Why Generalists Epstein Is Right About Range: Why Generalists Win in the Age of AI (Or Why Alex Karp Is Wrong)

In a recent Axios interview, Palantir co-founder and CEO Alex Karp offered pointed advice for the AI age: forget broad knowledge, get specialized. According to Karp, the path to a six-figure salary no longer runs through traditional college and general education. Instead, aspiring professionals should focus on deep, domain-specific expertise, ideally by working directly at companies like his.

It is a seductive argument. Specialization feels like the rational response to an increasingly complex world. If AI can handle the generalist work, should humans double down on narrow expertise?

There is just one problem: Karp himself took an extraordinarily generalist path. Liberal arts college at Haverford. Stanford Law. A PhD in social theory from Goethe University Frankfurt in Germany. Years as a money manager in London. Then, finally, tech CEO. His co-founder Peter Thiel followed a similar route: philosophy degree, law school, brief stints in law and finance, then PayPal and venture capital. The advice they are giving does not match the path they took.

I recognize the hubris in some random guy on the internet criticizing a well-educated, wildly successful billionaire. But hear me out.

David Epstein’s Range: Why Generalists Triumph in a Specialized World makes a compelling case that the advice to specialize early misses something crucial about how people actually build valuable expertise.

The Case for Breadth

Epstein’s central thesis is simple: in complex, unpredictable environments, generalists with broad experience often outperform early specializers. Excellence does not always come from a linear path or an early head start.

The book opens with Tiger Woods versus Roger Federer. Woods is the poster child for early specialization, golf club in hand before he could walk. Federer sampled widely: soccer, skiing, wrestling, skateboarding, basketball. He did not commit to tennis until his teens. Both became the greatest in their sports.

Epstein introduces a crucial distinction between “kind” and “wicked” learning environments.

• Kind environments are predictable, with clear rules and fast feedback (chess, golf).

• Wicked environments are messy, with unclear patterns and delayed feedback (most of modern work, parenting, organizational leadership).

In kind environments, early specialization works beautifully. In wicked ones, breadth becomes a strategic advantage.

Tools, Equipment, and Human Limits

One insight that stuck with me was not about education at all. It was about track and field.

Epstein points out that our dramatic improvements in running speed and swimming times correspond directly with improvements in equipment. Better running surfaces. Better shoes. Better swimsuit materials. These athletes have not just evolved; they have learned to use better tools.

We are limited by our own frailty and mortality. But the better we learn to use tools and leverage our environment, the more we can accomplish. In wicked environments (the unpredictable contexts where most of us actually work) that ability to adapt and borrow solutions from adjacent domains becomes essential.

This resonates with my experience as someone with dyslexia. I have spent much of my adult life finding tools to work around it. The right tools do not eliminate the constraint, but they change what is possible within it.

There is a funny corollary, though. When I was a kid, my choir director kept insisting I audition for a special ensemble. I kept declining, explaining I genuinely could not sing well. She insisted anyone could learn to sing.

So I auditioned. I got about four lines in before she stopped me, thanked me for coming in, and never mentioned it again.

Tools and training can take you far, but they cannot take you everywhere. The trick is knowing which limits are real and which are just stories we tell ourselves.

The Polymaths Win

Here is where Epstein’s argument gets really interesting.

3M studied their inventors and found two groups equally likely to earn patents and innovation awards: specialists and generalists. But they found a rarer third group, deep specialists in one area who were also broadly capable in many others. These polymaths were the most innovative, consistently drawing on knowledge from adjacent realms and applying it to their specialty.

This is not an argument against depth. It is an argument against only depth.

Nintendo’s success came from recombining old, “withered” technologies in new ways. The Wii was not built on cutting-edge hardware. It succeeded because someone looked sideways at existing tools and saw a new possibility.

The ability to think laterally, to borrow from other domains, to see your problem as an instance of a broader pattern, these are generalist skills. And they are increasingly valuable in a world where the problems worth solving do not fit neatly into established categories.

Learning What Works (Even When It Feels Wrong)

One of Epstein’s most counterintuitive insights is that the strategies that produce quick performance gains often fail to produce lasting learning.

• Massed practice feels efficient.

• Interleaving (mixing up different types of problems) feels frustratingly slow.

But interleaving produces better long-term retention and transfer.

He introduces “desirable difficulties,” learning strategies that feel harder in the moment but produce superior results. Testing yourself feels worse than re-reading. Spacing out practice feels less productive than cramming. But these “inefficient” strategies lead to better learning.

This suggests that the path that feels most productive in the moment might not be the path that builds the most robust capabilities over time.

Strategic Quitting and Match Quality

Perhaps the most liberating part of Range is Epstein’s treatment of quitting. In a culture that valorizes grit above all else, he makes a case for strategic quitting as essential information gathering.

He introduces match quality, the degree of fit between your abilities, interests, and your work. Finding good match quality requires sampling. It requires trying things, learning what you are actually good at, and being willing to pivot.

Early specialization often means committing before you have good information. Sampling periods, even ones that feel like “wasted time,” improve your odds of finding work that fits.

Foxes and Hedgehogs

Epstein draws on Philip Tetlock’s research on expert predictions. Tetlock divided forecasters into:

• Hedgehogs, who know one big thing

• Foxes, who know many little things

In complex, uncertain environments, foxes consistently outperformed hedgehogs. The specialists were more confident and gave more compelling explanations. But they were less accurate.

The generalists, with their ability to synthesize information from multiple domains and resist the pull of a single explanatory framework, made better predictions about complex systems.

Why This Matters Now

So back to Alex Karp and his advice to skip broad education and specialize early. I think he is optimizing for the wrong thing.

Yes, deep expertise in a narrow domain can be financially lucrative, especially in the short term. But the world Epstein describes rewards something more than just depth. It rewards the ability to connect ideas across domains, to see analogies, to adapt when the rules change, to borrow solutions from unexpected places.

Generalists learn how to think in ways that allow them to leverage tools and solve problems far outside their initial domain. They build the kind of flexible, integrative thinking that becomes more valuable as problems become more complex and less predictable.

This does not mean you need a traditional college degree. What you need is wide reading, diverse experiences, and genuine intellectual curiosity about domains outside your specialty. You need to interact with ideas broadly, whether that happens in a classroom, through books, in different jobs, or through deliberate exploration.

The 3M polymaths were not shallow generalists. They were deep specialists who also cultivated breadth. But you cannot build that by betting everything on a single domain before you know what fits.

Maybe this is why Epstein’s argument resonates so deeply with me. As someone with dyslexia, I have never been able to follow the standard playbook. The straight path was not available, so I had to find workarounds, build different skills, learn to see problems from angles that were not obvious.

Karp talks about his own dyslexia forcing him into non-conformity and innovation, crediting it with fostering the mindset that made Palantir successful. He describes being unable to follow traditional playbooks as a competitive advantage.

But then he turns around and tells others to follow a narrow, specialized track. The very thing he credits for his success, the inability to conform, the forced creativity, the different way of seeing, is what he is now discouraging in others.

A More Generous Timeline

One of the implicit gifts of Range is permission. Permission to take a winding path. Permission to change your mind. Permission to explore before committing. Permission to be a late bloomer.

Epstein quotes a line that has stayed with me:

Compare yourself to yourself yesterday, not to younger people who are not you.

In a culture obsessed with prodigies and early achievement, that is a radical reframing. For anyone in the midst of a career transition, a mid-life pivot, or a period of exploration that feels inefficient, Range offers reassurance grounded in evidence: you are not behind. You are gathering information. You are building breadth. And that breadth might turn out to be your greatest asset.

Book Details

• Book: Range: Why Generalists Triumph in a Specialized World

• Author: David Epstein

• Genre: Non-fiction, Psychology, Education, Career Development

Closing Question

What is your relationship with specialization versus breadth? Have you found yourself pivoting between domains, or have you gone deep in one area? I would love to hear how your own path has shaped how you think about expertise.

About Enthusiastic Generalist. This blog explores ideas across disciplines: from the case for generalists to the benefits of tool-use, from career pivots to the limits of human capability. It is an eclectic mix of whatever I find interesting about the world, whether that is track and field records, dyslexia as both superpower and hurdle, or why breadth might be more valuable than we have been told. If you enjoyed this post, subscribe for more deep dives into the unexpected connections that make life worth paying attention to.