Temporal Saga Pattern for Reliable Agentic AI Distributed Transactions
DEV Community·high signal
Using Temporal's workflow orchestration for agentic AI systems enables automatic failure recovery, state persistence across long-running agent processes, and the Saga pattern for distributed transactions — where each agent step has a compensating action that executes in reverse order on failure. Critically, retry policies should distinguish transient from permanent failures using non_retryable_error_types to avoid infinite loops on business logic errors. For multi-agent pipelines, event-driven signals enable human-in-the-loop approval gates where agents pause indefinitely awaiting external signals with timeout protection.