From Demo to Production: Why Stateless Agents Fall Apart

Most AI agents fail at real-world tasks because they reconstruct context from scratch on every interaction—losing reasoning chains, confidence signals, and progress. Google Cloud's five patterns address this architectural flaw: checkpoint-resume for fault recovery, delegated approval for better HITL, layered memory to prevent data leakage, and ambient processing for continuous operation. These patterns are essential for scaling agents beyond demos to production workloads.