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guides/agents.md 2026-09-24 23:58 UTC to 2026-09-25 23:58 UTC

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Agents

For the complete documentation index, see llms.txt. Markdown versions of documentation pages are available by appending .md to the page URL.

Agents can plan and complete tasks using tools, work with other agents, and maintain context across steps. Choose a runtime based on where you want orchestration to run and who should manage the state between tasks.

Choose your starting point

You want to Start here
Run an agent with the Codex harness managed by OpenAI Agents API
Control the agent loop in your application with reusable agents, tools, and handoffs Agents SDK
Work directly with model responses and control your integration Responses API
Add an embedded chat experience ChatKit

Compare agent runtime options

Agents API Agents SDK Responses API
Use for Long-running tasks where OpenAI manages the agent and saves its progress Building agents with custom tools and workflows in your application Calling models directly or building an agent from scratch
Where the agent runs OpenAI runs a managed Codex harness The SDK runs inside your application Your application, with optional hosted orchestration
Agent integration effort Low Medium High
State between tasks Saved session configuration, turns, and items Your storage and SDK sessions, or Responses conversation state Manual history, response chaining, or Conversations
Tool execution Service-connected tools, application function handlers, and an optional sandbox Tools and integrations configured in your application Hosted tools and tools your application runs
Execution environment OpenAI hosted sandbox, self-hosted sandbox, or no sandbox Your runtime and sandbox provider integrations Your own execution environment
Start here Agents API overview Agents SDK overview Responses guide

The Agents API runs the Codex harness and manages the underlying agent infrastructure so you can focus on what your agents do. It includes automatic context compaction, multi-agent orchestration, programmatic tool calling, and support for MCP servers. See Architecture.

The Agents SDK gives your application control over deployment, storage, approvals, and runtime integration. Its runner handles the agent loop and handoffs. See Running agents.

Add tools, skills, and prompt caching

Tool design, reusable skills, and prompt caching apply across agent workflows. Their configuration and lifecycle can differ by API.

An Agents API session, an SDK session, a Responses conversation, and a sandbox are different resources. Follow the state and cleanup instructions for the runtime you choose.