GTM Engineering Has a Scope Problem
The discipline claimed the tools. It forgot to claim the strategy. Why GTM engineering needs to expand its strategic boundaries.
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GTM Engineering Has a Scope Problem
The discipline claimed the tools. It forgot to claim the strategy.
GTM engineering showed up around 2022-2023 with a compelling pitch. RevOps was too slow, too buried in process, not technical enough to keep up with a sales and marketing stack that had quietly become a software problem. GTM engineers would fix that. They’d write code. They’d build pipelines. They’d automate what RevOps had been doing manually with spreadsheets and Zapier flows.
The market agreed. LinkedIn RevOps postings dropped 19% between May 2024 and May 2025, while GTM engineer listings on the same platform climbed from effectively zero to over 1,400 in the same period, according to Pavilion’s analysis of job market data. Indeed showed an even steeper RevOps decline at 22%. The shift was real, and the frustration driving it was legitimate. RevOps had become a bottleneck in organizations that needed to move faster than quarterly planning cycles allowed.
But here’s what I keep coming back to: the discipline defined itself by what it replaced. It inherited RevOps’ scope, added Python and API integrations, and called it a new function. That’s not a new discipline. That’s an upgrade package.
The Boundaries We Drew
Bloomberry analyzed over a thousand GTM engineering job postings and found that nine out of ten listed responsibilities overlap directly with RevOps. Nine out of ten. The only meaningful divergence? RevOps postings emphasize sales forecast accuracy. GTM engineer postings emphasize automation and integration. The “is this just a rebrand?” conversation has been circling the industry for two years now, and I understand why. From the outside, the overlap is hard to ignore.
But the rebrand debate is a dead end. It keeps us arguing about labels when the real problem is boundaries.
Look at what GTM engineering claimed when it carved out its territory: enrichment workflows, lead scoring, outbound automation, workflow orchestration. Tools like Clay and Apollo made these tractable as engineering problems for the first time. Where RevOps teams were stitching together manual processes across six platforms, GTM engineers could write code that handled enrichment at scale, built scoring models that actually updated in real time, and automated outbound sequences that would’ve taken a team of SDRs a full quarter to configure.
That’s genuine progress. Clay turned enrichment from a weekend-long CSV exercise into a programmable pipeline. Apollo gave outbound teams data access that used to require an enterprise Salesforce contract. The tooling layer that GTM engineering adopted solved real problems that RevOps couldn’t touch.
And then the discipline stopped. It drew the boundary line right there, at the edge of the toolbox, and never asked what was on the other side.
What GTM engineering didn’t claim: audience analysis, segmentation strategy, positioning validation, competitive intelligence, or the feedback loop from execution data back into strategic decisions. That’s the scope problem. We built half a discipline and furnished it well, but there are entire rooms in this house nobody’s walked into.
The Execution Layer Without a Strategy Layer
Hyper Growth Partners put it directly in their breakdown of what a GTM engineer is not: “GTM engineers scale an existing strategy instead of inventing one. GTM engineers don’t select markets, craft messaging, or determine positioning.”
This gets presented as a feature. A clean separation of concerns. Engineers engineer, strategists strategize, everybody stays in their lane.
I think it’s the limitation we should be most worried about.
If your discipline only activates after someone else has decided who to target, what to say, and when to say it, you’re a service function. A sophisticated one, with GitHub repos and CI/CD pipelines, but a service function. You’re waiting for inputs you have no influence over, and then optimizing execution of decisions you weren’t part of making.
Think about how the best software engineering organizations actually work. Engineers don’t just build what product management hands them. They push back on requirements that don’t make technical sense. They identify what’s possible that nobody asked for. They inform strategy with technical insight because they’re closest to the system’s actual capabilities and constraints.
GTM engineering has that same proximity. We sit on enrichment data, engagement signals, conversion patterns, competitive indicators. We see which accounts match our ICP and which ones convert despite not matching it. We see where outbound sequences break down and where they outperform expectations. That’s strategic intelligence, and right now most of it evaporates at the boundary between “our pipeline worked” and “someone else decides what it means.”
The data flows through our systems. The insight stays on the floor.
So what goes in those empty rooms? That’s the next conversation.