Post by RevOps Co-op

Your next RevOps hire might not be human. 👀 That's not a hot take. that's what Zach West is actively building at PatchOps, and the implications for every in-house ops team are real. In this episode of #RevOpsAF, Zach and Camela Thompson dig into how he's scaling a consulting agency by treating AI agents like headcount: junior hires that become senior as you build out their knowledge base. The framing is everything: 🧠 a zero-context LLM is a brand new hire with no institutional knowledge 📚 an LLM trained on your historical calls, SOWs, and delivery outcomes? that's a senior operator who's done this 100 times before and the skill gap between leveraging AI and relying on it? it's widening fast. "Leveraging can increase your output 10, 20x and you don't have to sacrifice quality. Reliance means you don't really know what's going on — it's vibe coding, but for your entire job." What that means for RevOps pros: → Your institutional knowledge is the moat — structured historical data is what separates good AI-assisted work from generic AI output → Guide your calls for the LLM — if a transcript is going downstream to AI, run the call like you're generating structured data (because you are) → Domain expertise still wins — AI amplifies the gap between specialists and generalists, it doesn't close it → Start simple — document generation, transcript analysis, process flowcharting are table stakes and already accessible also: the soft skills conversation. Camela makes the point that as AI handles more execution, the judgment layer matters MORE — translating what people ask for into what they actually need is not something you can outsource. This one's worth a listen if you're a team of one, a consultant, or just trying to figure out where to actually spend your time in 2025. Peep the highlight reel below ⬇️ 📺 catch the full episode + write-up on our site: https://lnkd.in/gv2iUzyd #revops #revenueoperations #ai #gtm

Video Content