Hlib Storchak · 2026-07-04 · ~10 min readThe Rise of the GTM Engineer: A New Job Title Built on Coding Agents
Quick answer
"GTM engineer" is becoming a real job title because coding agents like Claude Code now let non-engineers build and wire up their own GTM tooling. A survey of 200 GTM operators found 27% had already replaced an existing GTM tool with something they built themselves, and 92% said the switch saved them real time. The role isn't a rebrand of RevOps. It's someone who treats the GTM stack as software they can edit, not software they wait on a vendor roadmap to fix.
My take, up front
I run outbound for a living, 2000+ meetings booked for B2B clients, and for years the job split cleanly into two camps. People who ran campaigns, and people who wrote code. If you weren't in the second camp, you filed a ticket and waited. That split is closing fast, and it's closing because of coding agents, not because GTM people suddenly learned to code the old way.
A new survey of 200 GTM operators, run by Maja Voje and GTM Strategist across March and April 2026, is the clearest data point I've seen on this shift. It's worth walking through, because the numbers explain why "GTM engineer" showed up as a job title on LinkedIn this year instead of staying a meme.
What a GTM engineer actually is
A GTM engineer is a marketing, sales, or RevOps person who uses a coding agent to build and maintain their own internal tooling: enrichment pipelines, CRM cleanup scripts, custom scoring logic, outbound sequencing glue code, internal dashboards. Not a developer who moved into GTM. A GTM person who picked up just enough leverage from an agent to stop waiting on engineering for the small stuff.
The distinction matters because it changes who can do the job. You don't need a computer science background. You need to know your funnel well enough to describe what's broken, and an agent that can turn that description into working code.
Inside the numbers: a survey of 200 GTM operators
The survey split respondents by which Anthropic product they leaned on most, Claude Chat, Claude Code, or the Cowork desktop app, and the split was close to even (30%, 31%, and 32% respectively). That alone tells you this isn't a niche behavior confined to technical marketers. It's spread evenly across the GTM function. (Growth Unhinged, 2026 Claude Code GTM report)
The headline numbers: 92% of respondents said these tools saved them real time, 67% said the tools enabled something they considered previously impossible for them to build alone, and 55% said they'd replaced an existing tool or vendor because of what they could now build in-house. The average operator surveyed had adopted 3.5 distinct use cases, not one narrow trick.
| What the survey measured | Result |
|---|---|
| Said it saved real time | 92% |
| Said it enabled something previously impossible | 67% |
| Replaced a tool or vendor because of it | 55% |
| Already replaced a GTM tool (as of the survey) | 27% |
| Expect to replace a tool soon | 30% |
| Average use cases adopted per operator | 3.5 |
| Used it for GTM engineering / prospecting work | 54% |
Read that middle row again. More than a quarter of surveyed operators had already ripped out a paid tool and replaced it with something they built themselves. That's not a productivity anecdote. That's a procurement decision being made by people who, two years ago, had no path to making it.
Tip. If 27% of GTM operators in a broad survey have already replaced a vendor tool with something they built, assume at least one tool in your own stack is a candidate. The question worth asking isn't "could an agent build this," it's "why am I still paying a vendor for something this specific to my own workflow."
Why this is happening now, not three years ago
The obvious answer is that the models got better. The less obvious one is that the economics around them shifted enough to matter to a whole company, not just its engineering team. Anthropic's own reported revenue is the backdrop here: annualized revenue reportedly grew from about $9 billion in late 2025 to around $30 billion by April 2026, with Claude Code alone reportedly accounting for roughly $2.5 billion of that run rate. (Growth Unhinged, 2026 Claude Code GTM report) Growth at that pace inside a coding-agent product usually means the buyers aren't only engineering teams. GTM functions adopting a "coding" tool at scale is itself the story.
Pair that with what's happening on the AI SDR side of the same GTM stack. Enterprise B2B teams running at least one AI SDR in production reportedly jumped from about 12% a year earlier to roughly 41% in Q1 2026, based on a blend of Salesforce and Outreach state-of-sales research cited in industry tracking. (DigitalApplied, AI SDR statistics 2026) Two different categories, agentic execution and agentic tool-building, both scaling in the same year, inside the same GTM org. That's not a coincidence. It's the same underlying shift: GTM teams stopped treating "AI" as one feature and started treating it as infrastructure they run themselves.
GTM engineer vs a traditional RevOps hire
I get asked whether this is just RevOps with a new name. It isn't, and the difference shows up in how the two roles spend their week.
| Dimension | Traditional RevOps hire | GTM engineer |
|---|---|---|
| How a broken workflow gets fixed | Files a ticket, waits on engineering or a vendor | Describes the fix to an agent, ships it same day |
| Core tool | CRM admin panel, spreadsheet, no-code automation | Coding agent (Claude Code, Cursor) plus the CRM |
| Where time goes | Manual data cleanup, chasing stakeholders for specs | Building and maintaining small internal tools |
| Relationship to vendors | Buys a point solution for each new need | Builds the narrow ones, buys only the hard infrastructure |
| Skill that matters most | Tool fluency across many SaaS products | Knowing the workflow well enough to spec it precisely |
Neither role is strictly better. A GTM engineer still needs someone who understands deliverability, list hygiene, and what a good sequence looks like, an agent won't invent GTM judgment for you. What changes is the distance between having an idea and having it running.
What a GTM engineer actually builds, day to day
From what I've built myself and watched other operators build, the recurring list looks like this: enrichment scripts that pull and merge data across two or three sources the CRM doesn't natively connect, custom lead scoring that reflects your actual ICP instead of a generic model, one-off dashboards that answer a specific question your BI tool wasn't built for, CRM cleanup jobs that dedupe and standardize records on a schedule, and glue code that connects your sequencing tool to your CRM in the exact way your process needs, not the way the integration marketplace assumed you'd want it.
None of that is glamorous. All of it used to sit in a backlog behind actual product engineering work, which meant it never got built at all.
The AI SDR angle: where this role and Agent Frank meet
A GTM engineer and an AI SDR solve different problems, but they sit on the same stack. The GTM engineer builds and maintains the plumbing. The AI SDR runs the outbound motion through that plumbing. In my own setup, Agent Frank handles outbound execution end to end, sequencing, replies, booking, while the custom scripts and enrichment jobs I've built myself feed it cleaner data and route the edge cases a generic tool wouldn't catch. Neither replaces the other. The GTM engineer work is what makes the AI SDR layer actually good, instead of good on paper.
The skills stack you actually need
You don't need a CS degree. You need four things: a clear enough model of your own funnel to describe a problem precisely, comfort iterating with an agent instead of expecting a perfect first output, enough data literacy to sanity-check what the agent hands back before you trust it with real prospect data, and the judgment to know which problems are worth automating versus which ones need a human decision every time. That last one is the one people skip, and it's the one that separates someone building useful tools from someone shipping fragile scripts nobody else can maintain.
Where teams get this wrong
The most common failure I see is treating "we have a GTM engineer now" as permission to stop paying for any tooling at all. Some things are genuinely worth buying: deliverability infrastructure, dedicated sending IPs, verified data at scale. I still run Mailforge and Infraforge for exactly that reason, infrastructure that benefits from scale and specialization, not from being rebuilt in-house. The GTM engineer's job is to build the narrow, workflow-specific pieces that no vendor will ever build exactly right for your process, not to reinvent commodity infrastructure badly.
The second failure is letting scripts run unattended with no owner. An agent will happily keep a broken enrichment job running for months if nobody's watching the output. Treat anything you build the same way you'd treat a vendor tool: someone owns it, someone checks it, and it gets retired the moment it stops earning its keep.
How to become one, or hire one, this quarter
If you're the operator: pick your single most annoying recurring manual task, the one you personally dread doing every week, and spend a few hours describing it to a coding agent instead of doing it by hand one more time. Ship something small before attempting something ambitious. If you're hiring: stop screening for engineering degrees and start screening for people who can describe a broken workflow precisely and have already built one small internal tool, even a rough one, to prove they'll actually ship rather than just talk about it.
What this means for the next year of GTM hiring
I expect "GTM engineer" to keep showing up as an actual title on job boards through the rest of 2026, not just a LinkedIn buzz phrase, because the survey data backs a real behavior change, not a fad. Teams that build this muscle in-house will out-execute teams still filing tickets for every small workflow fix. That gap compounds fast in a market where reply rates are already tightening and speed to a working experiment matters more than it used to.
FAQ
Is "GTM engineer" just a rebrand of RevOps?
No. RevOps fluency is still valuable, but a GTM engineer's core skill is using a coding agent to build and ship internal tooling directly, instead of specifying requirements and waiting on engineering or a vendor.
Do I need to learn to code to become a GTM engineer?
Not in the traditional sense. You need to describe workflows precisely and iterate with a coding agent. The survey behind this piece found operators across Claude Chat, Claude Code, and Cowork, not just people writing code by hand.
What's the real evidence this is more than a trend piece?
A survey of 200 GTM operators found 27% had already replaced a GTM tool with something they built themselves, and 55% said they'd swapped out a tool or vendor overall because of what they could now build in-house.
Should a GTM engineer replace every vendor tool?
No. Infrastructure that benefits from scale, like sending infrastructure or verified data, is usually still worth buying. The value of a GTM engineer is building the narrow, workflow-specific pieces no vendor will ever get exactly right for you.
How does this connect to AI SDRs like Agent Frank?
They sit on the same stack but solve different problems. A GTM engineer builds and maintains the plumbing, an AI SDR runs the outbound motion through it. Better plumbing makes the AI SDR layer perform better.
I've built my own stack this way for a while now, wiring Agent Frank, Salesforge, and Leadsforge together with scripts nobody else was going to build for me on their timeline. The teams winning right now aren't the ones with the fanciest tool list, they're the ones who stopped waiting for someone else to fix their workflow. If you want a second opinion on what's worth building versus buying in your own stack, that's a conversation I'm happy to have.