OpenAI has released the Agents API：https://openai.com/index/introducing-the-agents-api/ in public beta. It gives developers the same harness and infrastructure that run Codex. OpenAI hosts and maintains the harness. Developers run the agent’s compute in an OpenAI-managed sandbox, their own infrastructure, or a partner sandbox.

Is it deployable? Yes. It is live for all developers in public beta. Data stays US-only, and Zero Data Retention is unsupported.

The Agents API is a managed service built on the open-source Codex harness：https://github.com/openai/codex. OpenAI team states scaling Codex and ChatGPT for Work showed what long-running agents need. They need a harness that manages context, uses tools efficiently, and coordinates subagents. They also need infrastructure that keeps them running reliably for days.

The official docs：https://developers.openai.com/api/docs/guides/agents-api/overview organize the API around 4 concepts:

A session runs in 4 steps. You create it and give it a task. Then you follow progress through streaming or webhooks. Finally, you continue with a new task or steer the current turn.

OpenAI’s announcement shows an incident-investigation agent created in a single call:

The quickstart：https://developers.openai.com/api/docs/guides/agents-api/quickstart covers API key permissions and SDK setup.

Environment choice is the main architectural decision. The Agents API supports 3 sandbox options, and it can also run without a sandbox.

OpenAI maintains the harness alongside its models, with versioned access at each model launch.

OpenAI’s runtime comparison：https://developers.openai.com/api/docs/guides/agents positions the 3 options this way:

OpenAI published these customer-reported numbers. They are vendor-supplied, not independent benchmarks.

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