The agent gets rescued. Where does the fix go?

An agent gets stuck, someone fixes it by hand, and the task finishes. The part worth fixing next is where that correction goes. If it stays in someone’s head, the next run gets the same agent with the same blind spot. Reef’s harness tutorial gives that feedback a route back: record the request, attach a score and correction to its receipt, let the model propose a skill change, then test the current and changed harness on the same tasks before publishing a version. That still leaves you defining what a good fix means for your workflow, and actually installing the selected version. But the human intervention can become input to the next change instead of disappearing when the ticket closes. Where do your manual fixes end up today: a run log, a prompt edit, or something the next version actually gets tested on?