Clearer Thinking: The Poker Player’s Guide to Productivity
Spencer Greenberg speaks with Chris Sparks about the development of feedback systems for productivity, pattern recognition and free will, perspectives on risk, and optimization for opportunity recognition.
Audio recording below (1h26m). Resources mentioned and full transcript following.
Resources mentioned:
Podcast Transcript
[Note: transcript edited slightly for clarity.]
Josh: Hello, and welcome to Clearer Thinking With Spencer Greenberg, the podcast about ideas that matter. I'm Josh Castle, the producer of the podcast, and I'm so glad you joined us today. In this episode, Spencer speaks with Chris Sparks about the development of feedback systems for productivity, pattern recognition and free will, perspectives on risk, and optimization for opportunity recognition.
Spencer: Chris, welcome. I'm really glad to have you here.
Chris: Thanks, Spencer. I'm really looking forward to this.
Spencer: One thing I'm really interested in talking to you about is your experience with poker and what you've learned from it. Can you tell us a little bit about your background with poker?
Chris: Yeah. So, where to begin? So there was an event we call kind of the "Moneymaker Boom," back in the early first half of the 2000s, where all of a sudden poker was on ESPN all the time, and there's this invention called Hole Card Cam where poker comes out of back rooms, becomes a celebrity spectator sport, and fortunately, circumstances aligned that I was paddling before the wave came. I happened to be a freshman in college. I was 2004, Ohio State, and you know, what do you do if you are a not-quite-twenty-one freshman at the dorms hanging out with a bunch of guys? We just played poker all the time. And I came from a little bit of a gaming background. I was the best player in the world at a small game called Microsoft Ants, which was an early precursor to the Starcraft/Age of Empires type games, which I'm decent at, but not quite the level of guys playing in stadiums these days.
And it was kind of a natural progression for me to move from Ants to—I became world-class in Gin, achieved a perfect rating in the Gin equivalent of ELO, and some of my Gin friends said, "Hey, there's this game called poker, you can also play online, but people are actually making money at it." That just blew my mind. "Hey, I'm a sixteen-year-old, and I can play a video game and make money." And so I started off pretty innocently playing large freeroll. So, free tournaments on my parents' dial-up internet in my dining room, to by the time I'm seventeen, I start college, I already have some experience under my belt. Start playing underground games at the fraternity houses, and some of the other players who I didn't think were particularly good started playing on a site called Party Poker and making pretty decent money. You know, the bar's pretty low when you're in college. This is beer money-type territory.
I immediately have a knack for it. Fast forward, we get to like Junior, Senior year, I've paid off my college tuition, I'm really doing exceptionally well. I have this, let's say, fortunate-unfortunate experience where—you know, I really wanted to make television commercials for a living. I was that really annoying overambitious corporate kid in college, and my management-track role, working in brand advertising for Team Detroit in Ford's advertising agency, falls through, and the auto industry collapsed along with the economy collapse, the great financial crisis of 2008 when I graduated. So I find myself kind of in hiring purgatory in Detroit where I didn't know anyone, and so the thing that I was spending ten to twenty hours a week on, usually foregoing sleep or classes to play poker—all the sudden I had no responsibilities, and I decided to dedicate myself to it full-time. As poker became an eighty-hour per week activity, it took me about a year and a half before I was playing in the biggest games in the world against the toughest competition.
That was about from 2008 to 2011—when there was an event called Black Friday when online poker in the US got shut down. Another really interesting case study story. At that moment I was ranked in the top twenty in the world. So it's really a big part of the way I think about things. I think there are so many lessons that can be applied from poker to decision making to managing risk to understanding yourself to understanding complex systems. And it's a big part of the principles and the techniques that I work with for investors and executives today: essentially, what does it take to become world-class in something? How do you rise through the ranks and become someone who can show up every day ready to perform?
And you know, my experiences through sixteen years at this point of playing pretty high-level poker are a huge part of the way that I see that.
Spencer: That's awesome. So I wanna explore some of those learnings with you, but first I want to ask—so you were good at multiple different games. What do you think it is that makes you good at games?
Chris: You know, I'm pausing because I'm not quite sure. What comes to mind, that is a huge thread that ties all of my work together, is understanding human behavior, and trying to predict it (in essence). So these games were competitive, in that your skill is relative. And so there are two approaches. You can go after your own goals, or you can thwart the other person in achieving their goals. So in Microsoft Ants, it was, "Can I accumulate resources while also slowing down the accumulation of resources for my opponent?" For Gin, it's, "How can I get my opponent to give me the cards that I need and prevent him from getting the cards that he needs to make this hand?" In poker, it's very much, "How can I determine what my opponent is trying to get me to do and do the opposite?" And so there is an understanding of what someone else is going to do before they do it.
One of my favorite decision-making models is called the OODA Loop, and one of the coolest parts about the OODA Loop is that if you are reorienting to new realities faster than your opponent, then you get inside of their loop: they are acting upon an outdated model of the world, and they expect you to be in one place, but you've already moved on to the next.
Spencer: Can you define the OODA Loop, just so people understand what that means?
Chris: Sure. So it comes from a fighter pilot named John Boyd. He was essentially looking at, "Hey, how do two pilots who are operating with similar machinery having an aerial fight in the sky, how do some pilots have exceptional records where they win, you know, hundreds of these battles without a loss, where you'd assume the base rate is about a fifty/fifty chance?" He realized that that common skill was the ability to reorient to the environment faster. So, essentially taking into account new information and using that to adjust faster than your opponent. So that being the critical skill: one, having a better model of reality, and two, adjusting that model in a faster and more accurate fashion than your opponent. OODA stands for "Observe, Orient, Decide, Act." These are discreet steps that one goes through while making any decision, whether it's crossing the street or investment or playing a poker hand. With each step in this decision-making process, one is receiving feedback from the environment, and just like any feedback loop, incorporating that feedback into the models, into observations, what you see and what you look for, into the way decisions are made, as well as ultimately the actions that are taken.
Spencer: So can you walk me through an OODA Loop applied to let's say a poker hand, or to another game?
Chris: Sure. So, super simplistic poker example: in essence, poker is someone is paying you off when you have a better hand than they do. So, you know, the most expensive hand to have is the second-best one. A good hand, but not a great hand. And a lot of this meta-game, or the game inside of the game, is you are applying pressure to opponents in that you are forcing them to make difficult decisions, the expectation being that the more difficult decisions someone is put into, the more likely they are to make a mistake. And so a common tactic is you keep the aggression on, you keep doing what I call a half-bluff, where you do something where you don't show them your hand, but you are putting them into a difficult decision. And at a certain point, they are going to break and play back against you, do something as a counter-aggressive tactic.
The trick, where the OODA Loop comes into play, is that first you are observing their reaction to your actions, knowing what to look for, and you are reorienting to that based on what you know about this opponent and your history with them. Some opponents I've been playing with for years. Where that breaking point is, not only in a general sense, but on today, what is their current mental state, in this moment? And then I am deciding, "At which point can I anticipate that they are going to make a move?" Once they're making a move I want my aggressive action to be with a hand, rather than with a bluff. So I am anticipating that they are going to try to make a move against me, and so I want to have the hand before they react. And so it's punch, punch, punch, counter-punch type of thing. The action is I take my foot off the gas right as they're anticipating, "Hey, this guy's bullying me, he's trying to pick on me."
And then that whole scenario works in reverse, where I am playing with the expectations that they have of my actions. I'm getting inside of their loop by I want to be bluffing the times that they think I can't be bluffing, and as soon as they've had enough of me and they say that they have to take a stand, that's where I want to have the better hand.
Spencer: That's cool. So, I do very amateur mixed martial arts just for fun, and what this reminds me of is this idea that you're kind of trying to train your opponent. So let's say you do a low leg kick. And you kind of hit their leg. It doesn't hurt them that much, but it's kind of annoying. And then you do another low leg kick, and then you do another low leg kick, and then you've kind of trained them to expect these low leg kicks on certain timing, and suddenly now they're kind of anticipating it, and that means that they're moving to block your leg kick, and now that you can predict that they're going to go to block your leg kick you can actually use that to your advantage by faking a low leg kick and then maybe doing something else, where they are now trained to expect it. So does that kind of relate to this idea that you're talking about?
Chris: Absolutely. And as you say that, I realized you had my answer of what makes me particularly good at games. I think it's that I have out-sized ability for pattern recognition, and what you describe as creating a pattern that you say, in this case, lulls an opponent into habitual behavior, and then disrupting that pattern once it's been established to your advantage. So you know, a lot of these games are establishing patterns, but there's a false pattern. Right? There's an over-extrapolation based on past behavior where they only see the tactics but they don't understand the strategy underneath, and that’s a key skill to all games: both recognizing the patterns and knowing when to extrapolate them and when to rely on the more fingertip-feel dynamic meta-game approach.
And I think this is a huge part of why I find—I really don't even understand it, sometimes, kind of my savant abilities to recognize core beliefs or behaviors that are holding my clients back. My assumption is that a lot of our behavior is pretty deterministic, in the sense that what we do, what we think, is determined by the context that we find ourselves in. In essence, that we are pattern-driven creatures. A lot of what I do with clients is to uncover some of these invisible patterns and then find ways to disrupt those patterns, either by altering the context that they put themselves in or by changing the narrative or habitual response to those contexts.
Spencer: Yeah, it's interesting. If you take a sort of outside view on your own behavior and you start to notice, "Oh, whenever I'm in situation X, I do behavior Y," right? "Whenever there are cookies on the counter I always eat them," for example. Then that gives you the ability to start realizing that you kind of are this pattern response system, and that means that you can start to learn to disrupt your responses by disrupting the patterns, and say, "Oh, well, if I don't leave the cookies on the counter then I'm not gonna eat cookies so often." And it also brings up this kind of thinking that I find super interesting, which is: imagine you're walking in the kitchen and you see the cookies, right? Well, you can now have this kind of reasoning that's like, "Well, if right now I grab a cookie and eat it, then probably I'm going to be the sort of person that always grabs a cookie and eats it in a sufficiently similar situation. And so if I can resist the cookie now, then that means I'm the sort of person that in this kind of situation won't eat the cookie, and I can project that forward in the future."
And I actually find that as a helpful trick to motivate myself to take action, because I'm not really just deciding based on this one moment, I'm deciding on how I'm going to behave in all situations that are sufficiently similar to this one.
Chris: Oh man, I love that so much. It's like every decision we make echoes into eternity. Everything that we do makes it more likely we will do that thing in the future. So it's not that—you know, eating a cookie today is basically zero cost. It's not a positive expected value, but it doesn't really matter all that much. Where the true cost is is that I'm reinforcing this behavior of trigger happens: "Hey, I'm bored, I'm a little bit hungry," I walk into the kitchen and see the pantry, I see the cookie, and in response, I eat a cookie. And thus you are digging a deeper hole. Imagine a river carving out the Grand Canyon. You've carved out a little bit more rock, that every time you are in a similar context, Cookie Action happens. And so that's a way to take control and exercise your free will: to think, "Hey, is this the decision that I want to be echoing into eternity? Do I want to be making a similar decision all the time in the future?"
And I think that's a really cool way to shift into a curiosity mindset, understanding that your decisions have consequences and being curious. "Hey, if I do the thing that maybe I wouldn't normally do, what are the second-order effects of that? What happens next?" It's cool, and it's a way that I describe viewing your life as an experiment. I mean, that's the workbook that I created—Experiment Without Limits—a lot of these limits that we place on ourselves are that we're afraid to just try things and see what happens. And so the approach that you describe of like, "Hey, I'm gonna just increase this gap." Right? A lot of meditation is just increasing the gap between stimulus and response. "Hey, wait a second. Like, if I eat this cookie, what else is going to be true? What path on the decision tree does this put me on? Is that a path that I want to be on?" Where it's not the initial decision itself that's costly, it's that you've put yourself on a different branch of the tree, and all of these branching alternate realities are going to be not quite as good as the branches where you don't eat that cookie.
Spencer: Yeah, exactly. It also reminds me of the distinction between action and policy, where an action is something you're doing in a particular moment in time, and a policy is a choice about how you decide that you're going to carry out in the future. And I think that thinking in terms of actions versus policies can be really useful, especially when it comes to risk. So, for example, the action of going skydiving is actually not that dangerous. Like yeah, sure, it's much more dangerous than walking to the store, but it's not that dangerous to go skydiving one time. But the policy of going skydiving every single weekend, that's way more dangerous than the action of going skydiving once, because now you're compounding that risk every single weekend. And at first approximation, if you're taking a small risk and you're doing it ten times, that's about ten times more dangerous than doing it once, and if you're doing it a hundred time, like every single weekend for a long time, then that's going to be a hundred times more risky. And so when there's an action, you can take on a lot more risk than when there's a policy. With policies, you have to be really risk-averse, because if you take a risky policy, it's gonna compound and eventually destroy you. Any reactions to that?
Chris: That's really cool, and I hadn't heard that framed before in terms of policies, where, yeah. I think it could be principle, it could be rules, could be defaults, guard-rails. There's a lot of different ways to think about it, but that their impact in protecting us from out-sized risks is multiplied by the frequency that we are in those situations, and so something that in a vacuum (as you said) is not that big a deal—I mean, skydiving is pretty safe compared to hopping in your car and driving to the supermarket, if you think about it on a base-rate basis. The issue is that if there is not an examination of how do I make decisions about this type of stuff (what do I value, what are the trade-offs that I'm willing to make) it's easy to multiply out a small risk across many different actions, and thus something that's relatively innocuous can become quite costly.
This is the concept of the micromort that some of my friends make fun of me about, is like thinking about—so, a micromort is essentially a one-in-a-million chance of death. And a common one being, hey, driving is up into probably like the age of forty is the most dangerous thing that we can be doing. So for a long period of my time, you know, up until recently where I'm in a place where I needed a car, I tried to avoid driving or being in a car wherever possible, because you know, it's—inversion. Like, if this is my most likely way to die, I'd like to do that as little as possible. And so there's this really, really pervasive bias in society towards results, and everyone sees a result and we think, "Hey, this thing happened before that thing. Cause and effect." And we're so oriented towards, "Something bad happened. Okay, well I need to not do that again." Or, "Nothing bad happened. Okay. I can keep on doing that." Versus thinking from an expected value perspective.
This ties into a moral luck aspect as well. So, moral luck is like, "Hey, you can drive after drinking many times and nothing is going to happen, but it doesn't mean it's a good idea." Right? If you play that scenario out enough times, it's going to be a very costly scenario. And just thinking about, process-wise, what is my expectation taking this action, even if that expectation is not realized for a very long time?
In poker, this comes into play in that people have very wildly shifting standards of risk depending upon how they're doing in a particular session. Everyone in this room is familiar with risk aversion, but you know, until you've experienced it—"Hey, I'm down tens of thousands of dollars!”—and all of a sudden you become risk-seeking because that narrative becomes, "I want to restore this equilibrium that I've created." Or, "Oh, now I'm up tens of thousands of dollars and I'm God and everything I do turns to gold." And you start, you know, taking extra risks that you wouldn't normally do. Or, "Oh, I haven't seen a hand to play for hours." If you're playing live poker, you can literally sit there and fold hands for ten hours, correctly, because chance is lumpy. You can go a long time without getting a good hand. But the tendency is people have a hard time sitting on their hands on the sidelines. And so what becomes a very low-conviction play turns into a very high-conviction bet, in that people have a hard time sitting and watching the action. They need to get involved, and those standards for risk loosen over time. Our boredom is our greatest enemy.
And so this notion of a policy in poker is like, "Hey, these are the hands that I play. If I don't receive one of these hands, I don't play." And the more you can stick to a policy like that, with clearly-outlined exceptions, that's how you avoid changing your standards and making risks that you might not make if you were in a better decision-making state. It's how you inoculate yourself against taking risks when your decision-making is clouded.
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Spencer: I've heard that there's a cultural idea in some poker circles where if you're analyzing someone's situation together and saying, "Oh, I was in this game and here's the hand I got and here's what had been played," that there's kind of a taboo against saying how it actually turned out. Like, whether you won the hand or not, with the idea being that it's terrible to think about the outcome, because really what matters is given the information you had available, what was the optimal decision, and the fact of whether you actually won or not can be highly misleading and depends on actual luck. What do you think about that?
Chris: So, discussing a poker hand, it's only a scenario to examine the thought behind the decisions. The decisions themselves aren't as important as what was the rationale behind it, and those are the threads that you're trying to pull on, and just because there's this natural human tendency to, "Hey, this thing went well, how do I do more of that? This thing didn't go so well, how do I do less of that?" Just avoiding that tendency altogether and, "Hey, let's examine the thought process here," with the understanding that if we hone and iterate on this thought process, the score will take care of itself. Like, the results will play out over time. And you know, everyone can tell you about the big hands that they lost, but the hands that they won, those get glossed over no matter whether they got it in incredibly bad, as a low probability to win, or hey, they played it really well. All those get well together.
I’ve coached hundreds of poker players—you know, players who were extremely high-level professionals but still had a lot of lapses in the way that they thought about this, and so the really annoying question that I would ask when they described a poker hand is, "Why?" You know, "You're doing this thing, explain to me why you're doing it." Because you can take what looks like the right action for the wrong reason. Say you're trying to bet because you want this person to fold, and they end up calling but with a worse hand. And you win the pot, and you're like, "Oh, I won money." It's like, well, no. You thought he had a better hand. You wanted him to fold, and that's why you bet, so it was not a good bet, even if it worked out in your favor. And so, kind of just drilling down. It's the same thing as a coach. Why are you doing that? What's the reason behind that? What are you looking to accomplish? That is the source code for our behavior, is the thought behind the behavior. And if you can think about things the right way, the actions fall into place naturally.
As I said, the money that you receive—chips, business, et cetera—all that stuff takes care of itself if you can nail down that thought process behind the decision.
Spencer: I think this is often really hard for people in life when something goes really badly to actually think, "No, you know what, given the information I had and the information I could've easily acquired, that was actually the correct decision, and the fact that it went really badly—Okay, maybe you know, if I made a mistake, maybe I have a moral obligation to try to fix things, but it doesn't mean that I actually did anything wrong.” And I think that's really hard to really grasp on a deep level.
Chris: Yeah. So I think about decisions in a bookend context. So, some of you guys might be familiar with the notion of a premortem and a postmortem. You know, CFAR refers to this as like a Murphyjitsu. So the premortem—you know, think of this as like a decision journal: capturing my thoughts about the decision that I'm making. And so I might do this for a poker hand that I'm studying, might do this for a major life decision like, you know, which city do I want to move to or what's the next move going to be in my career, but what are all of the thoughts that I have about this and specifically what are the assumptions that are implicit to making this decision.
I’m trying to tease out what is the key or critical assumption that is driving my decision, and calibrating a conviction level there, from zero to a hundred percent. And the cool thing is once you put a number on that conviction level, you can think, "Hey, what new information would change that level of conviction?" This works in multiple ways. First, if you have extremely high conviction about something and it is, you know, the key assumption which is driving your decision, well maybe you need to pull on that thread a little bit of, are you maybe a little bit overconfident in this area? Is there a really cheap experiment that you can run that would make sure that your conviction level here is correct? Because if you're overconfident on this one assumption, then all the rest of this decision gets called into question.
And so this is both like how you make better decisions, by making these criteria explicit, but also by capturing the way that you're thinking about things afterward, after the decision has been made, and you have some data upon which to reorient to the world, thinking back to OODA Loop. You can look back at your thought process and say, "Hey, was there anything that I missed? Was there anything that I could have known at the time which would have helped me make a better decision? And you can do this afterward, like I said, as a postmortem: "All right, I'm gonna be facing a similar situation in the future. What can I do next time for this to go better?" But the real quick version, like I said, is this Murphyjitsu, which is almost this mental time travel: you're simulating the decision after you've already made it and saying, "Let's assume that I've made the wrong decision here and this just goes completely wrong. What are some of the reasons why that could be the case?"
Spencer: Just to clarify, you do that prior to anything going wrong. Trying to say, you know, like, "Let's assume that this is going to go wrong. What are my best guesses for why?" Right?
Chris: Exactly.
Spencer: So it's like a postmortem, but it's called a premortem because it's done before you've figured out what's actually happened.
Chris: Yes.
Spencer: Absolutely. So, one thing I wanted to ask you about, thinking in terms of Experiment Without Limits and connecting that to our discussion of risk, it seems to me that experimentation is just incredibly valuable, but at the same time, some experiments can go horribly wrong. And if we do a lot of them, and each one has, you know, a small chance of going wrong, that can accumulate into a lot of risk. So I tend to advise people to experiment a lot, but to focus mainly on low-risk experiments and only do high-risk experiments sparingly. What's your thought on that?
Chris: Yeah, I'm with you. And, like I said, when I think of an experiment, I'm thinking what's the fastest, cheapest in terms of resources way to validate my assumptions or to reduce my level of uncertainty about the path forward? And that this is the constant iterative process: what is the next action that I can do to gain conviction in my current direction? How do I further validate what I'm doing? And so for me, I want to have constant tiny experiments running, and I think where a lot of people go wrong is that they wait for too much certainty in order to make what they think of as a very large experiment. You know, a huge career move, a very big, different approach, a rewire of personality. Rather than thinking about something as a dichotomy—you know, "I try to build a hundred million dollar business or I sell all my possessions and travel the world"—thinking about, what is the tiny experiment that can be conducted in a very short time period? I say, max thirty days, ideally like seven days, which would give me more confidence in this direction?
And keeping that loop very tight—when I say "loop," I mean a feedback loop—you take an action, you receive feedback, and you reorient to the world, you incorporate that into your plan for the next experiment. The more of these experiments you can run, and the faster you can be running them, the faster you can be reorienting to what you actually want. And yeah, I do think that when you think about risky experiments, usually the biggest risk is the risk not taken. One of my favorite studies was they had people who were considering making a really massive decision in their lives flip a coin to see if they did it. And you know, obviously flipping a coin is completely random. But those who had flipped a coin that said "yes" and then made that major decision were far and beyond much happier that they had made that decision than not. We tend to wait far too long to do something.
Chuck Bezos, in one of the Amazon shareholder letters, talks about if you are waiting until you have more than seventy percent of the information, you've waited too long. That most decisions are, "Are we gonna have chicken for dinner, or are we gonna have steak for dinner?" They tend to be reversible, the costs tend not to be near as much as we think, and historically on average, we are much happier having made the change than not having made the change. And why I think this experimental framing is so powerful: if we're within the confines of an experiment, right, we've decided, "Hey, for this next month I'm going to try this thing." You know, whatever that thing is. Like, I'm gonna swing dance, I'm gonna intermittent fast, I'm gonna move towards learning this new programming language. Whatever it is, you decide for that next thirty days, "I am going to act as if I am a hundred percent confident in this direction unless I see this assumption invalidated, and my whole focus for this next month is gonna be invalidating that assumption. I'm gonna sprint towards that knowing that at the end of the thirty days I can stop and say, ‘I'm not going to do that anymore,’ or ‘oh, this is going great, how can I double down and do more?’"
I think most reflection dials back to this double-down or stop. This ability to sprint, knowing that you're going to have the opportunity to stop everything and completely course-correct, gets rid of all this existential angst, all of this self-sabotage, all of this doubt that prevents us from moving forward at maximum speed. This is the main way that I've found to solve for ensuring that we're always moving forward, is by always creating experiments.
Spencer: You mentioned briefly this idea of reversibility, and I think that's really key, when it comes to making a decision quickly. Basically, with many decisions in life you can easily reverse them. Right? You make a mistake, you're like, "Okay, I'm just not gonna do that anymore." But there are some decisions in life that are very hard to reverse. Like, for example, you know, if you leave your romantic partner you may never be able to get them back. Like, maybe you could, but maybe you can't, and maybe even if you tried it might have jeopardized your relationship and it might be much worse. Right? So, I think one key aspect there is, with decisions that are reversible you can make them much quicker, and maybe seventy percent of confidence in the outcome is enough.
Another aspect is what you might call the maximum plausible risk. So you know, there's always risk in anything we do. Right? We could walk to the store and a brick could fall off of the roof and kill us. Right? But that's not really a plausible risk. But if you think about, you know, investing half of all your life-long savings in an investment, that has very high potential risk. Like, if that went to zero that could very seriously affect your quality of life and your retirement. And so I think these two ideas of the reversibility or irreversibility, and sort of the maximum plausible risk you're taking, could help us determine the level of certainty we need. If something's not reversible, or there's a lot potentially at stake, then we want a higher level of confidence. Maybe we need ninety percent, maybe even ninety-five percent or higher. Whereas if it's quickly reversible and there's not actually that much at stake, then we can just do these rapid iterative experiments, and seventy percent confident might actually be optimal.
Chris: Yeah. I mean that's exactly right. I mean first, this is encapsulated by expected value, which is, how large is the upside multiplied by how often that happens plus how large is the downside and how often that happens.
Spencer: But that doesn't take into account the risk, though. I feel like the expected value and the risk are separate concepts.
Chris: It really depends. I mean sometimes it can be worthwhile to take a large risk if the gain is a multiplier of that. And obviously, you don't risk all of your chips. Right? You don't put everything at risk. But you keep in mind—and again, a lot of this is dependent on value. I mean, sometimes you want to value a small but closer to guaranteed win, sometimes you want to go for something that is a low chance of occurring but has very high convexity, very high upside. Other times, hey, you can take a big risk if the reward is worth it. So you know, gamblers use what's called the Kelly Criterion—this is very common in the investing world as well—to determine what is the acceptable bet size, how much can you risk based upon what your edge is. And the obvious thing being there, the larger your edge, right, the higher your expected value from this bet that you're placing, the more of your bankroll that you're able to place at risk.
And so there are scenarios, let's say that if someone offered me a bet today where, "Hey, we're gonna flip this coin heads or tails. If it's heads you give me everything that you own, all of your money, everything, if it's tails, I give you triple the worth of everything that you own." Right? So that is a positive expected value bet that I'm going to take every single time, partially because I know, hey, if I lost it all I could rebuild, but you know, my math is failing me at the moment. That's a plus-million-dollar-plus expected value, and so I'm going to take that every time.
So obviously, there's a little bit of reversibility there. You can lose it all, and it's super costly, but you could get it back.
Spencer: I think for most people that wouldn't be a worthwhile bet.
Chris: All of these risks are personal. And so, in investing they call this the efficient frontier, in that essentially every trade-off that you make is in order to get a little bit more return, right? To have a little bit higher of an edge, you need to take more risk. And that it's very rare that you can get increased edge without increased risk. And the hope is that you get additional units of edge greater than additional units of risk.
Spencer: Can you define 'edge,' just to make sure that we're on the same page about that?
Chris: ‘Edge’ being that you on average expect to make more than you lose. So in a poker context, I have an edge if, you know, we sat down today, Spencer, and played, I would have a long-term edge over you in poker, in that a lot of times you are going to beat me, especially if we play for short-term periods of time, but the longer that I play, the increased confidence that I have that I will have more money than when I started.
Spencer: Got it. Makes sense. So I have a question for you about games. This is something I've thought about, a bit. So, when you're first learning a game—and this could be a formal game like poker or chess, or it could be more like a life skill game in life—it seems to me that at the beginning, really the game is about not blundering. You know, when you're a total amateur at chess, it's just like, "Just don't do something incredibly stupid." Like, that's the main thing you're focused on. And then it seems to me like after that you're a little bit better, what you're trying to do is learn some strategy that you keep explicitly in mind in your head. Right? Like you're just thinking about, "Oh, I need to try to control the center," or something like this. And then you get a little bit more advanced, and you start getting an intuitive strategy, where you start being able to notice immediately, "Ah, that's an opportunity."
But what I'm wondering—so, I've never become an expert in games like you have. What's after that? What do the next levels of being a master at games look like?
Chris: Yeah, exactly what you've described seems to be the case. And I just started learning tennis, which I think is a great example. If you watch two amateurs (and I am very, very much an amateur) play, who wins the match? The person who wins the match is the person who makes the least unforced errors. And so right now, all that we are drilling is literally, "Can I get the ball over the net and put it into play?" And just keeping the ball in play. Early on in poker, that's why people play their pre-flop hands based off a chart. It's like, "Play these hands, don't play these hands." And you make it really simple to not only reduce the early mistakes, but by getting involved in bad situations, by playing the wrong hands, those mistakes tend to compound.
And I think about progress in any field is a standard deviation analogy. So, say going from zero to sixty-eight percent, you know, the first standard deviation, is how do I avoid making the big mistakes? Right? Tell me how I'm going to die so I don't go to that place.
Spencer: And you're referring to the fact that with a normal distribution, sixty-eight percent of the values fall within plus or minus one standard deviation from the mean, I think. Right?
Chris: Yep, exactly. And I'm sure there's someone who knows more about math, and maybe my number isn't exactly right, but I believe it was sixty-eight. And so hey, you go from sixty-eight to eighty-five. Okay, I start developing strategy, I start to internalize some of these best practices, I can at least hold my own, and not only am I making fewer mistakes, occasionally I make a good play. I go from eighty-five to ninety-five, to, "Okay, now I'm an expert in all the best strategies," and I start to develop my own.
And so where I work with clients, and what I think a great deal about, is how does someone go not only from this ninety-five to ninety-nine, so from standard deviation three to standard deviation four, how do I go from ninety-nine, you know, being in the top one percent in a field to the top .01 percent of the field? And once you get to that point, particularly in games, it is knowing who you are playing against better than they know themselves. I talked about this a little while ago: you are predicting what they are going to do before they do it, and so they are operating off of an assumption which is incorrect. And so, like you discussed with martial arts, you are creating patterns and then disrupting them. You are a few moves ahead of them, in chess terms. And that is sort of the infinite game or the red queen type situation, is that bar of being ahead of your opponents is a constant moving target. The tide is always rising. And so not only do you need to be improving to get better, you need to be improving just to hold your place in the hierarchy. Just to keep your run on the ladder. And that pace of improvement, that derivative, is ever-accelerating. You have to get better at an increasing pace just to hold your own.
And this is where I would love to introduce this concept of centrality, which is a really key one in all games. In investing, you know, Buffett would refer to this as a circle of confidence. And so, centrality is there are many scenarios that come up within the context of a game. You know, different situations. All situations are unique, but they can be roughly categorized, that this is a situation that you know better than your opponent does. You've done deeper study, you have more experience, whatever it is. Think about this in tennis, it's like you've just been to a fifth-set tie-breaker more than your opponent. And so not only don't you crack under pressure, but you know some of the mistakes that might come up, and you already have guard rails in place to prevent those. You have an absolute advantage in this vacuum moment.
And so one cool thing: first, you want to establish as many of these centralities as you can. Pockets or motes of your unique advantage. But the next-level skill which you're referring to, Spencer, is that we spend more of the gameplay within my areas of centrality versus your areas of centrality. You know, a basketball metaphor, if our core competency is you know, full-court press, always pushing the ball down the court, you know, really trying to look for like three-on-two type situations, then we are gonna run the ball and we're gonna press the entire game, because we have more experience, that is more in line with our skills.
And that's like when you get to the very top levels, it's all match-ups. And how can I create match-ups or maximize the number of situations where I have an edge, where the odds are in my favor, versus when the odds are in your favor?
Spencer: This relates really well to something that my martial arts teacher taught me about, which is this idea that oftentimes the greatest martial artists are ones that force you to fight in their style. And the idea is that they're the best at their style, so they can't beat you at your style, but they can beat you at their style, and they make you play their game.
And he gave me an example of this, which people say is true (though it could be apocryphal), which is that a great martial artist shows up one day at the dojo, and he challenges everyone at the dojo to a fight one at a time. And so he starts with the white belts and he fights each of them one at a time, and then he works his way up to the higher belts and higher belts all the way to the black belts, and beats every one of them. But the really insane thing about his fighting is that he does the same move on every single one of them. So they know exactly what move he's gonna do, and yet he is so good at doing that one move that even though they know it's coming they cannot stop it. So he forces them to fight in his exact game. So, yeah. I love that.
Chris: I love that. It touches a little bit on explore/exploit, and a lot of success is exploring lots of paths and finding where your outsize advantage is, and then finding as many ways as possible to exploit that edge until that edge disappears. I'm a huge Japanophile, and so in the apocryphal tale of Musashi, the greatest swordsman who ever lived, that's what he would do, is he would go to all the dojos and challenge the greatest fighter that they had, but where he was a strategic master was: he took it away from—you know, he was visiting them on their home court—to subtly manipulating them out of that comfort zone into places where he had a unique advantage. Into, you know, Sun Tzu-type advantageous terrain or installing conditions onto the match which subtly put the odds into his favor, or you know, really throwing them off—you know, showing up hours late to the bout—all these types of psychological maneuvers in order to shift that field of play into where his unique advantage was.
One more aspect of this which I would touch on is, first, not only spending more time in your area of unique advantage, but identifying when the odds are in your favor and being able to place more into the middle, to be able to bet larger. So, you know, card counters—I'm not a card counter, but I know many professional card counters, including some of the original MIT blackjack team that got famous from the "Bringing Down the House" movie. And so, what a lot of people don't know about blackjack—obviously, the house has about a one percent edge on you on average—but card counting is powerful because based on the cards that are in the deck, there are certain times where you now have a one percent edge. It's a small edge, but it's a real one. And so being able to count the cards, you know when that edge is. But what these guys do is, they're betting the minimum. Say they're betting ten dollars a hand, ten dollars a hand. And then they notice that the odds have shifted into their favor. Now they have a one percent edge. So now they start betting a thousand dollars a hand. So that one percent is magnified during those moments where they have that edge.
And that's how a lot of card counters get discovered, is like, "Oh, this is really weird that these guys are betting ten, then all of a sudden they bet a thousand. That's a little bit suspicious." But that's one of the key skills as well: not only maximizing the frequency with which the odds are in your favor, but being able to have more at stake when the odds are in your favor.
Spencer: Yeah, once you take into account the risk of having your legs broken from card counting I'm not sure it's worth it anymore, but that's a really well-said strategy. And you know, I think if we bring these ideas back to everyday life, right, what I think we're really talking about here is, one, know what you're good at and make sure that the things you're doing are really leveraging the things that you're better at relative to others. Right? Play to your strengths. And second, that if we think about opportunities in life, it's not like, you know, "Oh, every day I have equal opportunities." It's like every once in a while, you're gonna have an opportunity that's way, way, way better than almost anything you're going to see in your life. And that's a time to strike, where you can really get enormous value created, whereas most of the opportunities you're getting maybe they're not that great, and actually if you try to take too many of those it might block out the room for being able to go big on the big opportunity.
Chris: That is so well said. Two key concepts there that I'd just want to underline. First, I think a lot of "productivity" is just knowing what you do well and finding ways to lean into that. Do more, leverage it. And usually, that comes by finding ways to complement your strengths, either by partnering up with someone who has complementary strengths or by choosing a pursuit that allows you to do most of what you do best, where you have the greatest leverage. But on a more macro level, as you said, I think that everyone has these few moments where there's a split second that really matters, where the opportunity presents itself, and it's just such a slam-dunk opportunity. You know, say you get maybe twenty of these in a lifetime. But the way that you are able to take advantage of these huge 10x opportunities—think of them as waves coming to the shore. Giant waves to surf. And you can't get to that wave if you're not already in position. You already need to be paddling.
And so in order to seize these opportunities which are very temporal, you need to know what they look like. And that means doing the hard work ahead of time, of, "What are the opportunities that you're looking for?" So that not only can you recognize those opportunities when they come, but you can feel very confident saying "no" to the ninety-nine percent of opportunities that aren't high leverage, that aren't high edge, so that you can have that space to fully get behind and seize these opportunities when they come. And that notion is just such a powerful one: once you get to a certain point, success is determined not by what you say "yes" to but by what you say "no" to, because that creates the space in order to be able to say "yes."
Spencer: Absolutely. And I would add that the importance of slack is really great. And that means slack in terms of time, it means slack in terms of resources. You know, if you have no free time then when that huge opportunity arises you can't take it. Or if you're literally living paycheck to paycheck (which unfortunately people can get stuck in a cycle, no fault of their own), but if you're in that situation it's going to be really hard to suddenly make that investment that could pay off huge, because you just don't have the slack to do so. So trying to keep enough slack that we can also take advantage of opportunities is also really important.
Chris: It's something that I really hammer my clients on, that's unexpected, is I'm always trying to find ways for them to do less. To say "yes" to less, to take things off their plate, to take more time away from their devices, away from work to create this slack, not only to think about the opportunities that are going to be most on this direct path to where they want to go, but to be able to have the space to pivot to these opportunities when they present themselves. And the less that we have slack, the less that we are able to course-correct when these opportunities come.
I mean, we are seeing this play out in real-time with the pandemic in that all of our systems were optimized for minimum slack. You know, just-in-time manufacturing, how do we minimize expense, but not thinking about, "Hey, what are the hidden costs of handing off all of our core competencies to, you know, geopolitical partners who are not necessarily aligned with ourselves?" And seeing all of those second- and third-order effects play out now: "Oh, we have this massive crisis, and because we are a giant train we aren't able to change the course of that train to meet the demands of this crisis, because there was no slack." And so the slack, unfortunately, has had to have been created by stopping that train completely. So yeah, a very clear historical example that we are living through of the downside of not having slack.
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Spencer: What do people get wrong when they're trying to be productive?
Chris: That's a longer answer than what they get right. So I always try to go with my first answer on these. I think people think of productive actions as ends rather than means. So it's this hypothetical end state that someone is moving towards. You know, the classic approaching-one situation, that once I learn how to be productive all of my other problems will somehow go away: "this is the instrumental skill." And I really like to differentiate productivity from what I do, where there is this expectation that I'm gonna come in and recommend tools, or you know, "Here's some hacks, here's some different routine that you can do." And I think there are some interesting fundamental building blocks that come from that. You know, we can dive more into habits and systems-type stuff, which is just fundamentally how do we get ourselves to do things. And I think that those principles are really interesting, because you uncover one pattern and you see ways to apply that pattern elsewhere.
But I tend to find that those who are most enthusiastic about becoming productive are generally the least productive in an "actually accomplishing things" sense.
Spencer: Interesting.
Chris: Yeah. I talk about this in a post that I call, "The Perils of Over-Optimization." And I do see this tendency, and I imagine a lot of people listening to this episode will fall into this bucket, of being biased towards perfection, and really, really planning things ahead of time and trying to create, you know, the perfect system, trying to find the exact right tool for the job—you know, "Here's my ideal day." And really trying to do a lot of that heavy lift upfront as far as, like, "What do I need to do to be productive?" And you know, I always—any time I get advice, it's like, "Well, do I want this person's life?" And it's something that I found super interesting: a lot of people who I actually take in productivity concepts for, I see behind the scenes. I go meet them, I stay with them, or we have conversations. It's like, they actually aren't that more productive than a lot of people who don't think about this stuff all the time, and it's really kind of simplistic and annoying but true that the key to productivity is just taking action, and that we create all of these substitutes for action.
And what I'm always looking for is how can I incorporate feedback into everything that I'm doing, where I'm always finding some way to move forward in every area of my life and collect feedback on? What are the things that I'm doing that are most leading me to where I want to go? And so I can double down on those. And presumably, something that doesn't make it into that group is something I can just stop doing, reclaim those resources and put them somewhere with a higher ROI.
Spencer: So just to make sure I understand what you're getting at, is that a lot of people, they approach productivity by saying, "Let me optimize every little variable," when in reality a lot of times the way to be productive is to just have a strong feedback loop to see whether what you're doing is actually taking you in the direction where you're trying to go in an efficient way, do some stuff, see if that feedback loop is working, and then make adjustments from there. Is that what you're getting at?
Chris: Yeah, that's a really good way of putting it. So thinking about velocity versus speed, right, everyone wants to move faster, but velocity is both speed and direction. And so the problem is, a lot of people will sprint really quickly but then realize that they're doing completely the wrong thing and need to change direction. All of those systems that they had built up get abandoned, and you know, it's starting off at square one, versus having something that's lightweight and flexible, and that way as we naturally course correct and reorient, we can repurpose what we have that's working and continually build off of that. And so never finding ourselves back at square one, because we're constantly reorienting and not having to scrap.
So you know, I think about what a lot of what I do is kind of like post-productivity, where productivity learning is somewhat of a gateway drug for figuring out, "Hey, what works for me? What are the conditions that allow me to be successful, and what do I really want? What are the trade-offs that I'm willing to make in order to achieve that?"
So, what I think about in terms of what I call high performance is there's a most direct path to get where we're going, and so obviously the fastest path between two points is the straight line, and so implicit to that is having a directionally correct way that we are heading, that our actions are moving ourselves down the path, and that we're not, you know, imagine hairpins going up the mountain, like constantly going back and forth really quickly. It's better to be deliberate and intentional but head in that correct direction. And the cool thing is, the better idea we have of where we want to be, we can usually identify a more direct path, in that there are things that we think are instrumental towards that that really aren't necessary.
A classic one that I talk about is a lot of people treating financial freedom as a terminal goal, rather than as an instrumental goal—where clearly financial freedom unlocks a lot of opportunities, but it's not an end in and of itself, and if you treat money as an ultimate goal, you're ultimately paying a really poor exchange rate on the things that you want from money, as far as like being able to have impact, work on what you want, et cetera. You can generally go after those things in a more direct fashion.
Spencer: It's funny, the two topics that come up on this podcast pretty much every time are instrumental values or intrinsic values, and probabilistic thinking. So I actually have a way of thinking about productivity I don't think you're familiar with, although my guess is it's quite similar to the way you think about it. But I'd be curious to just explain it to you quickly and get your reaction to it. How does that sound?
Chris: Absolutely, yeah.
Spencer: So, the way I think about productivity is with a simple formula, that productivity = time x efficiency x objective.
And I'll just break that down a little bit. So, first of all, what is productivity in that equation? Productivity is basically the amount of value you're producing each week according to what you care about. So, according to your own intrinsic values. I'm saying productivity is equal to time times efficiency times objective. So what is time? That's just how many hours you're working each week. And I think this is a classic mistake people make, which is they—the simplest lever to be more productive is just work more hours. Right? Because it's such an obvious lever, I think it's way more overused—just trying to put in more hours. But these two other factors in the equation we can also adjust. So the second is efficiency, and efficiency is the number of units of work you get done each hour. So you know, depending on what you're doing it could be like the number of words you write, or whatever unit of work you're doing.
That's kind of the second lever, because if in each hour you can somehow get more words written or more emails responded to or whatever, that's gonna make you more productive.
And then the third factor is objective. So, the objective is basically what you were talking about, with the idea of velocity being a direction, where speed is just a magnitude. The objective is basically the amount of value that each unit of your work creates. I mean, another way of thinking about that is, how good is the direction you're headed? Right?
So I think in your framework, efficiency is kind of like speed, and objective is kind of like the direction you're going. And then if you multiply all these three things together, time x efficiency x objective, that's basically how much value you're producing each week.
I'm curious to hear your reaction to that, because I think often people spend a lot of time optimizing number one, which is the time, and not nearly enough time optimizing the objective, which is like where they're trying to get to.
Chris: I one hundred percent agree. So, yeah. First, underlining that productivity is self-defined. We're all playing single-player games, and one person's definition is going to be different than your own. So you know, really nailing that in: how do we define success? Everything works backward from that goal. I agree with your first two buckets for sure. I think these are way, way over-emphasized. First, how do I work more hours, second, how do I be more efficient? I think a lot of those gains tend to be sub-linear. The main bucket, and where I work with clients primarily, as what you referred to as "objectives," which is essentially, "What are the activities that you are doing?" And it's both, "Hey, there are some activities that lead you to your goals faster and more direct than others, have greater leverage, have greater average value, et cetera." That a lot of improving the way that you spend your time is just working on higher average importance priorities. So you can work less, but accomplish more.
It's an arbitrage, right? So if you're putting a dollar value on it, everything somewhat can be reduced to this dollar value per hour. Hey, if you have something that has an expected value of a thousand dollars an hour, but you're doing all these things that have an expected value of ten dollars an hour, either they're not worth that much, or you could easily pay someone to do them for you. Right? Delegate, et cetera. There's a 100x return in getting rid of one of these ten dollar hours and replacing it, arbitraging it, with this thousand dollar an hour activity.
And this notion that the way we spend our time falls on a power law: the most important thing you could be doing is more important than everything else combined. And so that's where the greatest lever, the greatest opportunities are for someone who wants to become more productive is just really carefully audit the way that they spend their time.
Spencer: Absolutely. Just to use a metaphor that I think may make this a little simpler for people. Imagine that you're a writer, and so you know, time is how many hours you work per week, writing, efficiency is how many words you get done per hour, objective is what are you writing. Are, you know, you writing an article about this or are you writing an article about this other thing? And bringing in the power-law idea, chances are the different things you write are going to have wildly different reactions, and most of them maybe will have not much reaction, not much value produced, but then every once in a while you might have a blockbuster article you wrote that gets like fifty times more views than your average article, and that if you can do more of those, that's going to move the needle much more than you know, working an extra five hours a week. Yeah.
Chris: The example that I like to share—I think this came up in Less Wrong as well—is I wanted to do stand-up comedy. I thought there were a lot of skills that could be gained. Presentation, humor, being able to hold my own on an audience, et cetera. And it's like, "Oh, okay. If I perform stand-up comedy this will be a cool way to both check off a bucket list item and learn some of these skills that I think will be important to other things that I want to do." And realizing, "Okay, well I have limited time. And what are the efficiency gains? I have no idea what I'm doing yet. But I can be really clear about my objective: my objective is I want to perform a stand-up comedy routine." And so there's lots of things that I could backwards rationalize later that were "productive" towards that. I could have spent hours watching comedy sets on YouTube, I could have talked to other comedians. But like, what's the most direct path is, I write and tell jokes, and I see which jokes are funny, and I tell more of those, and things that aren't funny I tell less of those, and I keep doing the thing that's closest to actually performing.
And so that's how you can uncover that there are activities that are much more on the objective—right? This classic, "Oh, I did eight hours of work." But what was the actual work done? Was there something that could've been done in less time? Maybe more difficult, maybe more energy-intensive, but you would've made more progress in less time. That usually the clearer you are about that objective, the more you can have activities that are in line with it.
Spencer: Yeah. That seems much more efficient. And I think a lot of times when we view these other activities, they're actually a sort of fake work or almost procrastination. Right? You're like, "Oh, well I have to watch a bunch of comedy sets on Netflix because that's going to help me with comedy." But it's like, okay, but maybe you're just trying to avoid the anxiety of actually working on your set.
Chris: Absolutely. I mean every action we take is serving us in some way, and it's very easy to backwards-rationalize everything that we're doing, right? The more rational we are, the better we can rationalize, because we can come up with reasons to convince ourselves of anything. And that's why planning is amazing, because you have this default thing that has been externalized outside of your head, and if you do something completely different, well that's a lot harder to justify as, "Oh, I had a productive day." And I see this all the time with clients is they list out, hey, twenty things that they got done, but they were numbers twenty-one through forty on their list, and you know, number one didn't get touched.
Spencer: Right. You know, talking about comedy sets, it reminds me of an interesting thing I heard a comedian say, which is that you know, early on in their career they were just trying to keep building on their preexisting work, but eventually they moved to a model where they would actually throw away their comedy every year and start fresh. It forced them to generate new ideas every single time, and created a completely different optimization loop of like, what is it to do comedy? It's not just to hone the ideas you're working on for years, it's actually to generate original content. And then they felt that pushed their comedy to the next level. Any thoughts about that?
Chris: Yeah. I believe that comes from "Born Standing Up," Steve Martin's biography. And I think he was pretty unique, in that he was pushing the envelope more than just about anyone. He was almost changing the definition of what people found humorous. These are things that hadn't been done before. And there's a great risk to that, but it's also knowing what his personal objective was: he wanted to create his own form of comedy, where someone else's objective might have been different. Where, "Hey, I want to make a lot of money," and so that's like, you know, a "Tonight Show" type thing where you have a standard format that you optimize for, or, "I want to become famous." Okay, I become a pop star instead of creating progressive rock. That you know, once you know what you're optimizing for, it affects the way that you go about things.
Spencer: You know, one thing that makes me think about—if you really want to get good at a thing, a lot of times quantity kind of beats everything else. In other words, imagine you want to get really good at comedy. You know, are you better off honing one thing to perfection, or just trying to generate three jokes every single day of your life? Right? And I suspect, well, while the optimal is some combination, I suspect that if you just had to pick one strategy, the quantity strategy often wins. Or you know, similarly with writing, like it's just the person that writes every single day for two hours, generally that makes him a much, much better writer. I'm curious to hear your reaction to that. Do you agree with that?
Chris: Yeah. The science is pretty clear on this. The classic study was you had a course where the entire grade was based off of who could make the best ceramic pot during the semester, and one group only had to make one pot, and you could spend your entire semester perfecting that pot, and the other group was, "Hey, just make as many pots as possible." And across the board, you know, whoever made the most pots ended up having the best pot. That, you know, people see this a lot with writing is you don't actually know the pieces that are going to take off. Like, our taste can differ from the market. And so this is something that I talk about frequently, is the speed of your improvement in any skill is proportional to the tightness of your feedback loops, which is just a fancy way of saying that the more often you're getting feedback on what you're doing, the faster that you will improve.
And so, yeah. I always encourage, especially with this type of audience, is releasing things way before that you're ready. So, you know, having the crappiest rough draft imaginable and have a couple friends looking at it. Have a minimum viable product that's barely usable to the point of giving some sort of utility and seeing how people use it. Essentially that is the race: how do you get from something in your head to something that is in someone else's hands? And that's something that I've really, really had to reorient myself around: I have really strong perfectionistic tendencies, and you know, my sort of pipe dream is I'm going to go into a cave and read two hundred books on a subject, do some really deep thinking, meditate a couple hours a day, and come out with one distilled compressed principle that's written on a stone tablet. And that's just not the way that these things work.
You know, I really love the framing that's in the classic essay, "You And Your Research," where he talks about the difference between open door and closed door. It's looking at, hey, who are the scientists—You know, everyone's publishing a lot of papers, because this is the dimension you have to optimize for, but who are the scientists who are publishing papers that actually change the way that science is done, that actually move towards a new paradigm? And you have a lot of scientists who were working with their door closed all the time, and they were publishing more, they were "more productive," but the things that they were doing were a lot less relevant than the scientists (I think Feynman being a pretty good archetype of this) who a lot of the time was spent doing intellectual play and conversation and goofing off, but the things that they did actually mattered because they were open to that feedback and were able to adjust quickly to it.
Spencer: When I was doing my most recent TEDx talk, I recorded an incredibly crappy version of it, just on my phone, and then I paid twenty people to watch it and critique it. And then I updated it, recorded another shitty version, and then paid another twenty people to watch it and critique it. And that was my own little self-made feedback loop which I found super valuable in kind of honing it quickly without investing too much time in going in a direction that might be way off.
Chris: And this is something that I think about a ton. It's what I call a forcing function. It's what I named my company after, so I think it's a really, really important concept for accelerating progress. And that presentation example is a really key one. Any time someone asks me for help with a presentation, that's the advice I give ’em is, "When are you doing the presentation? Set a date two weeks ahead of time. Pick a group of suckers who are going to watch your presentation. And you know, it's going to be the worst thing ever, you're gonna be completely embarrassed, but you don't know what you don't know until you have to stand up and talk about it, so you want that to be as early as possible so you can address your efforts"—going back to objective—"to the parts of the presentation that need the most work."
And so, yeah. Creating these false deadlines, these things we have to show up for and find out, you know, how on track are we? What are the things that need the most work? That's how you create those feedback cycles, so that by the time you give the presentation a lot of those failure modes have already been ironed out.
Spencer: Can you define forcing function for us, and talk about the relevance of that concept?
Chris: Sure. So I think of a forcing function as anything that changes your default. So it comes from both mathematics and design, and I like the design version the best, which is bringing to consciousness. Think of a design element that automatically draws the eye. The things that you can do to change the default, we'll continue in this same vein, are something that you have to show up for and deliver something. So I think this is the primary function of a meeting and how meetings can actually be productive, in the sense of: a stand-up meeting is you have to show up, and no one wants to show up empty-handed, so miraculously there was progress between meetings, and the more often you meet the more often you have to report progress, because no one likes showing up empty-handed. The more you ask the same question, the more people are inclined to have a different answer for you.
And so it's putting these things into place that make your behavior different than it might be. And oftentimes forcing functions can have the form of externalizing something that you want to do. When I say "externalizing," I mean it lives outside of your head and ideally has other people involved. Because the problem with a to-do or a long-term project living within your head is, because we have an easy time of backwards-rationalizing, it's very easy to keep kicking that can down the road, saying, "Oh, maybe that thing wasn't all that important after all, maybe now is not the right time." But hey, all of a sudden we have a deadline that's been created, we have something we have to show up for, people who are counting on us. That creates a very powerful intrinsic motivator to show up and have something to show them so that we don't waste their time. It's a really easy thing as far as leverage to just put this meeting in place, and all of a sudden all of the incentives have shifted towards now the default is to work on this earlier.
It's the difference between having one final exam and a weekly quiz, where the tendency with the final exam is we slack off the whole semester and then the day before the exam we try to cram the whole semester's worth of knowledge, versus you know, spaced repetition, learn a little bit as we go type approach.
Spencer: We talked a bit about two ways that you can create your own forcing functions. One is for a presentation, you can make a pre-presentation planned and give it to your friends, like two weeks before. And then we talked about scheduling meetings. What are some other ways that people can create their own forcing functions?
Chris: So I'd say there are major categories here. So we talked about deadlines, we talked about externalization, talked about having accountability. Right? Someone is expecting something, and we have to show up. I think another way is just having more at stake. So the intrinsic motivator is having other people involved, but it could just be on the opposite, where, hey. We have promised a launch date, and so now if we don't hit that date, hey, our customers are gonna know and they're gonna think less about us, so we have to ship. I think a lot of times productivity is a function of how much we have at stake, and so it can be useful to over-promise to the point that we have to kind of catch up to what others are expecting of us.
Spencer: Reminds me of the website stickk.com, where you put up money that will then go to some charity you hate, if you fail at a goal. Like, "Oh, if I don't get my homework done by Friday night, then I'm going to like give fifty dollars to this thing that I really don't want it to go to."
Chris: A really silly one that I've been doing recently that's been really powerful is I think my least consistent habit was meditation, and you know, for a number of reasons I think that meditation is probably the best time that I could be spending. You know, increases my ability to make decisions, improves my mental game, improves my serenity and presence when I'm with clients, and that's not before we start to on the ultimate pursuit of self-actualization, enlightenment, that kind of stuff. But for whatever reason, you know, I was just having a hard time putting my butt in my chair and sitting there. And so the thing that I did is I have a friend, and we have a Zoom call, and I sit in my chair and close my eyes and he sits in his chair and closes his eyes. And it's strange; we're not even looking at each other, there's barely any discussion. You know, maybe we'll talk afterward about how it went or anything that came up. But just that, hey, he's counting on me, and if I don't show up maybe he won't do it is enough to take me from—I was like thirty percent successful with doing the daily meditation to now it's a hundred percent.
And so it's pretty cool to identify these opportunities in your life, is just—all I did was set up a recurring call, and I literally solved this habit for myself, where now I don't even have to think about it, I just like click the button when the calendar reminder pops up.
Spencer: Yeah, that's a really good technique. And I've found a similarly powerful idea in my own life, which is that many years ago I used to start all these projects and not finish them. And it was one of the most frustrating things for me. And I think what was going on is that when you start a new project you're all excited about it and it's all shiny and new, and then you start getting into the details and it starts not only being a bit less exciting, but also you start realizing there's all these boring parts to doing it. And then some other project comes along, you're like, "Ooh, that's a new shiny idea."
And so, basically, the way I solved this problem for myself is I basically just involve another person who will be let down if I stop. For me, that's actually incredibly motivating. So now I can get myself to work on a project for years and really stick with it, because I'm just very motivated in that way. That being said, different people are different. Right? Not everybody is socially motivated like that, but certainly for me, that's just incredibly effective.
Chris: Yeah. Two things to unpack there. You know, first you know, lone wolf tends to be a misnomer. Basically, any accomplishment of any magnitude, even if you only know of one person who was involved, there were a lot of people behind the scenes who were working in complementary ways to make it happen. It's like, people who are successful come up together. Even in an extremely competitive pursuit like poker, there's a lot of collaboration that happens behind the scenes. The second is just understanding yourself. And I think that's where the post-productivity stuff comes into play.
First, there's the things that generalize across the board. So, yeah. Get a great night of sleep, have a morning routine, work on your most important thing first, you know, don't get caught in your email, social media, et cetera while you're trying to do deep work. All the basic stuff that every single book on productivity has covered in their completely un-unique two hundred pages. But the really interesting stuff is like, over time, as you're aware, as you observe what works, it's like, "Oh, these are really interesting. These are the conditions that work for me, that, hey. When I ship projects, when I feel happy, when the day goes well, these are the commonalities. These are the correlations." And the more that you notice the things that go well, or the failure modes, the things that prevent you from going well, it's just easy to reinstall those or to take one area of your life that it's working and export it to other areas.
And that's why I think this skill of pattern recognition can be so powerful: once you've uncovered something that works for you, you can find all these other opportunities to apply it elsewhere or to continue to double down on those results. So as you said, if you understand that you're very socially motivated, you can find ways to integrate social accountability and interaction, collaboration, into everything that you do.
Spencer: I would just add to that, that I think it also illustrates why experimentation is so important, because a lot of times you'll meet someone that says, "Oh, I tried this thing and it changed my life, you've gotta try it." And you try it and it doesn't work for you, right?
Chris: Yeah. There's no one size fits all.
Spencer: Exactly. It doesn't mean that person's wrong. Like, okay, sometimes we misattribute things, that's certainly a thing that happens. But maybe that thing did change that person's life, but it just didn't change yours. And so you have to try a lot of different experiments to find the thing that actually works for you, and then once you find that thing you can start reapplying it. Like, because I know I'm socially motivated I can use that in many ways. So for example, if I want to make sure I don't avoid doing something, I can say to my partner, "Hey, can you make sure I do this by Saturday?"
Chris: Yeah.
Spencer: And then I'll feel like I'm letting her down if I don't do it. You know, so that kind of becomes a reasonable strategy.
Chris: I couldn't agree more. I think—you asked about stumbling blocks in the beginning. I think another key one that's related is people try to take on tactics wholesale rather than trying to create the experiences or the experiments that allow them to internalize the principles and kind of remix them or make them their own. And so, yeah. It's like, what works for someone else is a cool thing to try, but you know, collect data and make sure that it works.
Spencer: Chris, thanks so much for coming on. This was great.
Chris: Such a pleasure, Spencer. I love talking about these topics. I really appreciate you being an excellent conversation partner to explore these. Hey, you know, anyone listening, if you enjoyed this, if you want to continue this, I think of this as the beginning of a conversation and not the end of one, so please reach out. We'd love to hear from you. My name's Chris Sparks, you can find me at forcingfunction.com, find me on Twitter, @sparksremarks.
If you'd like to learn a little bit more about what we're about, a couple places that I would send you. First, my workbook, Experiment Without Limits, ninety pages of what I've learned, helped executives and investors achieve maximum productivity in performance. It's free to download, forcingfunction.com/workbook.
I've also written articles on some of these topics. Over-optimization, how to maximize your productivity while working from home, how to build a service-based business, how to make optimal decision-making. You can find all those on our website, forcingfunction.com/articles. Such a pleasure to be here, Spencer. Thank you so much.
Spencer: Thanks, Chris.
Josh: Thanks again for listening. If you have questions or comments, we'd love to hear from you. To find out more about Spencer, visit spencergreenberg.com. To find out more about Chris, take a look at his bio in the show notes. And to find out more about our show, visit clearerthinkingpodcast.com.
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