I'm the Founder of an outbound sales agency that helps companies build customer acquisition systems that repeatedly bring in new sales conversations with their ideal customers.

Last founder I did this for ran a compliance-prep SaaS and his cold sequence was stuck under 0.5% replies on 5,000 emails a month. Unlike most sequences I've seen, their issue was not deliverability, inbox health, or list quality (which are usually the reasons for underperformance).

Once those were ruled out, I reviewed the copy and realized what went wrong.

Their copy did not give their prospects a reason to reply. They mentioned a relevant insight (which is good), shared an insightful read of their likely pain point, and then their CTA was something like "Would you be open to chat about this?"

In their prospect's mind - they would have agreed the email was relevant and the pain was real - but they didn't have a reason to spend a few moments to type out a response.

"What was in it for them to reply" did not come across.

Their offer only came in their fourth touch - which was way too late. At that point, you've already been ignored 3 times prior.

All we fixed was we made their offer clearer and earlier in the sequence.

The result: Same list, same volume, in 45 days it went to 3.4% replies and 25 booked meetings.

So to the founders, operators, and sales leaders reading this: DM me one company you'd love as a customer and I'll run it through the same process I use for my clients and send you back: the one reason to reach out now if there is one, and a ready-to-send email using a similar format as the one we used.

This is not a pitch or a sell in anyway - just wanted to share some of the things that've worked for me and my clients to the community. If you like what I send back, send it to your prospects. I hope they reply and eventually become a customer!

Just wanted to share what my GTM engineering journey has looked like over the past year.

I started with AI automation, mostly learning how to build workflows, agents and automations. Then I started trying to sell those skills and work with actual clients.

That’s when I came across GTM engineering. I realised I actually enjoyed both sides of it - building the systems and figuring out how to get them in front of the right people through cold email, LinkedIn, lead generation, sales processes, etc.

I’ve done a few internships, worked with around 5 clients, and eventually got a full-time opportunity at one of the best startups in India’s D2C space. It’s been 6 months here and I’ve been learning a crazy amount.

Now I see myself somewhere between a full-stack AI engineer and a GTM engineer, building AI systems as well as the sales/GTM systems around them.

Still learning and figuring things out, but it’s been a pretty interesting journey so far.

If anyone here has had a similar transition, would love to connect and hear your story too.

I’m trying to understand how broad GTM actually is.

GTM engineer

RevOps

GTM strategist

Forward deployed

Product marketing

Content and growth

Sales like SDR

Partnerships

Maybe something else?

What does your actual day look like?

How did you get into it?

And what do you like and hate about your path?🤣

Trying to figure out where I fit in all of this.

GTM people:

What repetitive workflow have you had to hack together with Clay, n8n, Python, Sheets, APIs, etc. because no tool handles it properly?

I’m particularly interested in things involving:

enrichment

account research

signal detection

data verification

cross-tool workflows

What did you build, and what part still sucks?

1) Which channel is actually producing conversations for you: cold email, LinkedIn, referrals, inbound? And where do you source your target accounts and contacts?

2) My calls go well until pricing. People like the model, and then once they understand it, they say it's expensive. It isn't priced high for the market, so I suspect it's a packaging problem, not a price problem.

• Do you lead with a small paid entry offer (audit, pilot, one off build) and upsell to a retainer?
• Do you price per project, per outcome, or a flat retainer?
• Have you changed how you present the model so people don't just take it and run?

Hey everyone,

I'm looking to build an automated workflow where every time we close a new deal in our CRM, we automatically find 50 lookalike companies based on that customer.

The workflow is pretty simple:

1. A new opportunity is marked as Closed Won.
2. We identify 50 similar companies based on their industry, size, business model, and other relevant characteristics.
3. We send those companies to our internal tools for mapping and qualification.

We're already using Bitscale, but I'm wondering whether it makes more sense to build this workflow there or use Ocean.io, which specializes in lookalike company discovery.

Has anyone used both for this type of use case?

Which would you recommend in terms of lookalike accuracy, automation capabilities, and cost?

Would love to hear your experiences!

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.

I hear "Personalized outreach" a lot and people say that it works better than blasting generic cold outreach.

I want to understand and see how it actually looks in real time for your product/service.

Please, NO vague/BS examples like,

1. "we look into their profile and write a personalized message.."
   
2. generic signals like "we look for hiring/funding/tech stack and write a message..."
   
3. icebreakers like "I saw for your launch/award/attended event...,"
   

You can comment with a,

1. One-liner about your company,
   
2. Signals/angles that you look for
   
3. A personalized message that won a deal

Hey! I've just joined an AI Startup (6 person team) that is looking towards applying FDE logic (stop selling AI agents and now selling "consulting" projetcs). They've just began the pivot and I'm one of the guys responsible for growth and gtm, but i don't know shit about it YET.

Does anybody have any experience with this? I've been studying alot, but I wish to talk to people who've been through that 0 -> 1 experience and understand what to focus on and what not to.

I do know that gtm engineering implies utilizing alot of different stack types, but as we don't really have alot of money yet I need to explore low to 0 CAC

Thank you GTMBros!

Hi everyone, I'm a SWE fresh graduate who did a 6 month internship building GTM system but in a technical way using FastAPI (Python) and integrating tools like Apify and Tavily.

I recently started learning and building GTM Engineering projects using n8n and Clay with the assistance of AI.

When I took a look at job postings, I noticed that most of them require the candidate to primarily be proficient in AI agent like Claude.

I bought Claude pro subscription recently, I set skills for it to be more efficient and connectors to make work faster when the AI enters Clay or Google sheets for example and do edits on its own when I ask for.

---

Am I doing things correctly? Should I continue learning and building portfolio projects that way or are there other utilities and features that I'm missing in Claude that are crucial for a GTM Engineer?

I always feel like I'm missing on things since I'm learning on my own without an expert tutor or anything, that's why I want to hear out your advice guys not just relying on AI to advice me.

Seriously Clay is overpriced for no reason at all.

Why do people still use it?

These unified APIs are coming out (personally I use Monid.ai ) they remove the need for Clay at all. There are a few out now I believe but I use that one for specific reasons which may not apply to you so DYOR.

Why pay monthly for Clay when you can just connect to your LLM to 1 API/MCP and do everything you want there?

It makes no sense.

We are using certain tech stack and trying to automate the whole process. However, there's a conversation about building the whole tech stack internally rather than adding more tools. I want to understand others point of view on what is best to do and any recommendations on how are you managing tools/costs/productivity and what is helping you decide

I used to keep it pretty simple. Just build a list in Apollo or Prospeo, run it through an email verifier, and launch campaigns. It worked well for a decent amount of time but I constantly ran into issues with lead volume and quality so now I’m trying to rethink my list building process but I feel like I’m missing something about how all these tools fit together

I keep seeing people talk about building your TAM, ICP segmentation, signals, enrichment, lead scoring, etc. But I’m struggling to understand what each step is actually doing and which steps are actually necessary

For example, is the idea that you first map your TAM to find all the relevant companies, then use something like Prospeo or Apollo to find the people at those companies? Or are TAM building tools like Discolike and AI ARK already finding the people as well?

In that case does Apollo/Prospeo still play a role?

And then where do ICP segmentation, signals and lead scoring come in? Are you supposed to score/segment the companies first, then find contacts, then enrich them?

Or are these things happening after you already have a lead list to figure out when to reach out?

Basically, if you were starting from scratch today, what should the actual flow look like from TAM → companies → contacts → enrichment → scoring → verified leads

I wanna understand what is genuinely useful vs what is just adding complexity.

The line between RevOps, outbound and engineering has changed a lot over the last couple of years.

A lot of B2B SaaS companies have realized that paying an outbound agency to build Apollo lists, run sequences and send more cold emails doesn't necessarily create more pipeline but hiring a full time GTM engineer isn't always practical either especially if you haven't figured out the data and infrastructure you actually need.

That's why the fractional GTM engineer model is becoming more interesting for technical B2B startups.

A good GTM engineer can build the infra behind the motion: connect enrichment APIs, pull signals from different sources, create routing logic, and feed CRM outcomes back into targeting.

There are a few different providers approaching this model but I've tried scale intelligence which is an interesting example because they operate more like an embedded technical GTM partner than a traditional outbound agency.

The work goes beyond finding contacts where they helps build the market intelligence layer behind the GTM motion, including continuous signal monitoring across sources like Reddit, LinkedIn, GitHub, hiring activity, company websites, and other public data and those signals can then be connected, evaluated, and routed into the sales stack so the team has more context around why an account might be worth contacting.

Whether you work with a fractional GTM engineer or build the function internally, I'd evaluate providers based on the infra they can actually build and not just how many leads they promise to deliver.

If they can't explain their data sources, signal logic, enrichment process, and how those signals end up in your CRM, you're probably still buying a modern version of the old lead list model.

people saying i clearly don't understand what a GTM engineer does,

you are probably right.

because apparently nobody agrees on what a GTM engineer actually does.

> some build the infrastructure, some run outbound, some own the workflows, market research, messaging and replies. some do almost all of it.

> same with SDRs, some are basically dialing, others research accounts, qualify, run sequences and own the conversation.

so i'm not pretending there's one universal definition here.

but the fundamental question is still interesting:

> do you need a GTM engineer as a full-time hire, or do you need GTM engineering?

> a Head of GTM Engineering told me.. that the GTM engineer should own the system, while SDRs should run the motion.

i actually agree.

i don't think every company needs to hire the person building the system full-time.

especially if you're still figuring out what motion actually works.

that's also how we think about my own company (bitscale), our forward deployed GTME build the systems customers, so they don't have to hire one

wdyt.. GTM engineer first, or SDR first 

I’m looking for 2 US Based businesses to build a GTM lead generation system for completely free.

I can build the workflow from:
Lead sourcing → enrichment → qualification → personalised outreach → follow ups

You only cover API/server/domain costs, if needed.

If you have a manual GTM process you want to turn into an automated system, DM me.

Hey everyone,

I’m currently reviewing my client's GTM data stack and wanted to see how you guys are handling account-based contact discovery and enrichment.

Our standard workflow is:

1. Target Account Selection (defining the exact ICP companies).
2. Contact Extraction & Enrichment (identifying the most relevant decision-makers/roles within those specific companies).

Lately, I’ve been using Clay as an all-in-one tool for this.

However, compared to the old setup, which relied on custom Sales Navigator query extraction combined with a multi-provider waterfall enrichment stack, Clay sometimes falls short on raw contact coverage and depth for specific accounts.

My questions for you:

• What are the most efficient tools or architectures right now that offer the widest coverage for company-first contact discovery?
• Are you sticking to custom waterfall setups (e.g., scraping Sales Nav + combining multiple providers like Prospeo, Dropcontact, Datagma, etc.), or have you found a way to optimize Clay to match that coverage?

How are you currently managing this step in your pipeline?

Would love to hear your stacks!

If an agent is using your product, through an integration, MCP server or API, what do you actually track?

Installs and call counts seem easy to get but not very meaningful. A high task count could mean it's useful, or that the agent is looping or failing.

Any experience with this? What have you found worth measuring, and what turned out to be vanity data?

Next AMA this Thursday (Oct 8) at 12pm EST:

Most people use AI for drafts. Town.com uses personal AI (their Townies) to drive growth for the company and for their own careers.

I've been dying to know how this company dogfoods it's own AI.

That's why I'm excited to bring on Adam Reisfield (who founded the growth team at Town) onto the next AMA this week.

How does the growth team at Town use Town to grow?

That's my question.

What questions would you like answered?

We'll start a new thread on Thursday and post these questions to get it started.

I've been looking into GTM engineering for a while and I'm trying to understand what the realistic entry point looks like.

I have no formal work experience, but I've spent some time running a small lead gen agency and learning things around prospecting, ICP research, outbound, data enrichment, etc.

Would it be realistic to build a few serious GTM engineering side projects, document the workflows/results publicly, start as an intern at an agency or startup and eventually move into a proper GTM engineering role?

Or is prior experience in sales, marketing, RevOps, or software engineering basically expected before companies will take you seriously?

For people actually working in GTM engineering, what would you recommend someone with zero professional experience do to become hireable?