"A human being should be able to change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders, cooperate, act alone, solve equations, analyse a new problem, pitch manure, program a computer, cook a tasty meal, fight efficiently, die gallantly.
Specialization is for insects."
— Robert A. Heinlein, Time Enough for Love
I heard this quote in a conversation between the founders of Vercel and Platzi and it hit home.
I learned the basics of programming in high school by breaking the work computer my father had brought home. It was one of the first computers in the small town I grew up in, so it never occurred to me I could make a living out of it.
At fourteen, I started playing piano. Got good enough to win a national contest and a trip to Europe, where I ended up meeting the Pope.
At seventeen I left my hometown for Buenos Aires to study economics and share a flat with three guys I barely knew. I landed a job doing customer support and implementing ERPs, got curious about how those ERPs were built, and switched careers to study information systems.
By twenty-five I had tried multiple roles and industries, was leading tech projects across LatAm, and out of necessity I'd learned to cover for engineers, sysadmins, business analysts, and project managers. You know, people take vacations, quit, or get hit by the proverbial bus. I'd also learned to change the diapers of my newborn daughter.
I loved the jumping around, learning something new and using it to solve bigger problems, but it came with a cost: the corporations I worked at needed to pigeonhole me into a title, a role, a set of expectations. It wasn't ok for a manager to still be doing software architecture. It wasn't ok for a tech lead to spend time helping sales. It wasn't ok to act as if the org chart didn't exist, even when ignoring it was the only way to see the bigger picture.
So I left the corporate world (mostly) and started working at startups, where being a generalist wasn't a character flaw but an advantage. I could jump from tech strategy to product definition, from hiring to architecture, from code review to customer calls, whatever the moment demanded.
This kind of career is rarely up and to the right. Mine was sometimes horizontal, sometimes straight down: I took jobs that paid less as long as they let me learn something new and build an edge I didn't have before. Every jump expanded the territory of things I knew I didn't know.
The specialist's career is different: it pushes deep into one area. That expertise is valuable, but it's a concave bet: it yields reliable returns in a stable world, but it's fragile when things shift. Imagine dedicating your life to driving a horse-drawn carriage, or operating an elevator. When your entire edge is knowing one domain better than anyone else, any disruption to that domain is an existential threat.
A generalist career is the opposite bet. It's convex. You're wrong a lot. Some jumps lead nowhere, you take pay cuts, you abandon skills and start over more times than you can count. But you become the one who ties together domains that nobody expected to connect. The payoff is asymmetric.
So who will the post-AI world reward more, specialists or generalists?
Daniel Rabinovich, COO and former CTO of Mercado Libre, says nothing is riskier today than being a super-specialist. He's a magician, chess player, speedcuber, musician, former university teacher, and today manages more than 80,000 employees.
There's a pre-AI version of this debate between Malcolm Gladwell, the guy who popularized the idea that mastery requires 10,000 hours of deliberate practice in one domain, and David Epstein, author of Range. Gladwell eventually conceded that his rule works in what he calls "kind" environments: settings where the rules are clear, feedback is immediate, and patterns repeat. Chess. Surgery. Tennis.
If you're building a compiler, designing an airplane, or operating on a brain, you don't want the renaissance man. You want the person who has done this one thing ten thousand times.
But most of life isn't kind. It's what Epstein calls a "wicked" environment: rules are unclear, feedback is delayed or misleading, and you can do the right thing and still get the wrong outcome. Business is wicked. Strategy is wicked. Innovation is wicked.
In wicked environments, the specialist is fragile, optimized for a world that stays still. The generalist is antifragile, to borrow Nassim Taleb's term: someone who gains from disorder because every disruption is just another domain to connect, and another opportunity to try something new. A concave strategy gives you reliable returns when things are stable, and disproportionate losses when volatility hits. A convex strategy looks messy, full of small failures and experiments that go nowhere. But when something connects, the upside is asymmetric.
AI is making that convexity matter more than ever. If your edge was deep expertise in one domain, AI just got 80% as good as you overnight. But if your edge was pattern recognition across domains, knowing which question to ask, and smelling when an answer is wrong, AI can only amplify it.
Before everyone had a PhD-level AI specialist on demand, it could have made sense to put all your eggs in one basket and fit the box the corporations asked you to be in. But now?
Maybe it's time to program a computer, change a diaper, and cook a tasty meal.
Specialization is for insects.
