Getting a research agent to call three tools in a demo is easy. The hard part starts when the seventh tool call times out and the first six have already spent money and changed state somewhere.
So this is a question about recovery, not about AI frameworks. Temporal and Diagrid Catalyst both do durable execution, and both position themselves for AI workloads. What separates them is what each one asks you to build and operate around your agent.
Start with the failure contract
Say your agent searches internal documents, calls an external research API, asks an LLM to synthesize the evidence, and then waits for a human to approve the result. Before that design goes to production, you need answers to four questions:
Which completed steps will not run again after a crash?
