Reliability

Discover unique agent failure modes like stuck loops, hallucinated tool calls, and cascading retries. Learn why agents fail differently than traditional services.

Learn agent reliability basics with 8 Python examples. Wrap flaky tools with retries, classify failures, budget attempts, and short-circuit errors.

Implement fallback chains in your AI applications to ensure graceful degradation when models or tools fail, preventing hard crashes and improving reliability.

Implement timeout strategies for long-running agent steps. Learn to apply nested deadlines, handle timeouts, and reserve budget for fallbacks.

Learn ten best practices for building resilient, boundable agent systems, including operating checks for production under load and outages.