Durable Execution
What are the limitations of durable execution for AI agent side effects?
Durable execution ensures your agent's orchestration resumes after failure, but it does not guarantee that external side effects (e.g., database writes, API calls) happen exactly once. Catalyst replays deterministic steps, which may re-execute side-effecting activities if not idempotent. You must design each activity with idempotency keys or reconciliation to avoid duplicates. Durable execution handles the recovery path, not the external consistency.
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- Durable Execution
What is durable execution in AI agent workflows?
Durable execution means an AI agent workflow can keep its progress even when a process crashes, a tool call fails, or the system restarts.
- Durable Execution
Why do production AI agents need durable workflows?
Production AI agents need durable workflows because real agent tasks rarely finish in a single clean request.
- Durable Execution
Is checkpointing enough for production AI agents?
Checkpointing helps, but it is usually not enough by itself for production AI agents. It explains the production reliability impact for AI agent workflows.