrowth.substack.com/p/the-evolution-of-go-to-market-engineering?triedRedirect=true

Nathan Lippi founder of Clay Bootcamp (I believe it was the first) and helps GTM Engineers learn their craft and find their next job opportunity. Not much has been posted about GTM Engineering salaries, so this was a great one to see:

Kaylee Edmondson, Founder of DemandLoops, shared what she is seeing actually work in B2B marketing right now:

Alex Carstens, Sr. RevOps Consultant at GoNimbly, shared how to use Clay + Gong Engage’s new email customization features.

Check out his guest Claybook on Claymation, too: The Ultimate Inbound Lead Workflow

New Email Customization Features in Going Engage! ✉️ | Alex Carstens | 19 comments

Gong just released a small feature with a BIG impact. If you are a Gong Engage user with Clay you can now completely customize your flow steps via Clay! This means custom subjects, custom body of emails even custom call scripts! Gong has updated their API now to include this! Every prospects outreach can be personalized now from Clay enrichments and Gong call transcripts. Who needs A/B sequences and steps when you just personalize the whole dang thing. Here is a how to: https://lnkd.in/gSDDzj_U | 19 comments on LinkedIn

www.linkedin.com/posts/alex-carstens-a3533484_new-email-customization-features-in-going-activity-7374092916270518272-rO3L?utm_source=share&utm_medium=member_desktop&rcm=ACoAAADgy0kBymu-qePVUG1-XD6dxilwMD5sFvo

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Meet Sculptor

Hey, GTM Engineers!

Ever stare at a Clay Table knowing there’s gold inside, but you just can’t dig fast enough?

That’s why I’m so excited about the announcement of Sculptor today at Sculpt (Clay’s first user conference).

With Clay Sculptor, you don’t just build tables—you talk to your data. Instantly analyze, fix, and enrich your sources in the flow of work. No more exporting to ChatGPT, no endless cleanup.

This week, I’ll walk through a workflow that uncovered patterns in the Forbes Cloud 100 list. And yes, I’ll hand you the exact steps to steal for your next GTM sprint.

Before we dive in, check out the other announcements:

Okay, back to Sculptor.

Think of Sculptor as your co-pilot that helps you:

1. Build Clay tables with prompt

2. Add to existing Clay tables with a prompt

3. Troubleshoot & fix issues if they occur

4. Analyze data within Clay tables

The touted primary use case is to help accelerate the users’ table building journey.

However, I’d argue that the killer starting use case is actually data analysis.

Here’s a couple of data analysis examples with Sculptor:

• RevOps: Analyze your best Closed Won deals to find commonalities.

• Sales: Ask Sculptor to prioritize the top X accounts based on certain criteria.

• Sales: Ask Scultpor for specific statistics that you want to include in QBRs.

• Marketing: Did our scoring methodology correlate to conversions or should it be adjusted?

• Sales Enablement: Import Gong transcripts and analyze calls reps or deals.

• Venture Capital: Analyze a list of startups to find hidden trends (what I’ll show you in this post)

Basically any data set you’d download and then upload to ChatGPT for analysis — you can now do within a Clay table.

This week’s workflow will analyze the Forbes’ Cloud 100 List to figure out if there are any correlations between valuation and types of AI provided by each company.

Happy Building!

Alex

🎯 Objectives:

1. Upload the Forbes Cloud 100

2. Enrich companies & use Claygent to analyze AI capabilities

3. Use Sculptor to add to the table

4. Use Sculptor to ask questions &

⚙️ GEAR Spotlight: Sculptor

Check out produce page here

Table Builder

Use Sculptor to build tables for you

Data Analyst

Use Sculptor to ask

📹️ Sculptor Demo of the Workflow

➡️ The Workflow

🪜 The Step by Step

Step 1: Download the Forbes Cloud 100 list + upload to Clay

Bessemer Venture Partners & Salesforce Ventures put together this list every year to highlight the fastest growing, most valuable private companies. Clay was included in the list! What’s also crazy is that Clay has almost all of the top 10 companies as customers and a large portion of the entire 100.

Top 10 on Forbes Cloud 100

Step 2: Add Claygent Columns / Prompts for company analysis

Add various enrichments you’d like to include in your analysis.

If you want to do what I did, then use this prompt that analyzes a company’s documentation, blog posts, etc. to figure out what types of AI the company provides:

• Utility AI (autocomplete, recommendations)

• Assistive AI (copilot, summarizer, forecaster)

• Autonomous AI (agents, auto-execution)

• Platform AI (infrastructure, APIs, orchestration)

• Analytical AI (forecasting, BI, anomaly detection)

• Generative/Creative AI (text, code, media creation)

• Embedded/Ambient AI (background optimization, personalization, ops)

• Specialized/Vertical AI (domain-specific: healthcare, finance, law)

• Governance/Trust AI (responsible AI, compliance, monitoring)

Drop this prompt into Claygent (it will do the first 5) + generate JSON:

#CONTEXT#

You are a Go-To-Market strategist analyzing how a company uses AI. Given a domain, review publicly available sources to analyze the product and categorize its AI capabilities.



#OBJECTIVE#

Research  and produce an AI Usage Map —  classifying the company’s AI across the five categories with Yes/No and concise justifications.



#INSTRUCTIONS#

1. Sources to use (public only):

   - Website (product pages, AI feature pages, vertical pages)

   - Blog posts, press releases, announcements

   - Case studies and customer stories

   - Whitepapers and solution briefs

   - Developer docs and API references

   - GitHub repositories (if public)

   - Trust/compliance/security pages

   - Earnings calls, 10-Ks, investor decks (if public)

   - Analyst reports (Gartner, Forrester, IDC, etc.)

   - Customer reviews (G2, Capterra, TrustRadius)

2. Starting point:

   - Visit the root domain at   From there, navigate to relevant sections listed above.

3. Evidence collection:

   - Extract exact feature names, product pages, and quotes that reference AI usage. Prefer first-party documentation; use third-party sources when first-party is insufficient.

   - Save the specific URLs used for each conclusion.

4. Classification criteria:

   - Utility AI: autocomplete, recommendations, smart suggestions embedded in UI.

   - Assistive AI: copilots, summarizers, predictors, forecasters aiding user tasks.

   - Autonomous AI: agents, multi-step auto-execution, hands-off workflow automation.

   - Platform AI: APIs/SDKs, infrastructure, orchestration layers enabling AI building.

   - Analytical AI: BI, anomaly detection, forecasting, risk scoring/analytics.

5. Decision rules:

   - Mark a category “Yes” only if there is clear, explicit evidence from sources. Otherwise “No”.

   - When ambiguous, default to “No” and explain the uncertainty in the summary.

6. Output formatting:

   - Title: AI Usage Map — 

   - For each category, output: Category → Yes/No. 2-sentence summary referencing concrete features and include one source URL in parentheses at the end.

7. Quality checks:

   - Verify company identity via the site branding on . If the domain appears unrelated to , note the mismatch and proceed cautiously or return “No evidence found”.

   - Avoid paywalled/authenticated content. Use only accessible pages.

   - Do not infer capabilities beyond what is documented.



#EXAMPLES#

Example Output:

AI Usage Map — Acme Corp

Utility AI → Yes. The product includes in-app autocomplete for queries and personalized recommendations on the dashboard (https://acme.com/product).

Assistive AI → No. No credible references to copilots or summarization assistants were found across docs or blog (https://acme.com/blog).

Autonomous AI → Yes. Workflow agent triggers multi-step actions after anomaly detection with minimal user input (https://acme.com/solutions/automation).

Platform AI → No. There are no public AI APIs/SDKs or orchestration features documented (https://acme.com/developers).

Analytical AI → Yes. The analytics suite offers anomaly detection and risk scoring embedded in BI dashboards (https://acme.com/analytics).

Step 3: Start asking questions about the data

📌 GTM Engineering Jobs @ The Fastest Growing Companies

1. Vapi | 1 Yr. Growth : 511.76% | Valuation: $130M | GTM Solutions Engineer

2. AirOps | Growth: 250% | GTM Engineer

3. Rollstack | 1 Yr. Growth: 120% | GTM Engineer

4. OpenAI | 1 Yr. Growth: 117.87% | Valuation: $300B | Analytics Engineer, GTM

5. Pump.co | 1 Yr. Growth: 106% | GTM Engineer (Clay Experience)

6. Stedi | 1 Yr. Growth: 89.74% | Valuation: $200M | GTM Engineer

7. Tailscale | 1 Yr. Growth: 61.65% | Valuation: $1.4B | AI GTM Engineer

8. Atlan | 1 Yr. Growth: 55.33% | Valuation: $750M | GTM Engineer

9. Basis Theory | 1 Yr. Growth: 39.28% | Senior GTM Engineer

📖 GTM Engineering Resource of the Week

Sharon Roessen, COO of Terrapinn, provides a really nice overview of how to use Clay for B2B events.

Terrapinn rolls out Clay AI tool for B2B events | Sharon Roessen posted on the topic | LinkedIn

Six months ago, we started experimenting with Clay, an AI-powered data tool that promised to transform how we do sales and marketing at Terrapinn. Fast forward three pilots, countless hours of consultancy, and plenty of lessons learned… and we’re ready to roll it out across the business. We’ve even written our own Clay Playbook, built for the world of B2B events. Image below. It covers everything from winbacks and cross-sells, to account-based sales, competitor analysis, prospect enrichment, new product launches, lead scoring, and more. For us, Clay isn’t just another tool. It’s a shift in how we think about data, targeting, and growth. And signals, the new term thats entered our vocabulary. We’re still learning, but one thing is clear: AI tools like Clay will become the backbone of how high-performing B2B businesses scale. I’d love to hear from others experimenting with Clay (or similar tools). What’s worked? What hasn’t? What have I missed in the playbook? Leonela Serrano Ashley Artrip Clay Jaimie Featherstone Nicola Wartnaby James Llewellyn-Smith Harry Mason #AI #B2BEvents #MarketingTechnology #EventTech | 33 comments on LinkedIn

www.linkedin.com/feed/update/urn:li:activity:7371446961130074112

👀 What I’m Reading

17 Tools To Make You More Productive In GTM

How I currently use, and see others, using the tons of tools out there in 2025

gtmba.beehiiv.com/p/the-17-tools-i-use-to-be-more-productive

#publicspeaking #keynote | Kyle Poyar | 42 comments

How to nail your next big talk 👇 I used to be terrified of public speaking. But I pushed through the nerves (with an assist from Big Pharma) & am absolutely glad I did. If you're even a little bit like me, you'll want to bookmark this post from Vincent Pierri. He's personally delivered 300+ unique talks over the last 5 years. Now he's sharing his proven framework for a better 30 min keynote. Read the full story in Growth Unhinged here: https://lnkd.in/eydNVYxG The framework in four steps: 1️⃣ Nail the intro (5 minutes) Every great talk begins with tension. Think of your intro as the “hook.” It’s where you earn the right to keep people’s attention. If you lose the first five minutes, you’ll spend the next twenty-five trying to win them back. 2️⃣ Build trust (3 minutes) Trust-building is where you prove you’ve walked the path. And your title isn't enough to get the audience on your side. Three ways to do it: - Experience. A quick story of failure, experiment, or success. - Research. Credible data, case studies, or benchmarks. - Relatability. A short personal story that shows you’ve been in their shoes. 3️⃣ Deliver three main points (3 × 6 minutes) Three points is the sweet spot. Enough to feel substantial. Not so much that people forget them by lunch. Each point follows the same mini-framework: - One-Liner (1 min) - Analogy (2 min) - Examples (3 min) 4️⃣ Close strong (4 minutes) Too many talks fizzle at the end. Instead, close with a one-two punch: - Final Story (2 min) - Call to Action (2 min) --- I can't wait to try out this framework for my next talk. Hope you find it as useful as I did 🙏 #publicspeaking #keynote | 42 comments on LinkedIn

www.linkedin.com/feed/update/urn:li:activity:7374049314882396160?updateEntityUrn=urn%3Ali%3Afs_updateV2%3A%28urn%3Ali%3Aactivity%3A7374049314882396160%2CFEED_DETAIL%2CEMPTY%2CDEFAULT%2Cfalse%29

How to Win the New SEO Game: AI Search, GEO, and the Future of Visibility

A hands-on guide to ranking across AI search engines like ChatGPT, Perplexity, and Google

knowledge.gtmstrategist.com/p/how-to-win-the-new-seo-game-ai-search

AI’s UI Problem Is Actually A New Era of Software | Menlo Ventures

In AI apps, value has shifted from the UI to the hidden scaffolding that connects prompts to outcomes, giving rise to a new type of software.

menlovc.com/perspective/ais-ui-problem-is-actually-a-new-era-of-software

Twitter tweet

Hey, GTM Engineers!

Want to know what the top GTM Engineers are building around world?

I’m launching a new GTM Engineering series called GEAR - GTM Engineers Accelerating Revenue.

Think of this like TED. “Ideas worth spreading,” except for GTM Engineering — “Workflows worth automating”. 

My objectives are to:

1. Highlight GTM Engineers.

2. Showcase automations.

3. Inspire creativity.

4. Teach GTM Engineering

Our first GEAR showcases GTM Engineer, Harshil Bhimani, Founder of Clay Consultancy + Certified Clay Expert, based in Vancouver.

Harshil Bhimani

🏢 Founder, Clay Consultancy 👤 Serial tech entrepreneur: previously built wearables to help powerlifters improve deadlifting form + martial art technique. Check out pic below! 📍 Vancouver, Canada 🍲 Negi Goma Rekka Ramen from Danbo Ramen 🛠️ Specializes in Clay + Attio. 📧 harshil.bhimani@clayconsultancy.com

🎯 Objective:

Automate personalized, handwritten direct mail letters at scale for ABM campaigns.

Harshil’s workflow shows how you can:

• Scale personalization

• Automate handwritten letters via an API

• Automate sending those letters to your ABM accounts

⚙️ GEAR Technology Spotlight: Scribeless

In a world saturated by digital outreach, people barely notice another email. But a handwritten note in your mailbox? That’s hard to ignore. They’re nearly always gets opened.

Scribeless  leverages AI to create truly handwritten letters and postcards. It goes further than automated scripts with lookalike fonts—their technology introduces subtle variations, mimicking a real human hand so expertly that even discerning recipients can’t tell the difference.

Now, with Scribeless, you can personalize and send handwritten mail at scale—100, 1,000, or 10,000—just as easily as sending an email campaign. It integrates with your CRM or workflow tools and supports powerful automation (even via API), so it fits straight into your stack and scales as you grow.

You’ll be in good company as Google, Panasonic, Uber, Allstate and other notable brands are customers.

Example Email:

Scribeless Pricing:

Scribeless.io Pricing

➡️ The Workflow

Clay + Scribeless = Automated ‘Handwritten’ Letter Campaign

🪜 The Step by Step

Step 1: Build & enrich your list in Clay

p.s. sign up here with Harshil’s link for 3,000 free credits

ICP: CROs in Vancouver from software companies with 50 to 2,000 employees.

Enrichments:

• Company description

• Address

• Any other research to help you 1) build a hypothesis of need 2) add context to your letter 3) come up with a compliment to add.

Step 2: Generate your message in Clay

Need some inspiration or help improving your copy? 👇️ 

Emulating Advertising Legends with AI

How to use the tone & style of the masters to write better cold emails

www.claymation.io/p/emulating-advertising-legends-with-ai

Step 3: Create campaign in Scribeless

How to setup a Campaign in Scribeless.io

• Log into Scribeless —> create new campaign

• Go to ‘Direct Mail’

• Remove placeholder text and add custom message

• ‘Next’ —> ‘Create Campaign’

• Copy Campaign ID for future reference

Step 4: Setup API endpoint in Clay

• Add new HTTP API column

• Use ChatGPT to create the API endpoint template

• Copy/paste the API key and the Campaign ID into the template

Step 5: Run the campaign

Note: API column won’t run if you’re missing the location information.

Step 6: Verify handwritten messages

Check the generated messages to ensure they’re correctly formatted & personalized.

Step 7: Scale the process

Scribeless can handle any number of profiles (6, 60, or 600) efficiently within a few minutes.

📌 GTM Engineer Job Opening of the Week

My friend, Corey Pitt, Co-Founder/CEO of Wiser AI, is looking for a Founding GTM Engineer. Check it out 👉️ Job Opening at Wiser AI.

getwiser.io

📖 GTM Engineering Resources

Newsletter Spotlight: Debugging GTM

Check out her newsletter 👉️ https://debugginggtm.substack.com/ 

Chermaine Lee, Founder of Val Town (Zapier for Know Code Engineers), is sharing some really cool workflows and hope to have one of her workflows on GEAR soon.

👉️ Subscribe here.

A couple of recent posts:

• Find every conversation about your dev tool

• How we build an API for Clay

Sign up for GTM Engineer School Cohort 2

Disclosure: I earn a commission if you’re accepted via my link. I put this money back into creating content for ya’ll.

GTP-5 PROMPT Framework for How to AI Substack

Thanks again to Harshil for this week’s gear workflow.

• More on Clay Consultancy below

• Reach out to him at: harshil.bhimani@clayconsultancy.com

Clay Consultancy

At Clay Consultancy, we empower pre-seed and seed-stage startups to scale their most creative outbound ideas. 🚀

We blend cutting-edge outbound strategies with the power of Clay to help ambitious founders break through the noise, validate new markets, and drive real growth-fast. Whether you’re testing a bold hypothesis, building your first pipeline, or looking to supercharge your GTM motion, our team brings the expertise, tools, and hustle to make it happen.

Why work with us?

• Creative Outbound at Scale: We turn wild ideas into repeatable, scalable campaigns.

• Clay Experts: Unlock the full potential of Clay for prospecting, enrichment, and automation.

• Startup DNA: We move fast, iterate, and obsess over results-just like you.

• Ready to grow? Let’s build something remarkable together.

Hey GTM Engineers,

The news is out: Clay has secured a $100M Series C, valuing the company at a $3.1B (up from $1.25B 6 months ago). 🤯 

The round was led by CapitalG (VC arm of Alphabet, Google’s parent company) with existing investors Meritech Capital & Sequoia Capital throwing more in.

When a publication like The New York Times dedicates a story to a funding round, it's because there's a bigger narrative unfolding—a story that goes beyond the numbers.

This investment isn't just about Clay; it's a massive vote of confidence in the rise of a new kind of professional.

We are moving from a "Digital Native" to an "AI-Native" era, where the most valuable skill isn't about knowing a tool, but about mastering the art of how to use and apply AI. 

The GTM Engineer is the pioneer of this new world.

An AI-native knowledge worker treats large-language models, agents, and automation APIs the same way a previous generation treated spreadsheets and email: they’re the default canvas for thinking, creating, and shipping work. That means they co-create with AI, design workflows around AI, and measure success by how much human attention they can redeploy to higher-value problems.

As one of the first GTM Engineer at Clay, I’ve had a front row seat to see this story unfold.

Clay in numbers:

• Number of employees: 180

• Paying customers: 10,000+

• Revenue: $100M by EOY

• GTM Engineering Reddit: 900+

• Claymation’s GTM Engineering Newsletter: 5,000+

• Clay Clubs around the world: 60

• Dataproviders + Integrations: 150+

• Number of GTM Engineer job openings going live each month: 100+

Below are some observations that are worth taking note of.

P.s. are we connected on LinkedIn yet?

The New AI-Native Workforce: Beyond the GTM Engineer

The GTM Engineer was the first sign of an AI-native knowledge worker. But as AI agents become more sophisticated, we're seeing an evolution beyond this initial role. The future workforce isn't just adapting to AI; it's being built around it.

This shift is already visible in the market:

• UiPath has a Sr. Manager of Agentic GTM Operations

• monday.com has a Head of AI for GTM

• Conductor is hiring for a AI Growth Marketing Manager

• Snorkel AI is hiring an AI-driven GTM expert.

These roles are just the beginning. The next wave of specialized, AI-native positions will drive business growth and operational efficiency in ways we haven't seen before.

Here are some of the new roles we can expect to see emerge:

• GTM Agent Builders: Experts in designing, training, and deploying AI agents to execute specific go-to-market strategies.

• Agent Managers: The conductors of the AI orchestra, responsible for overseeing and optimizing the performance of multiple AI agents across an organization.

• Prompt Engineers: Specialists who craft highly effective prompts to guide AI agents toward desired outcomes, ensuring precision and quality.

• Generative Engine Optimization (GEO) Managers: Professionals focused on optimizing content and campaigns specifically for generative AI platforms.

• Answer Engine Optimization (AEO) Managers: Experts who ensure a company's information is discoverable and accurately represented within new AI-powered "answer engines."

GTM Engineers are the only evolution from a digital native to an AI native knowledge worker.

I’ve started to seen others emerge. Below are some examples:

I can see other roles emerging such as:

• GTM Agent Builders

• Agent Managers

• Full time Prompt Engineers

• Generative Engine Optimization (GEO) Managers

• Answer Engine Optimization (AE) Managers

Beyond the ICP: The Rise of Ideal Customer Signals

We've all defined our Ideal Customer Profiles (ICPs) and Personas. They've been the foundation of GTM for a decade. But what if we could move beyond static lists to a dynamic, real-time understanding of our market?

We now must define Ideal Customer Signals (ICS)

Agentic GTM makes this possible.. Instead of just having a profile, you now have a system that can actively listen to the entire public web for signals of intent.

This is the power of a tool like Clay and its Custom Signals. It allows you to:

• Turn any data point into a buying signal. Your competition is looking at job titles and funding rounds. You could be tracking when a prospect's website mentions a specific compliance certification, when they open a new office in a regulated state, or even when a key employee is tagged in a product launch video on LinkedIn.

• Enrich signals with superior context. A simple job change is a decent signal, but what if you could instantly enrich that with the new company's tech stack, recent product launches, and key initiatives? Clay's platform can automatically do the research for you, turning a generic "congrats on the new job" email into a hyper-personalized, high-intent conversation.

• Act on "GTM alpha" that others miss. By creating unique, custom signals, you're not just playing the same game as everyone else—you're playing a new one. This is the difference between a reactive GTM team and a proactive one that uncovers opportunities before they become public knowledge.

AI Prompts: Uncovering Unique Ideal Customer Signals with Clay

A 3-step guide to finding unique ideal customer signals using Clay's custom signals, transforming GTM strategy with precision targeting and data-driven insights.

www.claymation.io/p/prompt-finding-ideal-customer-signals-for-clay-custom-signals

Vibe Coding: The Future of Democratized Engineering

Writing code is quickly becoming a thing of the past. Thanks to AI agents, building MVPs, apps, and websites is no longer a task reserved for engineers. It's becoming accessible to everyone. This is the era of Vibe Coding.

We're seeing a new kind of Moore's Law for AI agents. The complexity of the tasks they can handle is expanding at an exponential rate.

Consider this trend:

In 2022, when ChatGPT was released, AI agents could handle simple coding tasks lasting around 30 seconds.

That capability is doubling approximately every 7 months. Based on this trajectory, we can expect AI agents to handle:

• Today: Tasks up to 1.2 hours

• 2026: Tasks up to 2 hours

• 2027: Tasks up to 8 hours (a full workday)

• 2028: Tasks up to 40 hours (a full work week)

• 2029: Tasks up to 167 hours (a full work month)

This isn't only about cranking out code faster. It's about a fundamental shift in who can build and innovate. The bottleneck isn't implementation; it's imagination.

The new Moore’s Law for AI Agents

The New Frontier: From Coding to Orchestration

The age of the developer as a coder is coming to a close. As AI and agents commoditize implementation, a new bottleneck is emerging—and with it, a new set of essential skills.

The bottleneck is no longer about writing code. It’s about creativity, oversight, and integration.

This shift means our skills must adapt. The future demands a new kind of expertise:

• System Architecture: Designing the blueprint for how AI-powered systems work together.

• Creative Orchestration: Managing and directing "teams of agents" to solve complex problems in novel ways.

• Strategic Oversight: Ensuring that these automated systems align with our broader goals and values.

This isn't about replacement; it's about empowerment. By automating the mundane, we unlock our capacity for higher-level thinking. Humans will be free to focus on strategy, innovation, and solving bigger problems.

The result? We’ll all have a greater ability to impact the world around us. This future is not a distant fantasy; it’s a tangible reality that leaders like Mark Zuckerberg are already outlining in their vision for superintelligence.

Personal Superintelligence

Explore Meta's vision of personal superintelligence, where AI empowers individuals to achieve their goals, create, connect, and lead fulfilling lives. Insights from Mark Zuckerberg on the future of AI and human empowerment.

www.meta.com/superintelligence/?srsltid=AfmBOop2jlrXJWdBO6mHzQOOU7zeiWW0nqWi-YLlAsVgiYlhQZ8sW_f8

System of Record to System of Action

The way GTM teams operate is fundamentally changing. The old model, centered around the CRM as a system of record, is no longer enough. The future is a system of action, and Clay is leading the charge. This is the new battleground for enterprise mindshare and real business value.

Here's what that shift means for your GTM team:

• Your reps won't need to live in the CRM. Instead of manually updating records, they'll have the information they need delivered directly to them, right when they need it.

• Proactive, not reactive. Custom Signals in Clay will automatically trigger the perfect campaign at the perfect time, ensuring you're always one step ahead.

• Workflows that enable, not just automate. Your team will get 'just-in-time' intelligence and enablement, providing reps with the insights they need to close deals faster.

• A GTM machine that never sleeps. With autonomous systems running 24/7, your GTM motion isn't limited by typical working hours. Your team can focus on strategy while the engine runs itself.

• More time for what matters. By automating all the mundane work, your reps can spend their time where it truly counts: helping customers succeed.

The CRM is a great database, but it's time to move beyond records. It's time to act.

Hey, GTM Engineers!

Close to 1,000 people requested my Ultimate Guide to LinkedIn Workflows and Automations (my first sponsored project with La Growth Machine). Check it out, I wanted to make sure you also caught it.

I’ve been using LGM for over the past year for multi-channel sequencing (LinkedIn, Email, X.com). It’s one of my favorites for its simplicity and power.

Haven’t tried it? 👉️ Get a full month for free here. (My affiliate link)

In this post, I share 20 tips for prospecting on LinkedIn and workflows, automations & prompts to help you.

Let’s dive in 👇️ 

Happy hunting.

Alex

20 Tips & Tricks for Successful LinkedIn Prospecting

#1: Prospect where your personas hang out

• If your Ideal Personas are on LinkedIn, then prioritize it. 

• I’ve seen success with personas in software development, cybersecurity, and go-to-market. 

The following is one of my favorite (and simple) workflow automations:

• Monitor a keyword

• Listen for posts with those keywords

• Find the people interacting with those posts (likes, comments)

• Automating LinkedIn prospecting to those people on LinkedIn

LinkedIn Signals to LinkedIn Automations

#2: Always multi-channel

• Don’t rely solely on one or two channels.

• Blend LinkedIn, email, phone, and X to build familiarity.

👇️ Example of a popular workflow on La Growth Machine. The auto LinkedIn profile views, likes (for social warming), auto-connects, and auto messaging are really the game changers here.

Multi-channel Prospecting

#3: Use Ideal Customer Signals for timing

• Act on signals (news, posts, role changes, profile views) to personalize outreach.

•  I’ve personally seen response rates of 45% when I automated personalizing a message based on someone’s post content.

AI Prompts: Uncovering Unique Ideal Customer Signals with Clay

A 3-step guide to finding unique ideal customer signals using Clay's custom signals, transforming GTM strategy with precision targeting and data-driven insights.

www.claymation.io/p/prompt-finding-ideal-customer-signals-for-clay-custom-signals

#4: Hyper-targeting > spray

• Skip volume; focus on tightly defined ICPs, personas, and Ideal Customer Signals.

#5: Use LinkedIn Intent

These are folks who are already interacting with your content.

This is super easy to do in La Growth Machine:

La Growth Machine LinkedIn Intent

#6: Open conversations, not pitches

• Frame messages as conversations. What curiosity-driven, benefit-led, or question-focused message could start a conversation? 

• A/B tests within LGM have shown that conversation-style messages outperform by 28% more replies when systematically tested

#7. Be casual & concise

• Write like a text: short, friendly, and avoiding formality.

• Read Paul Graham (Founder of YCombinator’s) essay: Write Like You Talk

You can also turn your message into more of a chat-like message. La Growth Machine’s ‘Real Chat’ mode can break up the message into multiple shorter messages to mimic text messaging.

#8. Send when green dot active

• Green dot = online

• Message when their green dot is live—often evenings when they scroll.

#9. Differentiate with video & voice

• Ask yourself, will this message stand out from everyone else’s?

An easy way to do this is to combine Sendspark + Clay + La Growth Machine.

Automating personalize videos + multi-channel prospecting with LGM

#10. Have an intriguing profile (& website)

• Ensure your headline & “About” tell a compelling story. Why else would someone enjoy connecting with you? What’s your unique value beyond where you work and your job title?

This is my new personal landing page: gtmengineer.ai 

#11. Connect after 1st call

• Quickly connect after calls so they begin seeing your content.

#12. Drop pushy follow-ups

• Stop reminders like “did you miss this?”—after 2 follow-ups, pivot to content engagement.

#13. Collaborate with key influencers

• Consistently comment on 3–5 influencers organically. Do not use AI to do this. Authenticity and thoughtful content win.

#14. Post consistently

• Aim for 3–5 posts/week. I haven’t seen any drastic correlation between whether I post in the early AM, mid-day, or 11PM before I hit the bed.

• This has not only generated my own inbound. Customers have started showing up to calls already knowing me.

Scripe.io is hands down one of the best LinkedIn content creation machines. It also gives you inspiration from other top performing posts within your ecosystem + AI that creates really good posts.

#15. Use storytelling formats

• Carousels & video do best for engagement & increasing your reach.

You can even automate building LinkedIn Carousels:

How to Automate Creating LinkedIn Carousels

A walkthrough of how to automatically turn a newsletter into a LinkedIn Carousel asset for content repurposing & engagement.

www.claymation.io/p/how-to-automate-the-creation-of-linkedin-carousels

#16. Soft‑sell in content

• No hard sells. Be thoughtful. Provide valuable content (this does not mean company one-pagers).

#17. Activate leadership multi-threading

• Encourage execs to connect with account stakeholders. Multi-thread as early as possible. 

• You could even setup an automation where your sales leader or founder automatically connects with potential decision makers after all your calls.

#18. Experiment & iterate

• Treat every post or message as a test.

Here’s a perfect experiment - use La Growth Machines’ lookalikes capability to find people who look like the ones who responded to your outreach. Repeat:

La Growth Machine Lookalike Play

What it looks like in LGM:

Lookalikes in LGM

#19. Set alerts for prospect (or influencer) activity

• Engage within minutes of their posts—prompt feedback increases visibility.

How to set alerts when people post on LinkedIn

#20. Get creative with different actions

More Workflows in the Full Guide

New Referral Program

I get a ton of requests on LinkedIn to set up time to talk about GTM Engineering or to get help with Clay. A lot of this is outside my focus of my day job and everything outside of that is limited.

However, now as part of my referral program, you can earn a session by helping me spread the newsletter.

30 Referrals = 30 Mins call for whatever you’d like help on!

Team Screaming Seagulls

Hey, GTM Engineers!

What’s the secret to build great AI prompts for Claygent (or in general)?

Let me take you behind the scenes of how I do it for customers at Clay. This is a process I’ve developed that’s been consistently produces great outputs.

But first, did you catch wind of the GTM Engineer content competition?

The short of it is my team ‘Screaming Seagulls’ will be dropping template, prompts, and our best Clay tips. Here’s who to follow on Screaming Seagulls so you don’t miss the action:

• Veronica Steiner 

• Joseph Fiorie 

• Marilin Berg 

• Rahul Mehta 

• Sabrina Glaser 

• Tong-Tong Li 

• Travers Nammack

Back to this week’s post. These are these steps and general process I take when building custom Claygents for customers:

1. Objective

2. Possibilities

3. What are the steps to get there?

4. Considerations

5. Build prompt

6. Test prompt & spot check

7. Iterate with your AI side kick

8. Repeat step 6

9. Organize

10. Add to Prompt Library + Create Template

11. Other Tips for Fine Tuning

This may seem like a lot, but it can be pretty fun and you’ll almost always learn things along the way.

1. Objective

What do I ultimately want to achieve with the prompt I’m developing?

In the context of PLG companies - I want to figure out all ways I can derive or infer insights from an email address to use for sales and marketing purposes.

2. Possibilities

Today I validate emails in Clay to figure out if they can be used, if they are personal, or work emails, and then use the email in a waterfall enrichment to find a LinkedIn profile. But, am I missing anything?

Turns out I was missing a lot. This is what I asked ChatGPT (I also use Perplexity for similar questions):

This is what I got back:

Useful Outcomes

Most people just classify personal emails vs. work emails.

But now that we have additional insights, we can build out a more powerful workflow/prompt.

This is how I’ll use the insights:

• Classify the email into one of the following

  • Personal Email

  • Work Email

  • Service Email

  • Cannot Determine

• Identify service accounts to:

  • Reduces noise for sales reps

  • Tells us what department is using the service

  • Now that we have the department, we can source people in that department

  • The use of a service email tells us this could be more significant usage compared to an individual user

• Extract the name + company (if it’s a work email)

  • This gives more additional inputs to improve coverage and accuracy of finding LinkedIn URLs with Claygent

    • The use of this approach in conjunction with waterfall for finding the LinkedIN URL increases coverage

3. Steps

Now lets figure out what steps the agent needs to take to get us to the above.

There’s 2 ways I do this:

• Use Clay’s Meta Prompter to get a baseline prompt

• Ask Perplexity or ChatGPT what the steps would be so we can include in the prompt

4. Considerations

This prompt likely doesn’t need any. However, sometimes I ask AI separately what constraints, guidelines, or simply “what else am I missing?”. This adds another layer of learning and works great for building more complex chain-of-thought prompts like the previous one I shared to find GTM Ideal Customer Signals.

5. Build Prompt

I do one of 2 things:

1. Use Clay’s Meta Prompter (see below)

2. Prompt ChatGPT or Claude

Clay’s Meta Prompter 👇️ 

Clay Meta Prompter

6. Test Prompt & Spot Check

• Are you getting outputs that make sense?

• Or, are you getting errors or unexpected outcomes?

• Do you need to adjust the fields?

• Are you asking the agent to do too many tasks?

Use ‘Steps’ & ‘Reasoning’ as breadcrumbs

7. Iterate with AI

If I’m not happy with the prompt, I’ll plug it back into ChatGPT and engage in a conversation to improve it.

What else am I missing?

What are 2 other outputs I can add to this? You get the outputs and then you can ask AI to add that to the prompt.

For content, you can experiment with style and tone and ask for variations. Choose the one you like and then have AI come up with a prompt for that specific variation.

8. Organize

Creating a collapsable template helps to organize and simplify your table.

I also like to change the column type to “Select” to make the table and outputs more aesthetic:

Plus, you can get some nice statistics:

10. Save to Prompt Library + Template

Now you have reusable components that you can drop into other tables and workbooks as you build.

How to Save an Claygent Template

11. Other Tips for Fine Tuning

Use the right model based on complexity & use case

Define desired structure

Customize Claygent

Define Creativity Level + Upload Documents for More Context

How Temp Impacts AI Email Copy

A Clay.com step-by-step guide that experiments with temperature's impact on AI generated copy (great for emails). Plus using DeepSeek in Clay & how to run automations on a schedule.

www.claymation.io/p/how-temp-impacts-ai-generated-email-copy

Add Temperature + Documentation

Check out the Template Library

Claygent Prompt Library

👋 Hey! I’m Alex - a GTM Engineer at Clay. Not a subscriber yet? Join nearly 5,000 GTM Operators from the likes of OpenAI, HubSpot, Airtable, Ramp, and others who subscribe for battle tested GTM Prompts & content on GTM Engineering.

Objective of this Week’s Prompt

Clay just launched Custom Signals - a capability that enables you to turn nearly any custom data point into a signal.

I’m totally stoked about this and believe it’s the future of GTM: Ideal Customer Signals (ICS).

We can no longer rely on ICP, Personas, or general campaigns.

To find GTM alpha, you gotta get to your target customers at just the right time and before your competitors.

What are these? Ideal Customer Signals are changes in your prospect accounts behavior and environment that indicates the company has an objective, pain, or situation that is ripe for your solution or services. They often leverage unique data points about your ICP and Personas.

It links the timing of a sales or marketing play to your ICP & Personas.

The purpose of this Chain-of-Thought prompt is to help you find your company’s Ideal Customer Signals.

Then you can start building custom signals in Clay to operationalize ICS.

Example Output (Company = Datadog)

The output is too long for this post. But check out some of the examples sections:

Signal summary table for Datadog

Provides a summary of the top 10 must read articles on Datadog

The Prompt

👉️ Copy and past this into ChatGPT. You can also experiment with Deep Research for a more more detailed output.

👉️ If it stops short and doesn’t include the last section with relevant news, then just ask it to finish the running the prompt.

👉️ Ask AI follow up questions.

🧠 Ideal Customer Signals (ICS) Deep-Dive Generator

🤖 AI Persona, Context & Research Process

Definition – Ideal Customer Signals (ICS):
ICS are observable changes inside a target account’s environment that indicate a business objective, pain point, or buying readiness that the input company can solve.

You are a Go-To-Market strategist tasked with identifying the best-fit target accounts based on signals that originate from external companies — i.e., potential buyers of the input company, not the input company itself.

Your goal is to uncover timely, actionable, and verifiable signals that suggest a target account is likely to need the input company’s solution soon.

🔍 Chain of Thought Reasoning (Before Surfacing Signals)

Use structured reasoning to identify what triggers a company's need for this product or service. Think across first-order and second-order effects.

1. What problem does the input company solve? Who benefits most?

2. Define the Ideal Customer Profile (ICP):

   • Industry verticals

   • Company size and maturity

   • Typical tech stack and infrastructure

3. Identify Key Personas:

   • Roles, titles, and departments most impacted

   • What KPIs they care about

   • Where budget authority lives

4. List Internal Triggers of Need:

   • Org restructuring or headcount growth

   • Technology migrations or stack changes

   • Compliance, security, or efficiency goals

5. Pattern Match & Synthesize:

   • Combine signals into repeatable patterns

   • Prioritize recency, verifiability, and relevance

   • Consider both explicit intent (e.g., job posts) and inferred intent (e.g., leadership changes)

6. Avoid Product Bias:

   • Think from the buyer’s perspective

   • Describe signals objectively

   • Don’t assume solution-fit without a trigger

🧶 Signal Prioritization Criteria

Give higher weight to signals that are:

• Originating from mid-market or enterprise accounts

• Recent and verifiable (within ~90 days)

• Tied to budget owners or key influencers

• Related to internal change, urgency, or growth

• Detectable via public or third-party data sources

📚 Data Sources to Use

👥 People & Org Changes

• LinkedIn job postings, team growth, org charts, promotions, leadership changes

• Executive announcements via press releases or blogs

• Team size trackers (e.g., LinkedIn Sales Navigator, Revelio Labs)

🧰 Tech Stack & Tooling Shifts

• BuiltWith, Wappalyzer, StackShare, G2 Stack

• Mentions in job descriptions (e.g., “experience with Terraform”)

• Product release notes or migration blog posts

💼 Hiring Trends

• Greenhouse, Lever, Workable, SmartRecruiters

• ZipRecruiter, Indeed APIs (for volume-based hiring signals)

• Hacker News “Who is hiring?” threads (for early-stage tech indicators)

📈 Strategic & Financial Signals

• ✅ SEC filings (10-K, 10-Q, 8-K): strategy shifts, spending priorities, risks

• Earnings call transcripts: transformation, compliance, GTM priorities

• Investor presentations and IR pages

• Fundraising and M&A data: Crunchbase, PitchBook, CB Insights

🔐 Compliance & Security

• SOC2 / ISO / HIPAA readiness or announcements

• Public security disclosures, breach reports, or compliance updates

• Vendor trust pages (e.g., trust.salesforce.com)

🌍 Market & Industry Signals

• TechCrunch, VentureBeat, Yahoo Finance, PRNewswire

• Analyst reports (Gartner, Forrester, IDC)

• Subreddits, Twitter, public forums for pain point chatter

🧠 Intent & Behavioral Signals

• G2, Bombora, 6sense: category research, solution interest

• Similarweb, SEMrush: traffic shifts to solution/competitor pages

• Webinar attendance or conference sponsorships

🛠 Developer & Product Ecosystem

• GitHub: repo launches, dependencies, forks/stars

• DockerHub, NPM, Terraform Registry: package downloads or updates

• Stack Overflow trends or spike in topic searches

🗓 Output Format

🔹 Executive Summary

• Key Trigger: What external pattern indicates growing need? (Provide 5 themes)

• Top Segment to Target: Persona + industry + likely use case

• GTM Risk: Where might targeting or timing friction occur?

🧹 1. Ideal Customer Profile (ICP)

📍 2. External Signals from Target Accounts

Break signals into categories. Include:

• Signal Description

• Why it Matters

• Relevant Persona

• GTM Play to Trigger Outreach

Examples of signal categories:

• Hiring-Based Signals

• Tech Stack or Infrastructure Changes

• Compliance & Risk Motions

• People Movement or Leadership Shifts

• Strategic Initiatives or Public Commitments

• Intent & Behavioral Data

🚀 3. High-Impact Signal Examples (10 Minimum)

🧹 4. Signal Clusters (10 Minimum)

📊 5. ICS Scorecard (10 Minimum)

🧠 6. Signal-Driven Narrative Hypotheses (10 Minimum)

Create hypotheses combining 2–3 signals per account or persona. Example structure:

📰 7. Top 5 Recent News Articles on [Input Company]

• Title: [Headline] – [Source]
  Summary sentence 1 (what happened).
  Sentence 2 (why it matters).
  Sentence 3 (implication for GTM, product, or market).
  👉 [Link]

(Repeat for 5 articles)

Let me know if you'd like this formatted as a Google Slide deck or used as the base for a custom GPT with automated outputs.

Hey, GTM Engineers!

Excited to drop Alex Carsten’s Part 1 of his 2nd guest Claybook.

Alex is a Sr. RevOps Consultant at Go Nimbly - a RevOps agency that reps some serious tech logos such as Rippling, Zenefits, Twilio, Zendesk, Coursera, the list goes on.

👉️ Check out his first guest Claybook on automating custom Gong summaries & follow up. Note: HTTP API was used to connect with Gong, but we now have a native integration.

All of the steps are below with a video walkthrough of the Clay table at the bottom.

Reply to this email and I’ll connect you for the template.

Also be sure to check out Go Nimbly’s RevFest on June 10. They have some killer speakers lined up from Snowflake, OpenAI, Scale Venture Partners, and Ironclad.

👉️ Register here

✌️ Alex

Guest Claybook from Alex Carstens

Part 1: Automate Lead Intake with Clay, Typeform, Slack, Notion, and Salesforce

Hi there! I’m Alex Carstens, Sr. RevOps Consultant with Go Nimbly. If you've ever wished that inbound lead intake could run itself—from form submission to CRM entry, Slack alert, Notion doc, and opportunity creation—this guide is for you.

Let me show you how we built a workflow that reduces 30 minutes of manual work per lead to under 90 seconds. Using Clay, Typeform, Salesforce, Notion, and Slack, we’ve created a powerful automation that ensures every inbound form gets routed, enriched, and actioned with no lag.

🟢 How It Starts: Typeform Submission

Our process begins with a partner or prospect filling out a Typeform. This form captures essential information: company name, contact info, CRM in use, engagement interests, and more. Clay automatically ingests these responses and parses them into structured columns.

That raw submission? It's the fuel that kicks off a fully automated deal desk process.

🕛️ Enrich and CRM Match in Real-Time

Once the Typeform data is in, Clay gets to work checking if that account and contact already exist in Salesforce. If they don’t, Clay creates them.

We then run enrichment on both the account and contact—pulling in LinkedIn profiles, titles, company details, and anything else a rep might need. The result? Your CRM stays clean and complete, and reps are never left guessing.

👉️ Assign and Rout Leads Intelligently

Here’s where things get fun: if a lead isn’t already assigned via the form, Clay uses a round robin assignment to automatically hand it off to an available AE or SE. This ensures every lead is followed up promptly and fairly.

We track the sender of the lead too, whether it’s an internal partner or referral, and update Salesforce with their details. Everything stays aligned.

🎨 Create Beautiful Notion Docs Automatically

Once assigned, we generate a Notion doc pre-filled with all relevant lead info, including a pricing calendar link, account notes, and a checklist tailored to the engagement type.

These Notion docs act as working deal briefs—making it easy for AEs, SEs, and others to align without a single Slack message.

⏰ Fire Slack Alerts for Speed and Visibility

Speed to lead is everything. Clay triggers a custom Slack alert to the assigned rep or team channel when a new deal is ready. The alert includes a direct link to the Notion doc and a brief summary of the deal.

There are even different messages depending on whether the deal was manually or auto-assigned.

🏗️ Create Salesforce Opportunities, Products, and Custom Objects

Once the lead is assigned and enriched, we use Clay’s Salesforce integration to:

• Create or update the opportunity

• Attach relevant products

• Create custom objects (like revenue schedules)

• Assign contact roles on the deal

All the required Salesforce validations are handled automatically, ensuring smooth record creation without errors.

📊 Reporting and Analytics

We push every enriched row to a Google Sheet for advanced reporting. This lets us analyze intake trends, team performance, and coverage using pivot tables and dashboards—all without touching Salesforce reports.

📹️ Video Walkthrough of the Clay Table

🚀 The Impact

What used to take 20–30 minutes per lead now runs in under two. Reps are better prepared, deals move faster, and no lead ever slips through the cracks.

If you’re managing inbound interest, running SE capacity planning, or scaling a services org, this workflow can give you time back while improving outcomes.

Want help building your own version? Reach out—happy to share what we’ve learned.

And stay tuned for Part 2, where I’ll walk through how we use Slack workflows to automatically generate contracts and send them for signature once the opportunity is ready. It’s the next step in turning this intake flow into a closed-won engine.

—Alex Carstens Sr. RevOps Consultant, Go Nimbly

Cool GTM Findings

GTM AI Tools survey from Alex Tewari, Co-Founder of Conversion.ai.

They also have a great post on “What Is Answer Engine Optimization (AEO)? Your Guide to AI-Driven Visibility”.

Link to LinkedIn post

Box’s AI-first Principles from Aaron Levie, Founder/CEO:

Link to the LinkedIn post

Have you checked out Clay’s AI Hackathon’s?

1 Day, 3+ AI/Clay workflows developed & deployed. Check out what Canva built with Clay:

If you missed it… Clay’s Finding GTM alpha blogpost.

The main takeaway:

How to find GTM alpha (your competitive advantage)

Want to Automate LinkedIn Connection Requests & Messages like this?

LinkedIn Sequencer Automations with La Growth Machine

It’s super easy with La Growth Machine.

👉️ Get a Free Month Here 

Hey, GTM Engineers!

4,000+ of you to be more exact… which keeps my excitement high for creating GTM Engineering content for you all.

You may see some content tweaks. High level, my goal is to create a couple different types of posts (all deeply researched):

• Claybooks - step-by-step in-depth guides you can learn from

• Prompts - tested, fine tuned, and designed to be super useful

• Custom GPTs - built off of the prompts & extended so you can reuse more easily

• Integration Features - to help you stay on top of the best as many come out

My first integration feature will be with The Swarm - an API/data provider that maps your company’s network (executives, investors, advisors, etc.) and find connections that are most likely able to make warm introductions for your target accounts.

Included in this feature:

• Overview of The Swarm

• How it works

• How to set it up (with a Clay template you can copy)

• 2 emails you can steal

• Additional use cases to explore

🤘 Alex

p.s. check out the growing Reddit community: r/gtmengineering (top 39% now)

p.p.s. I’m doing a webinar with The Swarm tomorrow. Come join to see this in action.

🔦 Overview of The Swarm

The Swarm was started by:

• David Connors, Co-Founder & CEO

  • Previously Entrepreneur in Residence at Sequoia Capital where the idea was born after spending years developing recruiting methods.

• Michal Bil, Co-Founder & CTO

• Olivier Roth, Co-Founder & Chief Growth Officer

They help you map you & your companies networks to find optimal introduction paths to your prospects, target accounts, hiring candidates, investors, and so on.

I’ve wanted a solution for this at all of the 8 Series A companies I’ve worked at. Leveraging your investor and executive networks has always been the best way to break into accounts when few know you.

However, the Go-To-Network has historically been manual and spreadsheet based. Almost impossible to scale.

Now we can include The Swarm in Clay workbooks and sales automations via our native integration. This is one of four ways to use The Swarm:

• The Swarm for LinkedIn, our free Chrome Extension, reveals unlimited business emails and intro paths on top of LinkedIn.

• Our Clay integration lets you find intro paths to the people and companies you want to reach, right from your Clay tables.

• The Swarm API gives product builders and data leaders next-level people and relationship data.

• Our SaaS application lets you securily combine and search through the network of your team members and stakeholders.

🎯 Use Case w/ Clay

Find warm introductions at target accounts at scale.

Inputs:

• Company Name

Outputs:

• Target person at your target company

• LinkedIn URL of that person

• The most likely person to have a connection to that person (Connector)

• How they are connected

  • Work overlap (default mapping)

  • Education overlap (default mapping)

  • Shared investors (default mapping)

  • LinkedIn connection (with Swarm account)

  • Email contacts (with Swarm account)

  • Calendar contacts (with Swarm account)

• Personalized emails for each type of connection

⚙️ How to Setup

Overview:

1. Copy provided Clay table (subscribe for access)

2. Log into The Swarm in the Clay template

3. Setup Swarm inputs (your website, personas, etc.)

4. Add your Account signals

5. Tweak the provided emails as needed

6. Run table

Step-by-step Guide:

1. Copy this Clay Template

2. Log into The Swarm & setup Inputs

Inputs:

• Target account (tag in the domain column)

• Add your target job functions

• Add your target seniority

Getting The Swarm setup in Clay

3. Add your Signals

The shared table doesn’t have any signals built into it.

There’s too many variations to make it custom for everyone.

All companies have what I call Ideal Customer Signals, which look something like the following:

👉️ use these Ideal Customer Signal prompts for OpenAI DeepResearch to find yours.

The signal is what you want to reference in the reason for:

• The context of why the target person would be interested to connect

• How you’d provide value to that person/company

This makes it easier, and more comfortable, for your connector to make the introduction.

Conditional Snippet in Clay

4. Tweak the intro emails templates

There’s 2 email variations for 2 of the 6 different scenarios (that indicate a connection) in The Swarm:

• Connector is connected via work experience overlap

• Connector is connected on LinkedIn

Email 1: Work experience overlap

Email 2: Connected on LinkedIn

4. Run your table

✅ Additional Use Cases

1. Network driven recruiting

2. Fundraising through trusted connections

3. Investor network management

4. Community building and engagement

5. Job hunting

👉️ check out The Swarm: www.theswarm.com

Hey, GTM Engineers!

I’ve been testing this idea of “Ideal Customer Signals”.

We have Personas, Ideal Customer Profiles, and Sales Playbooks. But, nothing really defines WHEN to deploy a sales play to your persona and ICP account.

Historically, we’ve had some basic signals:

• Job changers

• Promotions

• Funding announcements

These are foundational and table stakes. (Though, I’m always surprised how many companies still don’t track their champions and when they move jobs.)

AI and AI Agents now give us the opportunity to define & monitor much more custom data points. 

In Clay, this would be setting up a table and running it on a schedule (daily, weekly, or monthly).

For example:

1. Find whether a company is hiring for a specific role (could be hiring a CFO for the first time).

2. Set the table on a schedule, lets say monthly.

3. Clay will then check to see if that company has started to hire that person each month.

4. When that signals pops on the radar, then send a notification to the sales rep in Slack.

So, how do you define YOUR signals?

I made a Custom GPT (access below if you’re a subscriber) that is based off of my Ideal Customer Signal to get you started. It also combines competitive research and persona messaging.

Check out it out in action👇️ 

🎯 Objective

To automate research so you can more effectively:

1. Compete against your competition

2. Define signals to find your customers first

3. Draft messaging & case study recommendations for each persona

4. Content for:

   • Competitive battle cards

   • Positioning for competitive takeout campaigns

   • Sales training on personas

   • Defining your Ideal Customer Signals

   • Marketing for better targeted and more contextual ABM

Here’s an example of one of the table outputs:

Ideal Customer Signals

How to use

⚙️ Inputs

Provide the following inputs:

1. Your company

   • “My company is Clay.com”

2. Your target competition

   • “We compete against ZoomInfo”

3. Your best industries

   1. “Clay.com’s target industries are Software, Financial Services”

4. Your segments

   1. “We sell into Mid-Market, Enterprise”

🎯 Outputs

Output 1 - Competitive Analysis:

• When is it better to sell your services vs. competition?

• Key product strengths & use cases favoring your company

• Economic benefits of your services vs. competition

• Top 3 selling points to displace the target competition

• Primary weaknesses of target competition

• Your differentiators & strengths

Part of the analysis since its long

Competitive Analysis

Output 2 - Ideal Customer Signals Table

Ideal Customer Signals

Output 3 - Persona Value Prop Map Table

Persona Value Proposition Mapping

📓 Notes

👉️ If it doesn’t not give you all 3, then ask it for the output.

👉️ Results may vary if your company is very new without a lot of info on the web.

Access

Subscribe to gain access to this GTP below

Prompt 1: Competitive Research

Example Output:

Prompt 2: Competitive GTM Signals Table

Example Output:

Ideal Customer Signals Table

Hey, GTM Engineers!

Hope ya’ll don’t go throwing office supplies at me.

Yesterday was April Fools and many of you got fooled 🙃 

Claymation did not get acquired by Clay for $1,000,000.

It did help acquire 300+ new subscribers and 250+ of new LinkedIn connections in 24 hours. Kinda surpassed my expectations…

Claymation April Fools Acquisition Prank

The results so far:

👍 650+ post interactions
🚀 300+ new subscribers and growing
👥 300+ new LinkedIn connections and growing
👀 100k post impressions (well, 95k but it'll get there today!)

Similar to any marketing campaign, my goal is to leverage this moment to build on the moment. There’s a couple new ways we can do this in Clay with some new social signals:

1. Build a list of everyone that interacted with the post

2. Connect with those that I’m not connected with already on LinkedIn

3. Send them a message after they connect

4. Share link to this post

After all, I gotta reach them somehow to make sure they’ve been pranked.

You guessed it, we can automate the entire workflow.

Let’s dive in 👇️ 

🎯 Objective:

Capture interactions from a LinkedIn post and automate connecting with those who are not currently connected with me.

End goal = leverage the moment to build my network.

This is also super useful for marketers who want to capture more activity and leads from high interaction marketing events such as:

• Funding announcements

• Big product announcements

• Significant partnership announcements

• Conferences

⚙️ Workflow

Made with Puzzleapp.io

Step 1: Grab the URN of the LinkedIn post URL

The output should look like this: urn:li:activity:7312808979087151104

Save this for the next step

URN from LinkedIn

Subscribe for steps 2-5:

• Step 2: Create table & use “Find Post Audiences on LinkedIn”

• Step 3: Enrich Person

• Step 4: Create a La Growth Machine “Audience”

• Step 5: Create a La Growth Machine Campaign

• Step 6: Connect Clay to La Growth Machine

Step 2: Create table & use “Find Post Audiences on LinkedIn”

Our LinkedIn ‘Find Post Audiences” is a new integration that is direct with LinkedIn’s API.

1. Grab the URN from Step 1

2. More Sources

3. Search for “LinkedIn”

4. Choose “Find Post Audiences on LinkedIn”

5. Add the URN

6. Run source

Find Post Audiences on LinkedIn

The resulting table looks like this:

Claymation Acquisition Audience

Step 3: Enrich Person

Now let’s get the Title & Company that the person works at with “Enrich Person”.

This will help you see what personas the post attracted.

To get a statistical breakdown, you can use AI to segment the titles into specific buckets, export the data to a CSV, and then upload to ChatGPT for analysis.

Enrich Person to find Title, Company, and more…

Step 4: Create a La Growth Machine “Audience”

This is one of my favorite sequencers because it can automate the following:

• LinkedIn Connect Requests

• LinkedIn Messages

• LinkedIn Profile Views

• LinkedIn Post Likes

You can do all of this on an individual plan for $55/month. As a sales rep, or anyone who is active on LinkedIn, it’s a no brainer. Use this link to get an extended trial: 1 month free (instead of 14 day trial)

The Audience is where we’ll upload the leads.

Creating an “Audience” on La Growth Machine

Step 5: Create a La Growth Machine Campaign

It’s super easy to add the sequence steps.

Be sure to add “Is a contact?” so you can segregate the audience into connections and non-connection paths.

Setting up a La Growth Machine Campaign

The final sequence looks something like the following.

• Existing connections will get Message A

• Non connections will get a Connect Request + Message B

Automated LInkedIn Connection Request + Message Sequence

Step 6: Connect Clay to La Growth Machine

The native integration makes this super easy.

Now you can upload to the Audience and Campaign and you’re ready to go!

Connecting Clay with La Growth Machine

Step 6: Messaging & Launching

Note, you’ll probably want to create some messaging so that the Connection Requests and Follow Up Messages are personalized.

The post is already a bit long, so I’ll save that for another post.

However, once you have messaging in columns, then you can upload that to custom attributes in LGM and tag into the messages.

💡 Clay Tip of the Week

Instead of having AI write an entire email, have it write a snippet. One technique here is to have it complete a sentence. Here’s an example of a prompt:

🌐 From The Claymation Network

The silent deal killer

A simple AI experiment to reduce buyer uncertainty before it stalls the sale.

www.theaugmentedseller.com/p/the-silent-deal-killer

You’re doing signal-based outreach wrong — How to Create your GTM Ikigai 🧘‍♀️

Fix the disconnect between what buyers signal and what your team sends.

engineeringrevenue.beehiiv.com/p/you-re-doing-signal-based-outreach-wrong-how-to-create-your-gtm-ikigai

Attribution is HARD AF; but doesn't make it any less impactful

Marketing attribution is like having a secret recipe that makes the best dish ever, but no one believes it until they take a bite.

revengine.substack.com/p/attribution-is-hard-af-but-doesnt

Reply if you’re interested to collaborate.

💼 GTM Engineering Job Openings

Pipeline Catalyst hiring Head of GTM Engineering in United States | LinkedIn

Posted 11:24:47 PM. About UsWe’re a fast-moving, client-focused GTM consultancy helping early-stage startups run…See this and similar jobs on LinkedIn.

www.linkedin.com/jobs/view/4192950821

Want to add a job opening? Reply for pricing details.

🍬 Some Goodies

My favorite AI productivity app 👉️ Hoop: 1 month free

GTM Engineering platform 👉️ Clay: 3,000 free credits when you subscribe

Where I host Claymation 👉️ Beehiiv: 1 month free + 20% off 3 months

The 🐐 of LinkedIn sequencing 👉️ La Growth Machine: 1 month free (instead of 14 day trial)

How I create beautiful screenshots 👉️ Xnapper

GTM Engineers,

I’m thrilled to announce that Claymation has been acquired by Clay for $1M.

Everett Berry, Head of GTM Engineering, approached me in my 1-1 several weeks ago about the newsletter. At first I thought, uh oh, am I spending too much time on this?

Explanations raced through my head - “I’m really only creating content after hours”, “The newsletter has been generating leads, so I need to continue putting in the reps.”

The conversation was much different.

Everett explained that Clay is taking a page out of the HubSpot playbook when they acquired The Hustle. There’s several cases of this where B2B SaaS companies acquire media companies to become part media company themselves:

1. HubSpot Acquires The Hustle

HubSpot acquired The Hustle in 2021, a popular startup-focused newsletter with over 1.5 million subscribers. This strategic acquisition aimed to expand HubSpot's media presence and engage users through educational and trend-based content, complementing its inbound marketing philosophy.

2. Stripe Acquires Indie Hackers

Stripe acquired Indie Hackers, a community-driven blog and newsletter, to foster engagement with entrepreneurs and developers. This acquisition allowed Stripe to position itself as a resource hub for startups while promoting its payment solutions indirectly.

3. Robinhood Acquires MarketSnacks

Robinhood acquired MarketSnacks, a financial news newsletter, to deliver curated financial insights directly to its user base. This move aligned with Robinhood's goal of empowering retail investors with accessible financial information4.

Claymation isn’t yet as big as The Hustle, Indie Hackers, and MarketSnacks; however, become the go to place for GTM Engineering content and

That plus the GTM leadership rich subscriber base made the acquisition a no-brainer.

Btw, have you subscribed yet?

What’s next?

Well, I could never give up my day job as a GTM Engineer (connect with me on LinkedIn).

It’s been one of the most enjoyable jobs I’ve had to date. So, the plan is to ultimately split my time between helping customers with GTM Engineering and building content for Claymation.

Here are some sample posts:

8 GTM Engineering Trends for 2025 🧪 

8 key GTM engineering trends for 2025: A comprehensive guide exploring innovative strategies, experimental approaches, and the evolving role of GTM engineers.

www.claymation.io/p/rise-of-the-gtm-engineer-and-8-gtm-engineering-trends-for-2025

Building a Slack Bot with Clay

A brief guide on how to setup automated Slack alerts with a Slack bot that is powered by Clay.com. Use cases: inbound lead alerts, subscription changes, etc.

www.claymation.io/p/building-a-slack-bot-with-clay

Prompt Engineering with Clay & Perplexity.ai

A 3 step guide to improving technographic enrichments.

www.claymation.io/p/clay-prompt-hacking-w-perplexity-ai

Automate Finding Lookalike Accounts with Clay

A 3 step guide to setup a Clay + ChatGPT for customer cohort analysis + Ocean.io to find lookalikes at scale.

www.claymation.io/p/find-lookalike-accounts-at-scale-with-clay-chatgpt-oceanio

APRIL FOOLS!!!!!

Claymation did not get acquired.

🙃 Gotcha!!!

Btw… I have another newsletter that I’ve been working on with my friend, Oscar Moore.

The Augmented Seller

Tired of busy work? Reclaim time and sanity w/ 1 tested AI workflow every week. Trusted by top AEs at HubSpot, Clay, and LinkedIn.

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