What a GTM Engineer is NOT??

The origins of GTM Engineering, and how it came to be

In 2025, companies are increasingly turning to “GTM Engineering” as a way to automate and scale creative go-to-market strategies across sales, marketing, and success through a blend of data, LLMs, and workflow orchestration.

As this discipline emerges — like every time new trends do — it’s normal to hear contrasting opinions and misconceptions. We’ve seen it 10 years ago with the growth hacker, and even with RevOps. Companies confuse GTM engineers with RevOps, growth PMs, and even CRM admins.

So, what is GTM Engineering? First of all, we feel more needs to be said about the origins of the term, how it came to be, and why now. With that in mind, we’ll have more context to define it. But while everyone is trying to give a positive definition of the term, we’ll do the opposite and unpack our anti-definitions instead — what GTM Engineering is not.

Then, in the next post, we’ll lay out a first principle thinking framework and primitives to help people get their heads around this emerging, multi-disciplinary position.

The origins of GTM Engineering

Let’s first trace back the DNA of GTM Engineering. While the first job titles were made popular in early 2024 by Clay, the role isn't as new as it seems.

Companies like Ramp, Gorgias, and Rippling — considered among the golden standard of growth teams — have been the pioneers of embedding engineering talent and skill sets within the go-to-market function.

Whether they were called growth engineers or growth ops, these roles shared the usage of automation, data, and APIs to scale pipeline and revenue without increasing the size of the go-to-market team.

Growth engineers were the technical counterpart to growth marketers — building technical solutions to solve GTM use cases in an efficient and scalable manner.

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But, where does this need for GTM efficiency suddenly come from? There are two key factors contributing to the rapid rise of GTM engineers last year.

First, When VCs pulled back their money in 2023, startups had to keep scaling revenue without expanding headcount — or actually firing half of their teams — making GTM efficiency the name of the game. In other words, they needed to:

• Maintain or speed up time to market, pipeline and revenue velocity

• While improving efficiency and costs metrics (eg. cost per opportunity, ROI, etc.)

• And keeping headcount constant (eg. revenue per employee)

However, “automation” still meant getting an engineer to work on building custom scrapers, ETLs and data warehouses connections — strategies that were not that accessible to most teams, especially given growth engineers were not just rare, but also expensive!

That’s where the promise of the last generation of LLMs comes in. New SaaS categories quickly emerged between 2023 and 2024 wrapping few critical ingredients of growth engineers into low-code SaaS and making them A LOT more accessible to non-technical users. Think like:

1. Custom waterfall enrichment to make prospecting and research dead easy

2. Workflows UI to line up multi-step, tailored GTM operations across the lifecycle

3. LLM capabilities and prompt engineering to scale research and personalization

4. Robust integration layer with built-in APIs

The result has been a fervent and colorful GTM tech industry popping up in the last 24 months — with plenty of leading players like Clay, Cargo, Lemlist, LaGrowthMachine, Common Room, and AirOps, blending or specializing in the above capabilities.

Suddenly, you could do the advanced work of a growth engineer with just a few lines of code — and you could actually code the rest by just prompting ChatGPT.

And in late 2024, the concept of “founder mode” popularized by Brian Cesky compounded this efficiency mantra of “doing more with less” into the industry. This — coupled with the ever-present promise of AI — made the idea of small, lean, and technically-enabled orchestrators too compelling to ignore.

With the entire industry on founder mode — and the right AI tools for the job — there were no more excuses. A new storm was coming.

Service-as-Software and the wave of Clayagencies

In this new hyper-competitive arena, everyone needed to keep scaling GTM operations efficiently but no one could afford in-house growth engineering that would do custom “integration or automation work”.

That’s why GTM Engineering started to become popular; because it’s a role that blends capabilities and knowledge across sales, marketing, customer success, and engineering in one person.

A cross-functional GTM skillset alone yields massive efficiency gains — because you have one person doing the job of three — and when enabled by the right AI tools and workflows, its promise scales 10X.

With that in mind, it became clear that a growth engineer wasn’t a must-have to build complicated workflows in your GTM motion. But a hands-on, semi-technical GTM operator with Clay and an email sequencer could do it. And as more non-technical teams got exposed, the promise of GTM Engineering grew, and the overall movement accelerated.

However, it’s still very rare to find this type of talent; and even when you do, it can be expensive and risky, especially as a full-time hire.

That’s why we believe one of the first cohorts to really help grow awareness of the role were the so-called Claygencies. These were outbound agencies (and consultants) that embraced the GTM Engineering principles on various fronts. These operators consistently:

• Use AI-powered GTM tech to scale beyond $1M ARR with extremely lean teams, really embodying the core premise of GTM Engineering.

• Provide expert GTM services in the form of process workflows, and have strong incentives to productize these workflows with software and AI.

• Use AI and their toolstack as a core differentiator from ‘traditional agencies’, and to showcase their differentiators via the creative workflows they build.

• Offer a more specialized and lower-risk alternative to full-time hires, who are harder to find and more costly to onboard.

And that’s why we’ve seen Clayagencies take over LinkedIn with tool- and workflow-related content on LinkedIn. All the tools, plays, and workflows were all over Linkedin for grab — an insane awareness machine for the entire GTM tech industry and players alike.

Emerging vendors seized this moment to carve their spot in the industry and spin up their agency programs, each for their own ‘niche’ — RB2B for website deanonymization, AirOps for content and SEO, and so on and so forth.

And a new category of agencies and consultants was born — service-as-a-software. A new business model — with AI and GTM Engineering capabilities at its core — that would answer both calls — GTM efficiency and ‘founder mode’.

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Stack vs. Expertise — what matters most?

At this point, the underlying question emerged:

“What matters most to drive GTM efficiency? The tool stack or the GTM Engineering execution expertise?”

The Clayagencies buzz initially took off largely due to capabilities that these new tools democratized — waterfall enrichment, AI workflows, and the likes. If you step back, the underlying tech primitives haven’t changed — we had Clearbit for enrichment, workflow editors like Zapier, and ETLs like Segment even before 2020.

The real spark came from making these capabilities more accessible to semi-technical users, and layering the LLM component and prompt engineering on top — which shortened the learning curve and opened the door for more niche, specialized platforms.

Look at any feed and you’ll see a flurry of tactics and workflows touting a slick, new specialized data provider or email sequencer — often packaged as plug-and-play workflows you can easily copy and paste.

“Just comment ‘workflow’ and you’ll scale 1000 meetings in 1 day.” We’ve all been there!

Yes, it’s hard to resist the allure of a “silver bullet,” and yes, these new workflow tools really make it super easy to achieve results. However, now that the cat is out of the bag and these tools are known and accessible, we believe that the elephant in the room comes down to one thing — execution.

So, to answer the question, we believe expertise matters A LOT more than the underlying stack.

Which brings us to the next topic.

What GTM Engineering ISN’T all about

Armed with this additional context, let’s move onto our anti-definition(s) of GTM Engineering.

1) GTM engineers don’t define the entire go-to-market

First and foremost, we believe GTM engineers scale an existing strategy instead of inventing one. GTM engineers don’t select markets, craft messaging, or determine positioning — those decisions come from leadership, marketing, and product. Instead, GTM engineers enable these teams to streamline scattered processes into scalable workflows.

And while GTM engineers don't set strategy, their technical expertise can help uncover new, creative, and performant ways to achieve an outcome. For example:

• The Marketing Director doubles down on LinkedIn Conversation Ads, targeting Salesforce users, who drive higher retention, engagement, and ACV.

• Instead of relying solely on the TAM list and CRM contacts, GTM Engineering proposes to expand the audience by pulling recent companies using Salesforce as their CRM.

• The Marketing Manager runs a focused Salesforce campaign, while the broader team targets US-based SaaS companies (50-500 employees).

• The GTM Engineer then helps build an automated system to enrich incoming LinkedIn leads with technographic data, analyze intent signals, and use an LLM-driven scoring model to prioritize leads.

• For Salesforce campaign users, reps receive key insights enriched with real-time news, promotions, new hires, and job postings. An LLM like Claude 3.7 Sonet summarizes the data, making it ready for outreach.

• For high-intent leads, the system automatically triggers personalized outreach emails from the AE’s account, tailored to the prospect’s tech stack and company news. AEs get timely notifications for follow-ups, turning hours of manual work into a streamlined, data-driven process, while still supporting the original marketing strategy.

Marketing still owns the ad strategy and Sales the engagement process, but the GTM engineer's technical capabilities opened up new, scalable ways to achieve the same outcome.

2) GTM Engineering are not Growth PMs or Growth Engineers

We’ve made this distinction before, but we want to make this even clearer.

Growth PMs and engineers emerged to drive activation, retention, engagement, and monetization metrics through experimentation. While there are overlaps with GTM Engineering, there are two crucial differences:

• Technical execution: While growth PMs coordinate with growth engineering teams, GTM engineers directly build and implement technical solutions.

• Scope of impact: Growth PMs and engineers typically own specific product metrics like activation, free-trial to demo conversion, or sign up page conversion improvements, while GTM engineers influence and contribute to pipeline and revenue metrics across the entire customer lifecycle.

And whether there’s a lot more overlap between Growth engineers and GTM engineers, let’s just say that:

• Growth engineer is more involved in the dev work based out of experiment hypotheses — and work with PMs and designers to pull it off — less so in the business understanding.

• GTM engineers are more involved in the business, work primarily with the business teams, and are proactively influencing those decisions.

3) GTM Engineering are not RevOps

Out of all the mixed-up roles, RevOps is probably the most often mistaken for a GTM engineer, probably because RevOps and GTM Engineers work closely together. However, they serve fundamentally different purposes. The key difference is that:

• RevOps focuses on the foundational strategy and pipelines — like setting up the CRM instance, decide which fields to report, the pipeline stages, foundational journeys, and reporting layer across marketing, sales, and success.

• GTM Engineering scales the efficiency of these foundations via tailored, automated and technical solutions.

So while RevOps helps decide where to allocate budgets, GTM engineers focus on maximizing that ROI through technical innovation. And when GTM engineers identify successful experiments, they work with RevOps to roll them out to the entire organization.

For example:

• RevOps might suggest increasing ad spend on Google because they mined as an insight from their attribution model.

• GTM Engineers work with RevOps and Demand Gen to implement server-side tracking enriched with firmographic data and feed that data back to Google to improve Performance Max campaign results, therefore, achieving higher conversion rates and more pipeline.

Let’s see some more aspects where these two compliment each other:

If nothing else, GTM engineers are probably the wingman RevOps has been searching for.

4) GTM Engineering isn’t just about new business and outbound

The common misconception is that GTM Engineering primarily serves top-of-funnel activities — building outbound automation, enriching lead data, or creating target account lists. And while a lot of GTM engineers and agencies made the movement famous with list building and personalized outbound, reducing them to these tasks misses their potential.

Think of a GTM Engineer building an intelligent early warning system for customer success.

• Rather than just tracking basic usage metrics, this system combines multiple signals: product engagement patterns, job changes across multiple stakeholders — like when champions leave or new executives join — sentiment indicators like NPS scores, support ticket tone; and renewal context.

• When the system spots potential churn patterns — such as a champion departing followed by declining feature usage — it automatically triggers the right messages to the right stakeholders on the right channels.

• This proactive approach helps teams prevent churn before the obvious signs appear, turning potential risks into retention opportunities.

GTM engineers don't just support existing processes — they reimagine what's possible through the lenses of the new AI tooling available today.

Good GTM engineers ask: "How do we automate this manual process?" But the best GTM engineers ask: "How can we use AI and tech to give our GTM teams superhuman capabilities?"

Again, consider these other use cases way beyond just list building and outbound:

• Automating win/loss case analysis from customer calls to refine ICP, messaging, and trickle those updates into multi-channel campaigns.

• Programmatically score and route prospects into tailored nurturing journeys with AI without SDRs doing manually allocation and CRM hygiene.

• Create an automated workflow to turn customer calls insights into long-form content that can be repurposed across blog, LinkedIn organic, and retargeting ads.

These use cases show the potential for scaling GTM efficiency across teams, and stresses how GTM engineers build the technical bridge between strategy and efficient execution — and not just for generating new business, but also expansion!

Most importantly, this approach creates a compounding, ripple effect across the organization:

• Sales teams ask "Could we build something to predict which deals need attention?"

• Marketers think "How can we automatically personalize campaigns based on intent data?"

• CSMs wonder "What if we could predict churn before it happens?"

It's this cultural transformation that empowers every GTM team to think creatively and consider technically-enabled capabilities to achieve specific outcomes that makes GTM Engineering truly powerful.

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5) GTM Engineering isn’t just about technical execution

While most of today's LinkedIn discourse suggests GTM Engineering success comes from simply connecting tools and writing code, once again, this view dangerously oversimplifies the role.

GTM Engineers are, yes, technical strategists who build integrated systems across the entire revenue organization, but they’re not like “developers taking requirements” from business teams. They translate business context into technical architecture while orchestrating solutions across teams — making the role both challenging and critical for scale.

Technical skills are crucial, but they're just one piece of the puzzle. The reality? GTM Engineering requires three-dimensional thinking.

1. Business understanding. Instead of just automating a process because "we can," top GTM engineers go deeper, and probe things like:

   • Why does this matter to revenue?

   • How does this scale with our existing GTM motion? (eg. given our PLG or SLG)

   • What are the short- and long-term impact of this on adjacent teams?

2. Systems thinking. Rather than building isolated solutions, they consider:

   • How do marketing, sales, and product workflows intersect?

   • How does this affect the customer journey, experience, and buying process?

   • Where are the data inputs, outputs, and handoff points?

   • What breaks if we scale 10x?

3. Technical excellence. Beyond just making things work, GTM Engineers build for resilience:

   • How can we intentionally vet, test, and integrate new GTM tools?

   • How do we plan for gracefully retiring them if they no longer fit?

   • What happens when data quality from different vendors degrades?

   • What metrics or logs can detect performance issues, data synchronization failures, or API outages in real time—and who gets alerted

So, what does GTM Engineering mean then?

Taking all into consideration, here’s our best definition of a GTM Engineering.

GTM Engineering blends technical expertise — waterfall enrichment, AI workflows, prompt engineering, and custom APIs connections — with system thinking and business understanding across the entire funnel. Based on this skillset, GTM Engineers build systems that open up new, creative ways of scaling business outcomes and GTM efficiency without the scale headcount proportionately.

This definition highlights how GTM Engineering isn't a one-size-fits-all toolkit you can simply plug in and play — it requires careful customization to your organization's GTM motion, product complexity, and team setup.

If you look at Unify and Common Room, you’ll see playbooks are already becoming productized and will soon be commoditized. The real value comes from using these unique skills to unlock creative ways that give your company unique advantages in how you engage and grow your market.

In the next post of this series, we’ll dig deeper into the lifecycle of GTM Engineering, and reveal our framework to execute on these problems.