How to Build AI Agents That Survive Constant Interruptions

A developer shares five key strategies for creating long-running AI agents that can handle frequent interruptions. The approach includes storing state on disk, re-deriving state from the world, making actions idempotent, checkpointing at boundaries, and separating durable from disposable data. These techniques ensure agents recover cleanly after being killed or rebooted.