TemporalCornelia Davis13 min readintermediate
Temporal Agent Harness: An early look at durable agent infrastructure
Summary
Temporal’s Agent Harness wraps existing LLM agent SDKs in a Temporal workflow, giving production‑grade durability, policy‑driven tool approval, and typed interfaces. It lets you keep your preferred inner harness while adding reliable execution and composability.
- Agents run as Temporal Workflows, so crashes, deployments, and long waits are handled without losing state.
- A policy layer can pause tool calls for human approval and resume later, with policies configurable at runtime.
- The "turn" abstraction lets an agent execute a single inner‑harness run, then continue later with preserved context.
- Agents expose strongly typed operations, enabling programmatic calls and composition of agents as software components.
Teams deploying AI agents in production need deterministic control, auditability, and composability—this harness supplies those guarantees on top of familiar agent frameworks.
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