In the AI era, you’ll have more chances to succeed if your approach to your developer career is thinking in a more generalist way. This means, for example, if you’re a front-end engineer, you can fill the gaps using AI, by spinning up something on the backend or simply using Supabase. And the opposite is true too: if you’re a designer, you can fill in the gaps as a front-end engineer using AI. Technically, you can become a kind of full-stack engineer, including bits of design, although that’s obviously a different specialty on its own, just by leaning on AI to complete your skills. I think that’s something we can all agree on.

At the last Supabase meetup in Madrid, there was a roundtable, and one of the topics that was brought up was exactly this: should you become a generalist or not during the AI era?

My thoughts, and based and from my experience since 2012 working on developer tools is that while it’s great to be a generalist and you’re probably going to have a great career doing that, especially if you have good product taste and can influence the product and the experience, your company will still need specialists. The conclusion we came to was that there will probably be fewer specialists, not none.

This is most likely the case if you’re developing a product for the general consumer, but not if you’re part of an infrastructure team that’s creating a product for developers.

What I’m trying to say here is: if your passion is Postgres or some other infrastructure tool, something that has been around for decades and isn’t going anywhere, like a specific programming language or runtime, you shouldn’t be diminished.

You shouldn’t feel bad focusing on that if that’s what genuinely makes you happy. Because specialists will still be needed. There will always be people who build new libraries or who work on something very deep core, things like database storage engines, query planners, compilers, network protocols, or critical runtime internals. These won’t disappear, especially when you need to squeeze out performance, correctness, or reliability.

AI will probably get better at this eventually, sure, but from my perspective, that’s still a long way off. Ultimately, AI still needs to be trained, and humans will still be part of that loop.

Curiosity and passion to shape specialists

I would say curiosity and passion are key. Curiosity to keep looking for answers until you find what you’re looking for, without getting disappointed or frustrated or giving up before you’ve proven you’ve found the real answer. And passion to keep you motivated in that whole journey. Obviously you need to know what you’re looking for in terms of product, or what a good DevEx feels like, or ideally have a foundation in one of the product-development specialties.

The Specialist Journey

When it comes to the time you spend learning and doing, you cannot stay on the surface if you want to become a specialist. You can’t just ask an LLM a question and be satisfied with the answer. You still need to go deep into the library, into the code, into how things actually work. The balance really is about time invested. There’s definitely a journey between going from a generalist to a specialist and also the other way around, but the path to becoming a specialist is a long one. So you kind of have to bet on one direction.

That’s where the risk is: while you’re not sure what you want to specialize in, it’s probably better to approach your career as a generalist and only go deep once you’re in a place where those specialist skills are needed. But that takes time. You can’t switch from generalist to specialist overnight.

The Main Challenge: Fast Pace

I feel like the main challenge, not only for generalists, is the fast pace we’re all living in. The iteration speed. To me, the biggest impact AI has had on the industry is how fast we can iterate on development and product creation. All the way from idea to product. Companies can iterate incredibly fast now, or die just as fast if they run out of money. That speed is the real challenge.

When to Specialize

You specialize when you find something that sparks your curiosity no matter what. Something you’re naturally good at. Skills you absolutely need as a specialist are patience and curiosity. You have to be resilient when you’re not finding the answer. Keep looking, keep investigating. So, how do developers know when it’s the right time to specialize? It really depends on the person. But my short answer is: when you feel like you’ve found it.

Standing Out

In order to stand out from one company to another, specialists will be the key. Generalists will definitely have a chance to succeed, and it’s probably the safest path. But my whole take is that if you want to stand out compared to others, or if a company wants to stand out compared to others, it’s the specialist who does that.