OpenAI agent builder is launched — the AI workflow automation Agent Kit

OpenAI has officially launched its Open AI agent builder together with AgentKit, introducing a complete ecosystem for building, testing, and deploying intelligent agents. As a result, AI workflows are becoming more visual, connected, and accessible than ever before. This move marks a major step toward visual, no-code open ai workflow creation — combining simplicity, speed, and deep technical power in one platform.

Unveiled during OpenAI’s Dev Day 2025 event, the company described AgentKit OpenAI as a set of “building blocks” that help anyone take agents from prototype to production with far less friction. While tools like n8n and Zapier have long defined automation, OpenAI’s new suite, however, shifts the focus from connecting apps to creating agents that can think, reason, and act independently.

The chat gpt agent builder is the centerpiece — a visual, drag-and-drop canvas that lets users design multi-step workflows. Each node on the canvas can represent a task, a model call, a data fetch, or a conditional branch. Instead of coding manually, creators can connect nodes, define logic, and instantly test outcomes.

Sam Altman described it as “like Canva for building AI agents” — you drag, connect, and instantly see the logic take shape. Moreover, the interface supports inline testing, real-time previews, and built-in evals so teams can quickly iterate and debug. Therefore, instead of scripting hundreds of lines of code, a working prototype can be built in minutes.

While the visual builder handles design, AgentKit OpenAI is what powers everything under the hood. In other words, it provides the SDKs, APIs, and management tools that bring those visual workflows to life in production.

AgentKit includes:

• Agents SDK — libraries for Python, Node.js, and Go that let developers code agents programmatically using the same logic that powers the visual builder.

• ChatKit — an embeddable chat interface that gives agents a ready-to-use front-end. With ChatKit, companies can drop a ChatGPT-style assistant directly into their app or website, complete with message streaming, typing indicators, and custom themes.

• Connector Registry — a control panel for managing which external tools or APIs an agent can access. From Google Drive to internal databases, every connection is managed and secured from one place.

• Evals for Agents — a built-in testing suite for measuring agent reliability, accuracy, and decision-making quality. Teams can trace an agent’s reasoning path, run benchmarks, and automatically optimize prompts based on results.

Because these tools work together seamlessly, AgentKit covers the full agent lifecycle: design, deployment, evaluation, and improvement. The result is a self-contained open ai workflow ecosystem that handles everything from idea to production.

To showcase how these tools connect, OpenAI demonstrated how ChatKit lets builders embed their agents anywhere. For example, Canva and HubSpot were among the first testers — integrating ChatKit into their products to power in-app assistants that handle user queries in real time.

ChatKit manages the chat logic automatically, including message streaming and session history, so teams don’t have to rebuild those systems. Moreover, the interface can be customized to match brand identity, making it easy for companies to launch an AI assistant that feels native to their platform.

Developers aren’t left behind. In fact, the Agents SDK mirrors everything in the visual builder, letting technical teams fine-tune logic in code or extend capabilities beyond what’s available on the canvas.

The evals framework introduces trace grading — a method that shows every step an agent took to reach an answer. As a result, teams can audit behavior, detect weak spots, and improve accuracy. Although OpenAI confirmed that AgentKit supports third-party models, so developers can compare performance between OpenAI models and others in one place.

Importantly, there’s no additional cost for using AgentKit itself — billing follows standard API usage. Therefore, teams can experiment and scale agents without upfront infrastructure investment.

Visual automation isn’t new. Tools like n8n, Zapier, and Make have long enabled users to link apps through trigger-action workflows. What makes agent builder OpenAI different is that these workflows now include reasoning.

Traditional automation moves data — an email, a form entry, a spreadsheet row. AgentKit automation, on the other hand, moves intelligence. Each agent can analyze context, decide which tool to call, and adapt its behavior based on results. In summary, it’s automation that learns.

As one analysis put it, this could be “the beginning of the end for classic workflow tools like n8n, Make, and Zapier.” Instead of rule-based chains, users will build decision-driven systems that evolve.

For readers who want to explore these alternatives in depth, see our Best AI Workflow Automation Tools 2025 collection for a complete comparison.

The potential is vast. Agents could manage research, summarize reports, or interact across business tools — from CRMs to help desks — without constant supervision. Meanwhile, through ChatKit, these agents can live inside everyday software, automating tasks while maintaining human-like interaction.

Yet the shift from static to adaptive automation brings challenges. As visual builders grow more complex, maintaining control and transparency becomes harder. Strong guardrails and eval systems must keep agents reliable and safe. Integrating legacy systems into the new agent builder OpenAI environment will also require time and careful design, especially for enterprise workflows that depend on sensitive data.

Looking ahead, the next phase depends on how far developers push this ecosystem. Will chat gpt agent builder support external extensions and third-party modules? How predictable can agents remain as autonomy increases?

Early experiments already show teams combining n8n triggers with AgentKit OpenAI workflows — blending traditional automation with adaptive AI logic. Ultimately, that convergence hints at the future: automation that doesn’t just follow rules, but understands goals.

Whatever direction the market takes, open ai agent builder and AgentKit OpenAI clearly mark a shift. The line between code, workflow, and intelligence is disappearing — and OpenAI just gave everyone the canvas to paint what comes next.

Discover how automation meets intelligence as AI-driven workflows evolve beyond code. Explore our Best AI Workflow Automation Tools 2025 collection to see how top platforms — from n8n to OpenAI — are shaping the future of smart, connected systems. You can also read our latest update on the ChatGPT Atlas browser — OpenAI’s new AI-powered web experience that connects browsing with intelligent task execution.