AI agent pipelines are transforming how we automate complex tasks, but their inherent complexity also introduces unique challenges in reliability. This article delves into practical strategies for building resilient AI agent workflows, focusing on automatic error recovery mechanisms. We’ll explore common failure points and implement robust solutions like intelligent retries, circuit breakers, and human-in-the-loop fallbacks to ensure your AI agents operate smoothly and effectively, even in the face of unexpected issues.