Production is down. Slack is on fire. Your phone is ringing. You've seen this exact error before — ConnectionResetError: [Errno 104] cascading through your FastAPI worker pool — but you can't remember exactly which Redis configuration tweak fixed it last time, who applied it, or how long the incident lasted. You're starting from zero again. Twenty minutes of context-building before you even touch a fix.
I got tired of that feeling. So I built an AI agent that never forgets.
The Problem With Generic AI in Production
When production breaks, most engineers reach for their LLM of choice and paste in the stack trace. And the response is almost always the same: a competent, thoughtful, completely useless answer. The model has no idea that your team already tried increasing max_connections six weeks ago and it made things worse. It doesn't know that your infrastructure runs on a specific internal Kubernetes setup that changes how standard fixes apply. It gives you textbook advice for textbook problems, and your problems are never textbook.
This is what I started calling the Round 1 problem.
