- Published on
OpenAI AgentKit: Building AI Agents Just Got Easier
- Authors
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- Name
- Jitendra M
- @_JitendraM
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Table of contents:
OpenAI just introduced AgentKit, a unified toolkit to build, test, and deploy AI agents — without juggling ten different tools.
For years, developers have been piecing together agents using scattered components: prompt templates, APIs, fine-tuning, and custom integrations. AgentKit simplifies it all, combining orchestration, connectors, evaluation, and UI into one clean workflow.
What’s Inside AgentKit
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Agent Builder — a visual canvas to design, chain, and version your agent workflows.
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Connector Registry — a central hub for integrating data and tools like Google Drive, Slack, or your own APIs.
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ChatKit — plug-and-play chat UI components to add real-time agent interactions to your app.
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Evals & Reinforcement Fine-Tuning (RFT) — measure, grade, and improve your agents with built-in evaluation datasets and feedback loops.
Why It Matters
AgentKit bridges the gap between prototyping and production. You can now move from an idea to a working AI agent — complete with UI and integrations — all within OpenAI’s ecosystem.
OpenAI reports companies like Klarna and Clay are already using these tools to power real-world agents handling customer support and sales.
AgentKit is still rolling out, but ChatKit and Evals are already live. Expect the rest to follow soon.
“AgentKit feels like the missing layer between models and real applications.”