Making the Browser Agent Resilient: Implementing Autonomous Error Handling and Retries

A tutorial on adding autonomous error handling and retry logic to a browser-based AI agent's ReAct loop. It classifies tool failures into two categories: recoverable transient errors (network timeouts, rate limits) that trigger automatic retries with delays, and persistent logic errors (hallucinated tools, bad parameters) that are fed back into the LLM's context as observations to force self-correction. Concrete utility functions (isRecoverableError, runWithTimeout, delay) and a full updated runReActLoop implementation are provided, building on a series that previously covered Web Workers, IndexedDB persistence, and RAG-based tool retrieval.