The Power of Thinking Inside the Box

In this episode of Motley Fool Money, Motley Fool Chief Investment Officer Andy Cross talks with David Epstein, author of Inside the Box: How Constraints Make Us Better, about how investors can make better choices in an overwhelmingly complex market.

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A full transcript is below.

This podcast was recorded on May 17, 2026.

David Epstein: We think we want more information, but the evidence is it does not improve our decision quality.

Mac Greer: That was best-selling author David Epstein on how less can be more. I'm Motley Fool producer Mac Greer. Motley Fool Chief Investment Officer Andy Cross recently talked with Epstein about Epstein's new book, Inside the Box: How Constraints Make Us Better. Enjoy.

Andy Cross: Welcome to another Motley Fool Conversation. I'm Andy Cross. David Epstein is the author of the No. 1 New York Times bestseller Range: Why Generalists Triumph in a Specialized World, and he's the author of The Sports Gene. His latest book is Inside the Box: How Constraints Make Us Better. David, welcome back to The Motley Fool.

David Epstein: Thank you for having me. It's nice to be back.

Andy Cross: Thanks for being here. I say, welcome back because you spoke at our annual Motley Fool member event back in 2019, and it was fantastic. Thank you for being there. Now, thank you for being back here, talking to our members. Let's talk about your new book. I have it right here. Inside the Box: How Constraints Make Us Better. Let's get right to the chase. How do constraints, David, make us better?

David Epstein: Broadly speaking, they can force us to clarify our priorities and to launch into productive exploration. Those are two things that, because of the way our brains work, which they are wired for convenience, which you might call laziness, we very rarely do those things to the extent that we should unless we are forced by useful constraints.

Andy Cross: Some of the inspiration for the book came from a class that you took in college, studying haikus. Now, haikus are poems that are three lines. First line is five syllables. Second line is seven syllables. The third line is five syllables. I've actually started writing some haikus myself, just because it does really kind of help focus. But what makes a constraint so well designed as opposed to so stifling? I think some of us think of constraints as stifling. Why are they not stifling? Why are they actually beneficial?

David Epstein: Not just some of us. I think the word is practically synonymous with something that's frustrating. In fact, there's a recent international survey by psychologists of known creativity myths. These are things we know from research are not true. The most popular one was that people are most creative when they're most free. In fact, because our brains, again, are made for, as the cognitive scientist Daniel Willingham says, not for thinking, but for preventing you from having to think whenever possible, that we will reach for easy, convenient solutions, path of least resistance, unless that is blocked, and we're forced to go in another direction. Constraints are incredibly useful for getting us to think in new ways. I think the challenge is when constraints give people a feeling of taking away agency. Say your boss gives you some directive, and it feels so stifling. First of all, if you get that directive and say, could I still surprise myself? If the answer is no, then it's too constrained. Because the whole point is to get people to think in different and productive ways. But short of that, we actually need constraints that force us off the most convenient ideas and get us to do our best work, and in many cases, that actually leads to personal satisfaction.

Andy Cross: I recently interviewed Stephen Witt, who is the author of The Thinking Machine, a fantastic book about Nvidia co-founder and CEO Jensen Huang. I know you read it. Great book, because you have a nice blurb on the cover. Stephen talked about Jensen's willingness to pursue these markets long before there were any constraints, these billion-dollar opportunities, long before there were even customers. How do you square that side of that outside-the-box thinking with this idea that constraints make us better inside of business?

David Epstein: I think one of the things that Jensen also did is made sure to keep things small and focused on very well-defined problem-solving early on. Early on, they were doing computer graphics, period. That's not because Jensen Huang thought that the only applications for this were computer graphics. He used it the same way that Jeff Bezos used books, where it was, I'm trying to make something much bigger, but in the meantime, I need a very defined problem that I can work on to get started. Bezos chose books because if people ordered, they knew what they were getting. It wasn't going to break in shipping, so you weren't going to have tons of returns and things like that. But that was just this stepping stone problem to see, can I start problem-solving in this context? If I can do that, then you can start expanding from that. That's the same thing that Jensen did with computer graphics. It was, here's a defined problem. It keeps it small and contained enough and well-defined enough that we can experiment in this well-defined case, and then we can build from there. When companies or organizations haven't done that, where they jump ahead to the full vision, that's where they tend to have a disaster.

Andy Cross: You talk about in your new book, this great story about the rise and fall of a company called General Magic, a company that had really, as you write, too much creative freedom fueled by too much money. Tell us the story of General Magic and what you learned from it.

David Epstein: General Magic was the first so-called concept IPO in Silicon Valley history. Goldman Sachs took the company public in the mid '90s with an idea, not a product, because their vision was so incredible, and their vision was right, by the way. They were making a personal communicator, basically the iPhone. It was founded by three former Apple employees, two who had designed the original Mac, and one who was just this absolute visionary. His job had been looking at the future of technology, a guy named Marc Porat. I read his PhD dissertation in reporting. It's eerie. He coins the term “information economy” on the first page, and he sees the next half century of what's coming, both the promise and the problems.

In 1989, he's sketching in his notebook, a thin glass rectangle with no protruding buttons and a touchscreen and rectangular apps that was going to be a remote phone computer, as it said near the diagram. They have the vision. Money pours in. They have so many international telecommunications companies invest millions of dollars and come on board that they have to start meetings with an antitrust lawyer listing all the things they're not allowed to talk about. This is beginning when only 15% of American households even have computers. Porat later says that his goal in raising all this money so quickly was to create heaven for engineers, where they were free to play and create, no limits. What more could anyone want? He asked. I think the answer was a little less freedom because they could do anything, and so they did do anything. Every time someone had a good idea, they added it on, and the project grew and grew, and they're missing deadlines.

I interviewed dozens of former employees, and the refrain was, I just couldn't figure out what not to do. They couldn't figure out what not to do. They did so much that the project, the product, it just kept growing. It was essentially incoherent by the time it appeared. Nobody could figure out what they were supposed to do with the thing, and it was a disaster. The stock price had doubled on the first day when they went public. By two years later, it was essentially worthless. It was really this cautionary tale. In some ways, it was a success, though, because so many of the people inside learned these lessons about the importance of boundaries and constraints, and they went on to create technology that every single person listening to this has used.

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Andy Cross: Bill Gurley, the legendary VC investor who, as you write, has invested in Uber and Zillow, his line is more start-ups die of indigestion than starvation. We're in this environment now where there are echoes of the '90s with the amount of capital that is flooding through AI. First of all, your reaction to what Bill writes about start-ups, and do you think it also applies to companies that aren't start-ups, that have been around for years and years, this idea of that more die from indigestion than starvation, maybe unwrap that a little bit.

David Epstein: Yeah. In fact, I think there were several people that claimed that that was their line when I was interviewing them, so I don't know really what the origin of it is. But like, Tony Fadell, who co-founded Nest also, and he's like, that's my line. But I actually think it has never been easier to do too much than right now. Over the last year, I've spent some time with one particular company that helps other companies implement AI. One of the things I've seen as I've been doing that is that a lot of companies are rushing to implement. It's alluring. It's powerful. They feel their competitors are ahead of them, and so they implement, and it's a sprawling implementation and leads to what researchers are starting to call work slop. Incredible amount of volume of stuff, not all of it connected to the larger strategy. Kind of unclear who's supposed to deal with all this stuff sometimes.

The companies that have done it successfully, the ones that I've been exposed to at least, have said, we're going to really well define the problem we're trying to solve. Then, how does the tool match to that? It's almost like they're mapping the jobs to be done in an organization and saying, where does the tool fit? This is another case where it's not what Bill Gurley was talking about with just capital alone, but with the tool that can do so much. That people are often applying it in this incredibly sprawling way where they haven't taken the time to define the bounding box or the problem it's really solving. I think that's one of the reasons why the productivity data so far is surprisingly disappointing for how much implementation there's actually been.

Andy Cross: Another company you write about is Pixar, and how its co-founder and longtime president, Ed Catmull, incorporated constraints in the creative process. Tell us a little bit about the Pixar experience.

David Epstein: I liked to contrast Pixar to General Magic because General Magic was total creative freedom, and Pixar was evolving at exactly the same time, equally audacious vision to make the world's first fully computer-animated feature film. It's thought of as this place of unfettered imagination, I think, where, in fact, it is a place of very many fetters that channel creative ideas into creative achievement. For example, they would keep things as small as humanly possible for as long as possible in film. Directors can spend years in story development, stripping away complexities in a story, like the Schadenfreude was a character from Inside Out that got pulled out because it's adding too much complexity. That might seem wasteful to spend years in that phase, but the costs only explode once you move into production. Staying that small in the long run actually ends up being really efficient.

They have all sorts of rules for creators, like one that I adopted for my own writing called the Three Pitches Rule, where they find that people fall in love with their first idea, even though it's usually not their best one. It's called the creative cliff illusion. We think our best ideas come first or not at all, but in fact, they usually come later. They were forced to pitch three different ideas. That was not a suggestion. It was a rule, the Three Pitches Rule. They just had all kinds of rules and constraints that would help people who otherwise could get carried away in the way General Magic did.

Actually, one I love was what Ed told me about they called the beautifully shaded penny problem. This problem at General Magic was if someone had a good idea, they did it. They could never figure out when to stop. The beautifully shaded penny problem was named because directors might get fixated on the shading on a penny in the background of a shot that the audience would never see, some inconsequential detail, and they'd keep working on it while other things needed to be done. They came up with how's this for a high-tech fix. Popsicle sticks Velcroed to a board. Each popsicle stick represented the amount of work one animator could do in one week. If that director wanted to keep animating that penny, they had to start taking away Popsicle sticks from other characters and moving it to the penny. Making that constraint visible instantly solved the problem.

Andy Cross: That's really brilliant. When I was talking to Mac, our producer, about your work and just the story of Pixar, I was thinking about Steve Jobs because my recollection or thinking around Steve Jobs, his obsessive about these details like the shaded penny. Just thinking about the brilliance of someone like that, and how do they stay focused enough, or how are they able to unwrap that really focused detail with, like, I have lots of other things to get to and to do in running a business or just in my life.

David Epstein: There's a few things about Steve Jobs. One, by the way is, he was banned from certain meetings at Pixar because they felt his opinion would carry too much weight, even if it wasn't good. This is the HIPPO principle, highest-paid person's opinion, carries too much weight. I think people who have read about him much probably know that there were times when he was a micromanager. But I wasn't reporting about Apple, but because of some of the other reporting I was doing like General Magic, I ended up interviewing a ton of people who worked with Steve Jobs. What came through to me was that one of the big differences in the time, after those so-called years in the wilderness, where he was pushed out of Apple, then he came back in the late '90s. When he was at NeXT Computer, he had this famous thing where he wanted the hard drive casing to be in this perfect cube in a certain metal, and it drove the engineers crazy because they had no freedom to problem-solve inside of that. When he came back to Apple, I was told is he was much more like, I'm going to really define the problem, but then I'm going to trust my people and let them do their thing.

What's portrayed to me with some of the people who worked with him, the big area of growth for him was setting the boundaries and letting brilliant people problem solve. I think he may have evolved in his career to the point where he became obsessive about setting up the problem, and what is it that they were trying to do and simplifying that as much as he could. That actually liberated people to then go and create. Even when he first came back to Apple, I think it was '97 maybe, Apple at the time was making printers and servers and the handheld thing, the Newton. They had a million different computer models. He drew on a whiteboard, famously, a two-by-two grid, and on one axis, it said consumer and pro, and on the other desktop and portable. We're only going to have four products, period. People were upset because he killed most of the stuff they were doing, but that complexity was stealing clarity. By narrowing it down to these buckets, it actually liberated people to problem-solve.

Andy Cross: That's great, because I do want to ask about one of the people that you write that you say, if you had to choose one single thinker who really influenced the book, it was Professor Herbert Simon and his work on decision making. Now, he was a polymath, and he did a lot of research in how we make decisions and whether we're maximizing or whether what he calls satisficing, not letting perfection be the enemy of the really very good. Unpack those ideas and why that research resonated so much to you when it comes to decision making, which is so important as we think about making investing decisions.

David Epstein: Simon, as you mentioned, he's trained as a political scientist, but he won the highest awards in computer science and psychology. He won the Nobel Prize in economics. But all of the work revolved around how humans make decisions. What he found was that we cannot really optimize the way that economic theory, according to the rational actor model of humans, because we have limited bandwidth, we have limited ability to predict the future. We have to use shortcuts. One of those shortcuts he called satisficing. We use good-enough rules to get to things. He argued that we should do this very proactively, because we actually spend a ton of time and energy on attempting to optimize, even though we can't. He had decision rules for everything he did. He was like, what is good enough? That helps him avoid what's called Fredkin's Paradox, where we end up spending the most time on the least important decisions because the options are hard for us to tell apart. That probably means it doesn't matter much, or if it does, we can't figure it out. Yet, that's where we spend a lot of our energy just because the options seem similar.

I think when it comes to any kind of decision making, before you get into the heated part of choosing, setting these satisficing rules are, what would good enough look like here? The evidence is that typically, once you've reached that, applying more effort actually isn't going to make your decision any better. It may make you feel better, but it's not going to make your decision any better. Thinking about that ahead of time, whether it's purchasing stock or purchasing a broom on Amazon, like, what is good enough here? Once you get to that, recognize that your decision quality is really not going to go up anymore and just stick with it.

Andy Cross: The quote that you talk about that Simon says is people are always faced with imperfect information about their options and equipped with limited ability to anticipate the consequences of their choices. Investors were always dealing with imperfect information. Yet I feel like investors always want perfect information to make that perfect timing around a buy or a sell. The concept of this idea of maximizing versus satisficing and dealing with imperfect information for investors, I think is very important.

David Epstein: Wanting perfect information, I understand, but that's exactly the tension that he was getting at, is that we think we can do this. We think we want more information, but the evidence is it does not improve our decision quality. To quote a line that has influenced some of my own investing, it comes from the illustrious David Gardner, co-founder of The Fool. When we were having a conversation about trying to buy or sell at the right time, there's the classic saying, buy low, sell high. David said, buy high, never sell. Don't try to do that. If a company is good, buy it. Don't worry about that timing. I think that's an amazing decision rule that is doing exactly what Simon said is, you're having that good enough decision rule. The perfection you want, you're not going to get it anyway. There's no evidence you'll improve your decision quality. Having those kinds of simple decision rules that are based on a principle, I think can be really powerful.

Andy Cross: I think there's also some Daniel Kahneman and Amos Tversky in here, too, with the idea that we feel our losses twice as much as we feel our gains, especially with money, but I think decisions in general. It leads to this analysis paralysis or even the paradox of choice when we have many decisions. There are something like four ETFs created almost every day now. There are more ETFs than there are public stock. It's like the decisions you mentioned about 401(k)s. Maybe we talk a little bit about this, the plethora of information out there for investors to try to digest, and how it can be a little bit overwhelming, and how we really need boundaries, maybe to help us and really focus on certain things when making those decisions.

David Epstein: That 401(k) research again is pretty clear. As the choice set gets bigger and more complex, more people just back out of it, because they're just having trouble making a decision. In hoping that they'll get perfect information, they're putting it off, and often end up never making a decision at all, which is the worst-case scenario. I haven't seen any research yet about this proliferation of ETFs. That's really interesting. I didn't realize there were four a day that are being created. I wonder if some of that, because I've noticed that with Vanguard, I get fed a lot of their emails about new ETFs. I even look into some of them, and I can't even tell the difference between some of them. It seems to me that they're just trying to make, sometimes, more possibilities, even though there's not that much material difference between them, or maybe just an excuse to email saying we've got something new that prompts you to remember, maybe to buy something. I don't really know. But I don't actually think it's good for decision quality. I think having some basic simple principles and sticking to those, and then all these other bells and whistles are mostly a distraction and marginal stuff at best, anyway. I think knowing what those principles are before you get into that morass of all the bells and whistles is really important.

Andy Cross: I do want to get into some AI, and just as you think about the world of AI now, with this idea of how boundaries can help us when information and knowledge is more available to us than ever before. But on the investing side, just maybe a little thoughts on your own investing style if you think about maximizing “satisficing” when you're investing on your own.

David Epstein: Big-time satisficer. Big time. I'm not attempting to maximize. David's going to be mad at me for saying this, but lots of stuff just in simple index funds and things like that, in part because I want simplicity. But I do a lot, a certain amount of money for particular bets I want to make. When I think about my money, I think about money that I can afford to lose and money that I can't. If I can't afford to lose it, I want it in something really conservative. If I can afford to lose it, I'm OK with taking a fair bit of risk. I want some pretty risky things. I will invest in some individual stocks if I just think a company is great. I don't attempt to buy it low. I do the Gardner, and I say, wherever it is, when I decide I want to buy it, I buy it and don't worry about it. Then there are a few cases where I have particular specific interests in things where I'll invest in those as well.

Andy Cross: Excellent. We are fans of ETFs and simple investing, and then adding on stocks as you grow as you wish. So I don't think David will be mad at you for saying that, David. Any ending guidance around a tool or something we can start today that helps us think about constraints in a very positive way and how we can really kind of get inside the box in the most effective way possible?

David Epstein: Again, to reiterate, I hope Inside the Box is a mental or emotional reframe for how we face limits and that we can come to see them as opportunities to clarify priorities or to experiment in new ways. One thing that I think can be really useful, I write in the book about a genomics lab that did this, and then I adopted it myself, is to make all of your current commitments visible. Post-it notes on a wall, for example. Usually what people will see is that they have more things going than they can actually get done, and that a lot of maybe medium priorities are competing with the higher priorities. We don't like to drop things in process. In fact, humans have what's called additive bias. We overlook solutions that involve taking things away in order to solve problems. I think, in this world with so much information, and so many tools, and so many possibilities, we should be doing subtraction audits once in a while. We're making visible all the things we're doing. It's almost like those Popsicle sticks on the Velcro at Pixar. It's like, here are all the priorities. We can't weight them all equally. We are mortals. We have a limited time on Earth. We have limited attention to focus. I think we should regularly go through this practice of saying, what can I take away here so that I can focus on the things that are the most important?

Andy Cross: It reminds me of the Glengarry Glen Ross play "Always Be Closing", just always trying to focus and finish on things. I think that's good overall guidance for so many of us. In a world where just now, especially with AI, just the information, the overflow, and the distractions are coming from all over the place.

David Epstein: You will always get more. Again, because we have two biases. There's additive bias, and the cousin is subtraction neglect bias. We don't take away. As you just go through life, you'll add more and more commitments, meetings, tools, dashboards, etc. Regular subtraction audits because we don't do it naturally. Otherwise, you'll just only build and add more and add more, and it'll dilute the most important things.

Andy Cross: Before I close, the one stat in the book that you mentioned was since the Industrial Revolution, the amount of choice has grown like 100 million times, I think, whereas just wealth has created maybe 400,000x or something like that. Just the difference is just incredible.

David Epstein: Fantastic.

Andy Cross: David, thank you for being here with us at The Motley Fool. The book is Inside the Box: How Constraints Make Us Better. You can follow David on Substack, so go out there and check him out. David, thank you so much for being back here. Hope you join us back here again for another Motley Fool conversation.

David Epstein: It's a pleasure. Thank you for having me.

Mac Greer: As always, people on the program may have interest in the stocks they talk about, and The Motley Fool may have formal recommendations for or against, so don't buy or sell stocks based solely on what you hear. All personal finance content follows Motley Fool editorial standards and is not approved by advertisers. Advertisements are sponsored content and provided for informational purposes only. To see our full advertising disclosure, please check out our show notes. For The Motley Fool Hidden Gems Investing team, I'm Mac Greer. Thanks for listening, and we will see you tomorrow.

Andy Cross has positions in Apple and Nvidia. Mac Greer has positions in Apple and Nvidia. The Motley Fool has positions in and recommends Apple, Goldman Sachs Group, Nvidia, Uber Technologies, and Zillow Group. The Motley Fool has a disclosure policy.