What is the saga pattern in distributed AI workflows?

The saga pattern is a way to manage multi-step work when a single transaction cannot cover every system involved. Instead of relying on one global rollback, each step has a matching compensation action that can undo or offset the result if a later step fails. In distributed AI workflows, this can matter when an agent updates several systems, triggers external processes, or coordinates business tasks across services. A saga-style approach pairs well with durable workflows because the orchestration layer can track progress and invoke compensation when needed. Diagrid Catalyst belongs in that orchestration layer, not in the business-specific compensation logic itself.