I’ve been thinking about Leonardo da Vinci. Not the Mona Lisa, not the helicopter sketch, but the fact that one person could embody so many fields at once. Today we call that impossible. Universities, careers, and funding systems reward specialisation. Yet with AI reshaping how knowledge is made, I wonder if we’re on the cusp of rediscovering the polymath.

For me, this isn’t abstract. I’ve always felt the tension between curiosity and career. Colleagues tell me to focus on Generative AI and design, to double down and build my profile. But narrowing down has never felt natural. My curiosity drifts (and I hope it continues to do so!). More-than-human design, life design, creativity, cognition etc. These are the interests that fuel me, even if they don’t fit neatly into a single niche.

We killed the polymath

There was a time when society celebrated polymaths. Leonardo da Vinci was both painter and engineer, anatomist and inventor. The Renaissance thrived on curiosity that spanned fields. But with the Industrial Age came a shift. Factories rewarded speed and repetition. Universities rewarded narrowness (why can’t I go to a university to learn any subjects I like, and instead have to pick a course and do the required subjects?). Efficiency needed specialists, not explorers. That legacy still shapes careers today. To be a “serious” scholar or professional is to pick a lane and stay in it. The polymath became an endangered species. And yet, the curiosity never disappeared. It just went underground.

But curiosity drift does pay off

Ironically, my biggest career leap happened because I allowed myself to drift. My first foray into research (my phd) was about reflective practice and design cognition. I was fascinated by how and why architects design the way they do, and spent three years trying to understand how they think. Right after that, Generative AI arrived, and I couldn’t ignore it. I wondered how this tool influenced the way designers design. So I followed that curiosity.

Generative AI wasn’t mainstream yet, and many researchers saw it as a novelty and have not tried it. But my drift into experimenting with that technology became a defining moment. One of my first papers on Generative AI in design gained recognition because it combined two fields not brought together. What looked like distraction to some became my edge.

This is what I mean by curiosity drift: the willingness to step sideways, explore new ground, and see what happens. Specialists may see it as a detour. I see it as how new connections form.

And AI might be giving the dividends

Today, the conditions for curiosity drift are multiplying. AI acts as a bridge across domains. It gives me a way to test ideas quickly, without having to spend years building entry-level expertise in a new field. If I want to sketch how ecological ideas might influence urban design, I can prompt a model. If I want to explore the language of life design alongside architecture, I can prototype ideas in minutes. It’s not that AI gives me perfect answers. Far from it. But it gives me good enough information to start experimenting. Enough to translate a hunch into a first sketch. Enough to see whether a connection is worth pursuing.

That is the real power of AI to me: it lowers the cost of curiosity.

And so the cracks in the specialist model are widening. Just as the printing press once spread knowledge beyond a privileged few, Generative AI is spreading creative power to anyone with an idea. We no longer need to wait for institutions to grant us permission. The tools are at our fingertips, and the stage is global. Those who lead with curiosity, exploring and combining diverse practices, are the ones most likely to stand out.

My shapeshifter mindset

If polymaths once thrived by being artists, engineers, and philosophers all at once, what does that look like in the AI age? For me, it’s about being a translator, experimenter, shapeshifter.

• Translator, because much of my work is about making connections between design, technology, and innovation that others don’t see.
• Experimenter, because I’m always testing new workflows, tools, and methods, knowing that most will fail but some will open doors.
• Shapeshifter, because it’s not just about skills. It’s about mindset. The ability to step into different modes of thinking (e.g. design, research, pedagogy, futures) and let them inform each other.

Of course, there is a danger here. Breadth without depth becomes dabbling. A polymath is not someone who skims endlessly, but a person who learns deeply in one area and then carries that depth across boundaries.

This is where craft matters. AI can generate polished outputs, but it cannot reproduce the memory, meaning, and friction of making. Similarly, treating AI as a craft which requires slowness, iterations, and discernment, keeps our practice grounded. The future polymath must be reflective, not reactive. The skill is not just in knowing many things, but in knowing how to connect them with care.

The Renaissance Person 2.0

If we are entering a second renaissance, it won’t look like the first. This one is digital, distributed, and fuelled by algorithms as much as ideas. The inventions of our time are hybrid, shaped by human intention and machine collaboration. Yet the spirit feels familiar: creativity sparked by curiosity, and progress driven by those willing to cross boundaries.

For me, embracing this moment means resisting the pressure to specialise at the expense of joy. It means treating curiosity drift as a practice, not a weakness. And it means cultivating the shapeshifter mindset,  not to prove I can do everything, but to show how different ways of thinking can speak to and strengthen each other.

Perhaps the first renaissance rediscovered human potential. This one may rediscover the value of curiosity itself.