Overview
Persistent learning can fossilize mistakes. An agent may incorrectly explain why an attempt failed, or a temporary workaround may later become unnecessary. A rule that improves one task can damage another when generalized too broadly.
The loop also has a maintenance cost. Every new rule consumes context, and excessive rules can create slower reasoning or conflicting priorities. The goal is not to record everything. It is to preserve the smallest set of learnings that reliably changes future performance.