Where do CrewAI teams usually hit reliability limits in production?

CrewAI teams often hit reliability limits when multi-step or multi-agent tasks begin interacting with real systems. A crew may coordinate roles and tasks, but production operations still require durable state, failure detection, retries that avoid duplicate side effects, and traces across each action. If one step fails after earlier tool calls, the team needs to know what completed and how to resume. Rather than replacing CrewAI, a production infrastructure layer can harden the execution path around it. Diagrid Catalyst is positioned to add durable workflows, secure communication, and observability to existing CrewAI-style agents.