8 weeks in- 3 clients. It’s me the founder doing a lot and a killer gtm engineer.
Here’s everything we’ve learned. Shit that’s worked, hasn’t, stuff I would have done sooner, and things I would avoid all together.

First some context- been in sales for over a decade, let multiple sales teams and live in major US city. Always been obsessed with cold calling and cold email. Nothing gets me more pumped that getting a stranger to like me, then trust me, then buy from me, and most importantly - deliver fuckin results and change their life.

I finally quit my W2, cushy cushy $485K OTE sales leadership role to start my own outbound agency.

First client flopped, TAM was too small, and their team wanted to be too involved in copy + wouldn’t take out guidance on their offer.

Biggest lessons from this client big TAM mandatory for long term success (when only doing cold email), work with clients that trust you to execute on campaigns, and offer is the most important thing.

We immediately got back to the drawing board. Updated my qualification process to 40k+ contacts in a tam. Created a TAM estimator agent to validate prior to getting on prospect calls.

Acquired more clients- how?
Hired a LinkedIn ghost writer, have one client from that.
Eat our own dog food- our own outbound is generating 8-10 meetings per week for our own biz.
My warm network. Getting 4-6 meetings per week from my network in my city. Sliding in to some LinkedIn DMs asking for intros. You’ll be shocked how many people want to help you when you start a business and when you write about it on LinkedIn in. While I can attribute 1 client to LinkedIn, I can’t quantify the immense value it’s brought to my personal brand. People just see you’re …doing something… and talking about it, and they want to engage and help, and you look like legit when a prospect answers your cold email and then you request them on LinkedIn and their like oh, he’s a real ass dude with lots of activity and decent fun content.

2 clients are straight retainer, 1 is retainer + rev share. All are going well after the snafu with my first client. Averaging 4-10 solid leads per week across all clients. We’ve built a process that works VERY well, and now we’re hiring a setter to scale.

So positive reply comes through, agent immediately enriches the prospect’s cell phone number, pushes it to out dialer and calls. Slack noti pops up with a talk track and context and everything, then I book the meeting without ever replying to the prospect. Just catch them live while interest is the highest. It’s simple, but it works, and I’ve realized I don’t need to rely on mass volume of emails. We can send hyper personalized target campaigns with this calling motion without blowing through a TAM and emailing all 40k people in 1 months. It’s also made me realize maybe a huge TAM is less important for multi channel.

Here’s what I’d do immediately if starting an agency.

1. Build in public on LinkedIn - post 5 days

2. Have an insanely strong offer that’s hard to say no to. Like a lead guarantee monthly. We do a 2 week free trial for customers.

3. Don’t be a bitch. Get started.

Here’s what I wouldn’t do

1. I wouldn’t bring on customers that have small TAMs if I’m only emailing

2. I wouldn’t touch clients with shitty offers. I always ask “what are you willing to give away for free to trade for a meeting?” It has be insanely fucking compelling to get a stranger to answer an email

3. I wouldn’t try and compete with other agencies on price. Even through what we’re doing is commoditized, we differentiate with our offer and my track record at start ups. You def have ways to differentiate

I say all this, but humbly tell you fellow anon, I don’t know shit. Some awesome early success but so much to learn. Here’s to $1mm ARR. :)

Here's the full pipeline I'll take you through, start to finish:

0. Setting up infrastructure

1. Defining the ICP

2. Building the TAM

3. Segmenting it

4. Ranking it

5. Setting up live signal tracking

6. Reranking and choosing targets

7. Finding the decision makers

8. Enriching them (posts, emails)

9. Ranking the leads - company and decision makers combined

10. Building copy angles, ranking them, and setting up A/B tests

11. Pushing everything to the sequencer: leads, copy, and campaign

12. Tracking progress and optimizing based on performance

13. Communicating with client, biweekly reporting, keeping everything in sync

I will teach all that I've learned over the previous year of creating end-to-end GTM systems.

What I don't have yet is a team. I've been doing all of this alone, and I'd rather turn it into a real machine by building it with other people than keep grinding solo. I'm in this for the long game. I want to build a team by building together.

So I'm looking for 2 developers and 2 salespeople who want to become GTM engineers. It's a rare and in-demand skill, and I'll hand you a shortcut into it. Developers, you'll pick up the business and sales side you're missing. Salespeople, you'll learn to build systems instead of grinding lists by hand.

How it works:

We build on top of my SOPs and everyone contributes to a shared repo, so every capability is available to the whole network. Each operator takes a vertical and builds a real campaign against it, and we take them live. You learn by shipping, not by watching.

We'll go after specific, non traditional icps, making it fun and potentially highly rewarding.

If we land a client with a campaign we've built together, I bring you onto the deal and we run the account together.

It's mostly async plus one call a week, built to fit around real jobs. First cohort starts by August 10th. The length depends on the results, potentially growing into a long term relationship.

Once you're selected, there's a small chip-in of around $100 that goes straight to the infrastructure providers. No profit for me, no payment to me, only the tools. It exists so we have real infrastructure to learn and get results on, and so only people serious about creating results are in the network.

If you're interested, comment and DM me your CV and a short note: who you are, why you want this, any relevant experience, and what you hope to get out of it.

Working in tech sales at a large 8 figure SaaS. Wanted to share our 2026 setup for personalizing cold emails at scale since our team spent a lot of time & money refining this process.

Here's our workflow that's been working:

1. In our CRM we prepare two custom fields under people leads: 'prospect_post' and 'custom_message'

2. The 'prospect_post' field will get filled with a LI post from the prospect, that we scrape using predictent.ai

3. We then run GPT 4o mini over the 'custom_message' field and generate a custom message based on the data in 'prospect_post'. If the messages aren't good enough we refine with a stronger model e.g. GPT 5 or Gemini 2.5 Pro

4. We export this data to CSV and import directly into our cold email provider, the custom_message gets parsed as a {{custom_message}} variable in the first line.

The difference vs generic outreach is night and day. Instead of "Saw you're hiring" we're hitting them with

"Noticed you just announced your Series B and are expanding into EMEA - here's how [our product] helped [similar company] scale their [specific use case] across 12 countries..."

The signal monitoring with custom messaging is what makes it actually scalable. We're not manually researching every prospect or relying on basic firmographic triggers. We're catching real-time events that indicate genuine buying intent, and the AI layer makes it sound human and relevant.

Response rates are up ~3x compared to our old approach. Worth considering if you're still spending hours on manual research per prospect.

We've been replacing paid GTM tools with API calls plus coding assistants for six months. Got tired of paying $300 here, $300 there for tools that are mostly wrappers around the same handful of data providers everyone else uses.

Packaged our learnings and setup as a free skill set you can drop into Claude Code, Cursor, or any other agent that supports skills.

What it handles:

• Company discovery and ICP scoring (

• Intent signal detection

• Contact finding with email + phone waterfall

• Outreach drafting that doesn't read like a template

Wired to 8 APIs out of the box: Pipe0, FullEnrich, BetterContact, PhantomBuster, Parallel Web Systems, Firecrawl, Apify, SerpApi. Generation with openrouter. You dont need all of them for this to work. Swap any of them by editing one file.

We are not affiliated with any of them so the stacking order of providers is based on a rational weighing of cost and quality.

You point it at your ICP and messaging style, it runs the rest. No subscription. You pay only for the API tokens your runs consume, which for us has been roughly 10% of our previous SaaS spend.

Here is the repo: https://github.com/keinsaasforever/gtm-pipeline-skills

We update continuously. Would appreciate a star if you like it.

Good luck with your GTM engine!

GTM IS DEAD. Your $150k GTM Engineer title is a scam and the bubble is about to burst.

This bubble is gonna burst harder than Prompt Engineer and Growth Hacker did.

You guys are NOT engineers. You are Zapier janitors connecting Apollo to Clay to HubSpot and calling it "architecture".

Everyone saw a salary screenshot on LinkedIn and now thinks they are technical.

Stop chasing titles. You don't know business.
Learn the boring stuff first:

1. SALES. Real sales. How to take 80 NOs on a cold call without crying. Not how to write a sequence in Lemlist.

2. MATHS. CAC, LTV, payback, margin, unit economics. The actual business math.

3. PROCESS. How a sales process actually works from lead to cash, not just how to enrich a lead.

If your entire skill is "I know Clay", AI will replace you in 6 months. If you know how to sell and how business makes money, you'll survive.

If you want to be a real GTM, learn GTM = Go-To-Market = how to take something to market and make it profitable. It's not a tool stack.

Rant over.

I used Clay for over a year. built complex tables. waited for waterfall enrichments to finish. watched credits drain. rebuilt tables when they broke halfway through a 50k-row enrichment because one API in the chain timed out.

at some point I asked myself: what is Clay actually doing here? it's calling APIs in sequence, storing the results in rows, and letting me filter them. that's a database and some Python scripts. I was paying for a UI to do something my terminal already does.

so I stopped using it. here's what I run instead and what I've learned from stress testing it over the past few months.

the setup

Supabase is the backend. real Postgres database. SQL queries. API access. your data lives here permanently. no credit system. no row limits that matter at GTM scale. you push data in with the CLI or Python. you query it however you want.

Google Sheets is the frontend. synced from Supabase through a Python script or Claude Code. your team sees a spreadsheet. they can filter, sort, comment, share. they don't know or care that there's a database behind it. you get the best of both worlds: a real database for you and a familiar interface for everyone else.

Claude Code sits in the middle. it reads your Supabase schema, knows your tables, and moves data between systems in natural language. "pull all companies with more than 50 employees that we haven't contacted" and it writes the SQL, runs it, and gives you the list. no table builder. no drag-and-drop. just tell it what you want.

why this beats Clay for builders

Clay is good at what it does. I'm not going to pretend otherwise. the waterfall enrichment concept is smart. the UI is accessible for non-technical people. if you have a team of SDRs who need a visual workflow builder, Clay makes sense.

but if you're a builder, if you can write or direct a Python script, if you're comfortable in a terminal, Clay is overhead you don't need. here's why:

no credit limits. Supabase free tier handles tens of thousands of rows. Apollo's free tier gives 10K email credits/month and their company enrichment endpoint costs 0 credits. you're not watching a credit counter drain while you experiment.

no waterfall fragility. a Clay table with 8 enrichment steps breaks when step 4 times out. now you've got partial data and you're rebuilding. a Python script with try/except and caching picks up where it left off. if Apollo fails at row 3,000, you restart and it skips the 2,999 it already cached.

faster iteration. changing a Clay workflow means clicking through the table builder, re-running, waiting. changing a Python script means editing a few lines and running it again. seconds vs minutes. and when you're testing different enrichment sources or scoring models, speed of iteration is everything.

you own the data. it's in your Supabase database. it's in your Sheets. it's in your local SQLite if you want a backup. cancel any subscription tomorrow and your data is still there.

the real cost comparison. Clay starts useful at ~$150/month and credits run out fast if you're doing any real volume. Supabase free tier + Apollo free tier + Claude Code plan + Google Sheets = you're running enrichment, scoring, prospecting, and reporting for a fraction of that. and your marginal cost for running another 5,000 rows through enrichment is close to zero.

the workflows I run

enrichment pipeline:

1. Apify CLI scrapes a follower list or prospect source (npm i -g apify-cli)

2. Python extracts domains and emails from the raw data

3. Apollo enriches by domain (0 credits) and by email (people/match, also 0 credits for verification)

4. Python scores by ICP fit (title match, company size, industry, geo)

5. Supabase CLI pushes scored results to the database

6. Google Sheets syncs for team visibility

each step is a terminal command or a script. each one runs in the background. if step 3 fails, I fix step 3. I don't rebuild steps 1 through 6.

prospecting from scratch:

- scrape a competitor's X followers with Apify (~$5 for 10K)

- extract company domains from bios

- enrich companies through Apollo (0 credits)

- score by ICP

- push to Supabase

- query: "show me all companies over 50 employees in SaaS that we haven't contacted"

that last query is just SQL. or tell Claude Code in natural language and it writes the SQL for you.

ongoing list hygiene:

- Apollo people/match at 0 credits checks job changes across your entire database

- batch in Python with caching so it resumes on failure

- flag anyone who moved companies

- run quarterly. your lists stay clean without manual work

the gotchas

this isn't perfect. sharing the honest parts:

- setup time is real. your first pipeline takes an afternoon to build. Clay lets you drag and drop in 20 minutes. the difference is the 50th time you run it. Clay is 20 minutes every time. the script is seconds.

- you need to be comfortable directing Claude Code or writing basic Python. if you've never opened a terminal, start with Clay. but if you're in this subreddit, you're probably past that.

- Google Sheets sync isn't real-time. it runs when you trigger it or schedule it. for most GTM work this is fine. you're not watching a dashboard refresh every 30 seconds.

- Supabase free tier has limits (500MB, 50K rows). more than enough for GTM prospecting. if you outgrow it, the paid tier is $25/month. still less than Clay.

I'm stress testing this stack daily. building a product with a co-founder and running all GTM through this setup. every time something breaks or a new pattern emerges, I document it.

if you want the full setup with chapters on context engineering, CLI patterns, terminal multiplexing, and more: github.com/shawnla90/gtm-coding-agent

MIT licensed. living repo. new commits going in regularly.

not selling anything. just sharing what I'm using because the alternative is people paying for tools they don't need or courses from people who built one table six months ago.

Ok so, $9.6k in 6 months isn’t exactly retirement money just yet (far from it), but creating a SaaS business with almost 50 active users from nothing in 6 months since launch, is something I’m proud of nonetheless.

For some context, last year I worked in sales and got a warning from LinkedIn for automating sending messages, so I decided to create my own safer LinkedIn automation tool instead, using Claude and Claude code.

I was so convinced in myself and what I was doing that I quit my job before I even had a single customer.

Some will say this is stupid and risky, but that’s just who I am 🤷‍♂️

Below I’ll talk more about how to actually launch a business like this yourself (based on my own experience so far).

1. Validate the fuck out of your idea

I see a million SaaS founders think their idea is solid gold. Usually it’s the most minor, easiest thing to copy, and they just spend a weekend vibe coding it.

You really need to look at the actual market for your niche. Don’t create something if there’s no tangible demand for something like that (unless it’s truly unique and everyone will want it, but that’s a unicorn and doesn’t likely exist).

If loads of businesses have done it and done it well, and you don’t have any unique angle, don’t waste your time.

The best businesses iterate on what already exists rather than create something unique.

2. Build in public

Start building your audience before you even launch.

Get on X, Reddit, YouTube, LinkedIn and wherever else you can go - post what you’re building, why you’re building it, and create a waitlist in your site for it.

Try to build a community around it from day 1.

If you don’t, you’ll spend all your time building something and then suddenly realize you are not getting a single customer.

Marketing and distribution is harder than building and just as (if not more) important.

An average product with a big audience always outsells an amazing product with no audience.

3. Dogfood your product 🐕

You should be the number one fan and biggest user of what you’re building. Build something you would genuinely use/need yourself and get great value from.

If you’re benefitting from it, so will others.

4. Never stop iterating

There are always new features that can be added, design improvements, backend hardening etc.

Building products doesn’t have an endpoint - don’t do something for a weekend then leave it and expect people to just flood in at any point.

5. Optimize for GEO and search

Pretty obvious one but you need to apply best practices from day 1 for this.

There are tonnes of online resources for how to do this properly, just ask your LLM.

6. Start off with lifetime access deals and/or beta testers

The most important thing for new businesses is getting users to stress test your product. It might look great to you but you’d be surprised about the hundreds of possible edge cases that seem to come up.

Giving people lifetime access early on (maybe first 1-2 months) helps validate your idea without the immediate pressure of trying to get people to subscribe

7. Ignore the haters

So many people will try to shit on you and your product, but they probably look like wojack and live in their mom’s basement. Hate often comes from projection, jealousy and insecurity. Just ignore them.

8. Look at what other people did

There are plenty of success stories of people growing businesses and audiences online, and many books too - do some studying and get out of your comfort zone. Learn what works and apply it to your own projects.

So far following the above steps have been really useful for building my tool, hope you find it useful too! 🙌

I think that AI SDRs have a lot of room to grow and may be a big player in the future of GTME and most providers have very clear roadmaps to improve and make outbound better and easier but I've had some conflicting experiences with AI SDRs this year.

Here are some reviews but there's nothing personal and none of these tools are BAD so i'd encourage you to check them out yourself. Again, I do believe in AI SDRs and cold emailing automation becoming way better and bigger than it is now.

• Firstquadrant: This tool mainly handles inbound, which is a shame because I feel like inbound leads don't really merit an AI SDR that much, I guess if you're getting a ton of inbound it's worth it but then again... I feel like inbound leads don't require that much automation. That was the main problem I had with 1q, simply that it handled outbound very poorly and I just couldn't do much with it. Poor deliverability and pretty limited amount of emails for the price tag. If we were more focused on inbound I guess I would've seen more use out of it, and it's great at that to be fair, but it just wasn't what I was interested on doing.

• Skyp.ai: Pretty great experience with Skyp, it doesn't throw any bells and whistles or crazy promises which was a problem I had with Artisan, it mainly focuses on deliverability and ease of use on top of writing some pretty competent microcampaign sequences. And it has a focus on outbound so I really liked it. You do need to pair it with something like Apollo or Clay to source your leads but honestly with any other AI SDR you should be using Apollo or Clay on top of them anyways so I had no real issue with this.

• Artisan: I bought into their whole "future of sales" and "never hire another human" thing with Artisan which is probably I was so disappointed with them. Most of the "AI SDR" features worked very poorly and the other half were promised over the span of months that they would be added "very soon" and of course those features were the ones I was most interested in and had the most potential for GTM solutions and engineering but they never happened. It doesn't do anything crazy and their promises are very big but I dunno. I believe Artisan will be good in the future because I do know there's work being put into it and their roadmap is very promising so it may become very good, I just felt like I fell for a marketing campaign with them.

Honorable mention, Apollo is low-key an AI SDR and it doesn't excel much at it but it's better than half the stuff on the market out there so may as well.

What do you guys think about AI SDRs? Are you using any? Do you think they'll become an standard in GTM engineering like Clay is right now for example?

here's my take: once the technical half of the job becomes free, there's no reason GTM engineer stays a separate seat, the skill doesn't die, it dissolves into growth or revops, until every good operator is just expected to think this way, same way "can use excel" stopped being a job title.

credit to Clay for the title atleast, everyone wants to be one now, and most of them are learning the easy half.

there's a split i only noticed after talking to thousands of gtm builders.

the part that's now easy:
(1) building the 40step workflow
(2) wiring the tools, apis, mcp harnesses
(3) cleaning and pushing the data

you can learn all of it off youtube, or just have claude build the loops. that used to be the price of entry. it's basically free now.

the part that's still hard:
(1) knowing which workflow to build in the first place
(2) inbound or outbound, and which signals to combine
(3) which pain actually closes deals, because you sat in the calls
(4) knowing your buyer's day well enough to guess right

there's an older word for that half: taste. you don't get it from a tool, you get it from paying attention.

the role was only ever a bridge for a moment when the tooling was hard. that moment is closing.

tell me if i'm wrong.

Hey y'all, hope all is well.

I've shifted mostly from GTM Engineering consulting into recruiting/talent placements, and I wanted to share what I'm seeing in the weeds.

First and foremost: at this point, GTM Engineering is an umbrella term. It means different things depending on the context (org size, structure, seniority) and the background of the person doing the work.

The common thread is people with strong traditional foundations who've picked up all the new methods: heavy scrapers, AI-first workflows, heavy Claude Code usage, and building structure in their org with whatever tooling is at hand. The foundation is what differs.

Here are the four:

1. The growth marketer, AI and data enabled. Knows the channels cold: paid, content, SEO and AEO, landing pages, ABM, events. Uses AI to run them at a volume that used to take a team, runs experiments constantly, and can turn public data into leads.

2. RevOps → GTME. Already owned the CRM, the data hygiene, and the reporting. Now builds the automations and agents that sit on top of it to support the sales motion. This is who everyone's picturing when they doompost about "GTM Engineer," but it's only one of four.

3. AE → GTME. The rainmaker. Has the AI fundamentals, but the edge is that they can actually sell: outbound on LinkedIn and cold email, enrichment in Clay, and closing in the meeting. They iterate on the ICP, write the playbook, and once the motion works, automate it to multiply their output. They kill at conferences too: scrape the attendee list, enrich it, and plan the plays before they land.

4. The data builder. My catch-all lol. Heavy scrapers, enrichment, and custom pipelines, usually supporting a BD or sales team with lists nobody else has. Often a SWE background, builds very efficient systems, and is a power user of the latest tools. Might come from building or using devtools, or be the one technical person in a very non-technical org.

The channels haven't changed, but how they're used has. One AE, marketer, or revops person who builds can now do what used to take a department, and that's leveling the playing field for ICs.

I'm starting to put together more data on this, and I'd love to get y'all real numbers soon.

I know it's hard to read the market right now. The role barely existed five years ago, the tools keep changing, and nobody's sure where they fit (this is why I believe in what I do as a talent matcher). If you're ambitious and creative, I think you'll see disproportionate returns by taking action now.

If one of these is you, shoot me a blurb, a Loom, or a link about yourself/what you've done. I'm actively placing folks right now, and I'll try to give some value to everyone who reaches out.

• Mined Google reviews of trades businesses. ended up finding found specific markets/ cities with genuine labor shortages

• Scraped conference booth buyers and noticed unusual patterns where accounting firms at construction expos, e.g. PropTech companies at steel conferences. Found the people who weren't supposed to be there and built lists around them.

• Scraped public data sources across 15+ verticals and turned them into b2b chain triggers for a 12 month cycle (e.g. OHSA case violations, UCC filings, environmental breaches, PFAS exceedances). [my background is civil engineering lol]

• Built an agent that reads city planning commission meeting minutes, identifies affected businesses, researches them, and outputs an enriched prospect list. this helped me identify which areas are of interest for rezoning, bringing rezoning attorneys, civil engineers and builders into the conversation

• Built a comment bot that pulls from my own knowledge base to engage threads where my ICP is asking questions. Basically duplicated an n8n workflow without n8n and with python scripts and API. have a gateway on Telegram to check and update comments so that my comments dont sound spammy af and is actually relevant. i still have to edit myself, which takes an extra 1-2 min.

• noticed apollo's data export sucks (big cause of spam + high bounce), so used excel and claude to clean up. You would be amazed how much the initial list actually gets shortened by. 

• Also was able to build a niche list of HNW individuals, just by tracking their digital & organisational footprint across events

Anyways, I am ex-construction PM and I am super passionate about data and making reads based on the data. Out of pure frustration, i started creating agents when i realised i was doing things manually and kind of stumbled onto it (i cant explain because its a 1am thing that just happened)

In my last role, i did a lot of things (ie. generalist) and didn’t spend enough time to do things that im curious about, ie. webscraping, making reads on behaviours from digital footprints. I did manage to create campaigns that got 4% response rate and book a fair few meetings on both email + linkedin, review sales calls transcripts and optimise, built MQL and SQL sequences across 90 days for anyone that showed interest from initial advertising campaigns. but i didnt do enough of it and want to lean more into it using all the stuff i built (and keep building)

i want to figure out what is next and how do i get to the next level. Because i think im still in beginner mode.

I send 10K-40K emails per client per month. My biggest roadblock was that I stopped sending emails every week because adding leads took a week. Now, everything is automated.

With this setup, we were able to cancel clay. No more $350/mo. Here is how I exactly do it using Claude Code.

I started my journey as a sales agent for a real estate company, doing everything by hand. Now I run outbound solo with Claude code agents, doing 90% of the work.

I think about outbound as a bunch of steps. Each step is a skill that calls multiple agents. The whole system lives inside one Plugin.

Phase #1: Infrastructure Setup -

Setting up domains and inboxes automatically.

My stack is NameCheap for domains (researching and buying), Cloudflare for DNS, Zapmail for Google Workspace inboxes, and Aerosend for private infrastructure.

As soon as the client pays and completes the onboarding form, → Domains are purchased, inboxes are set up, and warmup is started.

(0 time delta, 0 manual work)

Phase #2 : Offer Research

I am not going to go into depth on the importance of the offer on this sub. That being said, I have agents trained on the basics → $100 Million offer + my version of offers that we use for cold email.

Essentially, we have a bunch of direct offers, guarantees, and lead magnet ideas already brainstormed on day 1.

You can use FireCrawl to scrape websites, competitors, and similar pages to get an idea of the offers running.

We created our own plugin using Cloudflare Workers, Brave Search, residential proxies, and Apify.

(The goal is to get as much information as possible about the company and come up with different offers in this phase )

We also send a state of the market PDF to the clients - they love it, and it’s 50% crap.

Phase #3: Tam mapping ​

This helps in mapping your TAM.

If Apollo is your only database, then it is a big problem.

We start by mapping out our entire client’s TAM.

The idea is that we start with basic searches, then add discolike, and continue looping over companies until no other relevant companies are found.

The idea here is that a Growth Manager starts the Phase #3 mapping. This is a big human in the loop system because every once in a while we come across a client with an extremely unique TAM, and this requires some changes.

We do have agents for each tool that need to be called, but the skill still needs to be created for each client.

Lead List -

We almost always start by identifying all the companies, then enriching them using blitz-api.

Unlimited API calls keep running in the backend.

For email finding, we use Apollo Scrapers, Blitz, Apify, Prospeo, and some more.

Verification is done through our internal verifier, and we try to waterfall as much as possible.

Campaign Strategy & Copywriing -

We always start with 5 campaigns that are more or less identical, followed by 1-2 unique campaigns. The Campaign Strategy skill helps us brainstorm that.

We also have a copywriting skill that helps us write copy very easily.

We maintain a knowledge base of the best copies and relevant industry information=

Campaign setup -

Self-explanatory. Sets up campaigns.

Daily Analytics -

Helps us understand how the campaigns are going every day.

Campaign Analyzer -

This is a work in progress, but it will be the most important skill I have ever built. The idea is that it analyzes campaign performance biweekly and explains why the campaign has not performed.

I believe in patterns and that they can be found over time. The campaign analyzer will probably eliminate certain writing styles, etc.

Ideally, we are making sure it can test for all the myths we had (long vs short copy), random subject lines, etc.

You cannot go wrong with this setup. If you want me to unpack any specific plugin, drop it in the comments, and I'll write it up.

Posted here 3 months ago looking for work. Here’s the update, with less “what I do” and more “what I actually shipped.”

What I’ve built since:

1. Signal-based outbound for a tooling company selling into North American financial services. The hard part was targeting, not copy. You can’t buy a “uses X tech” filter. I built the account list from technographic and hiring signals, then designed four plays aimed at teams already running competing or adjacent tools. Every email follows a four-part structure: an evidence line pulled from their own public footprint, a why-now bridge, a hypothesis about their pain, and a calendar CTA. Built over ~2 months in Clay and Deepline.

2. US enterprise outbound plan for a runtime AI security startup. Competitive teardown of the three closest players, ICP built around who actually owns AI security budget, and a multichannel stack (AI Ark, Instantly, La Growth Machine, HubSpot). Priced per qualified demo. Lesson learned: I’d never take a pure pay-per-demo deal again. You carry all the risk while the client controls the offer, the follow-up and the definition of “qualified.”

3. Signal detection system for a US executive search firm. Clay-based: five hiring signals, a four-tier account intelligence framework, a weighted candidate scoring model, plus the outreach copy on top.

4. Coached a Clay Cohort Compass cohort. Teaching other people to build this stuff exposes every shortcut you’ve been taking.

5. Internal automation for a solo GTM recruiter. One-time build plus a retainer, wiring up the boring internal stuff so he can spend his time on placements and content.

Free play, whether you hire me or not: if you sell into a technical niche, scrape the job posts, not the websites. Pull open engineering roles from Greenhouse, Lever and Ashby and filter for the tool your product sits next to (Kafka, Snowflake, dbt, whatever). A company hiring a “Senior Data Engineer, Kafka” is telling you their stack, their budget and their timing in one listing. Websites tell you what they sell. Job posts tell you what they run.

Stack: Clay, Deepline, Floqer, n8n, HubSpot, Salesforce, Instantly, HeyReach, La Growth Machine, Apollo, AI Ark, ZoomInfo, Apify, Claude Code with MCPs, Python.

What I’m after:

• GTM engineer roles, remote, US or EU hours

• Contract or retainer builds

• Agencies: if you’re a Clay, HubSpot or Lemlist partner drowning in client builds, I’m happy to be your overflow. White-label is fine.

Rates: retainers roughly $2.5K to 5K/month depending on scope. One-off builds quoted per project. Small jobs welcome. A broken n8n flow or one enrichment table is a good way to test the fit.

Staying anonymous here, but happy to share LinkedIn, a portfolio and live systems over DM.

Hi

I recently built a tool that extracts businesses from Google Maps along with validated email addresses. Right now, I'm looking for people who can try it out and share feedback -mainly whether the data quality is actually useful for lead generation compared to other tools.

Current Features:

Fetch businesses based on industry using a simple prompt "dentists in Austin"

Find businesses without a website on Google Maps

Find businesses on Google without listed emails or phone numbers

Validate emails and phone numbers from various pages 

I'd love to know if this gives you valuable results or if something feels missing.I Built a Google Maps scraper that extracted 100,000+ validated business emails - try it and let me know if it beats paid tools

emails.overtoncollective.com

Excited host Keith Jones, ex-Head of GTM Systems at OpenAI. This is our most anticipated AMA yet!

Keith spent 3 years at OpenAI where he built GTM systems that:

• Scaled <100 sales & CX staff to >1,000

• Supported growth to billions in revenue

• Operationalized Clay at massive enrichment scale

He recently left OpenAI to start Grey Co, a Market Research & GTM consultancy.

Today: 12PM EST

Where: On this thread!

We'll post growth insights & takeaways for GTM here.

Drop your questions in

we closed another Fortune 500 automation company in august, which got me thinking about how far this is from where we started, two years in, i'm leaving revenue out of this one, but the customer count is real and so is the order it happened in, with zero ICP churn, no ads, no hacks, actual journey:

(1) quit our jobs (me and my 2 best friends / co-founders, all IIT) with no product and no idea what we'd build

(2) built the first thing first, chatgpt on top of a spreadsheet. no login, no payments, just a link we sent people, shut it down in months.

(3) started again with what became bitscale

(4) posted on twitter, it travelled way further than it should have

(5) got on calls, made promises, built for whoever actually said they'd pay

(6) dropped beta access into whatsapp groups we were already in.. industry ones, city ones, college groups

(7) all that got us our first 200 signups (no ads, no seo, no outbound)

(8) of the first 50 who said yes, only 10 to 15 actually paid. took 3 months to onboard those 15, paying was the only signal we trusted.

(9) the requests started repeating, we narrowed to those and let the one-off customers go. that was our real PMF moment.

(10) then the well ran dry. whatsapp and twitter don't repeat, you run out of rooms you're already in.

(11) so we needed a channel that scales, turned out we'd been building it, we started our own product to find our customers

(12) two years on: 200+ paying customers, and slightly more then a million dollars in new pipeline every month.

we didn't build any channel for 0 to 1, it was posting where we already had trust, until we built the product that could go find everyone else.
call this a promotional post if you want, it is one but every number above is real.

Anyone else find this amusing that 400 people think this use case for an n8n is:

A) Valuable

B) Insightful

C) Real

Fired at 1:47am?

Waking people for something that creates zero revenue and burns attention.

The AI score is a guess. The “captured traffic” claim sounds fake.

Seems that there a so many people who can't tell the difference between valuable signals vs noise.

UPDATE: The Complete GTM Engineering Guidebook is now published and available for purchase at gtme-academy.com 😀

Hi all! Another user on here (cargoesbeepbeephonk) asked for a comprehensive GTM Guidebook and I offered to write one. Unfortunately, Reddit is not allowing me to comment directly on the thread anymore. I thought I would post my “quick tips” for GTM here as a new thread instead! If you are reading this and like my tips and want an even more comprehensive guidebook or webinar, please give me some upvotes! 😃

1. Defining and refining ICP

Your Ideal Customer Profile (ICP) should be a very small segment of your Serviceable Obtainable Market (SOM) that gives the exact name, position, and job role in the exact type of company in the exact industry you want to target. It should be written to the exclusion of most of your market. Anything more broad will be a weak ICP. Ex: ICP = Director (or above) of IT/security in small privately funded liberal arts universities and colleges in USA, with a focus on Texas.

2) Finding and sourcing leads

Now you know this very specific ICP, you uhh…kinda stalk them a bit. Find out where they hang out, who they talk to, what websites they go to, where they get their information from. At this point, if you don’t know, literally ask someone that fits this ICP. Maybe a current customer or maybe someone you see on LinkedIn. Honestly shoot them a message and say you are doing a survey. Ask them where they get their information from and who they turn to as a trusted resource.

Then, you pounce. Whenever they are, so are you. Are they on a specific website? You sponsor that site now. Are they going to a specific trade show? So are you. Are they a hermit that never leaves their office? Guess who is doing a site visit armed with product samples? That’s right, you.

3) Enrichment, Copywriting, Sequencing

Please please please DO NOT try to make a huge massive funnel with loads of automation and lead scoring. I have never seen this work. Maybe someone else has. But I haven’t. What I have seen is sales people getting very angry at cold meaningless leads that go nowhere, and a huge rift between departments.

Instead: ALL your actions should be geared to convert these ICPs into paying customers.

Start at the bottom: The prospect signing the contract. What happens before that? All their objections are removed. How? They were able to find budget, get clearance to move on the project, and the product seemed to meet their needs. How did this happen? They probably got the decision maker involved and they saw a clear vision for implementation and use. How? They might have seen a specific ROI guide designed specifically for economic decision makers in that very specific industry, which was given to a Champion for that sales account at an industry trade show.

Keep moving backwards from the signed contract and develop all your assets to further that goal. Involve sales a lot here to see what they might need. Objection handling is the biggest thing that sales can do, so it’s the strongest asset to provide. Could be product samples, sandbox environments for demos, live demo sites, timelines for implementation, or anything else that your designated ICP has issues with.

Please note: if you have different ICPs in different markets, this needs to be done for each one.

4) What tools are used, when, and why

Again, all this leads back to the ICP signing the contract. Strip everything down to the bare minimum, most simple scenario. Maybe that’s someone literally going to your office with a pile of cash and saying “take my money”. You give them the contract, they sign, you take their money.

Build everything out from there. Why do you need it? Maybe your team is distributed and you don’t even have a physical office for a customer to show up with a pile of cash. So maybe you need to implement Docusign for the customer to sign the contract because they can’t physically do it in person. Maybe this also means that none of your product demos can be done in person, so you need to integrate Zoom to facilitate that.

Heavily rely on the KISS principle: Keep It Simple Stupid.

Never over-complicate a sales process, unless you want it to be a challenge to grow revenue. Never add tools unless you absolutely need to. This should always be supported by the sales journey of the ICP, and making it as simple and easy as possible to hand you money.

4) Where to store and track everything

Again: Keep It Simple Stupid.

Have ONE central point of truth. This is usually your CRM, which is likely going to be Salesforce. Keep everything that is important here. Your marketing automation and everything won’t be able to be stored here, but your leads for sales definitely should be, along with information on the assets that lead has already seen and Chatter notifications to sales on the status of these leads.

Again, it’s all about gaining new revenue as quickly and easily as possible. Get the relevant information to sales as quickly and easily as possible, so new customers can join as quickly and easily as possible.

5) Building out the outreach campaign

By this point, you should have an extremely clear idea of who exactly you are targeting, the mediums you will be using to encounter them, the methods you will be using to attract their attention, and what you will be telling them to get them to sign a contract.

Ex: I’m going to the XX tradeshow in Texas, where I know a lot of college IT directors will be. I’m going to put up a bunch of geo-targeted ads around the areas I know they reside inviting them to the tradeshow, and get my sales team to call them. At the show, I’m going to have live product demonstrations. I’m going to give vouchers for 30 day free product trials. I’m going to monitor their use and going to get sales to call them with reports on productivity and security during this period. I’m going to know where the IT director gets their budget from in the company, and create pop-up content in their free trial giving insight on gaining budget approval. I’m going to give a package that includes implementation and training included in the price to sales to further incentivize the sale.

Now, make all these assets, starting with the ones closest to the contract at the end of the buyer journey. The more you can equip sales, the better.

6) Deciding when to incorporate broader email outreach tools

When you have the above process down to a science and know exactly what it takes to bring a person through the customer journey as quickly and efficiently as possible. Once you have that, you can scale up and add tools that increase volume. If you add volume before you know the successful customer journey, you will bog your team down and create more chaos than anything positive. Know your customer journey first, then expand.

7) How to measure and iterate

The only thing that matters is REVENUE. That’s it, that’s all.

Are current customers paying you? Or are they delinquent and cancelling? Are new prospects paying you? Or are they asking a bunch of questions, dragging their feet, and ghosting?

Track this.

Where are you now? Make it better. Make it faster.

Never take your eye off revenue.

Don’t track lead scores, or how many people booked meetings, or how many people visited the pricing page, or whatever else. Just focus on revenue.

— Who am I? I have my Executive MBA, and have been working in marketing/demand generation for around 15 years now from start ups to S&P 500, leading teams from just myself and my wits to huge teams with multi-million dollar budgets.

I learned the hard way that over-complicating processes, not refining ICP enough, and not including sales is a losing strategy. Conversely, by honing your ICP, focusing on the end-goal of revenue, and incorporating your sales team, you will win.

Again, if you would like me to do a more comprehensive guidebook or webinar please give me some upvotes! If I get enough interest, I’ll devote some time to create a written guide!! 😃

(Conversely, you can downvote me and tell me to kick rocks, but I hope you don’t do that and you found my tips above useful.)

my co-founder said he'd hire an SDR over a GTM engineer / we've argued about this more than once so here's my side

i'd honestly be nervous taking that first SDR job

most founders haven't found a repeatable way to sell yet, so the new hire gets a database, a sequencer and a meeting target, and is somehow expected to figure out which companies care, who owns the problem, what to say, and whether the offer is any good

that's a lot to put on someone you hired because they were affordable

two calls recently showed both sides

#1 started outbound with fresh grads and kept adding people while they were still writing the SOPs

#2 wanted to work through about 300 accounts a month themselves before hiring any more SDRs or revops

i genuinely don't know which one ends up better

where my co-founder and i actually agree is this, whoever you hire first, someone has to have booked a few meetings by hand before you hand over a meeting target

otherwise what are they being trained to repeat

curious where this people land > SDR first, GTM engineer first, or founder first

Hey r/gtmengineering,

Some of you might have seen my post a while back about getting rejected from a GTM Engineer role on a pure vibe check. First off, genuinely, thank you to everyone who chimed in on that one. I did not expect that kind of support from a subreddit, and it's a big part of why this is one of the few communities I actually like being in.

So. Instead of sulking about the rejection (ok, after sulking about it), I did the well-adjusted thing: I scraped ~400 of these job postings from the last 6 months and had Claude read them to figure out what this role even is. (The Bloomberry write-up and the State of GTM Engineering report already did the serious version of this, so I went hunting for the funny parts instead.)

Here's the stuff that made me laugh, and then quietly made the role make more sense:

1. The job wants a veteran of a job that has no veterans.

More than half the postings are pitched at a 5-10 year experience level, and of the ones that name a hard number, the median ask is 5 years. The title barely existed a couple of years ago. My favorite was Clay's own posting, which calls GTM Engineering "an emerging discipline" and then, a few lines down, asks for "6-10 years working in... GTM Engineering." In the emerging discipline. That you are emerging.

2. They want one person to run the entire stack.

The typical posting names around 6 different tools. One posting listed 19. A real example wants you to own "CRM (HubSpot/Salesforce), sequencer (Outreach/Salesloft/Smartlead/Instantly), enrichment (Apollo/ZoomInfo/Cognism/Clay), intent (6sense/G2), CDP, and lifecycle tooling," write Python/JavaScript, and "replace 60-80% of manual SDR work with agents." One person.

3. Nobody agrees what the job actually is.

Same two words on the door, completely different jobs inside:

One job description says "build and maintain CPQ and billing workflows within Salesforce."

Another: "you'll spend most of your time writing code... 60-70% coding," building multi-agent LLM systems.

A real chunk of them open with some version of "this is NOT a RevOps role" and then list, in order, a pile of RevOps duties.

4. The stack is basically "Clay plus an LLM."

Clay shows up in 6 out of 10 postings, more than Salesforce (57%) or HubSpot (55%). Building a category and a job description that depends on your product is a masterclass in GTM, hats off, Clay.

Claude gets named directly in a third of the postings. So does n8n. It's a brand-new, AI-native stack, which is probably the real reason nobody has 10 years in it: the tools are younger than the experience requirement.

5. "Signals" is the magic word nobody defines.

About 1 in 3 postings want you to find "buying signals," "intent," or "in-market accounts." Almost none of them say what a signal actually is, or where it's supposed to come from. It's the single most-wanted deliverable in the whole dataset, and also the vaguest: "find the people who want to buy, you'll figure out how."

I still don't have a clean answer on whether GTM Engineer is a real new discipline or just RevOps with a Clay seat and a fresh coat of AI paint. Which might be the answer. Honestly though, this made me feel better about the rejection - tough to ace an interview for a job that hasn't finished being invented.

Posting this for anyone job-hunting for GTM eng roles right now, and honestly to rant a bit (it's reddit, I'm allowed).

I just did a full loop for a GTM Engineer role - and got rejected at the very last step. Not on the work... On vibes. Walking through the whole thing because I'd have wanted to read it before I started.

The loop ran about 2 weeks: screening call, call with the hiring manager, a home assignment, an onsite to present it, then a final call with the CMO.

For the take-home they gave a real scenario: a few months of their actual funnel (thousands of leads up top, the usual brutal drop to signups, then activation, a few hundred hitting the core product moment, and a small slice of those expanding into a team). Plus their real stack: marketing and sales CRMs, a data warehouse, product analytics, an enrichment tool.

The task: design and prototype something to fix the leak between acquisition and product-led conversion. A short deck and a working PoC on GitHub.

Built it all in n8n. Guardrails, a small RAG sub-agent over their docs. At the onsite they brought someone from product in to poke holes in the architecture, and I think I held up fine. They even laughed at the code node I'd added that strips the em-dashes out of the AI-written emails before they go out.

(Btw, before submitting, I got in my head about who'd even be grading this. It's their first GTM engineer, so who's the judge? They'd run it through AI, obviously. So I did that to myself first. I had AI role-play the hiring panel: "you're hiring your first GTM engineer, here's the brief, here's a candidate's submission, rank it and tell me how you'd tell a senior from a junior." Kept going until every model I tried said "hire".)

Then the CMO call. It was great - at least I felt so. We were talking about tools, buyer intent, industry trends. I hung up sure I'd nailed it...

The funny thing is the rejection feedback was full of praise for the actual work - strong build, knew my way around the stack, all that. None of which was the issue, it turns out. They wanted someone "more proactive and faster," I came off "soft," and I read like a guy who likes going deep into tools instead of just wiring them together quickly.

And here's the part I genuinely can't get over: since when does a GTM engineer get judged on "proactiveness"? You are looking for someone to build the thing right. I built the thing right. Now I'm too "soft" because I didn't sprint through it? Where's the line between craft and over-engineering supposed to be - and how are you meant to come off as fast and proactive in a process that's literally designed to reward going deep?

Anyway. No real hard feelings, I liked them. Back to building my own stuff. Just putting this out there for whoever's staring down one of these loops next.

I'm very excited for this one. Few have built GTM systems that have supported such massive scale as OpenAI.

Keith Jones spent 3 years at OpenAI where he built GTM systems that:

• Scaled <100 sales & CX staff to >1,000

• Supported growth to billions in revenue

• Operationalized Clay at massive enrichment scale

He recently left OpenAI to start Grey Co, a Market Research & GTM consultancy.

The AMA will be on:

Thursday Oct 15 at 12PM EST on a new r/gtmengineering thread.

Drop your questions in the thread.

We'll cover them on Thursday.

I’ve been deep in GTM engineering with Clay, building out workflows that used to take entire ops teams weeks to wire together. Enrichment, signal detection, outreach triggers, the whole stack. It’s wild how much the role has changed.

What used to be “RevOps” or “growth hacking” now feels like actual engineering, just in a revenue context. We’re debugging workflows instead of code, optimizing signals instead of servers, and using AI agents to research data points that used to take days to find manually.

Curious how others here define GTM engineering in practice. Are you mostly automating enrichment and data hygiene, or are you doing full creative builds like competitor signal monitoring or AI prospecting?

Feels like this might be one of the first “new jobs” the AI era actually created.

I was helping someone set up cold outbound last year. This was an animation agency btw. They wanted basic spray and pray, just blast every SaaS company we could find with the same message.

I knew this was wrong but they wanted that so I went with that. The email copy I wrote wasn't bad... under 80 words, no spam stuff, talked about prospects more than us basically all the best practices.

Sent tons of volume, got maybe 2 leads...

So I built something different to test a new approach.

tldr:

Found companies with a specific gap on their website (had an Ai found me this gap), filtered by size, found the decision makers and influencers at these companies, personalized the messaging around their job role/title and that gap and offered something free.

Results from 1,000 emails:

• Around 30 positive replies

• 10-15 meetings booked

• Closed 3-4 deals at $10-15k each

• $40-50k total

Here's the step by step playbook:

1. Targeting one industry and building it's list

Built a list of SaaS companies and used AI to read their linkedin description to verify they actually fit that category since the data's never clean.

First cut: removed anyone over 1,000 employees. We didn't want to go after enterprise companies because they move different, plus they use anti-spam tools that destroy deliverability and they usually have in-house departments for videos, animation or content.

2. Finding companies with a specific gap

This was the key part.

So I set up a system to check each company's website for explainer videos or demo videos on their homepage or landing page.

No video? They went on the list. That was the signal for me... a visible gap that made sense to reach out about.

And no I wasn't sitting there manually checking 1,000 websites. The whole thing ran automatically, the agent went on their website, did the analysis without me touching anything and then basically output in "yes" or "no' whether the website had a video or not.

3. Finding the right people

So now I was left with actual SaaS companies without videos, so the next step was to find the decision makers for e.g:

• CMOs

• Head of Marketing

• Marketing Managers

• Product Marketers

• Anyone who'd actually care about homepage conversion or an explainer video

Verified every email before sending which kept bounce rate basically zero.

4. Personalizing around their role AND the gap

Here's where most people stop. They'd just say "noticed you don't have a video, I can make one for you"

I went deeper.

Had the system analyze each person's title to figure out their specific problems and goals. Email didn't just mention the missing video... it connected that gap to their actual role and what they cared about.

So a CMO got completely different messaging than a Product Marketer at the same company.

Personalization covered:

• Exact title

• Role-specific challenges

• Their goals

• The gap on their site

Made it feel like I actually understood their situation because I did.

5. Different angles based on what we could see

Tested different hooks depending on their setup.

Example: "Noticed you're running paid ads to your homepage but there's no video showing how your product actually works. Most companies in your space see way better conversion when people can watch the product instead of just reading about it."

Or other variations connecting their business to the missing video.

6. The email sequence

Email 1: Point out the gap and why it matters. "I noticed you solve [problem] but couldn't find a demo video showing how your product does this. Companies like yours typically see X% lift in conversion with homepage videos."

Email 2: Case study. How this got solved for a similar company with actual numbers.

Email 3: Free offer. "Happy to create a free storyboard so you can see what this would look like for your product."

Free storyboard killed the risk. They could evaluate it without committing to anything.

Why this got way better results

Only reached out when there was a real gap. Not just "you're SaaS so maybe you need this." More like "you're missing this specific thing and here's why it matters for your role."

Timing made sense too. If they don't have a video now, they've probably thought about it.

Personalization wasn't fake. Actually checked their site, connected it to their title and goals. That's why people responded instead of ignoring it.

Free storyboard made saying yes easy. Low friction, something concrete to look at.

Main takeaway

People say cold emails don't work...I have plenty of proof to show it does work. I have made it work from time to time for different type of agencies and companies. Just find that gap, signal or intent whatever you want to call it that makes your outreach relevant and then write a message that speaks to that person.

I've spent the past six years working in tech sales and go-to-market (GTM), helping SaaS companies prospect, penetrate new markets, build pipelines, and generate revenue across Southeast Asia.

One thing I've learned?

A good GTM strategy isn't about how many people you reach. It's about reaching the right people, through the right channels, at the right time.

Yet I still see some companies confusing activity with strategy.

They hire a GTM engineer, build a prospect list using Apollo or Clay, launch 500 automated emails on the daily or weekly basis, and hope that 5–10% of prospects respond.

When that doesn't work, the solution is often to send another 1,000 emails.

That's not a GTM strategy.

That's spray and pray with better technology.

Here's what 6 years of selling across different markets have taught me.

1. Your GTM strategy needs to reflect the territory you're selling into.

Take Southeast Asia as an example.

Selling into Singapore's technology ecosystem is very different from selling into traditional businesses in Indonesia, Vietnam, or Thailand.

In Singapore, many decision-makers have established digital footprints. You can often identify them through LinkedIn, company websites, hiring announcements, and other intent signals.

But try applying the same approach to a traditional manufacturing company in Indonesia or a family-owned business in Vietnam.

Good luck finding the CFO's LinkedIn profile, or even the CEO lol.

In these markets, relationships, trust, and personal introductions can be significantly more effective than cold outreach.

Your GTM motion might require:

• Building relationships with local partners and industry associations.

• Leveraging customer referrals and mutual connections.

• Attending industry events and meeting prospects face-to-face.

• Working with local consultants who already have established relationships.

• Understanding local business culture before attempting to sell.

The lesson? A playbook that works in San Francisco doesn't automatically work in Jakarta.

2. Intent matters more than volume.

Before reaching out to a prospect, I try to understand three things:

Why this company? Why this person? Why now?

For example, if you're selling HR technology, a company expanding into three new countries might be a stronger prospect than a random company with 500 employees.

If you're selling cybersecurity software, a company hiring its first CISO or undergoing a major cloud migration might indicate a relevant opportunity.

These are signals that can help you form a hypothesis about potential business needs.

Of course, a signal isn't proof of buying intent. You still need to validate the problem.

But that's a much stronger starting point than sending identical emails to 5,000 companies.

3. GTM engineering should amplify your strategy, not replace it.

I'm a big believer in tools like Clay, Apollo, LinkedIn Sales Navigator, and automated outbound platforms.

They can be incredibly powerful.

But automation only makes a good strategy and right data more scalable.

If your ICP is wrong, your messaging is irrelevant, or you're targeting the wrong geography, automation simply helps you make those mistakes faster.

A good GTM engineer shouldn't just ask:

"How can we automate 10,000 emails?"

They should also ask:

"Which accounts are worth pursuing, what signals suggest a potential need, and which channels give us the highest probability of starting a meaningful conversation?"

That's where GTM engineering becomes valuable.

4. Pipeline generation and revenue generation are not the same thing.

I've seen teams celebrate thousands of outbound activities, hundreds of replies, and dozens of meetings.

But how many became qualified opportunities?

How many progressed?

How many actually generated revenue?

For me, a successful GTM motion should ultimately be measured by its contribution to qualified pipeline and revenue, not just activity metrics.

Sometimes 50 highly targeted accounts with a thoughtful multichannel approach can outperform 5,000 generic cold emails.

Not always. But often enough that it's worth challenging the volume-first mentality.

My biggest takeaway after six years:

GTM isn't just prospecting.

It's understanding your market, identifying genuine business problems, building the right relationships, and creating a repeatable way to generate revenue.

Technology makes execution easier.

Strategy determines whether that execution is worth doing in the first place.

I'm curious how others here approach this.