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Why AI Agent Loop Detectors Fail and How to Fix Them in Hours

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A production AI agent was found repeating actions for 40 steps without triggering any errors or exceptions. The commonly recommended repetition detector failed because it only checked whether an action was repeated, not whether any real-world change had occurred. This subtle but critical flaw means agents can appear to be functioning normally while actually making no progress. The proposed fix involves implementing a progress signal that monitors changes in the environment rather than tracking the agent's own actions. Developers running unattended agents are advised that addressing this gap typically requires only a few hours of work, not a full system rebuild.

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Why AI Agent Loop Detectors Fail and How to Fix Them in Hours · ShortSingh