What happens when you give an AI agent a structured mistake log and let it write its own behavioral rules?

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I've been running a persistent AI agent as an operational manager for the past couple of weeks. Not a chatbot, not a one-off coding assistant. A stateful agent that maintains identity, accumulates knowledge, and runs autonomous jobs across CLI, messaging platforms, and scheduled tasks. The part I want to discuss is the self-correction architecture, because I think it gets at something fundamental about how we should be thinking about agent behavior. The problem with static instructions: Most ...