Short answer
Use a Codex-optimized model through the OpenAI API when you want model inference and will build the surrounding loop. Use a complete Codex agent run when your product needs repository work, commands, tests, session state, and reviewable changes as one workflow.
- A Codex model endpoint and a Codex agent harness are different integration layers.
- The model route offers lower-level control; the agent route performs work in an execution environment.
- Your product contract should represent tasks, status, files, and reviewable results instead of leaking harness-specific events into the UI.
Separate the model API from the agent harness
| Question | Codex-optimized model API | Codex agent run |
|---|---|---|
| Primary interface | OpenAI API request and model response. | A task executed by Codex in a working environment. |
| Infrastructure | Your team builds the loop, tools, sandbox, files, and persistence. | The harness provides the execution workflow around the model. |
| Product output | Text, structured output, or tool-call data you assemble. | Repository changes, test results, files, and a reviewable task outcome. |
Keep the product contract stable
- Send a clear product task and the repository or files the user authorized.
- Expose status and streaming progress without coupling the UI to every Codex event.
- Return diffs, files, test evidence, and summaries as explicit artifacts.
- Persist enough session state for the user to continue, revise, or retry the work.
- Keep credentials and harness execution on the server side.
Use the smallest layer that completes the job
- Choose the model API
- When you need coding-oriented inference and already own the agent loop and runtime.
- Choose a Codex agent run
- When users expect completed repository work, commands, tests, and a reviewable change.
- Choose a multi-harness backend
- When the product must route between Codex and other agent harnesses behind one stable integration.
FAQ
- Is the Codex API the same as the OpenAI Responses API?
- Not exactly. OpenAI exposes Codex-optimized models through its API, while Codex as an agent also includes an execution workflow around the model. Choose based on whether you need inference or completed agent work.
- Can I put Codex behind my own product UI?
- Yes, but the product still needs a secure server-side integration, run lifecycle, file handling, and a way to present reviewable results to the user.
- Why route Codex with other agents?
- Routing lets a product use the harness best suited to each task while preserving one task, session, streaming, file, and artifact contract.