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. Instead of treating an agent run as one fragile script, durable execution records workflow state and completed steps so the run can resume from the point of failure. This matters because AI agents often execute multiple tool calls, wait for external systems, and make decisions over time. Diagrid Catalyst applies durable workflow execution to agent workloads, helping teams move from demo-style agents toward production systems that can recover, continue, and be observed across the full execution path.
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- 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.
- Durable Execution
What is the difference between checkpointing and durable execution?
Checkpointing records the state of a run at a specific point. It explains the production reliability impact for AI agent workflows.