Not All Repair Helps: What I Learned Trying to Fix a Failing AI Agent
Picture a moment every person who runs an AI agent knows. A task is halfway done and starting to go wrong. The agent took a weird turn a few steps back and now it is confidently heading somewhere bad. You have to decide fast on this. Do you step in? And if you do a quick "wait, check your work" nudge will that actually fix it? Or do nothing? Or worse knock a run that was about to recover on its own off the rails? That question is the whole project. Here is the honest short version of what I found. Detecting a failure is not fixing it A lot of recent agent research is about failure attribution — figuring out which step in a long run broke everything. Useful but it stops one step short of what you need when you are on call. Knowing where it broke is not the same as knowing what to do about it . So I asked a blunter question: given a failure, which fix actually recovers the run and which ones quietly make it worse? To answer it without fooling myself I rewind each failing run to the exact step where it went wrong, apply one fix, let it play forward and check the real answer against a hard ground truth no LLM grading another LLM. And I always compare against a "do nothing" control, because some runs recover on their own, and I did not want to give my fixes credit for that (or miss a "fix" that's actually worse than leaving the agent alone). What a capable agent actually gets wrong First surprise: a decent agent mostly doesn't fail in the dramatic ways people worry about. It rarely loops, rarely forgets to answer, rarely fumbles a tool that throws an error in its face. It fails in two quieter ways and both are the same underlying mistake: acting on the surface of the situation instead of the real thing underneath. It makes up an answer it could have looked up. The fact it needs is sitting right there behind a tool call it just never makes, so it fills the gap with something plausible. Reads "manager: #202," never looks up who #202 is, asserts a name anyway. It trusts a t