How does durable execution handle state consistency for multi-step AI agents?

Durable execution maintains state consistency by persisting the entire workflow state after each deterministic step, including LLM responses and intermediate variables. On recovery, it replays from the last checkpoint, ensuring no steps are lost. However, it does not coordinate consistency across external systems—if your agent writes to a database and the workflow crashes, the write may persist while the workflow resets. You must use distributed transactions or sagas for cross-system consistency.