case study*
I built an AI assistant, then wrote down everything that broke.
I was capturing work in eight places and finding it in none of them. Links in one app, ideas in another, tasks somewhere else — plus five AI agents that couldn't see each other's work. The problem was never lost data. It was that I couldn't get anything back out.
So I built one front door. Everything goes to a chat app, and which chat you send it to decides where it ends up. No AI guessing your intent — you already made the decision when you picked the chat. It gets filed automatically, and every conversation from every app lands in one searchable place.
The fix wasn't code.
Six weeks in, it broke for two weeks and I didn't notice. When I came back, I didn't rewrite anything — I wrote down the filing rules on a single page that both I and the agents could read. Same code, same models, four times the use.
What's still broken
This is the part most write-ups leave out. All of it is still true as of today.
A 14-day outage that never alerted anyone
An expired token plus two automations pointing at a folder I'd deleted. Nothing crashed — it just quietly stopped working, and I stopped using it without deciding to. Silent failure is worse than loud failure.
The one scheduled job is still broken
It refuses to run because a safety check is doing its job, and its error notification can't send. The job meant to keep the system from needing me is the part that needs me. I automated the filing before I automated the monitoring.
I measured the wrong things
I tracked cost and message counts because they were free to collect. I never tracked whether I could actually find what I'd saved — the only number that would have justified the whole project.
The useful lesson wasn't technical. The system didn't fail because it couldn't do enough — it failed because the rules for where things go lived in my head instead of on a page. Writing them down cost an afternoon and did more than six weeks of building.