From Signal to PR: Anatomy of a Self-Improving Agent

Official Schedule Context

What if your observability platform didn't just tell you something was wrong, but told you why, and

opened a PR with the fix? We'll walk through how we built Autopilot at Arize: an autonomous

investigation agent that triggers on monitor alerts or schedules, pulls traces into a working

filesystem, runs root-cause analysis, and produces actionable assets: a PR with prompt or code

changes ready for review. We'll cover the architecture decisions (cloud agents vs. sandboxed

containers, AI harness + skills), why traces-on-a-filesystem is the key unlock for agent-driven

debugging, and how we dogfooded the system on our own agent, Alyx, before shipping it to customers.

You'll leave with a concrete picture of what "observability that fixes itself" looks like in

practice, and where and why the human stays in the loop.

No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

Pending transcript synthesis when an official recording or confirmed matching video is available.