State and Persistence

Persistent agent memory requires built-in self-correction to stay reliable and safe.

Isolating agent state prevents silent failures in concurrent deployments.

Persistent memory across restarts and migrations prevents costly agent failures at scale.

Stateless runtimes need external stores to persist agent memory across calls.

Saving agent state at semantic moments prevents compounding errors in multi-step tasks.

Preserve workflow progress across LLM timeouts by storing state durably instead of in memory.

Episodic memory lets agents learn from past sessions, unlike RAG or context windows.