Your ReAct Agent Is Wasting 90% of Its Retries — Here’s How to Stop It

ReAct-style AI agents are often wasting over 90% of their retries on errors that are impossible to fix, such as attempting to use hallucinated tool names that do not actually exist. This critical flaw stems from a common design where the agent's global retry counter cannot distinguish a permanent error from a temporary one, uselessly burning budget. The solution involves structural changes like moving tool selection into deterministic code and classifying errors before attempting a retry. By making it structurally impossible for the agent to call a non-existent tool, this improved workflow eliminates wasted retries and significantly boosts system reliability.