Sara McNamaraGTM Eng

Sara McNamara

Helping B2B teams scale with AI-powered RevOps strategy, tech, and automation // 👻 RevOps & GTM Strategy @ Vector.co //… · 12d ago

Lots of debate on here about the best background for a GTM Engineer. My take: ⭐ GTM Engineer = often starts with tools like Clay, maybe Apollo/ZoomInfo/Instantly, building GTM workflows around enrichment, signals, research, personalization, routing, outbound, etc. A lot of this can be built in a relatively lightweight, point-and-click way, which is scalable and valuable, especially as you get started. But AI GTM Engineer = goes a level deeper technically. 🌟 AI GTM Engineers are *also* up to speed with the latest AI capabilities and can build more advanced, programmatic systems across GTM: agents, APIs, orchestration, custom logic, etc. AND, as Charlie Saunders brilliantly added when we spoke: “GTMOps/MOps/RevOps background, leaning heavily into AI (and the latest GTM tools like Clay) and applying it to the GTM system as a whole, building agents for all GTM teams in the existing GTM system/infrastructure and tying it to outcomes in those systems (pipeline, conversions, etc).” Basically, anyone can learn how to create a widget or build a cool standalone workflow. But if that’s your only experience, your impact will probably be limited. 🤷‍♀️ If you can “play ball” with architecture, cost management, knowing when to build vs. buy, enablement, measurement + all the other fundamentals that have traditionally lived in Ops, you can make a MUCH bigger impact. 🏀

Sara McNamara

Helping B2B teams scale with AI-powered RevOps strategy, tech, and automation // 👻 RevOps & GTM Strategy @ Vector.co //… · 4w ago

2019 RevOps: “Learn SQL. Learn how to build every automation yourself.” 2026 RevOps: “Learn to write a spec an agent can build from.” If you can write a clean SOP, you’re probably closer to building than you think. Clay shared an example recently that made this click even more for me: A GTM engineer had a customer’s inbound enrichment process documented in a Markdown file. 📂 Every rule and exception was there: what to enrich, what to suppress, how to score, which CRM records to check, where each lead should route. She gave it to Claude Code. Clay’s Agent Plugin turned that spec into a Clay Workflow.* The obvious takeaway: AI makes building faster. The more interesting takeaway: getting the process design and spec right is becoming a bigger part of the “technical work.” If an agent can handle more of the implementation, your job shifts toward designing and describing the process well enough that it builds the right thing for you. The hard part becomes anticipating the failure modes and guardrails: Where does the normal path break? What should it never touch? What happens when the data is missing or contradictory? How do you prove it works before it goes live? Most RevOps people aren’t going to become software engineers, and that isn’t the point here. IMO, a lot of us are going to become people who can define a process precisely enough that an agent can help us turn it into a working system. I put together the Claude Code + Clay build process I’d use below. Steal th…