The invisible bottleneck that's limiting your creative pursuits David Epstein: Full Interview

[0:00] I'm David Epstein. I'm the author of the number one New York Times bestseller, [0:03] Why Generalists Triumph in a Specialized World, and now the new book Inside the Box, [0:08] How Constraints Make Us Better. [0:18] Chapter One, General Magic vs. Pixar, Why Constraints Are Necessary. [0:26] General Magic was a company that was conceived in the late 80s and founded by a trio of former [0:31] Apple employees. Two of them had been designers of the original Mac, [0:36] and the other had this job inside of Apple. His name was Mark Peratt, [0:39] and his job inside of Apple was looking at the future of technology, and he was an absolute [0:44] visionary. Internally, their innovations were legion. I mean, they made an early form of USB. [0:51] They made the precursors to emojis, virtual keyboards. They created a virtual meeting space [0:58] where devices could communicate to carry out tasks and do commerce. And what did they call that place [1:05] in 1990? The cloud. Like, they were way ahead of all these things. In fact, in one case, [1:11] they gave a demonstration of some of their disruptive technology. It happened to be a software [1:14] modem in this case, to one of their Japanese partners. And one of the Japanese engineers started [1:19] banging his head on the table. And so they asked, you know, what's wrong? And another one of the [1:25] Japanese engineers said, you have just obsoleted Kato-san's division. So this group of people [1:31] really saw the future of communications technology. And then they formed this massive alliance that was [1:36] a 17-company partnership that covered so much of the communications world that their meetings had [1:43] to start with an antitrust lawyer listing all the topics that they were not allowed to discuss. [1:47] And Mark Peratt, the CEO, started the process to go public, raised more and more money, expanded the [1:55] team, expanded the office. And he said his goal in doing that was to create heaven for engineers, [2:01] where they were free to play and create with the only limits being their imagination. What more could [2:05] anyone ask for, he said. And as it turned out, a little less freedom was the thing they really [2:11] needed. Because they could do anything, they did do anything. The project kept growing and growing. [2:17] And every time someone had an idea for something that would be cool, they made it. They started [2:21] missing deadlines because they kept adding everything and everything got bigger and bigger. [2:25] They didn't have a clear idea of who their customer was. So they defined their customer [2:29] as Joe Sixpack. And when the product finally did come out, the first product that ran their operating [2:35] system was called the Sony Magic Link. It was bigger than a phone. It didn't contain a phone. It was [2:39] overloaded with so much other stuff. It had so many features that the battery life was terrible. [2:44] The user experience was choppy. It had a 200-page user manual. And it sold about 3,000 units in six [2:50] months, mostly to people who they knew. And pretty soon the company was disintegrating. So they just [2:56] did not keep a boundary on anything they were doing. Something that I think was emblematic of [3:01] the problem, there was an engineer named Steve Perlman. And his job at General Magic was to create [3:06] a calendar function. So he writes a calendar function. It goes from 1904 to 2096. And he checks it in, [3:13] and he thinks he's done. And then one of the company's leaders comes to him and says, [3:17] hey, Steve, you know, somebody might make apps that go farther into the future or historical apps. [3:22] You have to make this calendar bigger. And so he redoes the calendar and he starts it from year one. [3:29] So now it goes from year one into the future. He thinks he's done again. And then a member of [3:34] another team comes to him and says, look, why are you tying this into an arbitrary religious context? [3:40] You know, starting at year one or year zero, you should start at the beginning of astronomical [3:44] time. So then he goes back again, creates a calendar function that starts at the beginning [3:48] of the universe. If he had just stuck between 1904 and 2096, it would have been about four lines of [3:54] code. And instead, it ended up being this long project because it expanded like everything did [3:59] at General Magic. And it was an enormous waste of time and resources. They just could not put any [4:04] constraints on what they were doing. When I interviewed a lot of the people who worked there, [4:07] they kept telling me the biggest challenge was figuring out what not to do, what to do and what [4:13] not to do, because they didn't have a bounding box around what they were doing. [4:18] If General Magic was built for unbridled freedom, where people could work on literally anything that [4:23] their minds could conceive, Pixar was the absolute opposite. One of the founders, Ed Catmull, was going [4:32] into grad school about the same time as Mark Perath, the CEO of General Magic. And he had a similarly [4:37] audacious vision. Ed grew up wanting to be a Disney animator, but he wasn't that great of a drawer, [4:42] which is a problem for that. And so he instead set the goal of making the world's first fully [4:47] computer animated feature film. And this was incredibly audacious. When he was starting grad [4:52] school in the 70s, the cutting edge was like shapes rotating on a black screen. And yet, 20 years [4:59] later, with the release of Toy Story, he did indeed create the world's first fully computer animated [5:04] feature film. And then he made it his mission for the rest of his career to create an organization [5:11] that could do that repeatedly. And you think of Pixar as this just unbridled imagination, [5:17] right? Because that's how the products look. But the way he did that was with the religious [5:21] implementation of constraints that were like bumpers in a bowling alley, channeling creative [5:28] ideas into achievement. As Ed says, he thinks ideas abound in organizations. It's a process for [5:33] containing them and channeling them that is more rare. And so as examples of some of the rules that [5:38] he and his colleagues implemented, they had one called the three pitches rule, for example, where [5:42] a director had to bring three different story ideas. They could not just bring one because when we have [5:48] one idea, we get anchored on it. And they didn't want directors to get anchored on their first idea, [5:53] so they forced them to bring three. And once those directors, once they picked a story, they kept [5:59] things as small as possible for as long as possible. They allowed directors and small teams to spend [6:04] years in story development, years refining the core of a story, slicing it away until it was [6:11] something simple. And it might seem excessive to allow directors and a small team to spend years in [6:15] development, but the costs and complexity only explode once they move into production. So they wanted to [6:22] keep them small for as long as possible. And during that time, they'd have dailies where they show their work [6:27] on a daily basis and get feedback on it. Brain trust meetings where they bring in people who haven't [6:33] been seeing the work every day to get outside advice. And when I went to meet with Ed and we spent [6:41] like 10 straight hours talking about constraints that he'd implemented, and he told me about one [6:48] problem at Pixar that he called the beautifully shaded penny problem. And this was an issue where [6:53] directors and animators' conscientiousness would actually work against them. And they would end up [6:58] perfecting the shading on a penny in the background of a scene that viewers would basically never even [7:03] notice. But they would keep working at it, working at it, and they'd start losing time on other things [7:08] that really needed to be done. And so fortunately, Pixar came up with a high-tech solution, Popsicle [7:13] sticks velcroed to a wall. And each Popsicle stick represented the amount of work that one animator [7:20] could do in one week. And they could keep animating that penny if they wanted, but the Popsicle sticks [7:27] would be set up next to all the different things that needed to be animated so they could visually [7:31] see that if they wanted to keep working on that penny, they had to start taking away Popsicle [7:35] sticks from some other character that really needed to be animated. And making the constraint [7:40] visual solved the problem instantly. In a way, I think this ties back to General Magic. Like, [7:46] their main problem was not defining a problem they were solving. Their customer was Joe Sixpack. [7:53] Nobody knew the guy. They didn't know what he needed, so they never defined a problem they [7:57] were solving, which meant that there was never a reason to stop, never a reason not to do certain [8:02] things. And it actually plays into a really hardwired human bias. It's called subtractive [8:10] neglect bias. We overlook subtractive solutions, even when they're obviously the best solutions. [8:17] In a fun study that demonstrated this, adults were given a Lego structure, and they had to balance [8:24] a masonry brick on the top of the structure so that it wouldn't crush a stormtrooper action [8:28] figure that was sitting below. And they could add as many Lego blocks to the structure to bolster [8:34] it as they wanted, but they had to pay to add those blocks. And yet, almost everyone added multiple [8:40] blocks when just taking one away that was upsetting the balance would have solved the problem for free [8:46] and immediately. And that's what happened at General Magic. Because they didn't put firm constraints [8:50] in place, every time someone had a cool idea, they did it. And it just added and got bigger and bigger [8:57] until it lost any sort of core of what they were building, who they were building it for, [9:03] when they were going to get it, how much was it going to cost. They didn't put tight limits on any [9:08] of those things. So everything just grew and grew and grew, because that's how human psychology works [9:14] if you don't put constraints in place. The subtraction audit is this idea that we have to proactively be [9:21] made to look at things that we can take away because we have a hardwired cognitive bias always to add to [9:27] solve problems and never to take away. So let's say if we're talking about a team, [9:32] sitting people down, going through all your types of meetings, your processes, your obligations, [9:39] listing things, and you will come up with things that exist purely because of momentum, right? [9:44] Maybe they served some purpose in the past, but now they're just hanging around and adding friction [9:49] because we never take things away. List those things and then stop doing one of them. Get together [9:55] and say, if I had to kill one thing in the next 90 days, what would it be? And you'll find something [10:01] that has outlived its purpose. And for individuals, the same is we're always adding, adding, right? [10:06] Like everyone keeps a to-do list until it becomes so long that they just have to like tear it up and [10:10] start over again. So what can you take away? So let me tell you how my own to-do list process worked [10:16] in the past. I would put down the things I had to do in a day. They'd be overly ambitious because of [10:21] something called the planning fallacy, which is we always underestimate how long it takes to get [10:24] things done. And so I'd carry some of them over the next day because they didn't get finished. [10:28] And that would add and add until the list got longer and longer until I would eventually flip [10:31] it over on my desk because it made me so anxious to look at it. And then as it got longer, I would [10:35] just throw it in the garbage can and start over. And so when I did a subtraction audit, I was looking [10:40] at what things really need to get done. And so many of the things on the list were not that important. [10:45] So now I start each day one thing at the top of the list that if this gets done, it will have been [10:51] a good day. Other things can be a bonus, but one main thing. And by subtracting all that stuff from [10:57] my to-do list, it allowed me to focus. So I wasn't multitasking, which meant I was more productive, [11:01] less stressful, and I knew the thing to focus on. And so if we want to have personal satisfaction [11:07] and contentment, we have to start putting some guardrails around our choices. I got interested in [11:12] constraints via a few routes, one of which is that I felt I needed to be better at them in my [11:17] own projects, like draw better boundaries around my own amorphous ideas so that I could actually [11:21] execute. Also, just after more than a decade of reading tons of psychology studies, I started to [11:28] notice all these studies where people would become more creative when they were given less choice. [11:33] Like you'd give inventors 20 pieces from a set of 100 and they would make something more creative [11:40] than if you gave them all 100. Or people would be able to name more white foods in 20 seconds than [11:46] they could white things. Why the form of a haiku liberates creativity rather than stifling it. [11:51] So I was really interested in that. And as the cognitive scientist Daniel Willingham says, [11:57] you may think your brain is made for thinking, but it's actually made for preventing you from having [12:00] to think whenever possible because thinking is metabolically costly. And so given full freedom, [12:06] what you will do is go down what scientists call the path of least resistance. [12:10] You will reach for solutions that are familiar, that you have seen before, that you have used [12:14] before. And so it is in fact essentially impossible to be creative unless constraints are forced upon [12:22] you that preclude the previous solutions that you are used to. Let's walk through three examples of [12:29] that. Early in his career, Theodore Geisel, or aka Dr. Seuss, was given a vocabulary list with words for [12:39] children and asked if he could pick about 200 words only and write a book with only those from [12:45] the list. And he looks at the list and he complains. He complains to his wife. He says, [12:50] there's no adjectives. How can I possibly do this? In fine Seussian form, he compared it to making a [12:56] strudel without any strudels. And then he decides he's just going to take the first two rhyming words [13:03] on the list. And whatever they are, he's going to write a book focused on those. And the first two [13:08] rhyming words are cat and hat. And the rest is history. In fact, for Green Eggs and Ham, a subsequent [13:17] book, he wrote that book on a bet that he couldn't write a book using only 50 words. And obviously he did [13:23] so. And because he had limited vocabulary, it forced him to experiment with rhythm and meter and explore [13:30] in all these ways that other writers had not. Virginia Woolf is one of the most phenomenal cases [13:36] of creative breakthrough coming from forcibly applying constraints to oneself. She used what [13:42] the psychologist Patricia Stokes calls preclude constraints. Basically, Woolf saw that she was [13:48] stuck in writing in a traditional form, even though the modern world was growing more complex and needed [13:53] something different in its novels. And so what she did was she outlined the traditional forms of [14:00] narrative structure and then said, I'm not allowed to use any of them. And so she wrote a book in which [14:07] even the omniscient narrator did not really know the main character very well. Even the narrator was [14:14] searching for that person in the way that we in our own lives have to take bits and pieces of people [14:19] to try to understand them. And this was her first modernist novel. It was her breakthrough called [14:23] Jacob's Room. And her next three novels after that experiment are three of the hundred greatest novels [14:29] ever written, according to the greatest books.org. So it was by outlining exactly the old way, [14:36] blocking herself from it, which forced her to come up with something totally new and that we now call [14:41] her stream of consciousness. The Japanese novelist Haruki Murakami, who is an international phenomenon, [14:48] didn't start writing until his late twenties. And when he started trying, he realized he had a generic [14:53] style that he didn't really like. It wasn't unique at all. And so in frustration, he decided to try [14:59] writing instead of in his native Japanese in English, which he barely knew, and then reverse [15:04] translating it back into his native Japanese. And it gave him this simple, clear, kind of mesmerizing, [15:13] rhythmic style that was totally his alone. And that's what he's recognized for. And that's why [15:18] his books have been translated all over the world. So he said it was that forcing that constraint on [15:22] himself to write in the simple English he knew and then translating it backward led to the creation of [15:28] a completely new and unique style. So these are examples that applying constraints to people, [15:34] even when they're arbitrary, often instantly make them more creative. And this ties back to general [15:40] magic. General magic was built to give people complete freedom, no constraints, only the limits [15:46] of the imagination on what people could try to do. Pixar was built in the exact opposite way. People come [15:52] with creative ideas, and then they layer constraint after constraint after constraint on top of them [15:57] to make sure that that creative idea is channeled into something manageable that they can actually [16:02] make. Chapter two, the dangers of too much freedom. The idea of having too much freedom would have been [16:14] crazy for most of human history, where people were born into a role and had very little freedom to [16:19] decide how their life would go. But starting with kind of the industrial revolution, that started to [16:25] change. And in fact, you can see that the idea of too much freedom starts to show up as a [16:30] preoccupation among some of the greatest thinkers, basically starting in the late 19th and then into [16:35] the 20th century, where people like Kierkegaard is writing about the dizziness of freedom, meaning [16:40] all of a sudden there's all this choice. Religion and rulers are structuring less of our lives, so it's [16:45] more up to us. Or Eric Frum writing about the urge to escape from freedom, meaning that we don't feel [16:52] grounded in a way, and so we often look to be controlled in ways that sometimes can be productive or [16:58] unproductive. And in the late 19th century, Emile Durkheim decided to do an analysis of suicide. [17:06] What Durkheim found was that it is actually a sociological phenomenon, that you could see [17:11] different social trends increasing or decreasing rates of suicide. For example, when a country underwent [17:18] economic collapse, suicide increased. Not a huge surprise. But what he also saw was that when a [17:26] country went through an economic boom, suicide also increased. Anything that unmoored people from [17:33] their identity anchors, the familiar structures they were used to, led to an increase in suicide. [17:39] One of the terms Durkheim used was animi, which means essentially rulelessness. Whenever society was [17:46] thrown into tumult in a way that removed the normal rules and reciprocal obligations between people [17:54] and community grounding and meaning, it didn't matter if the economic fortunes were going up or down. If [18:00] it removed those layers of structure, it caused more people to be anxious and desperate and to take their [18:07] own lives. And so it was really a completely new way of looking at the phenomenon of suicide as a [18:13] sociological phenomenon. But it gets at a much bigger issue, which is that the drive for ever-increasing [18:20] freedom, which seems on its face like it should be an unadulterated good, actually comes with a lot of [18:28] collateral damage. And we can see that today when the richest and most free parts of the world, the richest [18:35] and most free areas in world history at that, have these incredible rates of anxiety and depression that you [18:43] wouldn't expect if more freedom and choice made us healthier and improved our well-being. [18:47] Jonathan Haidt, the social psychologist, he's written several books about human thriving and [18:52] well-being. And that idea of animi, again, rulelessness, runs through every one of his books, [18:58] really. As he told me, it's not healthy for anyone to have access to everything, everywhere, [19:05] all of the time. We are not equipped to have infinite choice because our brains are comparison [19:10] engines. And so when there are too many choices, when we are overwhelmed by choice and possibility, [19:15] we become unable to be happy with our own decisions because we're always comparing, right? It's kind [19:21] of a classic FOMO that's built into our brains, but it also occurs at a more sociological level. [19:27] And this gets not just to Jonathan Haidt's work, but also to the political scientist Robert Putnam's [19:32] work in Bowling Alone. So as Putnam famously noted, your chance of dying in the next year is cut in half [19:39] if you join a single club, cut in half, because social integration, being grounded by obligations [19:47] to other people, not having total freedom over your own time, having what's called social control [19:53] of time in some cases, where you have to be in a certain place at a certain time and have certain [19:57] reciprocal obligations to other people, is hugely important for well-being. I mean, that's what Putnam [20:03] raised the alarm about in his book Bowling Alone, that as people, as the title indicates, [20:07] as people stop being in bowling clubs and having collective entertainment and collective regular [20:12] meeting times, this dissolution of these dense networks of reciprocal obligation would have [20:19] tremendous effects on health, well-being, and longevity. That book came out in 2000, and I would [20:26] say it looks absolutely prescient in retrospect, where we've become more virtual, we're engaged [20:33] in what Haidt calls this online, this endless cycle of micro-dramas populated with a cast of rotating [20:40] characters, a total lack of social norms, few obligations. We've often hyper-tailored our lives [20:47] so that they're totally individualized just for ourselves, and that feels like something you would [20:51] want, but it turns out not to help humans thrive. You can actually go back to the Soviet Union at one [20:56] time, when they tried to change the work week in a certain way to keep factories operating all the [21:01] time, and so they gave people different work weeks with four days of work and one day weekend. [21:07] So very rarely did two people have the same work week, so it decoupled people's schedules, [21:12] and it was a social disaster. They had to completely undo it. Now, on the other hand, [21:18] when there's kind of forced regulation of time, like in Sweden, you can see that in periods when a lot [21:24] of the country is forced to take time off, essentially, the dispensing of antidepressants plummets, [21:29] and it's proportional to the portion of the country that has time off, and importantly, [21:34] it's true even among retired people. So it isn't just about having time for vacation or having time [21:40] not to work. It's about the collective use, the collective enforcement of using time in a certain [21:46] way. So we always think we want more choice and more freedom over our own time, but there's a [21:51] mountain of evidence showing that we actually want to give up some of our autonomy to sync with other [21:57] people, preferably at a large scale, because it's tremendously important for a hyper-social [22:01] species like humans to thrive. I think one of the ways that people have responded to this seemingly [22:08] infinite choice in the modern world is to try to optimize more, or what psychologists call [22:13] maximize, to make the best of everything and to make the best decisions. And in fact, we can see in [22:20] research that maximizing behavior, which is the attempt to evaluate tons of options and make the best [22:26] decision is actually on the rise. So we know that that's increasing, as is perfectionism, is increasing [22:32] in many parts of the world. But that's actually a problem, because maximizing, even though there's [22:37] like tons of influencers who are showing you all these productivity hacks and how to maximize and how [22:42] to get everything done, it makes us miserable, and it's an illusion. And as Oliver Berkman would say, [22:48] they're just trying to help you avoid grappling with your mortality. They give you the illusion that [22:53] you can actually get everything done if you only have the right system. But in fact, what you have to do [22:57] is face the fact that you're mortal, you're going to die, and ruthlessly prioritize based on that, [23:05] and set criteria, as Herbert Simon would have said, for satisficing. What is a good enough solution [23:11] instead of looking for what is the best? Herbert Simon is the thinker who had the biggest influence [23:16] on this book of anyone. And he was trained as a political scientist, but he won the highest award [23:22] in computer science, the Turing Award, because he was a founding father of AI. He won the Lifetime [23:27] Achievement Award in psychology, because he was a founder of cognitive psychology. And then for good [23:31] measure, he won the Nobel Prize in economics. And he was what I call an incorrigible satisficer. [23:40] Satisficing is a term that he developed that means picking something that is good enough. [23:46] So it's in contrast to maximizing, where you try to consider all of the options available and pick the [23:51] optimal one based on evaluating everything you possibly can. And what Simon showed was that we have [23:57] finite brains. And so even though classical economic theory says, yes, we evaluate everything [24:01] about every option and make the optimal choice, we can't actually do that. And when we strive to do [24:07] it, we end up less happy and less satisfied with our decisions. So instead, what we should do is [24:13] proactively satisfy, set criteria for what's good enough, and then go with that. And Simon did this [24:20] everywhere. He had the same few sets of clothes he wore, same breakfast. He had simple decision rules that [24:27] he used for things. You could almost accuse him of having low expectations if not for his trophy [24:31] case, which has the highest awards in economics, psychology, and computer science. What we want [24:37] to do is get a system that works well enough, think of criteria ahead of time for decisions that are good [24:43] enough, and then take those. Because you can't realistically optimize or maximize anyway. We can't [24:50] grapple with infinite choice. And it just makes us miserable. So I don't want to tell you not to be [24:55] ambitious, because that's what it sounds like. But you should start setting criteria for good [25:00] enough solutions. It's not about having low standards. It's about having any standards at all [25:07] that can possibly be met. And it will make you a happier, more satisfied person, and lead you to [25:12] prioritize. And the realization that you simply can't get everything done, and what you actually need to [25:16] do is start cutting stuff out so you can prioritize. [25:24] Chapter 3, How to Fix Bottlenecks. [25:26] Eli Goldratt was an Israeli physicist who, in the 1970s, was studying how atoms behave in crystals [25:35] when a friend of his came to him with a comparatively pedestrian problem, which was how to increase [25:41] production at his chicken coop building business. The friend had a small business building chicken [25:46] coops, and he noticed that even when he hired extra help, it didn't increase the overall output of [25:51] chicken coop, so he was kind of confused. Of course, he asks his physicist friend if he can study the [25:58] process, basically an assembly line, and see if he can improve production. And what Goldratt notices [26:03] is that in the production of chicken coops, there's always one step that limits the overall output of [26:10] the system, no matter what's going on anywhere else. And this observation became the core of what he [26:15] called the theory of constraints, which is the idea that a single bottleneck, or the single slowest step [26:21] in a system, limits the overall output of the system. And so in the case of the chicken coops, [26:27] he took one individual worker and moved them from one of the steps that had plenty of people working [26:31] at it, and moved that one worker over to the bottleneck, the slowest step, and that tripled the [26:36] overall output of the system. And Goldratt expanded on this idea in a bizarre novel called The Goal, [26:45] in which this fictional plant manager named Alex Rogo has to save a manufacturing plant and his [26:51] marriage, and luckily he bumps into his old physics professor who gives him these like [26:56] Socratic lessons. You know, go figure, of course, it's his Jedi-like physics professor. And it's a [27:01] very strange book, but Alex starts to see the world through these kind of bottleneck glasses, [27:06] where when he takes his son's Boy Scout troop on a hiking trip, he realizes that some of the kids [27:12] are really fast hikers, but then there's Herbie, this kid who's really slow. And so the fast kids [27:16] can go way ahead, but it doesn't speed up the whole team, because the whole team can only go [27:21] at the pace of Herbie, the slowest hiker. And so he decides to take the backpacks and redistribute [27:26] some of the weight, so the faster kids have heavier packs and Herbie has a lighter one. Slows down the [27:30] fastest kids, but speeds up the overall group, because it speeds up Herbie, who was the bottleneck. [27:36] So Alex, the plant manager, starts to see the whole world in this light, and he saves the plant, [27:40] and he saves his marriage. And again, it's this quite strange book. That said, it sold 10 million [27:44] copies. And, you know, Jeff Bezos made all of his executives read it and hosted a full-day book [27:49] club on it. It spawned a whole genre of even more bizarre business novels, where people get these [27:55] lessons from professors they bump into. And it also gave birth to a 1,200-page Theory of Constraints [28:01] handbook. In that handbook, Goldratt wrote the foreword, and he asks, can I condense all of the [28:08] Theory of Constraints into one sentence? And he says, I can do even better than that. I can condense [28:15] it into one word, focus. The system constraint shows you where to focus, because if you apply [28:23] effort somewhere else, it doesn't change the overall fate of the system. Let me give you an [28:28] example from a Theory of Constraints, a case study that I was learning while I was researching the book. [28:33] And it's about manufacturing, but it's an analogy for something more broadly relevant. [28:39] In this case, it dealt with a company that made custom gearboxes for industry. So every single one [28:46] had to be totally customized. And they were struggling, essentially. And so they decided [28:51] to do a Theory of Constraints audit, basically. Where is work piling up? Why are we not able to [28:56] produce these more rapidly? And it turned out that their bottleneck was in the tiny 15-person design [29:02] office, where the designs of the gearboxes were made. The designers were totally ravaged by [29:08] multitasking. They're changing focus more than 50 times a day. And it turns out that that destroys [29:14] your ability to get stuff done. It raises stress levels. It makes you worse at everything you do. [29:18] So it led to errors, and eventually it led to quitting. So they implemented a rule called stop [29:24] starting and start finishing. You were not allowed to take in a new design and start it until you had [29:30] finished one. In a few months, they were getting three times as many designs out the door. And it [29:36] dropped the total time for the company making a gearbox from one year to two months, because that [29:42] was the bottleneck. But this kind of focus bottleneck shows up all over the place. Like, [29:48] modern work is insidious. It is just hideously insidious at adding things to our plate. [29:54] More communication, more meetings, more apps, more dashboards, more obligations. Very rarely do those [30:01] things get taken away. So our attention and our ability to focus becomes the bottleneck. [30:07] And unless we're kind of doing what I call subtraction audits, that's just going to grow and [30:12] grow and grow. So I think regularly, people should take a look at what they're doing, try to list things [30:18] that maybe have outlived their usefulness. Maybe that's a tool. Maybe that's some type of notification. [30:23] Maybe it's some type of meeting. List them. And if there's something that's outlived its usefulness [30:28] and is only adding friction, take it away. Subtract it. But we have to do that regularly because [30:35] we just are not wired to solve problems by taking things away. We have to proactively be attuned to [30:42] it. So that theory of constraints, that idea of applying effort at the bottleneck can be incredibly [30:48] impactful even if the system is just you or an individual. For example, there's a woman named [30:54] Sheila Tarmina, who in 1992 was a swimmer at the University of Georgia, and she tried to make [31:01] the Olympic team, went to the U.S. Olympic trials, failed to make it, wasn't even close [31:05] really, decided to retire. But then for one of her last classes at the University of Georgia, [31:11] she took Management 577, in which she learned about the theory of constraints. And for her class [31:16] project, she decided to apply the theory of constraints to her own training and make a plan [31:22] to drop three seconds from her 200-meter freestyle. So she goes, she does like an audit of her [31:27] training. What's my bottleneck, she asks. And it turns out it's her strength, her power. She's [31:33] only five foot two, which is really small for an elite swimmer. And she has an incredible aerobic [31:38] engine, incredible aerobic endurance. But that's what her coaches have her working on, aerobic [31:42] endurance, over and over and over. But she's already great at that, whereas she's limited by her [31:47] strength, but they don't have her working on that. She decides to unretire. She gets a different [31:52] coach who's willing to work with her. Four years later, in 1996, she swims exactly three [31:57] seconds faster, makes the Olympic team, and becomes a gold medalist in the relay. And you [32:02] can see pictures of her. She's like half a foot shorter than her relay teammates. She [32:06] retires again. Then she decides to come out of retirement. She has this new way of looking [32:10] at her training as, what's my limiting factor that I should focus on? She comes out of retirement, [32:15] switches to triathlon, wins the U.S. National Championship, goes to the Olympics, finishes sixth. [32:20] Then she learns fencing and horse jumping and goes to the Olympics again in modern pentathlon, [32:25] becomes the only woman ever to compete in three different sports in four Summer Olympics. [32:31] And she was going to retire in 1992, if not for learning about the theory of constraints [32:36] in a management class. [32:42] Chapter four, regaining our focus in an attention economy. [32:46] As Herbert Simon said, in an information-rich environment, there's a poverty of whatever it [32:53] is that information consumes. And that thing is attention. And I would say we're in a very [32:58] information-rich environment. And so our attention is at risk. You can see this in all sorts of work, [33:05] like Gloria Mark, who did incredible research on attention in people's workplaces. When she started [33:11] about 20 years ago, the average worker switched screens about every two and a half minutes or so. [33:18] And then by about 2012, it was 75 seconds. But later on, it was down to about 45 seconds. And that's [33:26] where it stuck. So we switched screens about every 45 seconds. And that turns out to be incredibly [33:32] stressful. Like you can measure this in our immune systems, in our heart rate variability, [33:37] that the more often we're switching, the higher our stress level is at the end of the day. And the [33:42] worse we are at the various tasks. Because multitasking, it turns out, is not actually possible. [33:46] It's actually your brain dropping one set of rules, essentially, and having to activate another. [33:52] But there's a residue left on the brain. As Dr. Mark describes it, your brain is like a whiteboard. [33:57] And when you switch from one thing to another, you erase the whiteboard, but a residue stays on there. [34:02] And so the more times you do it during the course of the day, the more residue there is, [34:05] and the harder it is for you to focus on any one particular thing. And so what are some of the [34:10] recommendations? Well, first of all, batching your tasks. Dr. Mark found that people check email on [34:16] average about 77 distinct times per day. And that's a lot of multitasking. That's separate [34:21] checks. That's not numbers of emails. And so instead, you want to batch that email if you can. [34:26] So you're doing a certain task at a certain time. Instead of toggling between many within one hour, [34:32] maybe one hour is for email and the next hour is for something else so that you're not mixing [34:36] them all together. And I would be really wary about starting your day in your inbox. I know that's [34:41] the first instinct is to go check what's there, but you want to be wary of something called the [34:46] Zygarnik effect, which is this psychological effect that unfinished tasks leave an imprint [34:53] on your brain that takes some of your cognitive bandwidth until that loop is closed, until it's [34:58] finished. And because your inbox is probably a source of an unlimited number of unfinished things, [35:04] you might not want to be starting your day that way because you'll already be using up some of that [35:09] cognitive bandwidth that you might want to focus for other projects. Doesn't mean you can't do [35:12] your email, but maybe shift it after you've done some of whatever the most important task for the [35:17] day is. Another is that as you're multitasking, attention is like a bucket and you want to take [35:23] breaks before that bucket overflows or else it takes more time to recover. Maybe the thing that [35:29] scared me the most in all of the research that I did for this book was Gloria Mark's research on [35:34] self-interruption. That means thoughts that interrupt you when you're trying to focus. And what she [35:39] found was that we become accustomed to a certain level of distractions. Let's say that's notifications [35:45] from your phone or messages popping up or other people interrupting you. Eventually, as if you have [35:51] some kind of internal distractometer, you become accustomed to that rhythm. And then if you put away [35:58] all those distractions and silence your notifications and say, now I'm going to focus, you will simply [36:03] self-interrupt with intrusive thoughts at the same rate to which you've become accustomed. So you will [36:09] not be able to say, now I'm just going to focus. You will continue to interrupt yourself at that [36:15] customary rhythm. If you're not structuring your focus, then it will be co-opted. And this is why [36:20] it shows in studies of cognitive tests where if people have a phone visible, even if it's off, [36:25] even if they can't use it or touch it, if it's visible, it decreases their performance on the [36:30] cognitive task. And the more phone dependent they are, the bigger that effect. So start by trying to put [36:35] it out of the room when you really have to focus, but try to alter your cadence of interruptions so [36:41] that you can train your ability to focus for at least a half hour and an hour at a time here and [36:46] there. And finally, do something called cognitive outsourcing. Put a notebook or a pad on your desk [36:53] next to you. And when some intrusive thought pops up about what you should be checking or what you [36:58] didn't respond to, write it down. That's called cognitive outsourcing. And it takes that intrusive [37:02] thought out of your brain, puts it somewhere else, and improves your ability to focus on the task at hand. [37:07] I think one of the big challenges with modern work is that it can become so amorphous, [37:11] especially if some of the time you work from home, that it can kind of fill every gap in your life. [37:16] And that's not really great for your productivity or your mental well-being. And so we should set up [37:20] structures around our work, both seasons, humans are built for seasonality, not doing the same thing [37:27] every season, and for cycling between times of hard work and times of rest. As the music producer, [37:33] Rick Rubin has noted, discipline and ritual is actually the structure that then allows people [37:39] to do their best creative work. That they don't want to be totally free in the rest of their life. [37:43] They want to be free within that box of discipline and ritual that liberates them to create. And so one [37:49] of the examples of this I love was the time I spent with the writer Isabel Allende, who is one of the [37:56] best-selling writers in history. She's produced a best-selling book about every year and a half for the last [38:01] 40 years, 80 million copies in all. When she's written about, like in magazine features, because [38:07] she has magical realism in some of her writing, she's written about often as if she is like a medium [38:12] who's just, these spirits are speaking through her. And because her first book was called The House [38:17] of the Spirits. But in reality, when I spent time with her, she thrives on this rigid ritual and [38:25] structure and rhythm. She starts every single book on January 8th. And one of the reasons she does [38:31] that is because then everyone in her life knows that they better get what they need from her by [38:35] January 7th, because then she's going to be out of touch. She goes into a room where she feels her [38:40] story lives. She keeps it austere, so there's not a lot of distractions. She lights a candle to start her [38:46] workday. She blows it out at the end of the workday to signal the end of the day, the turning off of her [38:51] brain. She closes the door. She doesn't come back in until she starts the next day. And she always comes back [38:57] on January 8th, even when she went through a personal tragedy with the death of her daughter [39:01] at a young age. And she said, I don't know if I ever write again. I lost the muse. I didn't have [39:06] the inspiration. But January 8th rolled around, and she said, well, I have to try because my ritual's [39:11] coming up. And she did it again and got going again and wrote more bestsellers. As she told me, [39:17] without this structure and this rhythm, I could not do it. So from the outside, it seems that her [39:24] creation is this story of boundless creativity. But really, it's one of boundaries that channel [39:30] her focus, that give her life seasonality and ritual, that keep bringing her back and back and [39:35] back and back again and empower her creativity rather than stifling it. I myself, as an independent [39:41] writer in the 21st century, have also had this experience of living with more freedom and autonomy [39:47] than almost anyone in history. But then I've had the experience of going back and putting some [39:52] constraints in my life and place and those making me thrive in a way that total freedom [39:57] absolutely did not. When I started working on Range, I was working as an investigative reporter [40:02] also at ProPublica. But toward the end of the book, I left that job because I wasn't going to be able [40:07] to finish the book. I was thinking I'd go back. But then the book kind of took on a life of its own [40:12] and I went on my own. And that was a dream in many ways, because for years, it had been my goal [40:18] to get complete autonomy as a professional, to be able to spend every minute of my day [40:24] in the manner of my own choosing. And so that's what I did. I had total freedom. Fast forward about [40:29] two years of that, and I realized there is absolutely such a thing as too much autonomy. [40:35] My life became so atomized. I had a million different competing priorities and I had no real ritual. So my [40:44] workday expanded to fit every moment that it possibly could. I had no real seasonality [40:48] in my life. I had no structure. I had no rhythm. And I wasn't really syncing up with other people [40:54] either. And I realized instead of doing that, I actually needed to prioritize ruthlessly and focus [41:01] on a smaller number of things, have a workday that started and ended at a certain time, have certain [41:08] seasonality to my projects. I needed grounding in my community. So I joined the board of a nonprofit [41:14] in my community, an early childhood education center that served families in need. I started [41:20] going to a shuffle dance, meetups and classes so that I could have embodied experience with [41:25] strangers on a regular basis. So that I'm having this embodied experience with strangers that I [41:30] want instead of living totally unto myself. Chapter five, the myth of the lone genius. [41:42] So in most history books or books about innovation, individual innovations tend to be identified with [41:48] individual creators or inventors. And I think part of that is because it makes the story tidy, [41:53] right? It's easy to link. And also often because one individual wins what science historians call [41:59] a priority dispute. Like they fight to be the person who's remembered in the history books. [42:03] But it actually is not a good representation of how innovation really happens. The real story is one [42:12] of what science historians call multiple discovery. Multiple discovery is a term popularized by [42:19] Robert Merton, who was kind of the founder of the sociology of science. And what he noticed was that [42:25] most world-changing breakthroughs are arrived at by multiple people in almost the same way at almost [42:32] the same time, even though those people are working independently. And he found that this was the norm [42:37] with world-changing breakthroughs, not the exception. The light bulb, the telephone, Alexander Graham [42:43] Bell and Elisha Gray actually filed with the patent office on the same day for the telephone. The [42:48] microphone, the camera, the jet engine, the transistor, all of these things, even though they're often [42:54] identified with one individual when the story is told, multiple people who were not working together [43:00] were arriving at them at the same time. And what that tells us about the history of innovation [43:07] innovation is that we've actually overvalued and overprioritized the narrative of the lone genius [43:12] working on their own and breaking through in a way that nobody else ever has. Because if you look [43:17] at the actual history, there are lots of people converging on a solution. So it tells a completely [43:23] different story, that there are these boundaries that are being set up and channeling people toward [43:27] a breakthrough. Not that those geniuses aren't important, but that the context that's pushing them [43:34] toward a certain problem, defining a certain problem and putting it in frame is more important [43:40] than any individual mind. Let's walk through three examples of that. Demetri Mendelea was a Siberian [43:47] genius chemist. And the story that's told about him is that in the winter of 1869, he was trying to find an [43:55] order to all of the elements, the chemical building blocks of the universe, and that he thought there had [44:00] to be some order, but he just couldn't find it. There had to be some method to nature's prodigious [44:05] madness. So he famously spends three days, three sleepless days working to try to order the elements [44:12] until he can't stay awake any longer. He tips forward, his unruly beard folds into his arms, [44:18] and he falls asleep and drifts off into the most impactful nap in human history. And in that nap, [44:24] he sees the elements whirling and dancing around him until they snap into columns. And then the columns [44:30] snap together to form a grid. And as you move across the grid, the properties of elements repeat [44:36] predictably and periodically, hence the name periodic table. So supposedly Mendelea wakes up and writes it [44:43] down as a finished system. That's the periodic table. That story is beautiful. The Royal Society [44:50] celebrated it. The mattress company Casper used it in their marketing. Matthew Walker, in his blockbuster [44:56] Why We Sleep, touted it as the ultimate proof of our dreaming brain, loosed from the bounds of reality. [45:02] It's a beautiful story. It is also utterly false. That did not happen. And the problem with that [45:08] telling is that it obscures the real secret to Mendeleev's success. Mendeleev had a publishing [45:14] contract for a two-volume introduction to chemistry textbook. He had only gotten eight of the then 63 [45:21] known elements into volume one. So he had to get the other 55 into volume two. And he had to do it in a [45:28] way that made sense to his customers, which were intro chemistry students. So he was not even looking for a [45:33] fundamental law of nature. He was experimenting with a way to save space in his textbook. And so [45:39] he realized he would have to start describing families of elements together in order to fit [45:44] in the space he had allotted. And it was in doing that as he started sorting elements into families [45:48] with similarities that he noticed the periodic pattern. He was a genius. He's the one that's [45:53] credited in history books, but he wasn't the only one, not even close. In fact, there were zero [45:58] periodic tables before 1860. And then there were six in the next eight years, all of which had the [46:06] general idea. Mendeleev's had some advantages, but all of them got the periodic pattern. Why would that [46:11] happen? Well, in 1860, there's a meeting in Karlsruhe, a chemistry conference that's called for about a [46:18] little more than 100 people because they want to agree on some standards for chemistry. Everyone [46:23] is doing things differently. People are using chemical notation differently. They're weighing [46:28] elements differently, all these different things, which means that work can't communicate across [46:32] space because people aren't working the same standards. And at that meeting, an Italian named [46:37] Stanislao Canizzaro says basically, here's how we're all going to measure the weight of elements from now [46:43] on. And he passes out a pamphlet that says, here are the weights. He got some of them wrong, [46:47] but that doesn't matter. And here's how we're going to measure them going forward. [46:51] And that instantly allowed work in different labs across the world to communicate across space, [46:57] because now people could compare their work to others and understand what others were doing. [47:02] If you go back and look at the history of innovation, that's often the case that setting [47:05] standards essentially expands the problem solving team because it allows work to communicate across [47:13] space. So it's not very sexy, but it is very often a precursor for breakthrough. [47:18] The famous story of Einstein coming up with special relativity involves his thought experiment where [47:23] he's riding a beam of light. And it's a beautiful story, but Einstein didn't tell it until decades [47:29] after it supposedly happened. It's really unclear if that truly influenced him at the time or if it was [47:35] really useful at all. What we know really influenced Einstein was a much more quotidian, [47:41] well-defined problem that a bunch of scientists had framed and put into the open for solution. [47:47] And that was called the magnet and wire problem. Essentially, it involved moving a magnet and a wire [47:53] past one another to induce an electrical current. And the problem was the science explained it [47:59] differently depending on which one was moving. And Einstein didn't like that. He said, why should the laws [48:05] of physics be different depending on if the magnet is moving past the wire or the wire is moving past the [48:09] magnet? And what he ultimately realized is that the laws of physics didn't have to be different. Our [48:14] conception of time and space had to change. And that's the reality of this breakthrough was that [48:20] other scientists framing a specific problem that he could think about led him to something [48:25] groundbreaking. It wasn't the freedom of this thought experiment. It was this well-defined problem. [48:30] And that's very often the case in the history of innovation, that someone just defines a problem [48:35] really well. And that draws a bounding box for people's creative thinking. We think of Darwin [48:42] away on this boat on the Beagle, away from other academics, away from other researchers, totally free [48:48] to think and create. And that's how he makes this breakthrough that changes the world. But in fact, [48:52] he was totally enmeshed in the thinking of his day. Darwin was not so much a creator as he was a synthesizer. [49:00] He was really taking work that already existed and combining it in new ways. There were all these [49:04] questions that his peers were laying out in a really well-defined way. Things like, [49:10] why are we finding marine fossils on the top of mountains? Why do the bones in the flipper of [49:16] a whale and the wing of a bat and the arm of a human have so much in common? Why are we finding [49:22] fossils of animals that don't exist on Earth anymore? If everything was created in a small amount of time, [49:30] we shouldn't be seeing those things. In fact, Darwin would correspond with breeders and gardeners. [49:35] He had about 240 pen pals that he would pepper for information. And he learned that breeders [49:40] already had a name for spontaneous traits that are passed down from one animal to another. They [49:46] called them sports. So Darwin was really taking all this knowledge accumulated in his day and these [49:52] questions that had come up and synthesizing them into one coherent whole. And that was much more [49:58] his breakthrough than a single creative leap. It was synthesizing the things that were available [50:03] and applying them to the questions that other peers around him were posing. [50:08] As groundbreaking as Darwin's ideas were, Alfred Russell Wallace came up with basically the exact [50:14] same things at the exact same time. In fact, when he sent some of his writing to Darwin, [50:19] Darwin wrote to his mentor and said, I have never seen a crazier coincidence, basically. And he said, [50:24] everything I've written is going to be out before I publish it because it was so similar. And there was [50:28] one commonality between these two men, which is they had both read the same essay by Thomas Malthus, [50:34] his essay on population, where he argued that humanity would always reach a crisis point because [50:42] the population would expand faster than the food supply could expand to meet it. And so we would [50:48] always grow and grow and grow and then have a crash because resources wouldn't keep up with population [50:52] growth. Now, Malthus turned out to be right for some of human history, but wrong going forward. But it [50:58] didn't matter that he was wrong. He framed this problem in a way that made both Wallace and Darwin, [51:05] who read it at about the same time, think about how must species in nature respond to this if they [51:12] start to outgrow the available food supply. And the answer was they die out and there's competition [51:19] for limited resources. And they both reading that essay, which even though it was wrong about the [51:24] future of humanity, defined a problem so well that they both said it was almost like a light bulb going [51:30] on where all their past work was channeled into a specific problem. Malthus was what I like to call [51:35] a problem setter. I think of setter like the person who sets the ball on a volleyball team for the [51:40] subsequent spike, which would be Darwin and Wallace in this case. And when I was going through the history [51:45] of creative breakthrough, problem setters don't get a lot of the fame and attention, [51:50] but they're always there just before a breakthrough, someone who defines a problem really well. [51:56] Sometimes they are wrong about what they think their own solution is to it, but they're always [52:02] defining it really well. One of the great examples was David Hilbert, who's arguably [52:06] the most influential mathematician of the 20th century. And around the turn of the 20th century, [52:11] what he decided to do was basically make a list, go survey all the mathematics of the day, make a list [52:18] of about two dozen problems that he thought were important, define them really well, like really [52:23] home in on what should the definition of this problem be. He wrote them out in a pamphlet and he [52:29] passed them out at a meeting to his colleagues. And it set an agenda for math in the 20th century, [52:34] and most of those problems went on to be solved. As brilliant of a mathematician as he was, [52:39] and he's one of the most brilliant who ever lived, it's widely acknowledged that his biggest influence [52:44] was collecting a set of problems, defining them really clearly. And it set an agenda for everything [52:50] that came since. So that's a, that's kind of an extreme example. But everywhere in history, [52:54] when you see creative breakthrough, you see someone just before who defines the problem really [53:00] narrowly and that draw, that attracts other minds to the problem. The title of one of my favorite [53:06] scientific papers I read while working on this book was called Wrong But Seminal. And it went through a [53:12] history of scientific papers where someone would come up with something really intriguing, but that [53:17] was wrong. But because it would lead them to define some certain problem or challenge, it would instantly [53:23] draw all these other minds to that well-defined problem. And that would typically lead to some Nobel [53:29] level breakthrough. So these were problem setters who may have been wrong about their own solution, [53:33] but they defined a problem so well that it empowered other people to start working in a productive way. [53:39] Problem defining is a skill that's open to a huge number of people and incredibly important. And [53:44] some of that can be as simple as going out and doing research and characterizing a problem, right? Like [53:49] this is the best of market research. You go out and you see some problem, you observe people in their [53:53] work world, you try to figure out some problem that they're all orbiting and then define it for them. [53:59] There's one example I loved of this, actually. There's an engineer named Jayshree Seth. She worked [54:05] at the company 3M and she's won the Society of Women Engineers Lifetime Achievement Award, you know, [54:11] one of the highest awards you can win. And she described her process as mosaic building. What she [54:17] would do is she would go around to colleagues, to other inventors, kind of interview them about their [54:21] work, look at their work, try to figure out what problem did she think their work might solve. And then when [54:26] she would detect a common problem among a bunch of different people who are working apart from each [54:31] other, she would get them in a room together and then pitch them and say, here's the problem that [54:37] I think you're all orbiting. And she would try to define that problem and say, that's why we should [54:42] all work on it. So I think some of it is just finding out what people are doing and trying to as [54:49] narrowly as possible define what problem it might solve and being really specific about it. So there's [54:55] some research in the new book about what's called specific curiosity, which is when you are not just [55:01] kind of roaming, but taking on a certain question that intrigues you and going down a rabbit hole [55:07] on that. And when you're going down those rabbit holes, just looking for some really specific [55:13] curiosity that you can well define and even write out and refine and pitch to someone that can really [55:20] prompt other people's creative engines. There are other businesses like Tony Fidel, who was the lead [55:26] designer of the iPod, and he then went on to co-found the smart thermostat company, Nest. [55:30] And he's obsessed with constraints. And so one of the things he made the team at Nest do was he made [55:35] them work inside of a literal box, right? He made them prototype the packaging before they had a [55:40] product because he said, only things that fit on this package will convey what problem we are solving [55:46] to the customer who sees it. So get on this box the features that tell the customer what problem of [55:54] yours are we solving? So he was always using these exercises to try to force a team to define the [55:59] problem they were solving. I think he mentors entrepreneurs now. And his biggest piece of [56:03] advice is that they should write the press release for what they're doing before they start doing it. [56:08] And it's really just an exercise that's getting them to try to force them to define the problem [56:14] they think they'll be solving before they start working. I think problem setting or this problem [56:18] definition is a really undervalued skill. There's this one famous saying that people don't want a [56:25] quarter inch drill. They want a quarter inch hole in the wall. And what it means is when you're trying [56:29] to give people a product or service, instead of giving them the thing, you should understand what is [56:33] the problem they actually need solved. And then you can figure out various ways to attack it. And I [56:38] don't think we spend enough time doing this, right? We much more think about coming up with ideas [56:43] as opposed to coming up with problems. Let me give you an example. General Magic had lots of [56:48] third-party app developers because they were creating the App Store before the App Store. And [56:53] one of those third-party app developers was named Jeff Hawkins. And Hawkins had created an [56:58] app for the General Magic operating system called Graffiti. And what Graffiti did was if you took a [57:03] stylus and made some strokes on a screen, it would translate that into letters. When it became clear [57:10] that General Magic was going to fail, Hawkins took Graffiti and created his own device. It had three [57:17] functions, calendar, contacts, memo pad. General Magic had all that and a million things more. [57:24] What Hawkins did was he identified a clear customer problem. This was busy professionals [57:29] wanting to sync their calendars and contacts and take them on the go. And he did three of the million [57:36] things that General Magic did, but put them into a coherent device that showed the users why and how it was [57:43] going to solve their problem. And that was the Palm Pilot. And it became a smash hit in the same era [57:48] as General Magic. Demis Sasabas, who was a founder of Google DeepMind and recently won the Nobel Prize [57:55] in Chemistry, even though he's not a chemist, said recently that the most important skill now, which is [58:01] becoming even more important in the age of AI, is defining a good problem. Finding a good problem and [58:07] defining it really well. Because with the tools we have and the brains we have, it's making that [58:13] definition narrow enough that you really channel thinking. And I think that's a skill that's only [58:18] going to become more important, but it doesn't feel like creation. And so we often overlook it. [58:23] This importance of making boundaries around the problem that's trying to be solved. And if you look [58:28] at the history of innovation, what the science historian James Burke called the jigsaw of invention, [58:35] you can see one well-defined problem passing to the next in kind of a relay race of invention [58:42] that leads to things that change the world. In Burke's own work, he had a TV show called Connections. [58:47] And one of my favorite episodes was where he draws a line from one narrow problem to another that goes [58:53] from medieval castle battlements all the way to film projectors. Medieval battlements were shaped a [59:00] certain way in order to get rid of visual blind spots so that you could see who was attacking you. [59:06] And when they got rid of those visual blind spots, that meant that people firing cannons had to move [59:10] farther away, basically. And when they moved farther away, they needed to see farther to where they were [59:14] going to shoot. And eventually it led to film projectors. It wasn't just some giant leap, but it [59:20] was one tightly defined problem after another. And that is kind of the march of innovation. It's not [59:27] single lone geniuses who just break away from everything in the past. It's much more one problem after [59:33] another. And the philosopher of science Thomas Kuhn wrote a famous book called The Structure of [59:39] Scientific Revolutions, in which he talked about paradigm shifts, where some creator would come up [59:44] with something that was so different than what came before, they would essentially leave people on either [59:50] side of this break speaking different languages, like they couldn't even understand one another. [59:54] And so that did feel like it's this lone genius breaking through in a way that changes everything. [59:59] And that became very famous, that term paradigm shift. It sped through politics and business and [1:00:04] everything. But later on, Kuhn was working on a book that he didn't finish by the time he died, [1:00:08] but a few years ago it was just published. And in that book, he takes a very different tack, [1:00:14] and he talks about the evolutionary nature of discovery. And the subtitle of the book, [1:00:19] I think, speaks for itself, An Evolutionary Theory of Scientific Development. [1:00:23] He had nuanced that view of the paradigm shift into one of successive narrow problems that are [1:00:29] solved one after another and that lead to breakthrough. Of course, that work of his [1:00:33] didn't get as famous because it's not as sexy as the whole paradigm shift thing. But the history of [1:00:37] innovation really is one narrowly defined problem after another. And I think we should all try to do [1:00:42] that. And whatever we're working on, what is the most succinct way that I can define the problem [1:00:47] that I'm trying to work on? Want to support the channel? 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