How can Pydantic AI applications handle long-running, tool-calling tasks?

Pydantic AI applications can handle long-running, tool-calling tasks more safely when the agent logic is wrapped in a durable workflow. The application should persist important state, track completed tool calls, define retry and idempotency behavior, and expose traces for debugging. Type safety helps structure inputs and outputs, but it does not by itself solve crash recovery, operational visibility, or governance. For production use, teams should pair framework-level development with infrastructure for durable execution and policy. Diagrid Catalyst is positioned as a way to add those controls while keeping the agent application's existing framework.