What I've Learned to Do With AI That I Used to Think Would Take Years

Nowadays, when people talk about artificial intelligence, the conversation mostly circles around fear: that it's going to take our jobs, that we don't know where we're headed, that ethics is slipping out of our hands. I understand that concern, but I want to explain why, seen from another angle, I think it's actually great news.

Talking About Ethics Is Progress, No Matter Where It Comes From

The fact that society today is paying more attention than ever to the morality and ethics around AI seems fantastic to me, even if it's the technology itself pushing us into that conversation rather than a spontaneous human decision. The reason matters less than it seems: stopping to think about the consequences of what we build and how we use it is a step forward as a society, and I think it can make us better people, not just better professionals.

Fewer People, but Each One Carrying More Weight

The other common fear is substitution: that AI means fewer people are needed to achieve the same results. That might be true, but I'd flip it around: if fewer people are doing more, those people become more valuable within a company, not less. In practice, that can translate into more clearly defined, more essential roles, with more judgement and more responsibility. The "AI replaces jobs" stigma can become "AI makes the people who stay matter more."

What Used to Take Years, You Now Learn by Doing

But what I really wanted to talk about today is something else: how AI lets you do things that used to take years of learning. I'm not saying you reach the same level of expertise as someone who's spent a decade specialising, that part hasn't changed. What has changed is that you can start building small things right away, and learn by doing, which for me is still the most intuitive, comfortable and fastest way to learn.

Not being afraid to stumble matters a lot here. The sooner you start, the sooner you fall, and the sooner you learn. As I always say: when you win, you enjoy it; when you lose, you learn.

From Theory to My Day-to-Day

I'm an industrial engineer, and what I've been seeing over the last few months is that AI is letting me apply ideas (both technical and creative) that used to stay in the drawer for lack of time, budget or technical knowledge. From building websites and landing pages, to small apps that help me organise my day better, to mini projects that I used to have to outsource to an external agency and pay a fair amount of money for. Today, with a $20-a-month subscription, I can test an idea or even build something that adds real value for a client or for anyone at all.

Learning With Purpose: Hackathons

Something I find really interesting in this context are the hackathons that the best-known AI companies are running right now: a kind of contest where you show up with an AI-built project, compete against others, and there are cash prizes and even trips on the line. The good part isn't just the prize: it's that you're guaranteed to learn with a purpose, with extra motivation that goes beyond your day-to-day work.

I've put together a list of some that are open for registration over the coming months, with dates and format:

Open AI hackathons to learn, build and experiment →

A Resource to Put This Into Practice

For anyone who wants to turn all this into something more concrete, we've uploaded a new resource to the site with the step-by-step method I use to learn by doing with AI, from getting clear on what you want to build, to putting it out into the world and asking for real feedback.

The 4-step method I use to learn any skill with AI →

I hope it's useful. And if you get inspired to build something with this, let me know: I love hearing what people are up to.