OpenAI Launches AgentKit: Build and Deploy AI Agents Faster

AgentKit lets developers build, deploy, and optimize agents with way less friction.

During the recently concluded OpenAI DevDay, Sam Altman announced the launch of AgentKit, a new toolkit designed to make it easier for developers to build and deploy AI agents.

Over the past couple of years, agentic systems and automation have grown into one of the most exciting areas in AI. You’ve probably seen or tried tools like n8n, Langchain, or Make. They’re great, but I also understand why many users hesitate to use them. These tools are complex, require a lot of technical know-how, and are expensive to scale.

AgentKit is OpenAI’s attempt to simplify what has always been a complicated process. Instead of needing multiple frameworks, SDKs, and APIs to get something working, you can now design, test, and deploy agents directly inside OpenAI’s ecosystem.

In this article, I’ll explain what AgentKit is, what it can do, and how you can start building agents yourself.

Let’s get started.

What Is AgentKit

AgentKit is a modular toolkit for building, deploying, and optimizing agents. Its goal is to reduce the friction that comes with setting up and maintaining multi-agent systems. You can design visual workflows, connect to external data sources, and even embed your agent into an app or website.

AgentKit is made up of three main components: