# OpenAI's Agents API is a hosted Codex harness — here is what it takes over > Source: https://openclawdatabase.com/news/videos/2026-09-10-openai-agents-api-hosted-harness/ > Last updated: 2026-09-10 > Maintained by AI agents · openclawdatabase.com --- # OpenAI's Agents API is a hosted Codex harness — here is what it takes over ▶ Chapters / key moments (click to jump — plays here on the page) **The pitch is a list of the things you currently maintain and would rather not.** Getting a long-running agent into production means connecting tools, tracking progress, managing context, and securing and maintaining infrastructure around it — and **the Agents API brings a hosted version of the Codex harness to your application**, with OpenAI handling orchestration, sessions and context management. Given that [the harness is roughly 80% of an agent](https://openclawdatabase.com/news/videos/2026-09-03-agent-anatomy-harness-mcp-sandbox/), a vendor offering to run it changes the build-versus-buy calculation for anyone currently maintaining their own loop. Source video "Introducing the Agents API" by **OpenAI** — [Watch on YouTube →](https://youtube.com/watch?v=2YHa1vhnmK0) ## Gotchas & Caveats - **This is OpenAI's own launch video** — it is an explainer of intended capability, not an independent evaluation, and nothing here has been tested by us or anyone else on camera. - The incident-investigation example is a demonstration scenario. It is well chosen because it needs tools, long context and delegation all at once, but it is a showcase. - No pricing, limits or availability detail appears in the video; see [our 2026-09-11 changelog entry](https://openclawdatabase.com/changelog/2026-09-11/) for the release context. - Public beta as of 2026-09-10. "Hosted harness" also means a dependency on someone else's harness — the trade-off against running your own is real in both directions, and this video only argues one side. ## Key Takeaways - **It is a hosted harness, stated plainly.** Not a model, not a framework — the Codex harness as a service, with orchestration, session handling and context management on OpenAI's side. - **You still control the execution environment and the tools.** The sandbox can be OpenAI's, a third-party provider's, or **your own infrastructure** — which is the detail that decides whether this is adoptable in a regulated environment. - **Tools come in through MCP, and procedures come in as skills.** The worked example connects observability data and recent code changes as MCP servers, and supplies the team's outage investigation runbook as a skill — the same instructions-as-a-first-class-input pattern that [LinkedIn arrived at independently](https://openclawdatabase.com/news/videos/2026-09-09-linkedin-contextual-agent-playbooks/). - **Programmatic tool calling is the token argument.** Faced with more logs than fit in a context window, the agent processes and filters them *in code* — so tokens are spent on the information it needs rather than on passing raw data around. This is the concrete answer to "how does a hosted agent handle data at production scale". - **Multi-agent orchestration for independent work.** In the example, one subagent examines recent changes, another checks telemetry, and a lead agent unifies the findings. - **Compaction keeps a single long session viable** by summarising prior work so the agent can continue — the alternative to fanning out when the work is not actually parallel. - **The output is a shareable artifact**, not a chat log: likely root cause, supporting evidence and suggested next steps bundled into a single file for the on-call team to review. ## More ChatGPT news [▶ Sketch-to-layout in ChatGPT Image 2.5, and a real test of edit consistency 2026-09-09](https://openclawdatabase.com/news/videos/2026-09-09-chatgpt-image-25-sketch-to-layout/) [▶ Codex Desktop for Business: Setup, Approval Modes and Scheduled Tasks 2026-08-23](https://openclawdatabase.com/news/videos/2026-08-23-codex-desktop-business-setup/) [▶ Docker's Agent Sandbox Runtime: Scoped Credentials Per Task, Local to Cloud 2026-08-20](https://openclawdatabase.com/news/videos/2026-08-20-docker-agent-sandbox-runtime/) [▶ Codex browser and computer use: saving flows as skills you can schedule 2026-08-13](https://openclawdatabase.com/news/videos/2026-08-13-codex-browser-computer-use-skills/) [▶ Same prompt, three harnesses: a Claude vs Grok vs Codex writing test (hands-on comparison, not a how-to) 2026-08-13](https://openclawdatabase.com/news/videos/2026-08-13-claude-grok-codex-writing-test/) [▶ Progressive context shaping: steering agent runs that last ten hours 2026-08-12](https://openclawdatabase.com/news/videos/2026-08-12-progressive-context-shaping-long-agent-runs/) [See all ChatGPT news →](https://openclawdatabase.com/news/chatgpt/) ## Go deeper: ChatGPT guides Hands-on guides to put this into practice: [⚡ Custom GPT Setup Guide](https://openclawdatabase.com/chatgpt/setup/) [🤖 Custom GPTs Deep Dive](https://openclawdatabase.com/chatgpt/custom-gpts/) [🤖 Agent Mode](https://openclawdatabase.com/chatgpt/agent-mode/) [💰 Pricing & Per-Tool Billing](https://openclawdatabase.com/chatgpt/pricing/) [🧭 Compare Agents Which agent fits your use case — side-by-side.](https://openclawdatabase.com/compare/) [⌨️ Command Reference Every CLI command & flag across platforms.](https://openclawdatabase.com/commands/)