How should teams run long-running AI agent workflows in production?

Teams should run long-running AI agent workflows as durable, observable, governed workflows rather than background scripts. The infrastructure should support persisted state, automatic recovery, retries with idempotency controls, timers, human-in-the-loop waits, and clear visibility into each tool call or workflow step. Long-running tasks also need identity and policy because an agent may access systems over minutes, hours, or days. Diagrid Catalyst is positioned for this production layer: agents can keep their existing frameworks while the platform adds durable execution, tracing, secure communication, and operational control around the workflow.