AI is winning the competition for money.

Look at startup competitions, accelerators, grant programmes and investment rounds across global markets and one direction is becoming increasingly difficult to ignore: AI has become one of the strongest signals of innovation. That is not necessarily a problem, but it creates a question that deserves far more attention: what exactly are we funding?

Another AI that writes an email for us, summarises a book, prepares a presentation, produces a student’s essay or removes another piece of thinking from the process? We are investing billions in increasing the capabilities of artificial intelligence, yet we talk far less about increasing the capabilities of the humans who will have to work alongside it.

At FocusZen Labs, I am interested in reversing that model. Not another AI Assistant designed primarily to think for the user, but an AI Sparring Partner designed to make the user think. Challenge the argument, demand evidence, find the contradiction, identify the weak assumption, verify the information, defend another position and change your conclusion when the evidence requires it.

Instead of Question → Answer → Copy → Done, we can build Question → Challenge → Reasoning → Verification → Connection → New Question.

This becomes particularly important in education. If a student asks AI to write an essay, the assignment may technically be completed while the learning process has barely happened. But the same technology can be used in the opposite direction. Instead of asking, “AI, give me the answer,” the student can enter an environment built around a very different challenge: “AI, test whether I can reach the answer.”

There is also a warning here, because the saturation of the AI product market may arrive much sooner than many people currently expect. When almost every application contains AI, simply having AI will no longer be a competitive advantage. What attracts investors, grants and startup awards today as a symbol of innovation may soon become nothing more than a standard product feature.

At that point, we may see a pattern familiar from previous technology and speculative booms: a rapid influx of capital, thousands of similar products, increasingly ambitious valuations and eventually a brutal separation between projects that created durable value and those that were simply positioned inside the hottest category of the moment.

There is a parallel with Bitcoin and other speculative technology cycles: participation in a booming market does not automatically create lasting value. And I do not think this moment for AI is particularly far away.

That is why investors, grant programmes and startup competitions may soon need to ask something more demanding than “Does this project use AI?” The better question is: “What remains valuable about this project when everyone has AI?”

And then another question should follow: Does this technology only increase the capabilities of AI, or does it also increase the capabilities of the human using it?

Because eventually almost everyone will have access to a machine capable of generating an answer. The real advantage may belong to the human who can recognise when that answer is wrong, understand why it is wrong and know what question to ask next.

Don’t just teach people how to prompt AI. Teach them how to challenge it.

— FocusZen Labs