Late-Bound Sagas: Why Your Agent Is Not an LLM in a Loop

The passage argues that conventional agent implementations, which keep execution state inside an application loop, are inadequate for reliable long-running business processes because checkpoints preserve data but cannot prevent duplicated side effects after failures. It proposes a “Late-Bound Saga” architecture in which an LLM acts only as a planner that emits intents, while a durable runtime records each intent before execution, performs actions, persists results, and resumes work safely after crashes or extended waits. This model is presented as necessary for effectively-once side-effect handling, process-independent suspension and resumption, external signal delivery, and detailed auditability, especially as multi-step agent reliability declines sharply with accumulating operations. Using a recruiting workflow as an example, the author describes how an agent can dynamically construct its execution graph, fan out work, wait for human responses, and react to cancellation signals without maintaining a live process. The post positions Agentspan, built atop Netflix’s Conductor runtime, as an implementation of this approach, allowing developers to define agents and tools while the runtime manages planning, execution, persistence, and orchestration.

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