Context Is the Next Data

Context is the next data. The first episode of AI-Native Context opens with the problem underneath every AI project that disappoints: the context your work depends on is scattered across teams, tools and heads by design, and no one ever had to bring it together before. Chris Carolan traces the SaaS Trap back to where it started — a marketing-technology map that had grown to roughly seventeen thousand products, almost exactly the number of islands in an archipelago. Casey Hawkins brings the version everyone recognises: a sales team sets up invoicing the way that makes sense to them, the finance team opens the report and cannot understand what they are looking at, and nobody was wrong. Klemen Hrovat names what changed — the burden of building around a tool's limits is gone, so the question is no longer "what does the software let me do" but "what is my process, actually." Ask someone for the SOP and you get fifteen bullet points; watch their screen and they click fifty times. The gap between those two numbers is the context that was never written down anywhere. The practical thread runs through all of it: when AI gives you something you did not expect, the missing piece is almost always context you never thought to say out loud, because your own experience made it invisible to you. Every Tuesday.