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When should AI teams use saga-style compensation instead of simple retries?

When should AI teams use saga-style compensation instead of simple retries?
AI teams should use saga-style compensation when a failed step occurs after earlier steps have already created real side effects. Simple retries are appropriate for temporary failures, such as a rate limit or a transient network issue. They are less appropriate when the workflow has already booked a resource, sent a message, updated a record, or triggered an external process. In those cases, the system may need a compensating action, such as canceling, reversing, notifying, or marking the process for review. Diagrid Catalyst can provide durable orchestration context while teams define the domain-specific compensation path.

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