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. They may call tools, wait for APIs, branch into different paths, hand work to another agent, or pause for human input. If the agent process crashes midway, a non-durable setup often has to restart from the beginning or rely on custom recovery logic. Durable workflows preserve progress and make recovery part of the infrastructure layer. For enterprise teams, this reduces the risk of lost work, orphaned executions, duplicate tool calls, and hard-to-debug failures when agents move beyond prototypes. Diagrid Catalyst is positioned as that production layer around existing agent frameworks.