OpenAI just handed developers the keys to enterprise AI automation. CEO Sam Altman unveiled AgentKit at Dev Day, a complete platform designed to take AI agents "from prototype to production" with drastically reduced friction. The move puts OpenAI squarely in competition with enterprise AI platforms while its ChatGPT user base hits 800 million weekly actives.
OpenAI just fired its biggest shot yet at the enterprise AI market. During Monday's Dev Day event, CEO Sam Altman unveiled AgentKit, calling it the complete infrastructure developers need to build autonomous AI agents that actually work in production environments. "AgentKit is a complete set of building blocks available in the OpenAI platform designed to help you take agents from prototype to production," Altman told the packed developer audience. "It is everything you need to build, deploy, and optimize agent workflows with way less friction." The announcement comes as OpenAI revealed ChatGPT now serves 800 million weekly active users, giving the company massive leverage as it pushes into enterprise territory previously dominated by Microsoft, Google, and specialized AI platforms. But this isn't just another developer API - it's OpenAI's bid to own the entire AI agent stack. AgentKit bundles four core capabilities that address the biggest pain points developers face when building production AI systems. Agent Builder, which Altman described as "like Canva for building agents," provides a visual interface for designing agent logic and workflows. "It's a fast, visual way to design the logic, steps, ideas," Altman explained during the demo. "It's built on top of the responses API that hundreds of thousands of developers already use." The platform's ChatKit component tackles integration headaches by providing embeddable chat interfaces that developers can white-label for their own products. "You can bring your own brand, your own workflows, whatever makes your own product unique," Altman noted, addressing a key enterprise requirement for customization and control. Perhaps most critically for enterprise adoption, AgentKit includes comprehensive evaluation tools through "Evals for Agents." The component offers step-by-step trace grading, performance datasets for individual agent components, automated prompt optimization, and the ability to run evaluations on external models directly from the OpenAI platform. These capabilities address the black-box problem that's kept many enterprises from deploying AI agents at scale. The fourth pillar, OpenAI's connector registry, provides secure integration with internal tools and third-party systems through an admin control panel. This enterprise-grade security and governance layer could be the differentiator that wins over IT departments still wary of AI deployments. To prove AgentKit's speed claims, engineer Christina Huang built a complete AI workflow and two agents live on stage in under eight minutes. The demonstration wasn't just theater - it highlighted how the platform eliminates the months-long development cycles that typically plague enterprise AI projects. "This is all the stuff that we wished we had when we were trying to build our first agents," , suggesting the toolkit emerged from internal frustrations at OpenAI itself. The timing is strategic. While pushes Copilot across its enterprise stack and integrates AI into Workspace, is betting that purpose-built agent development tools will capture more value than embedding AI into existing software. Early signals suggest enterprises are ready. Altman noted that OpenAI has already signed several launch partners who've scaled agents using AgentKit, though the company hasn't disclosed specific customer names or deployment scales yet.
