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A common refrain I hear is that in the age of AI, you don’t want to be a “jack of all trades and a master of none.”

For example, my good friend (and former Every writer) Nat Eliason recently argued: “Trying to be a generalist is the worst professional mistake you can make right now. Everyone in the world is getting access to basic competence in every white-collar skill. Your ‘skill stack’ will cost $30/month for anyone to use in 3-5 years.”

He makes a reasonable point. If we think of a generalist as someone with broad, basic competence in a wide variety of domains, then in the age of AI, being a generalist is a risky career move. A language model is going to beat your shallow expertise any day of the week.

But I think knowing a little bit about a lot is only a small part of what it means to be a generalist. And that if you look at who generalists are—and at the kind of mindset that drives a person who knows a lot about a little—you’ll come to a very different conclusion: In the age of AI, generalists own the future.

What generalists are

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Become a paid subscriber to Every to unlock the rest of this piece and read about:

• Generalists: Masters of the uncertain
• AI's limitations in novel problem-solving
• How the allocation economy favors adaptable minds
• Why asking the right questions trumps knowing all the answers