Let’s look at Apple's App Store for a second.
Apple didn't try to build every app itself. It created the infrastructure, opened it up to developers, and let millions of people build on top of it. Apple took a cut. Developers got distribution. Everyone won.
OpenAI just ran the same playbook. Except with AI.
And if you understand how this works, you'll see a business strategy worth studying closely, no matter what kind of company you want to build.
From a Quiet Nonprofit to a $852B Business
OpenAI started in 2015 as a nonprofit. The mission was serious but simple: develop Artificial General Intelligence in a way that benefits everyone, not just a few powerful tech companies.
For a few years, it stayed relatively under the radar. Researchers were doing real work, but nothing that made the mainstream pay attention. Then in 2019, things shifted. OpenAI created a for-profit arm called OpenAI LP to raise the capital needed to actually build what they were imagining. The nonprofit mission stayed intact. But now there was also a business model to feed it.
That business model runs on three main engines today.
- API usage fees, where developers pay per "token" (basically, per chunk of words) every time they use OpenAI's models to power their own products.
- Subscriptions, the $20/month ChatGPT Plus plan, and the higher-tier Enterprise offering for larger companies.
- Licensing deals, like the exclusive GPT-3 agreement with Microsoft that helped unlock billions in investment.
But the real play was never just selling access to a smart chatbot.
The Platform Shift That Changed Everything
There is a pattern worth recognizing across the biggest tech companies ever built: the ones that dominate their categories are building platforms that other people build on top of.
Microsoft did it with Windows. Amazon did it with AWS. Apple did it with iOS. OpenAI is doing it now with AI.
This game became apparent when OpenAI launched its Agents SDK and the Responses API. In simple terms, the SDK is like a recipe book for developers. It gives them the language to call on OpenAI's capabilities, such as searching through files, browsing the internet, or running code. The API is the connection that makes those capabilities available inside any app.
Within 24 hours of the announcement, multiple companies had already pushed new products live using these tools.
Box, the cloud storage company, built a working AI agent in just 48 hours. Their agent could pull data from their platform, understand a company's refund policy, check customer order history, and automatically approve or reject refund requests without a human making each individual call. Billing agents, financial analysis agents, enrollment automation tools. Businesses are building all of this now, and OpenAI sits underneath all of it as the foundation.
That is the platform play. You stop being a product people use and become the infrastructure people build on. Two completely different business positions.
What One Developer's Story Actually Tells Us
A deep learning engineer shared about his experience with OpenAI.
He had never written front-end code before. Within 48 hours of working with GPT-4, he built and launched a full podcast search website. He built a Chrome extension in 15 minutes. He described the feeling as being "a team of a hundred people" packed into one person.
When one person can build what used to take an entire team, the number of products being created explodes. More builders mean more products built on OpenAI's models. More products mean more API calls. More API calls mean more revenue. The flywheel keeps spinning.
OpenAI understands that if developers feel genuinely capable of doing things they never thought possible, they will never stop building. And they will keep paying for whatever makes them feel that way.
Lessons For Every New Founder Out There
There is a question worth sitting with: are you building a product, or are you building a platform?
Most early-stage founders start with a product, which is exactly the right move. But here is the thing OpenAI teaches us: the transition from product to platform does not happen by accident. It is a deliberate strategic decision, and it starts earlier than most people think.
Here are three things worth asking about your own business, at whatever stage you are at:
Who could build on top of what you are building?
OpenAI did not wait until it was massive to open up its API. It gave developers access early, watched what they built, and doubled down on what worked. Even if you run a small SaaS, a consulting firm, or an e-commerce brand, ask yourself: is there a version of your core product that other people could extend, remix, or build around? If yes, that is your platform opportunity.
Are you creating switching costs through value, not just friction?
OpenAI's lock-in is not because leaving is technically painful. It is because the ecosystem built around it is genuinely useful. Every tool, every workflow, every agent a company builds using OpenAI makes leaving feel like starting from scratch. Build something so integrated into how your users function that they would not want to leave even if a cheaper option showed up.
What would your version of an API look like?
An "API" in a broader sense is simply a way for others to plug into your core value. A logistics company's API is its fulfilment network. A media brand's API is its distribution and audience. A marketplace's API is its supplier network. Whatever your business does best, figure out how other people or businesses could access and build on top of that capability.
One Thing to Remember
Platforms outlast products. Almost every time, in almost every industry, over a long enough timeline.
OpenAI started with a powerful product in ChatGPT. But the long game was always the platform. Developers as customers. Businesses as builders. An entire ecosystem running on OpenAI's infrastructure.
The companies that figure out their own version of this playbook, at whatever scale they're at, are the ones that tend to last.
