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Term Definition

Agent Checkpointing

The process of saving the entire state of an AI agent at specific milestones or after every 'turn' in its reasoning loop.

Full Explanation

Checkpointing allows an agent to 'save its game.' By taking a snapshot of the context window, tool outputs, and internal variables after every step, the system creates a recovery point. If step 5 fails, the agent doesn't need to restart from step 1; it can resume exactly from the last valid checkpoint.

Why it Matters

It dramatically reduces compute costs (by avoiding full restarts) and improves the success rate of complex, multi-step tasks.

Related Concepts

Eliminate Silent Failures

Deploy production-grade reliability for your agents.