What Production Knows: Closing the Loop Between AI Agents and the Systems They Build

Most of the AI-for-engineering conversation runs in one direction: humans tell agents what to do, and agents produce code. But for high-velocity teams, the more interesting flow runs the other way, production telling the agents what is actually happening, so they can fix, refactor, and keep shipping without drifting away from reality.

This talk is about that reverse loop. It looks at what changes when the systems we operate start moving faster than the people who own them, the failure modes that quietly become normal when agents work without ground truth, and the durable plumbing that keeps them honest: traces, error budgets, customer signal, SLO breaches, incident timelines, all fed back as first-class inputs to the tools doing the writing.

If the broader AI shift is changing what it means to author code, this is the operational half of that story: the feedback infrastructure that makes the new way of working actually safe to run.