A long AI chat is a terrible project database

After a few hours, a coding-agent chat contains everything except a reliable answer to what is actually true. It has the original request, three possible approaches, a correction, a half-finished branch, and a confident summary written before the tests ran. This is manageable with one small task. It falls apart when several agents work across multiple sessions. We learned to keep the plan outside the conversation. The durable plan says what is doing, done, blocked, and next. At handoff, we reconcile those claims against the actual pull requests, checks, and system state. If the chat says finished and the evidence says otherwise, the plan gets corrected. The chat still matters. It is where exploration happens. It just does not own status or intent. I think a lot of “agent memory” problems are actually authority problems. We keep trying to make the model remember more when the system needs one governed place to record what was decided and what is true now. For people running agents across sessions, what survives the chat? A plan, an issue tracker, an event log, or mostly a summary generated at the end?