Introducing AgentKit, new Evals, and RFT for agents

Update on June 3, 2026: OpenAI is winding down the Agent Builder and Evals products. From November 30, 2026 onward, they will no longer be available on the OpenAI platform. For workflows that should continue as code, we recommend the Agents SDK⁠(opens in a new window). For use cases better suited to natural language prompting, we recommend Workspace Agents in ChatGPT⁠.

Today we’re launching AgentKit, a complete set of tools for developers and enterprises to build, deploy, and optimize agents. Until now, building agents meant juggling fragmented tools—complex orchestration with no versioning, custom connectors, manual eval pipelines, prompt tuning, and weeks of frontend work before launch. With AgentKit, developers can now design workflows visually and embed agentic UIs faster using new building blocks like:

• Agent Builder: a visual canvas for creating and versioning multi-agent workflows

• Connector Registry: a central place for admins to manage how data and tools connect across OpenAI products

• ChatKit: a toolkit for embedding customizable chat-based agent experiences in your product

We’re also expanding evaluation capabilities with new features like datasets, trace grading, automated prompt optimization, and third-party model support to measure and improve agent performance.

Since releasing the Responses API and Agents SDK⁠ in March, we’ve seen developers and enterprises build end-to-end agentic workflows for deep research, customer support, and more. Klarna built a support agent⁠ that handles two-thirds of all tickets and Clay 10x’ed growth⁠ with a sales agent. AgentKit builds on the Responses API to help developers build agents more efficiently and reliably.

Design workflows with Agent Builder

Builders can get started with a blank canvas or with prebuilt templates.

At Ramp, the team went from a blank canvas to a buyer agent in just a few hours:

— Ramp

— LY Corporation