Book Summary: Range By David Epstein

Why Generalists Triumph in a Specialized World

Updated: November 1, 2022 Reading Time: 10 minutes rating: 10
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This book caught me by surprise. I didn’t do much research before diving into it. I knew Epstein from his previous book “The Sports Gene” but I didn’t think that Range would be so eye-opening and inspiring.

In simple terms, the book is just a counter-argument to specialization. According to David Epstein, today it is more important than ever to have range, to know about different subjects, to combine knowledge from different fields. This is particularly helpful to avoid the “Law of the Instrument”, a cognitive bias that affects all of us, experts in particular.

“To a man with a hammer, everything looks like a nail.” - Mark Twain

Notes and Highlights

Tiger vs Roger

Epstein starts his narrative with a comparison between Tiger Woods and Roger Federer. Both are arguably amongst the most successful players in their respective sports (Golf and Tennis) but their stories are very different. Tiger was pretty much born with a golf club in hand, he started to play as young as age 2—a huge head start—and is the epitome of the early specialization philosophy.

Tiger has come to symbolize the idea that the quantity of deliberate practice determines success—and its corollary, that the practice must start as early as possible.

If you only read about his story it seems that starting early and specializing early is the only way to get to the top. But if you see Roger’s experience, you start to question things. Roger didn’t start playing serious Tennis until he was a teenager. His parents let him roam free and try different things. Once he settled on Tennis they gave him all the support they could. According to Epstein, Federer underwent a “sampling period”: a period in which he just tried different things without a particular goal until something got his attention.

This really resonated with me. While I’m not at the level of neither of them, looking back I also underwent a sampling period, first in sports—I tried Tennis, Soccer, Basketball until finally settling on Swimming for many years— then in school, I enjoyed most subjects and always tried to learn as much as I could. I believe that my love for reading and knowing seemingly “random things” as some friends tell me, started there.


Experts are the ultimate specializers. Epstein argues that this is not an advantage but quite the opposite in many cases.

“Knowledge is a double-edged sword. It allows you to do some things, but it also makes you blind to other things that you could do."

Nassim Taleb has similar views especially when we talk about experts and forecasters in Economics, Psychology, and similar fields. (See the “empty suit problem” in “Black Swan”).

The problem with experts is that they tend to have a very narrow view of the world that leads them in wrong directions when they are faced with new and unfamiliar challenges. This is, they are prone to fit all problems to their familiar tools (see the “Law of the instrument” above).

Rather than adapting to unfamiliar situations, whether airline accidents or fire tragedies, Weick saw that experienced groups became rigid under pressure and “regress to what they know best."

Taking this to the extreme we can see why accidents like the crash of the 737-MAX can happen (I’m over-simplifying here, the 737-MAX issue is very complex, see here and here for an in-depth view on the topic). In fact, Epstein says that

Research on aviation accidents, for example, found that “a common pattern was the crew’s decision to continue with their original plan” even when conditions changed dramatically.

As an example to describe the “expert problem”, Epstein talks about the crash of the Challenger space shuttle. NASA was so used to their data-driven processes that they didn’t follow their intuition nor reason. There were hints of certain malfunctions that could cause issues but the experts got tricked by their own expertise and trust in their tools.

Highly credentialed experts can become so narrow-minded that they actually get worse with experience, even while becoming more confident—a dangerous combination.

So, we must always remember what Richard Feynman once said:

“When you don’t have any data, you have to use reason."


Whether specializing or not, learning is a fundamental part of the equation. On this subject, Epstein's views are less clear to me and he often provides views against deliberate practice (see Deep Work for more about this topic) but then argues for an approach to learning rooted in feedback and "desirable difficulties" which sounds exactly like deliberate practice.

In his own words:

Struggling to generate an answer on your own, even a wrong one, enhances subsequent learning. Socrates was apparently on to something when he forced pupils to generate answers rather than bestowing them.

The more confident a learner is of their wrong answer, the better the information sticks when they subsequently learn the right answer. Tolerating big mistakes can create the best learning opportunities.

His theory is that tackling hard problems and failing a lot is the best approach. Deliberate practice, on the other hand, focuses on doing problems and exercises that are hard enough for us to improve and get feedback but easy enough for the learner not to become discouraged in the process.


Modern work demands knowledge transfer: the ability to apply knowledge to new situations and different domains. Our most fundamental thought processes have changed to accommodate increasing complexity and the need to derive new patterns rather than rely only on familiar ones.

Range, or breadth of experience, is one of the most important traits that we can have today. The world is moving very fast, there are information and noise at every corner. With so much going on it is a mistake to just go deep into one subject. We will “miss the forest for the trees”. In order to really succeed and make a difference, we must use a more holistic approach. We must combine ideas from diverse areas and give our own personal touch.

Knowledge with enduring utility must be very flexible, composed of mental schemes that can be matched to new problems

This is what Epstein is trying to argue throughout the book, and presents quite a few compelling examples. One of them is the story of Gunpei Yokoi, the designer behind Nintendo’s early successes and devices like the Game Boy. In all aspects he was a common engineer with no particular expertise but a wide range of interests:

“I don’t have any particular specialist skills,” he once said. “I have a sort of vague knowledge of everything."

Epstein says that it is precisely because of this non-expertise that Yokoi was able to have an outsider’s view and come up with creative solutions. The history of how the Game Boy came to be, reinforces this. Yokoi, rather than trying to use the latest technology and solve very hard technical challenges—go deep in a single subject matter— opted for researching a wide range of commodity technologies that he could understand without expert knowledge. The result was one of the most successful gaming device of all time: The Game Boy a low-tech but creative device.

Another great example of the advantages of having range comes from an experiment that a scientist at Ely Lilly launched in 2001. The experiment was to publish “twenty-one problems that had stymied Eli Lilly scientists” on the web hoping that people with different skill-sets would come up with the solutions. That’s exactly what happened:

One molecular synthesis solution came from a lawyer whose relevant knowledge came from working on chemical patents. The man wrote, “I was thinking of tear gas,” when he came up with the solution.“Tear gas didn’t have anything to do with the problem,” Bingham said. “But he saw parallels to the chemical structure of a molecule that we needed."

This highlights the fact that in many cases there’s no need for huge specialization as many University professors and managers argue, and in fact, most companies probably need fewer specialists than we think:

Organizations simply don’t need as many specialists. “As information becomes more broadly available, the need for somebody to just advance a field isn’t as critical because in effect they are available to everybody."


Epstein backs up the theory about range and avoiding specialization by discussing our personality as we go through life. It is very easy to relate to this. Personality is fluid. As we experience life, our tastes change, we keep evolving. So, Epstein argues that specializing early is very wrong. What we like when we are teenagers will most likely be totally different from what we’re curious about later on.

The precise person you are now is fleeting, just like all the other people you’ve been. That feels like the most unexpected result, but it is also the most well documented.

We shouldn’t be surprised when we don’t like our job anymore of when something seemingly random seems to drive our curiosity.

Our work preferences and our life preferences do not stay the same, because we do not stay the same.

When reading about this I kept thinking about Jim Collins' interview on the Tim Ferriss Show. Collins claims that all of his projects have started because of a deep sense of curiosity, nothing more. It might not be the best example, but he also has range and has changed areas and focus multiple times throughout his career.

The challenge we all face is how to maintain the benefits of breadth, diverse experience, interdisciplinary thinking, and delayed concentration in a world that increasingly incentivizes, even demands, hyper-specialization.


One question that I couldn’t answer reading this book was about the limits of range. I would argue that there is probably an upper limit to how many fields we can be involved in, but this upper limit may be very high so we will never get to the point of diminishing returns.

What is clear though is that the worst situation one can possibly be is one in which there’s no depth nor breadth:

Inventors who had neither significant depth nor breadth—they rarely made an impact.

An approach to avoid this seems to be to become an expert (or close to one) in one or two fields and then let your curiosity roam free to try whatever catches your interest. Over time you’ll be able to draw ideas and connections from your very wide and some times deep knowledge.

I’ll work hard to always stay an amateur in many fields. After all, as art historian Sara Lewis put it

“Amateur” did not originate as an insult, but comes from the Latin word for a person who adores a particular endeavor.

Notable characters with range

  • Jack Cecchini is a guitar player, probably one of the best the world has seen. I didn’t know about him before reading this book and was quite impressed. Epstein uses him as an example of somebody with range that went through sampling periods before settling on the guitar as his instrument.
  • Nicolas Appert. The inventor of airtight food conservation.
  • Arturo Casadevall. A scientist and professor that is trying to change the specialization mentality of Universities.
  • Gunpei Yokoi. Check out his “lateral thinking with withered technology” philosophy.

New Concepts

  • The Einstellung Effect. This concept is related to the expert problem and the Law of the Instrument.
  • Match Quality “is a term economists use to describe the degree of fit between the work someone does and who they are—their abilities and proclivities.”
  • Cognitive entrenchment. This is another cognitive bias that is related to the expert problem. The more we become familiar with a concept or a tool, the more we start repeating ourselves. This concept is particularly interesting when applied to successful companies: as they grow due to the success of a particular product they stop innovating and creating disrupting products because they increasingly “become entrenched” in the solutions that worked for them in the past. To mitigate this we must keep a “beginner’s mind”.