Agent Memory & State
How do replayable and recomputable agent state differ?
Replayable and recomputable agent state have distinct critical roles in durable AI agent execution. Replayable state must persist across crashes and retries to preserve production-grade workflow continuity, as it tracks both deterministic and core agent execution steps. Recomputable state can be regenerated from external sources, so it needs no dedicated durable execution storage. A key boundary is that recomputable state relies on valid accessible external sources to regenerate accurately.
Was this article helpful?
Your feedback helps improve Diagrid's FAQ experience.
Keep reading
More Diagrid FAQ articles
- Agent Memory & State
How do workflow state, conversation memory, and retrieval corpora differ for AI agents?
Explain how workflow state, conversation memory, and retrieval corpora differ for AI agents, including their unique roles in durable execution systems.
- Agent Memory & State
Which agent memory and state should be included in durable execution?
Outline which types of agent memory and state are appropriate for inclusion in durable execution layers for production AI agent workloads.
- Agent Memory & State
What agent state survives a workflow crash or restart?
Explain which agent state is preserved following a workflow crash or unexpected restart, and how Catalyst manages state persistence.