Presentation: The Agent Harness: Control Planes, Invariants, and Approval Boundaries for Production AI Agents

Vinoth Govindarajan: This talk became possible by reading a lot of GitHub Issues over the weekend. I know based on your personality, either call it research, therapy, or cry for help. I know when you build production systems, you know the truth. Most of the important lessons lie in these bug reports and issues. Let's start with one sentence. A user saw the reply. The system forgot it happened. This is a failure shape I want to start with. Not a model hallucination, not a bad answer, not a crash. A system did something that looked successful at the user-visible edge, but the durable record behind it had a hole. Here in the screenshot, you can see the user asked for the agent to remember a refund for a customer. This assistant said it is going to remember for the next turn. From the user's point of view, there is no obvious errors. There is no failures. There is no red screen. Everything looked healthy. Behind the scenes, the system could not reliably reconstruct the future for the next turn. The action happened, but the record that should have made part of the agent's durable memory did not. For production…