OpenAI just dropped AgentKit at their DevDay event, and it's basically their answer to making AI agent development way less painful. Think of it as Zapier, but specifically designed for building and orchestrating AI agents.
Until now, building AI agents meant juggling a bunch of different tools. Custom orchestration, manual evaluation pipelines, connector setup, prompt tuning, and weeks of frontend work. AgentKit bundles all of that into one unified platform.
The toolkit has four main pieces:
- Agent Builder This is the visual canvas where you drag and drop nodes to create multi-agent workflows. You get versioning, guardrails, and the ability to preview runs right in the interface. No more writing complex orchestration code.
- Connector Registry Basically a central admin panel where you manage how your agents connect to internal tools and third-party systems. Keeps things secure while giving your agents access to what they need.
- ChatKit Pre-built UI components so you can embed chat-based agent experiences directly into your product. Way faster than building custom interfaces from scratch.
- Evals for Agents New evaluation tools that let you measure how well your agents are performing. You get trace grading, datasets, automated prompt optimization, and you can even test against other models like Claude or Gemini.
During the keynote, OpenAI engineer Christina Huang built a complete AI agent workflow in under 8 minutes to show how fast you can go from idea to working agent. Pretty impressive.
This is OpenAI's push to become more than just a model provider. They want to be the full platform for building agentic applications. It's a direct play against tools like Zapier's agent builders and other automation platforms.