{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Humans of Martech","title":"223: Lindsay Rothlisberger: How Zapier uses a shared brain to manage AI context and skills","html":"","width":"100%","height":180,"duration":3408,"description":"What's up everyone, today we have the pleasure of sitting down with Lindsay Rothlisberger, Director of GTM Innovation at Zapier.Summary: When a startup claimed in April 2026 that it invented the marketing engineer role and that RevOps professionals \"just do tool integrations,\" Lindsay Rothlisberger had heart palpitations. Her team at Zapier had been building AI into GTM workflows for years before the announcement. In this episode, she walks through the 6-component AI governance model she published publicly: a golden path to Cursor, a structured shared brain in Google Drive, data policies built with the security team, a visibility layer powered by a custom Zapier agent, a context engineering strategy that fights context rot, and a red-yellow-green skills review gate. She also names the part of the model that's still broken, and it's more honest than most AI governance conversations allow. If your team is figuring out how to govern AI at scale without killing the momentum, this is the inside view from someone who's done it.About Lindsay RothlisbergerLindsay Rothlisberger is Director of GTM Innovation at Zapier, where she leads the company's AI-powered GTM transformation internally and works alongside customers navigating the same shift. She spent 4 years building Zapier's RevOps function from zero, scaling it into a cross-functional engine covering AI, systems, analytics, planning, and enablement, and growing ACV 10x in that time. Before moving into the innovation role, she led marketing operations and lifecycle programs at UNiDAYS across B2B and B2C markets. She writes on LinkedIn about what Zapier is actually shipping, what works, and what doesn't.How Zapier's RevOps Team Built Its AI FoundationMost RevOps teams doing serious AI work have been doing it longer than the current conversation suggests. The tools are newer and the terminology has changed, but building automated workflows that take unstructured data and produce structured, actionable outputs for...","thumbnail_url":"https://img.transistorcdn.com/4eBcAi2MlxuVPdaWgcnwbeXVYH5naGhZe-qIuSYOdjU/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9hZGE5/NTRiZjYwMDI0NWM5/MmE4MDQ1NWJlODA3/MjUxYy5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}