OpenAI Killed Off Cheap ChatGPT Wrappers… Or Did It?

In one of the major announcements at their Dev Day conference last week, OpenAI unveiled AgentKit, a new suite of tools designed to make it easier to build agentic workflows.

What does this mean for anyone building products on top of the OpenAI platform?

Is OpenAI competing with us?

Should we be excited, worried, or just ignore the hype?

Let’s dive in.

What tools are in the AgentKit?

AgentKit isn’t a single product – it’s a set of tools designed to work together seamlessly.

It builds on OpenAI’s existing Agents SDK, adding a visual no-code Agent Builder, out-of-the-box UI support with ChatKit, and simple integration for file search, web search, and external MCP servers.

Agent Builder is a visual workflow orchestration tool, similar to n8n, Langflow, and others.

Starting from an initial user input, you add nodes to a graph, each node representing an action or workflow step. The key one is the Agent node, which invokes the OpenAI model of your choice. Alongside LLM instructions and input data, the Agent node can access external data from file storage, vector databases, MCP connections, or web search.

If you’ve used the OpenAI Assistants API or Agents SDK, this will sound familiar. The Agent Builder is simply a more user-friendly interface for building the same functionality. You can even download your workflow as Python or TypeScript source code using the Agents SDK and run it locally.

This makes it great for rapid prototyping, but you can also publish (deploy) your workflow and invoke it from the client via – you guessed it – the Agents SDK.

Compared to tools like n8n, the Agent Builder has fewer options and focuses exclusively on AI workflows. However, it’s tightly integrated with the rest of the OpenAI platform and free to use – you only pay for LLM tokens.

ChatKit, a React-based UI component framework, is another new addition. It makes it easy to create chatbot-style UIs for agentic workflows without needing a dedicated frontend team. ChatKit provides a basic chat interface and supports custom widgets, which can even be uploaded to Agent Builder in a low-code fashion.

The good, the bad, and the (not-so) ugly news

AgentKit is great news for teams building in-house AI tools, especially for non-devs.

While it still needs some developer setup for production, iterating on workflows, prompts, and agent behavior is completely no-code. It’s also a powerful prototyping tool for product owners exploring new AI features or creating quick proofs of concept.

For AI solution builders, AgentKit will likely make a lot of existing chatbot code obsolete. Does that make you obsolete? Only if your product is a simple “chat with your documents” wrapper. If that’s the case, the writing’s been on the wall for a while.

But if your product has complex domain logic, your workflow design and instructions are your real value. That’s the hard part – the code is just an implementation detail. In that case, AgentKit frees you from boilerplate and lets you focus on the high-value work. That’s good news!

The main caveat: building on AgentKit ties you to the OpenAI platform. With the upgraded API, Agents SDK, and now AgentKit, OpenAI is clearly moving up the API value chain.

The original LLM API has become a de facto standard, making it easy to swap in other LLMs like Claude, which made the models somewhat of a commodity. But using AgentKit makes it harder to switch later, since you’d have to reimplement many components. Not necessarily a problem, but something to keep in mind.

Hot or not?

Does AgentKit spell doom for developers? No.

Like other workflow automation and low-code tools, it’s not replacing devs anytime soon. If anything, it’ll save you from writing repetitive boilerplate or endless tweaks requested by product owners and non-tech teammates. Your job is safe – maybe even less tedious.

It will probably kill off a few cheap ChatGPT wrappers. But the more interesting ones – those with domain expertise, specialized logic, and proprietary prompts – will be fine and could benefit.

AgentKit is an incremental but important update. If you’re building any kind of AI-enabled product – whether a quick prototype, an internal tool, or a new product – it’s worth checking out.