Will OpenAI’s Agent Builder kill Zapier, Make, and n8n? Spoiler: it won’t

Are n8n, Make, and Zapier on their last legs because of OpenAI’s new Agent Builder? That question blew up across tech communities the moment OpenAI unveiled its new tool for building AI agents.

The promise was big: an intuitive environment for building powerful agents, integrated into the OpenAI ecosystem, with the potential to simplify automations that currently rely on external platforms.

But reality, as tends to happen with launches that arrive with a lot of fanfare, turned out to be quite different from expectations. 😅

Those who actually went in and tested it found not one, but two major barriers before they could even run their first agent. One involves a mandatory organizational verification process. The other goes even further: it asks for biometric information to unlock access.

That is exactly what this article is about — walking through what happened during real-world tests with AgentKit, why these barriers matter, and what keeps tools like n8n, Make, and Zapier standing strong and relevant even with giants like OpenAI entering the game. 💪

What is the Agent Builder and why it generated so much hype

The Agent Builder is OpenAI’s latest bet on democratizing the creation of AI agents. The core idea is to offer a visual, accessible interface where anyone — with or without deep technical knowledge — can build automated workflows using OpenAI’s models. On paper, it sounds like a revolution. In the real world of hands-on testing, the tone changes quite a bit.

The excitement was genuine from the announcement. Developers, content creators, digital entrepreneurs, and automation enthusiasts started speculating that platforms like n8n, Make, and Zapier might finally face direct, heavyweight competition from within the OpenAI ecosystem itself. After all, if the company that built the models also offered the orchestration layer, what would be left for the other players?

That logic makes sense at first glance, but it overlooks a fundamental detail: building a good agent interface is only part of the equation. The other part — arguably the more complex one — is making sure that interface connects with the real world in a reliable, secure, and scalable way. And that is precisely where early Agent Builder users started running into obstacles nobody expected to find so early in the process.

The hands-on test with AgentKit: what actually happened

To understand what is behind all this discussion, it helps to walk through a real test done directly in AgentKit. The goal was simple: create an agent called Content Ideation, focused on generating content ideas in an automated way. Creating the agent itself went smoothly enough. The dashboard is functional, the interface is reasonably intuitive, and the setup process did not throw any technical errors during configuration.

So far, so good. The problem started right after.

With the agent created and configured, it was time to run a test. And this is where the experience falls apart completely. The agent simply cannot be executed unless the organization linked to the account goes through a verification process. Without completing that step, there is no preview, no execution, nothing. The agent just sits there, like a brand-new car with no ignition key.

And the verification is not quick or painless. It involves bureaucratic steps that go well beyond confirming an email or validating a phone number.

Verify your Organization and Biometric Information: the two barriers nobody told you about

Before any workflow runs, before any agent gets tested, the user is met with a requirement that is already significant: the Verify your Organization process. This requires the organization to go through a formal verification step with OpenAI, which includes confirming registration data, validating acceptable use, and depending on the plan and region, manual review of the account.

For anyone who expected to start testing in minutes, this barrier alone is enough to kill the momentum.

But the second obstacle is where things really get complicated. When you click on Verify your Organization, you are taken to a page that asks you to begin an identity verification. When you proceed and click Start ID Check, a requirement to share Biometric Information pops up — meaning biometric data from the user or the people responsible for the registered organization. This can include anything from facial verification to photo IDs processed through automated recognition systems.

For a U.S.-based company accustomed to this kind of process, it might seem trivial. For a large portion of the global market — especially independent developers, small startups, and lean teams — it is a massive friction point that blocks access before you even get started. 🚧

This set of requirements is not random. OpenAI is clearly concerned about the misuse of autonomous agents, especially after a wave of public debates about the risks of unchecked automations. The problem is that in trying to build a robust security layer, the company ended up creating an onboarding experience that pushes away exactly the audience that was most excited about the launch: independent creators, makers, and developers building solutions for small-scale operations.

The intent to protect the ecosystem is understandable, but the practical impact is a significant bottleneck right at the front door. Many users are simply not willing to share biometric data just to test an AI agent, and that position is completely legitimate.

Why n8n, Make, and Zapier are still going strong

While the Agent Builder faces criticism for its access process, tools like n8n, Make, and Zapier are heading in exactly the opposite direction. And there are very concrete reasons for that.

Robust and diverse integrations

All three platforms offer hundreds of native integrations with services that are part of the daily workflow of any digital operation. Google Sheets, Slack, Notion, HubSpot, GitHub, Trello, SQL databases, REST APIs, webhooks, and much more. This diversity of connectors is what turns these tools into the Swiss Army knives of automation. Whether the workflow involves sending an email, updating a spreadsheet, firing off a notification, or processing data between different systems, there is a ready-made connector or, at the very least, a clear path to building that bridge.

The Agent Builder, at least in its current stage, simply does not compete at that level of integration coverage.

Accessibility for non-technical users

Another decisive factor is ease of use. Both Make and Zapier were designed from the ground up to serve people without a technical background. The interface is visual, workflows are built with drag and drop, and the documentation is written for someone learning from scratch. This attention to user experience makes all the difference when the target audience is not exclusively software engineers.

And that is no small thing. A huge share of the professionals who benefit the most from automation are outside the programming world — marketing professionals, operations managers, financial analysts, content producers, and entrepreneurs who need to do more with less. For this audience, being able to build a working workflow in minutes, without writing a single line of code and without going through biometric verification, is what defines the choice of tool.

n8n and the power of self-hosting

n8n deserves special attention in this conversation. In addition to offering an accessible cloud version, the open-source platform can be run locally or hosted on the organization’s own infrastructure. This means that teams with strict compliance, security, and data sovereignty requirements can use n8n without sending any information to external servers.

For companies operating in regulated industries like healthcare, finance, and legal, this is a differentiator that is simply priceless. With self-hosted n8n, the organization keeps everything within its own environment, with full control over what goes in and what goes out. Cloud-based proprietary tools like the Agent Builder cannot offer that level of autonomy. 🔐

What really separates the two approaches

At the end of the day, the debate between OpenAI’s Agent Builder and tools like n8n, Make, and Zapier is not about which one is better in absolute terms. It is about what each one is for and who each one truly serves.

The Agent Builder is clearly positioned for those who want to build conversational agents with OpenAI’s models at the center of the experience, within a controlled and verified environment. For specific use cases within that scope, it could be a powerful solution once the entry barriers are softened or removed.

n8n, Make, and Zapier, on the other hand, address a completely different need: orchestrating data, systems, and processes across diverse platforms, with or without AI in the mix. They do not depend on a single model provider, do not require biometric verification, do not block access while the organization goes through a bureaucratic process, and most importantly, they can be used today, right now, by any team with a real automation need.

That immediate accessibility has value that goes far beyond the technical. It represents the difference between having an automation idea and getting it up and running the same day, without middlemen and without artificial barriers.

n8n already incorporates artificial intelligence natively

It is also worth highlighting that n8n has not been sitting on the sidelines watching the AI revolution happen. The platform has already started incorporating AI functionality natively, including dedicated nodes for language model calls, chains, agents with memory, and even workflows that combine multiple AI providers in a single automation.

This means n8n is not limited to the OpenAI ecosystem. It can connect with models from Anthropic, Google, open-source providers, and any compatible API. This vendor flexibility is a huge advantage in a market where depending on a single provider can be risky. The tool is evolving alongside the advancement of artificial intelligence, but without giving up what has always been its strongest asset: the freedom to integrate anything with anything, without asking anyone for permission. 🔗

The current landscape and what to expect going forward

The Agent Builder launch was significant and deserves attention. OpenAI remains one of the most influential forces in the AI market, and every move it makes has the potential to reshape entire dynamics. Ignoring that would be naive.

However, the barriers imposed by the Verify your Organization process and the collection of Biometric Information showed that, for now, the tool is still far from being the universal replacement many imagined. The onboarding process is unnecessarily complex for anyone who just wants to test things out, and the biometric data requirement represents a line that many professionals and organizations are not willing to cross.

Meanwhile, n8n, Make, and Zapier keep doing what they have always done well: connecting the real world through integrations that work, without red tape and without surprises along the way. They are mature platforms with established ecosystems, active communities, and a value proposition that does not depend on a single AI model to exist.

Coexistence between these tools and the Agent Builder is not only possible but likely. Each one occupies a different space in the ecosystem, and the automation market is large enough to support distinct approaches. What this test made clear is that the idea of the Agent Builder wiping out n8n, Make, or Zapier is, at the very least, premature. In practice, these platforms continue to deliver real, accessible, and immediate value — and that is not changing anytime soon. 🚀