The Return of the Polymath: from the Greeks to AI

There’s something that’s been chasing me for months.

I work as marketing and sales director for a private security company in Mexico. In parallel, I develop digital tools and workflows, write poetry, compose music, run a YouTube channel, and manage design and development projects for international clients. I invest hours of study, research, analytical thinking, questions and counter-questions into each of these interests. All with the goal of doing it as excellently as possible.

You might think marketing and sales is my real job and everything else is hobbies or part-time work. And to some extent, that’s true. But it doesn’t quite work that way. Everything I do becomes a competitive advantage. The tools I program, the workflows I create, even the artistic sensibility I use for poetry and music—all of them are essential pieces for executing the business growth I develop. People ask me how I do so many things. The truth is I don’t know if I do them well. But I know that in the future it will become increasingly common to seek professionals with diverse skills who, more than anything, have the judgment to make the right decision at the right moment.

In the 15th century, if you asked someone what they were, they’d answer: “I’m a person.” Now they say: “I’m a systems engineer specialized in relational databases.” Something happened in between. And that something is starting to reverse.

When it was legitimate to cross borders

There’s a mistaken idea about the past. We think the Greeks knew everything because there was less knowledge available. That Aristotle wrote about biology, physics, ethics, and politics because the entire world fit in one library. That’s not correct.

In Plato’s Greece there were doctors, mathematicians, rhetoricians. There was differentiation of knowledge. It’s not that Aristotle was a professional doctor or that Da Vinci was a jurist. But they could think about those subjects without being expelled for intrusiveness. Newton could write about prophecy with the same academic seriousness as calculus, and no one told him stay in your lane.

Knowledge was already divided. The difference is that there was no system that segmented you as a person. There was no machine that assigned you a function and punished you for stepping outside it. You could move between areas because the world didn’t need you as a cog. It needed you as a thinker.

That lasted until modernity destroyed it.

The problem wasn’t that knowledge grew

Here’s the part almost everyone misinterprets. You could argue specialization was born because there was too much knowledge. That it was impossible for one person to know everything. And yes, that’s partially true. Some fields grew so much they needed entire lifetimes of study. Quantum physics. Molecular biology, etc.

But that’s not the main force. The main force was the industrial machine and the emerging modern market.

An oncologist isn’t more specialized than a general practitioner because there’s too much knowledge about cancer. They’re specialized because the hospital system needs someone who handles the products, procedures, protocols, and workflows of that specific world. If it were only about knowledge, a doctor could pick up a second specialty in two years, then a third and a fourth, and serve all of them to the same sick human being. The problem isn’t the volume of information. The problem is that the system needs assignable human pieces for a function.

There are three forces behind specialization. One is epistemic: yes, some fields grew. Another is institutional: licenses, certifications, hierarchies. But the third is decisive, and it’s economic-industrial. The system needs you to be one thing. To do one thing. To produce one thing. Knowledge stopped serving understanding and started serving production.

And as soon as that happens, the freedom to cross borders is over. Because the system won’t pay you to be curious. It will pay you to fit into a slot. And if you don’t fit, you’re out.

That didn’t happen with Newton. Newton could write about prophecy because no one needed him as a cog. They needed him as a thinker. His value was in his head, not in his ability to execute a repeatable task within a production flow.

For the last hundred years, your value was in how well you executed your assigned function. The guy who knew everything about internal combustion engines but nothing else had guaranteed employment. Not because he was a better thinker. Because he fit perfectly into a slot in the system.

And culture adapted. We started celebrating the expert. The guy who dedicated his life to a microscopic piece of reality. We called him rigorous. We called him serious. And the one who moved between areas we called a dilettante. Superficial. Someone who doesn’t commit. A jack-of-all-trades.

But the real problem is that discoveries became trapped in silos. Someone in psychology discovered something about decision-making. Someone in economics discovered something about markets. It took a long time to connect theories and discoveries because no one knew enough about both to see the bridge. The world became a puzzle where everyone has a piece but no one sees the complete picture.

That system just started to collapse.

AI lowers the cost of crossing borders

Artificial intelligence doesn’t eliminate the specialist. That would be nonsense. We still need the guy who spent twenty years studying oncology. But what AI does do is lower the barrier to entry for territories that were previously closed.

Before, if I needed to understand how a machine learning algorithm works, I had two options. Spend six months studying, or hire someone who already studied. Now I have a third option. I ask an AI that was trained on all available knowledge about the topic. And it gives me quick access to what the experts know.

I’m not saying that makes me an expert. I’m saying I can move in that territory without having dedicated ten years of my life to specializing. And that changes everything.

Because the generalist becomes valuable again. For the last hundred years, competitive advantage was in knowing a tremendous amount about very little. Now that advantage is shifting toward the person who knows enough to draw on AI’s vast expertise and make informed decisions about multiple things that can and should be connected.

Specialized knowledge is no longer a monopoly. It’s compressed, accessible, consultable. What’s not compressed is the ability to see the complete panorama. To connect ideas from different domains. To formulate the right questions. To understand context.

AI doesn’t do that. The human who learned to move between worlds does.

I work in private security. I have to sell contracts to companies. That requires understanding the business, buyer psychology, proposal design, copywriting, data analysis to know which campaigns work. I master some of these areas, but not all. However, I know enough about all of them to know where to look, what to ask, and how to evaluate the result. That way it’s possible to build something that works.

And when I need depth in an area I don’t handle, I can dedicate a few hours or days to interact with a tutor that contains all human knowledge: AI. I need to understand a data analysis concept, I ask, debate, request bibliography, consult what I didn’t understand, and so on until I get what I’m looking for.

I need a first draft of code to automate something, it generates it. I need to research consumer psychology, it gives me references and explanations. This wasn’t possible before. Before you had to be an expert or hire an expert. Now you can be a generalist with instant access to expert knowledge. And that gives you back something we lost. The freedom to cross borders.

The one who knows how to ask wins

AI is only as good as the questions you ask it. And asking good questions requires understanding the broader context.

If you ask ChatGPT “how do I do SEO for my site”, it will give you a generic answer you already know. But if you ask “how do I optimize a B2B private security site in Mexico considering that decision-makers are operations directors of medium-sized companies who prioritize reliability over price”, while uploading benchmarking data from a previous scrape of competitors’ websites and requesting that we identify ourselves in the market but differentiate ourselves in what can solve our target’s pain points that our competition neglects… the answer changes completely.

And to ask that second question you need to understand the business, the market, some programming, client psychology, and what information is relevant. That doesn’t come from knowing a lot about SEO. It comes from knowing enough about several things to formulate the problem correctly.

The tool is the same. The difference is in who uses it.

And this applies to everything. The designer who only knows design will ask for a reducible logo, with proportions defined by a previous grid, and so on for everything related to their area. The designer who understands psychology, branding, positioning, programming, art, architecture, mathematics, and business context will ask for something completely different.

The ability to connect worlds gives you access to problems no one else can see. And in a world where purely technical tasks can be done by a machine, what remains is seeing complete problems.

Companies still hire by specialty because that’s how they’ve done it for a hundred years. But real problems don’t come in those little boxes. The winner is the one who can move between those areas, connect the dots, and orchestrate the solution.

What’s happening

This movement was already coming. What AI did was accelerate the change. Before you could afford to be a pure specialist because there was still enough demand. Now that demand is evaporating fast. Purely technical tasks can be done by a machine.

What remains is what machines can’t do. See the complete panorama. Connect ideas from different domains. Understand human context. Make decisions with incomplete information. Navigate ambiguity.

And that’s basically what the Greeks did. Not because they were better than us. But because there wasn’t yet a system that segmented them as cogs.

The difference is that now we have the tools they didn’t have. We have instant access to all human knowledge. We can consult artificial experts in seconds. We can learn enough about a field to move in it without dedicating ten years to it.

So competitive advantage is no longer just knowing a lot about little. It’s knowing enough about much, knowing what to ask, where to find the info you didn’t memorize but remember exists, and knowing how to connect it.

We’re not going to become Greeks again. Human knowledge is already too large for one person to encompass everything. But we can get closer than we could in the last hundred years. We can be generalists with access to specialized knowledge. We can connect ideas from different fields. We can see complete problems instead of isolated pieces. And the more companies realize they need this type of professional, the more the label jack-of-all-trades will stop being derogatory.

Specialization won’t disappear. We still need the guy who knows everything about combustion engines. But we no longer need only that. We need the guy who understands engines, materials, aerodynamics, production economics, and can see how all of that connects to design the car of the future.

That guy couldn’t exist before. The cost of crossing borders was too high. The system punished you for trying. Now the cost is dropping. And when that happens, interesting things start to happen.

Because it’s not just about technology or jobs. It’s about how we think. It’s about recovering a way of seeing the world we lost when knowledge stopped serving understanding and started serving production.

The person who knows how to move between worlds has a place again.

That, I think, is bigger than most people understand.