Building an "AI operating system" for a small team — and I keep hitting the same architecture question. Curious how others have solved it.
The setup: small office (think 3–4 people, mixed technical ability). One person (lets say me but its for client ) has the power-user seat — Claude Code, all the skills, the full context. The others need to feed information in and benefit from the skills, but they're not going to live in a terminal. Where I've landed so far — call it "one brain, many feeders": • A shared brain (Drive folder) holds context, intake, and output • I sit in "mission control" with the one Claude Code seat and run the skills • Everyone else just drops structured files into intake folders — no terminal, no setup • Claude validates, organizes, drafts, flags what's missing — a human does the final publish/send Two principles that keep proving themselves: 1. Force the data + its context to arrive together (one folder per item, a fill-in template beside each file). Orphaned data is what kills these pipelines. 2. Automate the 95%, keep a human on the last 5%. What I'm chewing on: • Is per-person seats actually better than one operator + feeders? When does it flip? • Where should the shared brain live — Drive, repo, DB, something else? • How do you get non-technical teammates to feed it *consistently*? If you've built something like this — what's your stack and what did you learn the hard way? Genuinely want to hear implementations, not just theory.