Agent Resilience in AI Agents

Lessons in this section

1. Errors and Fallbacks

   How an agent notices tool errors, bad output and runtime faults, recovers with retries and other actions, and falls back to partial answers or escalation instead of returning nothing.

2. Loop Protection

   The guards that stop a stuck agent: duplicate and cycle detection, frequency limits, forced exits, timeouts and failure isolation, proved with a 12-case chaos suite.