Semantic Loop Detection: Catching Stuck AI Agents
It is 2am. The agent has burned 40k tokens and reverted the same file four times, and from where I am sitting it looks like it is working hard. That is the part that fooled me. It was busy. Every loop produced a new patch, a new diff, a new paragraph of reasoning about why this time would be different. The log scrolled. Things were happening. The agent just was not getting anywhere.
The task was a bug fix. Generate a patch, run the tests, watch them fail. Read the error, generate another patch with different variable names and different line numbers and the exact same underlying logic. Tests fail again. Third attempt, it wraps the fix in a try/except. Still fails. Same root cause, untouched. By attempt seven it had written and reverted the same file four times and was no closer than it had been on attempt one. I was watching a machine spend my tokens to stand perfectly still.
The thing I could not get past was that my loop detector said everything was fine.
The detector that lied to me
