How is an AI agent workflow different from a traditional workflow?

A traditional workflow usually follows a known sequence of steps defined by developers or business process owners. An AI agent workflow can include runtime reasoning, model output, tool selection, and dynamic branching. The agent may choose different paths for similar inputs, and each tool call may create external side effects. This changes the production requirements. Teams need stronger observability, durable state, identity, policy, and recovery behavior because it is not enough to know that a step ran. Diagrid Catalyst targets that production layer around dynamic agent workflows.