The new operating model for GTM

AI is reshaping go-to-market (GTM) in two directions at once. It's creating massive leverage for the companies that wield it well, and it's flooding buyers with noise.

We believe the companies that win the next phase of GTM won't be the ones with the best tools. Everyone has the same tools. They'll be the ones who build a moat in how they identify and engage prospects. If you're using the same signals, the same enrichment data, and the same AI-written messaging as everyone else, you're just another ignored email in a crowded inbox. The advantage now belongs to sellers who use public data to find buyers who are actually in-market, then earn a response with outreach that's differentiated and high-signal.

Enter the GTM Engineer. The title is still evolving, but the function is becoming critical. Whatever you call the role, early-stage companies need to put data and AI at the center of their GTM motion or risk falling behind.

We hosted 20 of the top GTM Engineers in San Francisco for a dinner to pressure-test what this function actually is and where it's headed. Below are the four themes that emerged, and what we'd tell founders thinking about the role.

Hire for candidate attributes, not the title

The role is in its infancy, so don't expect to find a bench of GTM Engineers with years of role-specific experience. Demand is running well ahead of supply. The companies hiring well are developing GTM Engineers from adjacent roles and screening for mindset over resume.

The best GTM Engineers are builders who don't wait to be told what to learn. They've independently been building with AI tools and have a genuine hacker mentality. Ask them what they built last month that no one asked them to build, and which AI tool they're most excited about right now. You'll know quickly whether the curiosity is real.

They also need strategic range. The failure mode of a purely technical GTM Engineer is that they build impressive systems that solve the wrong problems. The best ones operate like a product manager. They interview top reps to find what's being done manually that shouldn't be, they talk to founders to surface the projects that never make the priority list, and they build, ship, and measure what comes out. Ask about a project they're proud of: can they articulate the strategic problem it solved, not just the technical implementation?

Finally, they're metrics-driven. Strong GTM Engineers connect the systems they build directly to measurable business impact. They work backward from the company's north star metric and identify the activities, signals, and systems that move it. Ask how they'd diagnose where conversion is breaking down, and to walk you through a workflow they built that improved pipeline, conversion, or revenue.

Chris Prinz recently joined the ranks of GTM Engineers at Modal, coming in with a data science and product background. "I think GTM Engineering is the next frontier for data people who want to have more impact. Ultimately the job is the same: turning noise into understanding and action for the business. You identify the sources for signals and enrichment data, distill them into abstractions like segments and account scores, and then build agentic workflows that drive measurable impact. What matters more than the tooling is the mindset. Whether you're working in Claude Code, Snowflake and dbt, or Clay, you're applying the same principles," said Prinz.

What does a GTM Engineer actually own?

The market consensus treats a GTM Engineer as a technical operator who builds automations, integrates the CRM with the sequencing tool, enriches leads, and keeps the outbound machine humming. That definition turns the role into a hybrid of Sales Ops and SDR work, with someone automating the existing playbook instead of redesigning it.

We think that's too narrow. The "GTM" in GTM Engineer stands for go-to-market, not lead gen. The full motion includes marketing, sales development, sales, customer success, and support: every team that touches a customer from awareness to renewal. A true GTM Engineer is a leverage multiplier across the entire customer lifecycle, not just the top of the funnel.

Graham Murphy, GTM Engineer at Gradient portfolio company Clarify, builds efficiencies across the whole motion. "A core responsibility of a GTM Engineer is to question what can be improved throughout the entire customer lifecycle to increase efficiency and unblock value, and thus revenue. Spotting inefficiencies was never the hard part, but time constraints left us with deep backlogs of improvements that never saw the light of day. Now with AI we're knocking out multiple tasks in parallel across the customer lifecycle," says Murphy.

When should you instill a GTM Engineering mindset?

Earlier than you'd think. Timing the hire was the most hotly debated question at the dinner. As companies find product-market fit and scale their GTM, a dedicated GTM Engineer becomes critical. But the mindset can and should take hold before you ever make that hire.

Even if you can't hire a dedicated GTM Engineer yet, the founder or early team should adopt GTM Engineering practices from day one. Building proprietary data layers about your ICP, tracking behavioral signals, and leveraging public data triggers are accruing advantages that get harder to replicate over time. Start early and the lead compounds.

This works at seed stage precisely because there are no specialists yet. Mature GTM orgs have a function for everything. Seed-stage startups need one person who can think across all of them and build systems that multiply output. AI has made it possible for one person to produce what used to take a team of four or five.

And you don't have to do it all in-house. Clay has built an ecosystem of consultants and fractional advisors who help teams get started, so don't hesitate to pull in help where you need it.

Andy Tozier is an early GTM Engineering hire at Freckle. "We adopted a GTM Engineering mindset early because we believed our competitive advantage wouldn't come from having more people. It would come from building better systems. In an early-stage company, the impact is massive because every workflow, dataset, and process you build compounds as the company grows," said Tozier.

Be human

This is the part that sounds counterintuitive for a role built on AI: the best GTM campaigns and sales cycles are the ones that drive human behavior.

AI has created so much noise in outreach channels that the only way to stand out is to prove there's a human on the other end. For all the promise of AI SDRs, this is exactly where they fail, and the GTM Engineers in the room admitted that fully handing customer outreach to an AI SDR rarely works today. The best GTM Engineers lean heavily on technology while keeping a hand on the wheel.

The instinct to add personalization usually backfires. The "we went to the same school" or "I see you're connected to my third cousin" line is a dead giveaway that AI wrote the message. Instead of personalization, write something timely and relevant to the specific company and buyer, and inject your own point of view.

Events are one of the most promising frontiers here. Walking into a giant conference hoping to meet the right people is a recipe for failure. A founder or rep should book meetings in advance, and buying a conference ticket often unlocks an attendee list you can work before you ever arrive.

"Events create a human touch that a cold email alone cannot. The more a GTM Engineer can support a program with a human on the other side, the more likely a prospect will engage. Manufacture serendipity at conferences by doing outreach in advance," says fractional GTM Engineer Steven Moody.

The opportunity is now

When everyone has access to the same AI tools, differentiation comes from how intelligently you combine data, timing, context, and distribution. That's the whole game.

The role is still early, and that's the opportunity. The companies that figure out in 2026 how to give the GTM Engineer real scope beyond outbound, that hire for genuine AI curiosity and strategic range, and that build their GTM architecture around one exceptional person instead of a committee of specialists will compound an advantage that's very hard to catch by 2028.

The GTM Engineering playbook is still being written. The direction is already clear.

Special thanks to my colleague Clayton Petty for his insights on this piece.