OpenAI AgentKit explained: What it is & how it works (2025)

When OpenAI announced AgentKit at its recent DevDay 2025 conference, it definitely got the AI world talking. The promise is a toolkit that simplifies how developers build and manage AI agents that can handle complex jobs. It sounds powerful, but it also brings up a pretty practical question for business leaders: is this a tool your team can actually use, or is it another complex platform that’ll have you calling the engineering department for help?

This guide is here to cut through the noise. We’ll break down exactly what OpenAI AgentKit is, who it’s really for, and what’s under the hood. We’ll also look at its practical uses and, just as importantly, where it falls short for business teams, especially in customer support. Finally, we’ll introduce a more accessible, business-ready alternative.

What is OpenAI AgentKit?

Think of OpenAI AgentKit as a toolbox for developers looking to build AI agents that can actually do things. Before AgentKit, creating an AI agent often felt like a patchwork project, piecing together different tools for logic, data connections, testing, and the user interface. AgentKit’s goal is to bring all of that together on the OpenAI platform.

As OpenAI’s CEO Sam Altman put it, "AgentKit is a complete set of building blocks… to take agents from prototype to production… with way less friction.”

It’s really important to get this one thing straight: AgentKit is built for developers, first and foremost. It gives engineers the low-level components they need to construct custom AI agents from scratch. This makes it incredibly flexible for creating specialized solutions, but it’s a world away from no-code platforms designed for business users who just want to get something up and running without writing a line of code.

The core components of OpenAI AgentKit

AgentKit isn’t one single thing; it’s a collection of tools that cover the whole process of building an agent. Let’s take a look at the key pieces.

Agent Builder: A visual canvas for agentic workflows

The Agent Builder is the main event in AgentKit. It’s a visual, drag-and-drop canvas where developers can map out an agent’s logic. You can connect different steps, plug in various tools, and set up custom rules to control how the agent behaves. It can handle everything from simple, linear tasks to complex systems where multiple agents work together.

However, as any developer who has used visual programming tools can tell you, they can get messy. What starts as a clean flowchart can quickly become a tangled web that’s a nightmare to manage and debug. This is a huge hurdle if you don’t have dedicated AI engineers on staff to look after these systems.

Compare that to a truly no-code platform like eesel AI, which is designed for the people actually running the teams. Instead of asking a support manager to design a complicated workflow, eesel AI gives them a simple dashboard. They can connect their helpdesk with a click, choose which knowledge sources the AI should use, and define its personality in plain English. The whole point is to get a helpful support agent live in minutes, not to spend weeks designing and debugging a visual workflow.

ChatKit: Embedding chat experiences

Once you’ve built an agent, people need a way to talk to it. ChatKit is OpenAI’s answer to this. It’s a UI toolkit that lets developers embed a customizable chat window right into their website or app. This is a nice time-saver, since building a polished chat interface from the ground up can easily take weeks of front-end development.

But while ChatKit offers flexibility, it still requires code to implement and tweak. For a business team, the goal isn’t to build a chat interface; it’s to solve customer problems where they already are. This is where an all-in-one solution really shines. eesel AI provides pre-built products like the AI Chatbot for your website or the AI Agent that slots directly into help desks like Zendesk and Intercom. There’s no separate UI to build or code to embed, it’s just ready to go within the tools you already use every day.

Evals: Measuring agent performance

To trust an agent, you have to test it thoroughly. Evals is OpenAI’s framework for developers to measure how well an agent is doing its job. It has advanced features for creating test datasets, checking every step in a workflow, and even automatically refining prompts to improve the agent’s instructions. It’s a solid suite of tools for technical teams who need to ensure their custom agents are accurate and reliable.

For a business leader, though, performance is less about technical scores and more about business results. This is where eesel AI’s Simulation Mode offers a much more practical approach. Instead of asking you to build test datasets from scratch, eesel AI lets you run your AI agent on thousands of your real, historical support tickets in a safe environment. You can preview every single response, see exactly which tickets would have been resolved automatically, and get a clear forecast of your resolution rate and potential cost savings. All of this happens before the agent ever talks to a live customer, giving you risk-free validation that’s focused on business impact, not code.

eesel AI's Simulation Mode provides a business-focused alternative to the technical Evals in OpenAI AgentKit, allowing users to test agent performance on real historical data.

Connector Registry and Guardrails: For control and safety

For an agent to be useful, it needs access to information and rules to keep it from going off the rails. The Connector Registry is a central hub where IT admins can manage how agents connect to data sources like Google Drive or SharePoint. Guardrails provide an open-source safety layer to stop agents from doing things they shouldn’t or sharing sensitive information.

While AgentKit provides these as separate pieces to assemble, eesel AI builds this functionality right into the platform. You can instantly sync all your knowledge from sources like Confluence, past tickets, and internal docs. Features like scoped knowledge and a fully customizable prompt editor give you tight control over what the AI can say and do. You can easily define its tone, when it should escalate a ticket, and what actions it can take, all without needing a developer to configure safety rules. This ensures your agent is always on-brand and secure.

Unlike OpenAI AgentKit, eesel AI integrates guardrails and customization directly into its platform, allowing for easy, no-code configuration of an agent's tone and behavior.

Is OpenAI AgentKit right for your business?

So, with all these components, the big question remains: should your business be looking into AgentKit? It really depends on who you are and what resources you have.

Key use cases for developers

The ideal user for AgentKit is a developer or a company with a dedicated AI engineering team. It’s perfect for situations that require highly customized, complex agents built from the ground up. The examples from OpenAI’s launch partners, like Ramp building a "buyer agent," show this well. These are bespoke projects where a one-size-all tool just won’t cut it and developer time is not an issue.

The challenge for non-technical teams

But for most business departments, like customer support, IT, or HR, this is where the roadblocks appear. AgentKit is not a plug-and-play solution. Getting an agent live means blocking out developer time for workflow design, front-end coding for ChatKit, and technical work to use the Evals platform. This brings a lot of hidden costs in both time and money, creating a major barrier for teams that need to get more efficient now, not in six months.

The business-ready alternative: eesel AI

For teams that need results without the engineering overhead, eesel AI is a straightforward alternative. It’s designed to empower the people who actually own the workflows, like support managers and IT leads, to build and manage their own AI agents.

Feature	OpenAI AgentKit	eesel AI
Target User	Developers & AI Engineers	Support Managers, IT Leads, Ops Teams
Setup Time	Days to weeks	Minutes
Required Skills	Coding, API knowledge, workflow design	No-code, simple dashboard configuration
Helpdesk Integration	Manual (via SDK/API)	1-click for Zendesk, Freshdesk, Intercom, etc.
Testing & Validation	Developer-focused Evals	Business-friendly Simulation Mode
Knowledge Sources	Connectors require setup	Instantly syncs past tickets, docs, wikis
Pricing Model	API usage-based (unpredictable)	Flat, predictable monthly/annual plans

This video provides an in-depth review of how OpenAI's new AgentKit is reshaping the way AI builders approach their projects.

Understanding pricing and availability

According to OpenAI, the AgentKit tools are bundled with their standard API model pricing. This means your cost is tied directly to how much you use models like GPT-5 and GPT-5 Pro. While that sounds flexible, it creates a variable cost that can be a real headache for budgeting. A sudden jump in customer inquiries could lead to a surprisingly high bill at the end of the month.

As for when you can get it, ChatKit and the new Evals features are available to all developers now, while Agent Builder is currently in beta.

In contrast, eesel AI offers simple, transparent, and predictable pricing. Plans are based on a set number of AI interactions per month, with no extra fees per resolution. This allows you to set a budget and scale your support without getting any nasty surprises.

OpenAI AgentKit is powerful, but not a business solution

Look, OpenAI AgentKit is an impressive toolkit that will absolutely help developers build custom AI agents faster. It provides a unified platform for creating the next wave of smart applications.

However, its complexity, reliance on developers, and unpredictable pricing make it a tough sell for business teams that need to automate workflows today. For most customer support and IT departments, the immediate goal isn’t to start a complex development project. It’s to find a simple, powerful, and integrated solution that works with their existing tools from day one.

Go from prototype to production in minutes

If you’re looking for an AI agent platform you can set up in minutes, not months, that works seamlessly with your helpdesk, and gives you the power to test with real data, then eesel AI was built for you.

Get started for free or book a demo to see how you can automate your support workflows today.