A PhD is great. An MBA is great. But what if you are not planning to become a scientist or a manager? What if you simply want to become useful?

Useful, open, deep and wide. Someone who can understand difficult things, work with other people, create something of their own, and keep learning when nobody is giving you a syllabus anymore.

Universities are very good at teaching disciplines. They are much less equipped to teach a person what to do with themselves after the disciplines are learned. There is no degree in becoming human. There probably cannot be one.

What can exist is support. Support in understanding what you know, what you are interested in, what you are good at, and what you could become useful for. Support in finding the people, work and problems that can turn that potential into experience.

This is becoming especially important for people entering technology. AI is changing the relationship between people and work at a speed that makes traditional career paths increasingly difficult to follow. The skills that used to take years to acquire are becoming easier to access. At the same time, judgement, curiosity, responsibility, communication and the ability to work with other people are becoming more important.

Some of the most interesting answers are already coming from inside the institutions. Arizona State has appointed will.i.am as a professor of practice to teach a fifteen week course called The Agentic Self, in which students build a personal AI learning companion they can keep refining through a career. Founder Institute runs an accelerator built for the AI era, where the curriculum adapts each week to the founder in front of it and you can practise a pitch against an AI investor before meeting a real one. Both are right, and they sit at opposite ends of the same road. One lives inside a degree. The other begins at the moment a person has already decided to found a company.

What interests us is the road between them.

So what happens after university? Not everyone is ready to start a company from scratch, and they should not have to be. Work experience is useful. You need to see how real organisations work, how real customers behave, how decisions are made, how things fail, and how people solve problems when there is no textbook answer.

But getting that first meaningful job is becoming strangely difficult. Companies ask for years of experience for entry-level positions. It is almost a joke, except that the person graduating this year still has to solve it.

We believe the answer is not another generic career course. Imagine that a graduate's skills, interests, projects and ambitions could be understood as a whole. Then the system could look at the actual market, identify where that person could be useful, and build a personalised path between the two. Not another curriculum everyone follows. A personal one.

Learn this. Build that. Talk to this person. Practice this skill. Work on this real problem. Try again. Then look at what changed.

The goal is not to make someone employable in the abstract. It is to help them become useful somewhere that matters to them.

We are not starting from a blank page here. Most of the pieces exist and are running.

There is a public map of technologies where every node is reviewed by a named contributor and attached to the use cases it actually serves, which is what turns "learn this" from an opinion into something with a reason behind it. There is a public profile where what a person can do is demonstrated rather than claimed, which matters more with every year that a CV becomes easier to generate.

And there is Product Engine, where real projects are scoped into milestones, priced, and staffed from the community, with an experienced operator confirming the plan before anyone starts. A graduate does not simulate work there. They are staffed on a milestone somebody is paying for. That is the most direct answer we have to the entry-level problem, because the first line on the record is paid work with a named person who watched it happen.

Around that sit mentors who give judgement for a living. The categories the mentor programme already runs on say something about what we think matters: tech skills, self-presentation, emotional intelligence.

What we would build on top of that is a context layer for a person. We are already building one for companies, where goals, constraints, decisions and principles are held as real objects with an owner, a confidence level and a history, instead of disappearing into chat and a few people's heads. Those four turn out to describe a person quite well. What do you want. What are you not willing to do. What have you decided, and why. What do you hold to. A graduate track would carry that context from the first thing someone learns to the first thing they are paid for, and it would stay theirs. The schema we use for software topology is published as an open standard for the same reason: a record you cannot take with you is not really a record of you.

And once a person has enough experience, another possibility opens. They can start something of their own.

This is where the path can continue from employment to entrepreneurship. Instead of asking every young person to become a founder immediately, we can give them the tools, curriculum, mentorship, community and practical environment to start when they are actually ready. Some will bootstrap. Some will build with a small team. Some will eventually need venture capital. The important thing is that entrepreneurship becomes another stage of personal development, not a lottery ticket you have to buy immediately after graduation.

And the journey does not have to be purely professional. People need mentors. Sometimes they need psychological support. They need friends, peers, role models and people who can tell them that they are going in the wrong direction before they spend five years going there.

They also need something harder to measure. A personal curriculum. Books worth reading. Ideas worth thinking about. People worth meeting. Philosophy. History. Art. Science. Consciousness. The ability to understand not only how to do something, but why it is worth doing. Because becoming better at work is not the same thing as becoming a better person.

And eventually the direction reverses. The student becomes the practitioner. The practitioner becomes the founder, expert or leader. The person who once needed help becomes the person who can provide it. They become a mentor, they create opportunities for other people, they hire someone younger, they introduce someone to a person they would never have met otherwise. This is how a real community compounds. Knowledge moves forward, but it also comes back.

We believe AI can make this possible at a scale traditional education could not. It can follow a person's evolving skills and interests, help construct a learning path, provide practice, analyse progress, find relevant opportunities, and carry the enormous amount of small work required to move from one stage to the next.

But AI should not become the institution that decides what a person should become. The point is almost the opposite. The technology should give a person more agency over their own development. And the human layer matters just as much as the technology: mentors, peers, practitioners, founders, teachers, therapists, friends and communities.

We are interested in building that layer for the people entering the future of work now. Starting with technology, because technology is where much of the change is happening first. But not ending there.

Because the real subject is not technology. It is people. And we believe the most interesting people of the future will not necessarily be those who know the most technology. They will be the ones who know how to use it without losing their curiosity, their judgement, their relationships, their freedom and their humanity.

And they will build the future together, beyond borders and politics.