Hello, listeners, welcome to the Farnam Street podcast called The Knowledge Project. I'm your host, Shane Parrish, the curator behind the Forum Street blog, which is an online community focused on mastering the best of what other people have already figured out.
The knowledge project is where we talk with interesting people to uncover the frameworks that you can use to learn more in less time, make better decisions and live a happier, more meaningful life.
On this episode, I have Michael Moussab and Michael is one of my favorite people to talk with.
This dude is a true polymath. He's the director of research at Blue Mountain Capital Management. Prior to that, he was the head of Global Financial Strategies at Credit Suisse and the chief investment strategist at Legg Mason Capital Management. He's also the author of three books, including one of my favorite multidisciplinary reads, More Than, You Know, Finding Financial Wisdom in unconventional places. As you'll see when the two of us get together, we geek out over decision making.
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Bring me up to date. What have you been working on in the last few years since we chatted?
Well, I think it's a lot of the same stuff. And really what I've been trying to do is deepen some of the themes that we've been working on. So just a couple examples. One, I think we talked briefly about some work on the inside versus the outside view and really the application of base rates to improve the quality of forecasting and decision making. And in that regard, we really try to do some deep dive, especially corporate performance, to understand a large sweep of history in terms of corporate performance for sales, growth and growth, profitability, earnings growth and so forth.
Some of your recent stuff I've been working on, that's fine, where I've been doing a lot of research on the concept of comparing things and it turns out writing comparisons, actually something comes quite naturally to us as humans. And it's been a deep study of cognitive psychology for four decades. But not surprisingly, we're not very good at it. So that's another that's another area where I've been doing a really big deep dive, but more of the same, a lot of work on Decision-Making.
But again, thinking about the sweep of things from how our markets, efficient or inefficient, thinking a lot about still issues around valuation and thinking a lot about what makes for a good business and sustainable competitive advantage.
Where have you landed on with threads and talked to me a little bit of the nuances that you've come up with in terms of how you apply them to make more effective decisions?
Yeah, it's really simple. So just to take one step back, the concept here relates to the notion that an economy popularized but has been around for a while and he calls it the inside versus the outside view. So the inside view basically says, if I present a problem to the way we all tend to cope with it is to gather lots of information, to combine it with our own experience and inputs. And then we project into the future almost all problems we deal with in that fashion.
And what psychologists have come along and said is, you know, what you should probably do is start with something called a base rate and basically asking the question what happened when other people are in this situation before? And I and I should mention is not a natural way to think. Right, because you have to find the base rate and defer to it and you have to sort of leave aside your own experience and inputs. And we all are sort of slow to to discount our own views of the world.
So that's the basic idea. And I think there are a couple of things that come out of this that are extremely rich. The first is how you should wait, go inside versus the outside view. And the basic heuristic on this is that if there is a lot of luck, a lot of randomness, you should rely exclusively or almost exclusively on the base rate. If there's a lot of skill, you should rely almost exclusively on the inside, right on on your own experience.
And actually, most activities in life are between those two extremes. And so you should blend the two in some appropriate measure. Now, what this introduces immediately, if you think about it for a moment, is a framework for not only understanding regression toward the mean, but also quantifying regression toward the mean. Do you go talk to the investment community? Even in athletics, everybody understands the notion, at least at a high level, of regression toward the mean.
But very few people know how to operationalize it, and this actually lays out a very specific framework for operationalizing it. Let me just give you one kind of example to try to make it slightly more concrete in corporate performance to measures that are very common for people to look at our sales growth rates and earnings growth rates. And it turns out the sales growth rates are a lot more persistent. So you might say more indicative of some sort of underlying skill, perhaps related to the industry and so forth.
And hence they're much more predictable. So you don't have to address growth rates as much as earnings, which themselves are actually not quite random, but quite close to random, where regression happens really, really quickly. So to me, it's worth trying to get your arms around the idea of base rate, identifying the data, but then understanding how to intelligence integrate the inside the outside view. And again, was I really understanding not just how do I find out where I am on this?
Lucke randomness, skill, continuum? I mean, as a knowledge worker, I would think that I'm prone to believe, maybe overexaggerate the skill that I'm bringing to the table and thus I would discount the base rate. Favor my own skill, right, exactly. So there's a whole range of approaches to doing this, I'll mention that there is a statistical method. So I'll start with something that makes my life easy to explain the statistical method to do that.
And it's based on a something formulation of statistics that can be very useful in this formulation that says an independent independent, the standard deviation of the distribution, A squared plus a standard deviation of independent distribution B squared equals the standard deviation squared of eight plus B. So so basically it's called like the Pythagorean theorem of statistics. You say, all right, what the heck do I do with that? And the answer is you can apply this, for example, to professional sports leagues.
So let's take this example, say the NBA National Basketball Association, you say, well, how would I apply this formula? Well, you actually know what the standard deviation or the variances of the win loss records of all the teams in the NBA. So that is a known. And then you also can estimate through binomial distribution what the league would look like if it were totally dictated by law. So instead, the teams actually flipped a coin. Right.
So by inference, you can then back into the variance of skill and see how much skill contributes to the outcomes. And by the way, you can rank professional sports leagues on this. And not surprisingly, probably the NBA is the most. Let me say more carefully, the NBA is the sport that's furthest from randomness for this, from a pure luck configuration as sports like actually ice hockey and baseball are actually quite much closer to being random. So that's one thing I might say as a knowledge worker, I can I'm not getting win loss records and so forth.
There are some other things you can do as well. One example is how predictable is your field? How good are experts at anticipating particular outcomes? How much do experts agree? Because usually if there's a lot of skill or a lot of little, very little luck or randomness, experts will come to the same conclusion about similar topics. So there are some other more qualitative ways to do that. But that would be those would be some of the things to think about.
And I'll just say one more thing that's really interesting that about organizations. This is my observation. I don't know that I can prove this, but my observation would be usually when you're a lower level worker, your job actually tends to have a higher skill component. So you're doing something. You're an accounts receivable clerk and you're collecting accounts receivable. Right. We can measure what we're doing is pretty much skill based. But as you move up through the organization, it's not uncommon for the frequency of the types of decisions you make to go down, but the importance of the decisions to go up and also the luck of the outcomes related to those decisions to go up.
What's also ironic, of course, is the remuneration tends to be higher the higher you are in the organization. So CEOs are often making fewer sort of big consequential decisions and people below them, they are paid more. But also those decisions tend to be more luck related, which is really interesting. So sort of a funny, funny thought about how how organizations can work.
Is there also a bigger variance in the types of decisions that you're making at the high end?
Yeah, yeah, I suspect that's the case. Right, because conceptually, at least someone who is a CEO is making decisions really about resource allocation, and that would be financial resources, human resources and so forth. So, yeah, I suspect there is a lot more variance as you move up. Yeah. Which is all really super interesting. And the question is, are the are the what you learn at lower levels or as you as you grow up in an organization, are those things applicable as you get to that senior job?
So it's really it's these are all super interesting questions. So when you're thinking about organizations making decisions or maybe senior managers or CEOs, do you find that there's often a process involved in those decisions?
I think it runs the gamut. And one of the things that I've always found to be fascinating and actually somewhat disconcerting is that many executives will say that they employ a majority of executives will say that they rely on or lean on their intuitions for making their decisions. Right. And the definition of an intuition is sort of a sense of what you should do or view of things without really tapping your conscious thinking. And if that's the case, that to me would suggest that there's much more that we can do to improve.
That said, in other fields, for example, money management, the business that I've been so. It with you sort of learn to over time, think about their distributions of outcomes and probabilities attached to those distributions and really try to think sort of more of an expected value type of framework. So I think it runs the gamut. But clearly, I think that with a lot of the work by Cornerman Tversky and of course, Dick Thaler winning the Nobel Prize a few weeks ago has put into sharper focus some of the virtues of thinking about decisions more systematically and trying to to address or remove some of the biases.
So how would you advise me, hypothetically, if I was I had a company we were a Fortune 500 company. We don't really have a decision making process. How do we put one in place? What does that look like? And how do we how do we use that to get better over time?
Right, exactly. So there is the overarching theme here would be whether there and by the way, we should acknowledge at the outset that there's probably a continuum of decision types, some of which are very simple, cut and dried, and there are probably right, right answers. And they're wrong. There's other decisions that are inherently probabilistic and hard. Right? I will say that. So I think the broad concept concepts are there ways that we can be systematic, evaluating good decisions.
So, my goodness, you need to really think about two things. One is what's and what are the measures by which we judge this? Right. So in certain applications, that's pretty straightforward for a company. Might be creating value, might be for a portfolio manager and investing it would be pretty more attractive portfolio. But you need sort of good inputs and some measure of goods now when things go so. And the key is to try to be as systematic as possible and write down.
So one of the things that's really captured my imagination since we have spoken last was this article published about a year ago by Daniel Kahneman and some of his colleagues on Noise in the Harvard Business Review. Do you see that article, that article?
No, I don't think so.
Here's the basic idea. Cottman obviously is renowned and so renowned right now, work on jurisdiction bias. And this idea that we go play with rules of thumb that are incredibly I'm saving and by and large pretty accurate come with inherent biases that lead to suboptimal. So that's fine. And hopefully everyone's got the memo on that. This newer work actually is a somewhat different of a somewhat different. And he says, you know, so I should probably give an example.
So they so they went to a large insurance company. And these guys, these firms typically have, for example, insurance adjusters, people who will settle your claim if you make a claim. And there is the other train, the same way they have the same software. Basically, you should have expected, maybe not perfectly interchangeable with these. These folks should be basically doing similar jobs, similar tasks, and should have similar outcomes. So what they did is they gave these people a claim, a set of facts, and they first went to their managers and they said, hey, you know, how much variance do you expect in these outcomes?
Right. Again, the same way, same software and so forth. And the manager said apriority five and 10 percent variance. Some people have good days. Some people have bad days. Right. But they'll they'll be a little bit average, but pretty tight. Right. For the most part, when they got the numbers back, they found the variance between 40 and 60 percent of people who were just completely inconsistent in applying the basic rules and the basic algorithm.
So secondments come to call this noise. And it's this basic idea that even when there are systematic ways to do things as humans, we often don't stick to the script and there's a huge amount of variation. So that would be something I would really want to examine an organization. And that's from top to bottom is if there are systematic processes that make sense for different levels of Decision-Making, can we identify those? Can you articulate those? And perhaps most importantly, can we make sure that our our employees, due to those and you know, there is a series of papers that came out of Wharton that I thought were awesome about algorithm aversion.
You may have seen these. And the basic idea was that as human beings, we tend to be quite adverse to it, to sticking to a simple algorithm. And in fact, the algorithm goes wrong. We get very upset and very dismissive. And it turns out they said there a way to overcome this, which I think makes enormous amounts of sat. And they said the way you overcome this, you say to people you're going to your first answer is going to be what?
The algorithm. You just apply the algorithm and then will allow you to introduce a little bit of judgment. You can tweak the response. They said that it doesn't doesn't matter how much you let them tweak it, they can tweak it just a tiny amount. You could tweak the response. So then there's a sense of volition that the humans involved in some way, shape or form what you do, stick closer to what is ultimately a better solution. So so this idea of algorithm aversion and being systematic, I think that's that would be the approach that I would try to take if I were starting with a clean sheet of paper in any organization.
What sort of things would you incorporate into that process? Would you have a checklist, sort of that level of formulaic, systematic process where like what are the base threads or would you have more intuition based where people are feeling? But the process is generalized but outlined, but you kind of feel your way through it.
Yeah, I think that what you probably know where I'm going to come down on this, but it depends a little bit on the activity. But I think checklists are really powerful and checklists are mostly I mean, I think that most people don't like checklists because they feel strange. Something with a checklist does is compels you to make sure that you covered all your patients. It's certainly the lessons we learned. Medicine for checklists, extremely powerful. I think the application should go beyond that.
No intuition. I think we talk about intuition before. But I mean, the key intuition is that it exists. It can be very powerful, but we have to be very careful about where it applies. And I think the general rule is intuition can be developed in realms that are stable and linear. So there's a repeated pattern and things don't change that much. You can train your intuition. You have to train up, you can train your intuition.
It can be very powerful. So the canonical examples are chess players and grand masters are amazing, their ability to chomp, their ability to see what's going on quite, quite rapidly. But it should be noted that it's not some sort of superpower force of these grandmasters. If you change the rules of chess or change the size of the board, all bets would be off and they'd be back to square one. So, yeah, as you know, I probably I probably tend toward the more structured.
Now, all that said. Right, you need there are many things in life that do change over time. So they evolve over time. So you got to be careful about getting too rigid and having a mismatch between your decision processes and the environment. So there is that that blend as well.
Let's talk about intuition for one second there. How do we develop intuition? I mean, I'm thinking about myself in the context of working for an organization. And I have all of these people around me who might be domain experts and they have really good intuition in the particular domain. How do I acquire a better knowledge of that domain? So, like, how do I improve my intuition in other people's domains?
Yeah, I think that's a really interesting question. Once again, I think that there's there's a there's just some great quotes on this that just because you've been doing something for a long time doesn't mean you're an expert. Right. So so I think we should first be very skeptical is the right word, but we should just be careful about suggesting people have domain or don't have domain expertise. That said no to me, again, there's sort of two conditions.
By the way, there was a great paper written by Danny Cornerman and Gary Klein in twenty nine. And the history was really interesting because cognomen was obviously of the belief that people are sups can be suboptimal in their decision making or they have these biases and was just sort of celebrated the notion of intuition work. And they're both very thoughtful together on common ground. And I think the common sense expertise, lies or expertise applies when you have this sort of stable regularity in the domain itself and where you're trained with really quality feedback and accurate feedback.
So I think it's those two dimensions is a it's going to be to some degree domain specific and it requires training. And that goes back to the Anders Ericsson work on, say, ten thousand hours, but basically deliberate practice. Right. So deliberate practice being being at the boundary of your capabilities with all the feedback to prove. So can you sort of look over the shoulder and acquire their domain expertise? I think the answer is actually probably not, unless you are willing to dedicate some amount of time to to getting trained.
And through deliberate practice, which is not trivial, which is not trivial. So, yeah, no, it's interesting. And then again, the degree to which you should rely on others, also the degree to which, again, those two characteristics have been satisfied that it's a fairly stable domain and they were trained effectively.
I want to dive into that for one second. I mean, we improve through deliberate practice. Someone can't run, someone who can't run a few miles can work at it and get a little bit better. There's this feedback loop going on. But I want to talk about knowledge workers say I'm a manager, maybe a portfolio manager, maybe a people manager in an organization. Let's also say I'm above average in my performance, but I, I hit a rut and all of a sudden my performance is worse than normal.
I'm underperforming. This is normal. It's natural. I mean, it happens. But at the same time, I feel smarter and better because I'm always learning. But history is replete with people like me being stubborn or lacking humility and missing a big change.
How do I know I'm not one of these people? Like, how do you measure whether you're in a typical trend or you've lost the skill advantage? In his book, Ed Thorp talked about card playing and how he hit a rut. But as long as there was, he was consistent with the odds. He knew he was fine because cards are a physical system, but managing people is more of a biological system. So this type of analysis isn't as relevant.
How would you advise me to sustain in such an I mean, I don't know really what the answer to that is, but it is an interesting and I think a little bit of what I was saying would apply or some of those lessons might apply. And, you know, I think one of the observations we can make is if you are operating in this completely skill dominated domain, outcomes are all you really need to know about. Right. And so to your point, if you're performing well, performing poorly, that's almost a pure reflection of your skill.
And in those domains, it's easy once you get into things that are more, as you mentioned, maybe lucke Laden or biological. So they're going to be much messier. You do have to go back and default to understanding the process. And with some sort of faith, a good process will ultimately lead to good outcomes. So the simpler case in that realm would be the Thorpe story, right? Where you know that there's there is you're making bets with a probability and there could be stretches where you just have bad luck.
You know, you're making the right decisions in your process. But when you talk about managing people, it becomes altogether that much more difficult. Right, because we don't really don't really know exactly how the system is and it's certainly not a physical system. So, I mean, part of that would be to me is is to think about or revisit your process periodically. And again, one of the important ingredients to improving process over time is trying to get feedback.
And the challenge is, I think that the thing you're trying to manage, that you're trying to game, you're playing. Let's see it that way, the rules can be changed, can change. And as a consequence, you probably have to if you have to probably evolve. And a great example, that isn't markets where markets as a market practitioner, you have to be very process oriented. But there's and so that means that there are some elements of markets that are immutable, principles that probably carry throughout any environment.
But there are a lot of ideas that are immutable, that change and evolve. I mean, our economy evolves, the characters evolve, relationships between nations evolve. And those are things you just have to take into consideration. So I don't know if there's an easy answer to that at all, but I do think you have to be very process oriented. And I do think about the domain, whether that's changing. You have to think about trying to gather and implement whatever feedback you get to make sure that you're aligned with what what will lead to success.
You're going I'm curious about your take on the concept of invariant strategies or invariant ideas, something that never steers. You're wrong no matter the environmental changes, sort of a go to always on by default. Do you have any of these in your head, whether it's life or business?
Yeah, I mean, I think that when I think about it, I would just step back and just think about evolution. What is evolution trying to do? And really it goes back to Dawkins, right? I mean, is propagation of genes to some degree. So it's basically living to see another day of living, basically. Right. So strategies to propagate certainly would be a big one for that in money management. There probably would be a few things that are really important.
One is and then I would say close to immutable is not an immutable one is. That the value of usually a business or really a financial asset is the present value of the cash that it generates, and it's hard to get away from that ultimately being case. And that has always been true and I think always going forward. Second is, while it's extremely difficult to characterize, there should there should be a general relationship. Is the sure something is the less you get paid to bet on it and the more you get paid to bet on it.
And the very simple metaphor is the horse race. The track or the favorite should get paid less if you bet on the favorite than the long shot. And that that's probably pretty close to immutable. So so there are some of those principles like that. So again, evolution is a big one, but again, the cast of characters tends to change. The circumstances tend to change. So how you how you would evaluate those things might change quite a bit.
And you think about from an evolutionary point of view, right. There are some ecosystems that are extremely stable that encourage a certain kind of ecosystem development. And then there are other ecosystems that change really rapidly. And what allows for successful propagation in that environment could be quite different. Right. And this all ties back to things like how much how much as an organization or even as a species trade off between exploitation, which is basically doing the same thing you've always done and taking advantage of it, and exploration, which is seeking new domains, new ideas and so forth.
And those trade offs, again, probably conditional on the rate of change in the environment, but that that idea of how much you need to explore or how much you need to spend on R&D, that's also probably something that you could see almost everywhere you look.
How do you determine the rate of change in your environment?
Yeah, I mean, I think that I'm sure there's an ecological answer to that that's much more rigorous than anything I could come up with. But yeah, I mean, I think that, for example, in the world of business, in the world business, I think there are some things that we can do to try to measure that. I'll mention some of the tests that we use that may be useful. One is straight up entry and exit data.
So you're looking at a particular industry and the question you want to pose is how many companies come into it? How many companies leave? And all things being equal? Higher entry and exit would be a less stable, more changing. We look at a measure called market share change. So we look at all the participants over some period of time, say three years or five years. And then we look at the absolute average market share change. So what you've lost or gained becomes a positive number of that average and all things being equal.
If that number is higher, that means there's a lot of market share moving around. If that number is low, that means it's relatively stable. So that's another rough proxy for the third thing we do is we look at something called profit pools, which is basically a breakdown of how much each company makes, and we see how that changes over time. So those at least in the world of business, those might be some high level proxies change. That can be pretty helpful heuristics.
And again, you don't want to pay for a huge amount of competitive advantage in an industry where there's a ton of entry and exit, where market shares are very volatile. By contrast, you might be much more willing to pay for franchise value for an industry where market shares are very stable, where your entrance and exits are very scarce and so forth. So that that would be from an invite from a corporate point of view might be one way to think about that.
How have your your thoughts on algorithmic kind of decision making progress over time? Last time we talked, I think we talked a little bit about I think you called it the expert squeeze. Where are you on that these days? Do you think it's going to take over grown more quickly or perhaps less quickly than most people think?
Well, I think it's incredible. It's incredibly wide open. I think that we can continue as societies that continue to apply more of these kinds of concepts. So there's there's applicability. But all of this also gives me a little bit of a little bit of pause. And I guess the thing that concerns me the most, if you can imagine, almost like a little three by three grid and in the various columns, you would put business, government and academia.
And then in the road, you might put something like, you know, access to resources, access to data, and then maybe incentivize those three rows and then just fill them out in a way that you think would make sense. And I think we do that what you probably would find. The access to resources and the access to data is probably greatest among a certain handful of businesses, companies actually, and those are companies you can probably name right off the top of your head.
And then the question is, what are the incentives? And whereas in academia, the incentive might be to write some really cool paper and to get citations and so forth in government, it might be to obviously try to govern effectively and do the best for the most people for business. The incentives might be to sell more ads, get more people to click on my page, try something like that. And those might not be there's a question as to whether those are ultimately great societal good.
So that to me is something to give me a little bit of pause and all this. The second thing I'll just say in general, because I come at the world from the point of view of markets and know there are there are areas where applications of algorithms are incredibly effective. Again, goes back to the sort of more stable environments or predictive environments. But you have to be very, very careful about systems that are changing the fancy term for it's not stationary.
So the statistical properties and underlying systems change over time. And that's another concern I might have. And we see a little bit of finance is this concept of overfitting, right? So you have these data. You can match history beautifully, but you fail to anticipate that the world itself is dynamic. And so the rules that worked in the past may not work in the future. So, yeah, I mean, overall, I would say probably I'm a technology newsiest.
I tend to be an optimist, rightly or wrongly. But there are some aspects of all this that give me pause and the sort of this idea of incentives, who's got the resources data and what are their incentives, I guess is the thing that gives me the most most.
Do you think we ever end up in a situation where the data just becomes this insurmountable advantage?
Yeah, we may be there already. I don't know. You just think about you think about the amount of data that some of these large technology companies have. You know, the ones that come to mind, of course, Google and Facebook and Amazon.com is the staggering. And it doesn't seem to be a lot of slowdown in the momentum of a lot of those businesses. Now, broadly, those things generate huge amounts of value, right. For for consumers, for Google contracts, it gives you a huge amount of value.
I, I don't know that I could go through a day without deferring to my Google searches, which are all the time Amazon great value, Facebook societal value. So there are a lot of good things with this. But again, the amount of data that they can capture and because all those companies have substantial resources, they can put a lot of resources against not only capturing but analyzing data. The flywheel. Right.
Do you think that that should be a public good, like maybe hypothetically these companies should be forced to release data that anything over six months old so we can encourage people to compete?
I've never thought about that. I don't know. Yeah, I mean, I probably would be inclined to say that's not a bad idea, but I don't know.
Let's go back to your work on the you're on the the Santa Fe Institute. You're the head of the board of trustees. How did you originally get involved with complexity research?
So in the mid 1990s, I went to a Baltimore Orioles baseball game and my oath was Bill Miller, who preceded me as chair of the board. And Bill also is a very interesting guy, very eclectic reader. And he had read a bunch of articles that had been out the Santa Fe Institute and said, you know, this might be a place that would have an appeal for you. I ended up working with Bill a few years after that. And at the time I was reading a lot.
I was just reading a lot. But I was reading in particular a lot of science and biology and evolution. And I was really keen to understand the intersection between economics and biology. I was also doing a lot of work on competitive advantage. And in particular, the theory that got me sort of first wrote in was worked on by Brian Arthur, who sort of ran the first economics program at SFI. And Brian has this idea of something called increasing returns.
So we're taught in economics, microeconomics, and by the way, still largely true that returns on incremental capital tend to migrate toward the cost of capital. And typically the reason for that is competition. Right. If you're generating Shein massive excess returns, I'm going to come in and compete with you and those Whitlow's away. Eventually, over time, Brian laid out a situation, a set of circumstances where returns actually may not regress toward the mean. From the increasing returns, and it was a sort of a heretical thought in the world of economics, right?
He was sort of shunned a little bit for this this point of view. But it was based on a lot of this what now seem to be more mainstream with the tiger and more on networks and network effects and those kinds of contests. So I went out there and probably a little more than 20 years ago, and from the very first meeting there was enthral the whole thing. And as you probably know, OSFI was founded in the mid nineteen eighties by a whole slew of very prominent scientists, many of which had Nobel Prizes, who felt that much of academia had become siloed.
And so so people were speaking to one another within disciplines, but that many of the most important and vexing issues that our scientific and really our world faced were at the intersection of disciplines. So set up as an institute that was meant to break down disciplinary borders and have people of different disciplines speak with one another about problems that are common. And the unifying theme there is one is the study of complex systems and complex systems. I think we can articulate fairly simply, which is independent agents, which could be neurons in your brain or or people in the city of New York or ants in an ant colony allowing them to interact with one another and observing and understanding the systems that emerge from that interaction.
And so absolutely fascinating stuff. And I've learned so many important lessons that apply both to science in science and also the world of business. But perhaps most importantly, for me, at least, it's an extraordinary community in the sense of massive self selection for people who are intellectually voracious, willing to go across intellectual boundaries, just wide mind wide open, which is really fantastic. So we actually have our board meeting coming up this weekend. It's November, and I'm really always excited to go out there.
And we're going to be talking actually about intelligence and the application of intelligence as part of our things. So, yeah, very, very influential. Continues to be very influential and in my 20 years of involvement has been a really important contributor to my intellectual development.
You do so much. So you're on the board. You have a full time career in finance. You're a prolific author and researcher. How do you how do you balance all of these different demands?
It doesn't feel like I do very much. Actually, no, I there's no there's nothing magical about it. I think that this is the nature of the work that I've been able to do over the years. I've been I've been blessed with the opportunity to allocate a fair bit of time doing research and being able to write. And it's really fun for me. I like to think about it as input and output. And that's, by the way, really the essence, I think, of teaching or quality teaching.
So I've been able to have this balance between learning about things and inputting and especially being able to follow a little bit of of what I find to be interesting and then output, which is communicated certainly within our organization first, but also and more broadly and I'm a big believer that the notion of synthesis and being able to write speak reasonably intelligently on something is actually an indication of understanding or a first step toward understanding, let's say that way. And I just had to sort of lucky a lucky ability to like that.
I've been able to pursue some of these things. I also I think Shamima have talked about this before, but I think it's also important to always recognize and I think this is true for you as well. I can't speak on your behalf, but I think I'll speak on your behalf, which is a lot of this time allocation. Whereas I really enjoy reading books, I get a lot from it. I spend a lot of time doing it. That's I'm not watching TV much.
Right. I don't if you talk to me about popular TV show series or something, I don't know what's going on. And that's not a great Game of Thrones I've never seen, so I'm proud of that. But that's a trade off where we output results. It's important to acknowledge that there are some things that I see, many deficiencies that I've never seen.
An episode of Game of Thrones either. I think we're in the same boat. Do you think in the all the opportunities that you get, do you think of it then from an opportunity cost lens? How do you how do you think of it? Yeah, I do a little bit.
I mean, I think that, as you know, time is really our most scarce resource. And so trying to be thoughtful about allocation of time is always useful, but to some degree. And again, it's part of this I've been very lucky in my career and I've been able to work with in some degree, there's been a remarkable overlap between the kinds of things that I'm interesting, interested in and the kinds of things that I can actually do from a professional point of view.
So that's been to me, that's really been a life saver. So there's not it's not like you can, by the way, even all the stuff that I read outside of work, I can't I can't ever do that as separate from my work. So I basically everything that goes into this mix is part of the part of the overall thinking, part of the overall output. So, yeah, I mean, so. Yeah. And when we say opportunity cost.
Right. So I'm not not watching Game of Thrones is probably an opportunity cost. That's a tradeoff I'd be willing to make. But I also think it's not these are you know, it's not for everybody. And that's the way I live. My life is not for everybody. Should always want to be clear about that. There's no claim of superiority or anything.
Like I think we might be the only two people on the planet who who've never watched Game of Thrones. And we're talking to each other.
And you're a prolific reader. A lot of reading questions for you. I mean, I have to ask, of course, what a few of the best books you've read since we've chatted. Are there any that have you changed your mind on significantly? Yeah.
I mean, I think that even this year has been I've really found a few books to be really terrific over the summer. And by the way, I think it's and I always forewarn people on this, I think it's a very big commitment. But the summer I spent a lot of time reading Robert Sapolsky book Behave and doing that, although I haven't read it yet.
I did a skim of it already. But yeah.
So I think behaviour's I don't want to be too hyperbolic about it, but I think it's probably the best book I've ever read, not read on human behavior. And Sapolsky himself is a really terrific scholar, but he's a brilliant communicator as well. It's a slog though. It's seven hundred pages and it's a lot of work and requires some commitment. But it starts really with neuroscience and goes everywhere from neuroscience up to culture and basically everything in between. And I think when you read a book like that, when you put that down and really contemplated, it makes you really circumspect about a lot of things, about people's behaviours by your own behaviours, how we fit into societies and so forth.
So Sapolsky book Behave, I thought was was epic. And again, it's not just something you can just dip in and out of what I recommend if someone goes away on holiday or whatever, is to allocate a couple hours a day for a week or so if you can really get into it earlier this year. One of my Santa Fe Institute colleagues, Geoffrey West, published a book called Scale. I find this work to be among the most wondrous research I've ever seen.
The principal scale is that there's a relationship that's been well understood in biology for a long time, which is if you plot the mass and metabolic rates of mass and energy usage of something simple, say, mammals, and if you do it on a logarithmic scale, so that's the key is not one, two, three, four, five, but rather logarithmic means each tick mark is the same percentage difference of one ten, one hundred thousand, so forth.
So you put it on a logarithmic scale and then you plot where each mammal is. It follows a perfect line on a log of the scale with a three quarters exponent. Amazing, right? So you tell me the mass of a mammal. I can tell you that mammals. Metabolic rate, precisely. I can tell you a bunch of other stuff as well. So that have been known for a long time. But but it turns out that Geoffrey was and some of the other colleagues is to Brian Brown came along with a theory to explain that to rats, a theory to explain that it's actually really cool.
And basically the simple version, I think, is energy dissipation in a network. But they really figured out the map and so forth, Geoffrey, that extends that work from biological systems to social systems. And we see very similar. There are different mechanisms for similar patterns for social systems. For example, cities follow scaling walls, corporations follow scaling laws, not exactly the same mathematical issue, but also scaling laws. And there's a really, really fascinating sort of research on this and some conjecture as to what those things mean.
So scale by Geoffrey West. By the way, here's my little cocktail party statistic. And on that, which I find I find is really both fascinating and also frightening. If you plot humans on that mass metabolic rate scale, humans should use about a hundred. Lots of debt, so you know what it takes to sustain your basic metabolic rate, which take sustained use about what it takes. But it turns out that in the United States, I think it's true for North America, the United States, our average energy usage is eleven thousand watts per day.
And around the world, it's three thousand watts per day. So why is this so much higher? Because we harnessed technology to allow us to deploy much more energy than our bodies require. So saying that differently is our genetic footprint is 30 x our maps. And so that is instead of having seven billion people, we have two hundred, ten billion people in the world. Right. This is a question that's really interesting is does how long will Mother Nature put up with that and will Mother Nature put a stop on that?
That's really interesting. And then a third book, by the way. I mean, I like to I really like the book. I like the first part. But in the second part, I really enjoyed Andrew Lowe's book Adapted Markets. But maybe the next book I would mention that I thought was interesting was Peter Godfrey Smith's book called Other Minds. And the book is actually and he's a philosopher by training. It's really about consciousness. But he does that through the lens of octopus, the octopus intelligence.
So it's a really, really fun read. You learn a lot about octopuses, but also about the notion of consciousness and sentience and so on, so forth. So that was a really fun book. But I think I don't read as much as you do, but I think I'm around at around twenty five or thirty books for twenty seventeen. Those are some of the ones that I found. I mean there are lots of other ones that I really enjoy, but those come to come to the surface.
Taught me a little bit about the Geoffrey West Book in terms of taking linear and nonlinear thinking. How how can we apply that to day to day life?
Yeah, so we're going to Geoffrey and his colleagues found that is really interesting, is that for, for example, cities that when they broke down some of these relationships, they found sub and super linear scaling. So what does that mean in plain language? So sublinear scaling basically is an indication of economies of scale. So, for example, if you look at cities of different sizes as they get larger, they tend to use the physical infrastructure more efficiently.
So you need fewer miles per road per person or distance of pipes and electric wires and so forth. So cities like larger beings tend to be more efficient as they get larger. So that's the sublinear scaling economies of scale. But they also found was super linear scaling. Does some things grow faster than linear scaling? And those are things that are good, for example, patterns. So larger cities tend to be more productive from an intellectual capital point of view than smaller cities, but also applies to things that are negative, for example, crime and things like that.
So I think that these guys are starting to make some headway and understanding these various properties of the cities, corporations, by the way, we're early on in that. But above both, by the way, for for animals, the four main biological systems, the all social systems, this idea of economies of scale seems to pop up in both of those particular instances. So so the cell of an elephant or a whale is working substantially less hard than the cell of a mouse, which is really the same mammalian cell, of course, but they work very differently.
So that those are interesting ideas. And then, Jeffrey, know, I think that this all this work ties back ultimately to things like and and we have how do we how how we've been able to harness so much energy as human rights, mostly via technology. But in a sense, we have to get better and better at innovation in order to sustain the growth that we've been able to achieve over the last few hundred years. And I think there's like I said, well, Mother Nature put up with this.
We'll see. But there might be a limit to how much we can continue to grow through innovation. And that that would be I don't think it'll be within our lifetimes. We have to worry about anything. But over the next couple hundred years, there might be some some challenges. And one way that may manifest, for example, might be something like just a population that in other words, there may be some tragic event, whether it's or sees propagation or something that respects the human population to a more manageable level.
It's a cheery thought.
My next question. What book do you give away the most to other people? Usually the books and I give away are usually a little trio. Pinker's book How the Mind Works. Wilson's book, Conciliations and the third book is The Metaphysical Club. So those tend to be the three books that if you said to me and I usually give those younger people, 20 year old kid, how do you go about reading when you pick up a book?
Do you read cover to cover? Is there a process? I know you there's probably a process well thought out behind this. I had to do this.
I go to the Farnam Street blog and read the section about how to read a book. No, I think the Ardler, that other stuff is really how you should do it. And I do some of that. I don't do it as systematic as I should. I usually do read things from cover to cover. I will I will periodically read part of a book and put it down. But for the most part I try to pick stuff that I like and that I usually will try to get through it cover to cover.
And I don't know if you find this as well. I do find that there tend to be ebbs and flow in my reading pace. So there'll be there'll be episodes, weeks where I'll read really a lot. Part of that might be the content and I'm going through part of my just how my schedule works and so forth. In other weeks where it tends to be much slower, I try to be consistent about doing something all the time, but it does speed up and slow down.
And I do there are certain books, right. We'll just do a sort of a heavy skim to make sure that I have some sense of the content. And hopefully I can remember if there's something in there that I should refer back to. So I will read the whole thing. But for the most part, I do read things to cover. And yeah, sometimes I regret that. For the most part I. I don't mind doing that. Do you keep all the books after you read them?
I do. It's becoming a sore spot because I don't have any place to put them anymore. So I'm going to probably have to some point get rid of some of them. But and I have books primarily in two places. One is my home office and one is an office that's outside of my home or work office. And they both probably have now, I don't know, fifteen hundred or two thousand books. So I don't want to sound like a crazy book, but probably three or four thousand altogether.
And I always feel very, very comforted about sitting in the middle of that pile of those piles of shells. Right. Because I always feel like I have access to just a lot of it's almost like they're friends, but a lot of knowledge and resources. And I always feel great being in the middle of all that. So and there will be days where I'm between meetings where I have a few minutes, I just might walk over to a shelf and pull a book off I haven't seen in a while.
I just flip through it and say or my friend and say, is there anything in here that I, I should probably be paying attention to? Because as you know, especially very good books and you go back with new with a new point of view, new knowledge that there are gifts that continue to give right there. You can always take something new from them, which is which is awesome.
How much time do you spend reading new books versus rereading older classics?
Mostly new. Probably ninety nine percent. 10 percent. But I but I can one caveat to that is that when I am researching so when I'm writing almost always, that will encompass going back to things that I and that that actually may not be books, might be academic articles, but that does require circling back around. So, so maybe to hire if you did it that way. But popular like books off the shelf. What am I, you know, what am I actually reading what's on my nightstand.
It's be is there a spot where you read or time of day that you're most comfortable and know that.
No, usually evenings at home will do that anywhere, basically in the house and then a lot on the weekends. And usually weekends are a fairly simple routine part of that. My wife and I have five kids almost all out of the house when it's at home, is now in high school. So that creates a lot more flexibility than I know what people, the younger kids and so forth. But on weekends, that's a very typical thing for me to get up on the earlier side of things.
Come downstairs, it's quiet, make it make some coffee and just go at it for a few hours of the morning. And that's great. So it's quite comfortable. It's the morning. I tend to be more of a morning person, evening person early. So that's that's where I can get a lot of reading. That's a weekend's big, big on the weekends.
A lot of us are you that person who goes to bed early or just that a person who rises early.
You know, and I think we may have talked about this before. One of the things that I become quite religious about is sleeping and. I find it helps so many different levels, so I, I probably go to bed all the time, but I try to be very religious. About eight hours, three hours of sleep a night is really, really good. And there are some nights where I'll sleep five or seven and a half hours, but it's not really sleeping.
And then that just just washes over so many other aspects of my life that it affects my exercise, it affects my diet and affects my productivity. And I just find it much better than if I don't. So and I think that's how many people under I still think there's been a ton written about this. I still think people don't understand how important it is to sleep. And it's often the case that one one less hour doing something else and one more hour, you're going to be much more productive if you're in your other activities.
What have you learned about what contributes to your sleep quality?
It's usually probably very common ingredients, right. Which is I also am a big believer in exercise and moving. So exercise helps a lot. So I will always sleep better, almost always sleep better nights where I exercise in the nights where I dance or the more days I exercise it better off to be. It's very important to try not to eat too much quality stuff. I am I don't not drink alcohol, but I drink very little alcohol. That also probably helps.
So I very rarely have more than one drink in a day, something like that. So those are probably the things that contributed. I've never had a problem sleeping, so but those probably are contributing factors.
Yeah, I would say you've got a firm grasp of what derails most people. Why don't you describe a time that you failed?
And I'm interested in the situation in which you failed through a personal mistake and then not only how you recovered and got out of that failure, but how did you go about learning from that failure?
Yeah, probably my you know, the episode that I think of as the greatest failure was right when I got out of college and I was in a training program for investment bank, which was terrific, by the way. I learned a lot and I was a year and a half long. And then that put us into our first jobs. And these were we're not we're now called financial advisors, but basically stockbrokers. And so I was given a job as a stockbroker.
And this, by the way, was early. Nineteen eighty eight. The firm I was with, Drexel Burnham, had gone through a bunch of legal issues involved in the heels of the stock market crash. So the environment may not have been ideal, but I was so ill suited for that work. And so I you know, I gave it a try, but I was miserable and I was certainly a big failure in doing that job. And essentially, I mean, I don't think I formally got fired, but basically got fired.
Right. There was a parting of the ways between the firm and out that made sense, by the way, at many levels. And so, you know, maybe the silver lining and all that. Maybe there are two things that came out of that for me that were really important. The first was that having gone through the training program, and this is why I'm forever grateful for that training program, we were exposing our program to lots of different parts of the bank.
And that allowed anyone who was there to understand sort of where they felt most comfortable, where they felt they could add the most value. So we were on the trading desks and we were in investment banking and we were in research and in operations. So it was a great opportunity to see where you fit and see where your skills and interests would align with what the organization was trying to do. And by the way, from that I realized the kinds of things that I thought I could be more effective at.
And then the second lesson was learning precisely what I'm bad at. And part of it was I'm a natural introvert. That job, I think, was much better suited for an extrovert. I was, in a sense, selling products that I had nothing to do with creating. So I had no real confidence in the underlying products and so forth. So I just learned a lot about what made me uncomfortable, what may be ineffective. And those are lessons that I both had.
There were some positive things because they taught me a lot about sales and how to sell things and some of those lessons I've been able to carry throughout my life. But yes, that was a big one. And so then from then I just resolved to find a job or a set of jobs that I thought would suit the kinds of things that I tended to be better at and work toward my strengths. And so usually the advice I often get called by young people, college students and so forth, they're saying, what should I do?
And so my first bit of advice is to degree what you can do. This, even when you're young, is to take an inventory of what you're what you think you're good at, what you think you're not as good at, what kinds of environment you're comfortable in, where you think you can be. Given what you're not good at and try to find a career path that sort of get you on the right trajectory to help you build your strength or the luxury, so so to me that that was my big failure.
And the last thing I'll say on that, as I used to take the train to go to work and I remember telling my my then girlfriend, now wife, you know, I'd rather ride on this train back and forth from the stations all day than go, OK, that's probably a good sign that I should not be doing this.
So I was a painful period of great moment on the notion of advice and kind of following your skills. One of the things that I tell people is to identify what they're really good at, that other people are typically really bad at.
I mean, I'd love that. I love that. That's great. And that's that's a little bit of like Peter TEALS, like how to build a great company. I think it's the same. Yeah, right. What problems can be solved that other people can solve and you're going to be good at. That's a great way to think about things. Now, you know, when you're young, you often don't have there's not that much you really have proven skills you can bring to the world, but you can start to think about do I want to do what people do I want to do by myself or my more project oriented or my want to take it slow.
And this is there are certain in my nine to five or my son refuse to be out the ballot. I mean, there are certain sort of dimensions. You probably think about that place yourself somewhere in those dimensions on the notion of Peter Tiller to steal one of his questions.
I mean, what is something that you believe that other people don't?
You know, I always find those to be tricky questions. But the one thing that I think that has really changed one view of mine that's really changed and was very much inspired by his work work by Judith RETAVASE is the work on parenting. And as a parent of five kids, this obviously is not a non thing for me. And I think the argument I think as parents, we all tend to think that we're really, really pivotal in the lives of our kids.
And on some levels, of course, we can be very influential. But I think the argument that Harris makes is quite compelling is that parents aren't quite as important as they think they are. And there are a lot of studies that I think will contribute to that. Some fascinating studies, by the way, and twin of twins, especially twins, would suggest that they turn out a lot more similar than different, notwithstanding their very different environment. And that's quite compelling stuff.
But I also think the other point that she makes it that I really try to take to heart talk a lot about the context of my own kids was the importance of your peer group, especially when you're sort of early teen through kind of high school is called that way. So some middle school and high school and that your peer groups are really important influence on your life in terms of everything academic. So so that's I think I would have placed much greater emphasis on the role of parents 20 years ago, 15 years ago.
And after reading that, that was something that really did really I really did change my mind on that a lot from that.
What other sort of I mean, possibly counterintuitive strategies do you use as a parent with your kids to either encourage them to think or so?
So one thing that I always try to do, especially when the kids get to a certain age and you look some things for young kids, you're you're telling them what to do, just basic things like go to bed, bathe yourself or whatever it is, and mask. You have to get around that. But when the kids get a little bit older for me, I try to be very mindful to give them ideas and ways of thinking and I call them recommendations.
So I say, here's a here's a way you might here's a recommendation for here's what you might think about this rather than saying here's what I think, or here's two. And it's been rare that the kids have come have done something different than what that recommendation is, because I am trying to illuminate it in a certain way that would make it sensible. But in a sense, it allows them to take ownership of these ideas. Right. So I think that's one thing.
Things I say, you know, here's a recommendation for years or something. Here's where I might think about that problem. See how that fits you and that suits you. That's it. That's helpful in your decision making process. So and I think this a lot of dealers, there's a book that was also very influential for me. My kids were much younger called Parent Effectiveness Training. And their basic argument was, as adults, you probably see the answer or a solution faster than your kid does, or you can solve the problem more effectively than your kids and especially in our society today.
The temptation then is to solve the problem for your kid, and that, of course, leaves the kids without the tools of problem solving. So in that book, they like to distinguish your problems that are not the kid's problem. You need the kids to help you solve problems and then problems that are the kid's problems, not your problems, in which case you should have them solve them and your facilitator right out. All right. That's what I thought.
That was a very useful distinction between whose problem my facing as a parent sort of holding back on this idea that I can solve this problem faster than you let me deal with it and you don't have to do with it. So essentially teaching the kids how to solve problems, you as an adviser or a guide or a facilitator rather than doing it on their behalf. So that that to me was another thing that I thought was really helpful as a mental model that a lot.
One of the members of our learning community wrote in with a question for you, asking whether you have a recent example of updating your views, maybe cryptocurrency, what to eat something along those lines or something like that?
Well, you know, I got to say that I don't discount is updating my views, but there's a book and I don't really talk about this, but there's a book I read last year that I thought was really awesome. And it was a book called I Contain Multitudes, that book.
Yeah. I think we talked about that at the retreat last year. You did awesome.
So the work on the microbiome. And so I think that's another area that I well, I don't I don't know that much about it. I think there's a lot to learn about that. But I have a I have a suspicion that that's probably much more important than most of us probably believe. So I have changed a couple of habits as a result of reading that and thinking about that a little bit. The main thing which I should have done a long, long time ago, but the main thing is I sworn off any type of soda in any way, shape or form those soft drinks, no Diet Coke, no anything like that.
And I don't know that this is causal. I should be really clear about that. But from the moment I did that, I found it much easier to maintain a lower weight. I found I just feel better. So again, that might be all psychosomatic, but it may not be as well. So I may have had an effect on me that I wasn't fully appreciating. So that's that's a big one. Oh, the stuff on crypto currencies, I don't know.
I mean, I've studied a little bit about this and I suspect many people have, but I'm always watching this closely at the corner of my eye. But it's really fascinating. It's certainly something like the block over Imagine will be a technology that will continue to develop, whether things like, you know, these basic occurrences with those mean and so forth. Yeah, I don't have a I don't have a strong view one way or another. It is amazing to watch what's happened the last four or five years.
Yes. No strong views on that one.
One of the questions that I wanted to ask you that I've never had a chance to ask you, which is what is happiness to you? What does that mean or does that word mean? Can you unpack it for me?
Yeah, a lot for me is, you know, ultimately, I thought a little bit about this. And really for me, it's a sense of I don't know, like independence actually is probably the word that comes to my mind, which is that I feel like I can do a little bit of what I want and don't have to worry about too many to not to be able to do that. What what brings me happiness, though, as I get older, certainly come to realize it is about people.
And I think everybody emphasizes. But it's really true. So I can say that I look forward to nothing greater than having being with all my family, because now we have all these kids and many of them out of college and so forth. It's difficult to bring everybody together. I look forward to nothing and I'm no happier than when we have everybody together as a group. And so family, I think, is ultimately the top thing being with those people, but in the sense of independence is decided not to worry about.
I guess it goes ties back to work on scarcity. I have to worry about where my wife is going to come from and having a little bit of financial stability and so forth would be related to that as well. And then I think a lot about you know, I think this is this idea. It's funny. One of the things I do is play and sort of purely hockey group. Right. So skating, you know, trying to skate, get out there and skate once or twice a week and and skating with the guys, obviously itself is fun and that's exercise.
But, you know. Also come to realize that part of what makes politics hockey so interesting is that you're spending essentially 20 or 30 minutes before the game and 20 or 30 minutes after the game hanging out with these guys. Right. If you go from all different walks of life and very different experiences, very different experiences, General, different ages. And there's just a lot to that, by the way. A lot of people saying a lot of zany things, but a lot there's a lot to that.
Right, in terms of the social processes and so forth that I really value. So, yeah, to me, it's being able to do what you want. Having that independence and ultimately being around people that. Yeah, that that you that that you want to be around. And and then the other thing is, I'll say that from an intellectual point of view, too. That's the affiliation with SFI has been incredibly valuable in that regard. So I'm I'm usually very happy when I'm there hanging out with those scientists and talking to people again, learning, growing.
It's a lot of fun.
I can imagine I mean, I would love that. What's next for you? Are you working on a new book these days?
No. So nothing nothing formal. And there are a couple of things that are percolating. And so we'll see something comes to pass. One of the things that has come up over and over is about a little over a year ago, I wrote a piece, I think it was called 30 Years, but basically I started on Wall Street just a little bit now. Now it's thirty one years, but 30 a little over 30 years ago. And I try to write down my reflections on what made for a great investor.
So the top 10 attributes of a great investor. And that was that then ended up being very popular, I think. I think for someone like Yushan, it would be mom and apple pie, because a lot of the ideas were about decision making and mental models and reading and so forth and sort of intellectual growth. But that that is something that I've been approached numerous times. Whether that could be something that would be reason to delve into a little book.
And it wouldn't be would be a work piece. It could be a relatively short book. And there are some other things. I mean, I think I've always been drawn to this idea, and it's really the answer to your question about the institute is really might would be able to do this. We'll be something probably more like edited volumes. Might we be able to draw on a handful of really great thinkers to talk about the role of complex systems and how how it permeates into the world of markets and into the world of business.
And then I might be in a position to be able to tap those people on to write a little introduction. Something like that would be a project, too, that I would be inclined to to entertain. So so nothing nothing in the immediate offing. But a couple of ideas that are percolating. Hopefully something at some point in the next couple of years will materialize.
Oh, that's awesome. I'm already waiting with anticipation. This has been great. Where can people find out more about you?
Well, a couple areas. One is if you don't follow on Twitter, I'm certainly on Twitter at MGM. Elverson is my handle and Michael and dot com is another website. We don't update it a ton, but there's references to all the books. There are free chapters. There are a couple of fun things in there as well. But if you're really and I'm not a hugely active person on Twitter, but I do post stuff from time to time a few times a week, probably as part of the best way to keep up a little bit of what I'm working on, what I'm thinking about.
Thank you so much. Michael has been phenomenal. My pleasure, Shane. Thank you. And. Hey, guys, this is Shane again, just a few more things before we wrap up. You can find some notes from today's show at F-stop blog podcast. You can also find out information on how to get a transcript there. And if you'd like to receive a weekly email from me filled with all sorts of brain food, go to F-stop logged newsletter.
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