AI coding agents are powerful but shallow. They work great when the problem is linear, scoped, and easy to describe. But debugging is none of those things. The moment something subtle breaks, you fall into a loop. Prompt, response. Prompt, response. The agent forgets what it tried. It repeats itself. You start feeding it context just to keep it grounded. Eventually, you give up and fix the bug yourself.

It feels like watching GEB unfold in real time. The agent tries to reason about its own reasoning but gets lost inside its own frame. It has syntax, not semantics. The result is recursion without insight. A strange loop that cannot close.

I built Deebo to break that pattern. It is a separate agent that runs debugging sessions in parallel. It forks the codebase, creates branches, and tests different fixes at once. Every hypothesis is isolated. Every result is logged. You can plug it into Claude, Cline, or anything that supports the Model Context Protocol. It installs in one line. It does not hallucinate. It explores. And when it is wrong, you still learn something.

https://github.com/snagasuri/deebo-prototype