Tag: Thinking

How The Four Laws of Ecology Help You Solve Problems

Ecology is the study of relationships and processes linking living things to the physical and chemical environment. Exciting, right?

In the 1971 book The Closing Circle, Barry Commoner gives us a clear and understandable example of what ecology really means, while being one of the first to sound the alarm on the impending environmental crisis. (Although Rachel Caron’s Silent Spring certainly holds the mantle for implanting ecological thought into the popular consciousness.)

Commoner’s life was devoted to helping people see the benefits of ecological thinking:

Ecology has not yet explicitly developed the kind of cohesive, simplifying generalizations exemplified by, say, the laws of physics. Nevertheless there are a number of generalizations that are already evident in what we now know about the ecosphere and that can be organized into a kind of informal set of laws of ecology.

He goes on to lay out four basic and inescapable laws of ecology (which nicely complement Garett Hardin’s Three Filters). The principles describe a beautiful web of life on earth.

The Four Laws of Ecology

The First Law of Ecology: Everything Is Connected to Everything Else

It reflects the existence of the elaborate network of interconnections in the ecosphere: among different living organisms, and between populations, species, and individual organisms and their physicochemical surroundings.

The single fact that an ecosystem consists of multiple interconnected parts, which act on one another, has some surprising consequences. Our ability to picture the behavior of such systems has been helped considerably by the development, even more recent than ecology, of the science of cybernetics. We owe the basic concept, and the word itself, to the inventive mind of the late Norbert Wiener.

The word “cybernetics” derives from the Greek word for helmsman; it is concerned with cycles of events that steer, or govern, the behavior of a system. The helmsman is part of a system that also includes the compass, the rudder, and the ship, If the ship veers off the chosen compass course, the change shows up in the movement of the compass needle. Observed and interpreted by the helmsman this event determines a subsequent one: the helmsman turns the rudder, which swings the ship back to its original course. When this happens, the compass needle returns to its original, on-course position and the cycle is complete. If the helmsman turns the rudder too far in response to a small deflection of the compass needle, the excess swing of the ship shows up in the compass—which signals the helmsman to correct his overreaction by an opposite movement. Thus the operation of this cycle stabilizes the course of the ship.

In quite a similar way, stabilizing cybernetic relations are built into an ecological cycle. Consider, for example, the fresh water ecological cycle: fish-organic waste-bacteria of decay inorganic products—algae—fish. Suppose that due to unusually warm summer weather there is a rapid growth of algae. This depletes the supply of inorganic nutrients so that two sectors of the cycle, algae and nutrients, are out of balance, but in opposite directions. The operation of the ecological cycle, like that of the ship, soon brings the situation back into balance. For the excess in algae increases the ease with which fish can feed on them; this reduces the algae population, increases fish waste production, and eventually leads to an increased level of nutrients when the waste decays. Thus, the levels of algae and nutrients tend to return to their original balanced position.

In such cybernetic systems the course is not maintained by rigid control, but flexibility. Thus the ship does not move unwaveringly on its path, but actually follows it in a wavelike motion that swings equally to both sides of the true course. The frequency of these swings depends on the relative speeds of the various steps in the cycle, such as the rate at which ships responds to the rudder.

Ecological systems exhibit similar cycles, although these are often obscured by the effects of daily or seasonal variations in weather and environmental agents.


The dynamic behavior of a cybernetic system—for example, the frequency of its natural oscillations, the speed with which it responds to external changes, and its overall rate of operation, depends on the relative rates of its constituent steps. In the ship system, the compass needle swings in fractions of a second; the helmsman’s reaction takes some seconds; the ship responds over a time of minutes. These different reaction times interact to produce, for example, the ship’s characteristic oscillation frequency around its true course.


Ecosystems differ considerably in their rate characteristics and therefore vary a great deal in the speed with which they react to changed situations or approach the point of collapse.


The amount of stress which an ecosystem can absorb before it is driven to collapse is also a result of its various interconnections and their relative speeds of response. The more complex the ecosystem, the more successfully it can resist a stress. … Most ecosystems are so complex that the cycles are not simple circular paths, but are crisscrossed with branches to form a network or a fabric of interconnections. Like a net, in which each knot is connected to others by several strands, such a fabric can resist collapse better than a simple, unbranched circle of threads—which if cut anywhere breaks down as a whole. Environmental pollution is often a sign that ecological links have been cut and that the ecosystem has been artificially simplified and made more vulnerable to stress and to final collapse.

The feedback characteristics of ecosystems result in amplification and intensification processes of considerable magnitude. For example, the fact that in food chains small organisms are eaten by bigger ones and the latter by still bigger ones inevitably results in the concentration of certain environmental constituents in the bodies of the largest organisms at the top of the food chain. Smaller organisms always exhibit much higher metabolic rates than larger ones, so that the amount of their food which is oxidized relative to the amount incorporated into the body of the organism is thereby greater. Consequently, an animal at the top of the food chain depends on the consumption of an enormously greater mass of the bodies of organisms lower down in the food chain. Therefore, any non-metabolized material present in the lower organisms of this chain will become concentrated in the body of the top one. …

All this results from a simple fact about ecosystems—everything is connected to everything else: the system is stabilized by its dynamic self-compensating properties; those same properties, if overstressed, can lead to a dramatic collapse; the complexity of the ecological network and its intrinsic rate of turnover determine how much it can be stressed, and for how long, without collapsing; the ecological network is an amplifier, so that a small perturbation in one network may have large, distant, long-delayed effects.

The Second Law of Ecology: Everything Must go Somewhere

This is, of course, simply a somewhat informal restatement of a basic law of physics—that matter is indestructible. Applied to ecology, the law emphasizes that in nature there is no such thing as “waste.” In every natural system, what is excreted by one organism as waste is taken up by another as food. Animals release carbon dioxide as a respiratory waste; this is an essential nutrient for green plants. Plants excrete oxygen, which is used by animals. Animal organic wastes nourish the bacteria of decay. Their wastes, inorganic materials such as nitrate, phosphate, and carbon dioxide, become algal nutrients.

A persistent effort to answer the question “Where does it go?” can yield a surprising amount of valuable information about an ecosystem. Consider, for example, the fate of a household item which contains mercury—a substance with serious environmental effects that have just recently surfaced. A dry-cell battery containing mercury is purchased, used to the point of exhaustion, and then “thrown out.” But where does it really go? First it is placed in a container of rubbish; this is collected and taken to an incinerator. Here the mercury is heated; this produces mercury vapor which is emitted by the incinerator stack, and mercury vapor is toxic. Mercury vapor is carried by the wind, eventually brought to earth in rain or snow. Entering a mountain lake, let us say, the mercury condenses and sinks to the bottom. Here it is acted on by bacteria which convert it to methyl mercury. This is soluble and taken up by fish; since it is not metabolized, the mercury accumulates in the organs and flesh of the fish. The fish is caught and eaten by a man and the mercury becomes deposited in his organs, where it might be harmful. And so on.

This is an effective way to trace out an ecological path. It is also an excellent way to counteract the prevalent notion that something which is regarded as useless simply “goes away” when it is discarded. Nothing “goes away”; it is simply transferred from place to place, converted from one molecular form to another, acting on the life processes of any organism in which it becomes, for a time, lodged. One of the chief reasons for the present environmental crisis is that great amounts of materials have been extracted from the earth, converted into new forms, and discharged into the environment without taking into account that “everything has to go somewhere.” The result, too often, is the accumulation of harmful amounts of material in places where, in nature, they do not belong.

The Third Law of Ecology: Nature Knows Best

In my experience this principle is likely to encounter considerable resistance, for it appears to contradict a deeply held idea about the unique competence of human beings. One of the most pervasive features of modern technology is the notion that it is intended to “improve on nature”—to provide food, clothing, shelter, and means of communication and expression which are superior to those available to man in nature. Stated baldly, the third law of ecology holds that any major man-made change in a natural system is likely to be detrimental to that system. This is a rather extreme claim; nevertheless I believe it has a good deal of merit if understood in a properly defined context.

I have found it useful to explain this principle by means of an analogy. Suppose you were to open the back of your watch, close your eyes, and poke a pencil into the exposed works. The almost certain result would be damage to the watch. Nevertheless, this result is not absolutely certain. There is some finite possibility that the watch was out of adjustment and that the random thrust of the pencil happened to make the precise change needed to improve it. However, this outcome is exceedingly improbable. The question at issue is: why? The answer is self-evident: there is a very considerable amount of what technologists now call “research and development” (or, more familiarly, “R & D”) behind the watch. This means that over the years numerous watchmakers, each taught by a predecessor, have tried out a huge variety of detailed arrangements of watch works, have discarded those that are not compatible with the over-all operation of the system and retained the better features. In effect, the watch mechanism, as it now exists, represents a very restricted selection, from among an enormous variety of possible arrangements of component parts, of a singular organization of the watch works. Any random change made in the watch is likely to fall into the very large class of inconsistent, or harmful, arrangements which have been tried out in past watch-making experience and discarded. One might say, as a law of watches, that “the watchmaker knows best,”

There is a close, and very meaningful, analogy in biological systems. It is possible to induce a certain range of random, inherited changes in a living thing by treating it with an agent, such as x-irradiation, that increases the frequency of mutations. Generally, exposure to x-rays increases the frequency of all mutations which have been observed, albeit very infrequently, in nature and can therefore be regarded as possible changes. What is significant, for our purpose, is the universal observation that when mutation frequency is enhanced by x-rays or other means, nearly all the mutations are harmful to the organisms and the great majority so damaging as to kill the organism before it is fully formed.

The Fourth Law of Ecology: There Is No Such Thing as a Free Lunch

In my experience, this idea has proven so illuminating for environmental problems that I have borrowed it from its original source, economics. The “law” derives from a story that economists like to tell about an oil-rich potentate who decided that his new wealth needed the guidance of economic science. Accordingly he ordered his advisers, on pain of death, to produce a set of volumes containing all the wisdom of economics. When the tomes arrived, the potentate was impatient and again issued an order—to reduce all the knowledge of economics to a single volume. The story goes on in this vein, as such stories will, until the advisers are required, if they are to survive, to reduce the totality of economic science to a single sentence. This is the origin of the “free lunch” law.

In ecology, as in economics, the law is intended to warn that every gain is won at some cost. In a way, this ecological law embodies the previous three laws. Because the global ecosystem is a connected whole, in which nothing can be gained or lost and which is not subject to over-all improvement, anything extracted from it by human effort must be replaced. Payment of this price cannot be avoided; it can only be delayed. The present environmental crisis is a warning that we have delayed nearly too long.

Lest you feel these are all scientific, Commoner ends by referring you to classic literature:

A great deal about the interplay of the physical features of the environment and the creatures that inhabit it can be learned from Moby Dick.”


Still Interested? Check these related posts out:

Garrett Hardin on the Three Filters Needed to Think About Problems — “The goal of these mental filters, then, is to understand reality by improving our ability to judge the statements of experts, promoters, and persuaders of all kinds.”

The Effect of Scale in Social Science, or Why Utopia Doesn’t Work — Why can’t a mouse be the size of an elephant? Weclome to the effect of scale on values.

Second-Order Thinking: What Smart People Use to Outperform

Mental Model Second Order Thinking

The Great Mental Models Volumes One and Two are out.
Learn more about the project here.

Things are not always as they appear. Often when we solve one problem, we end up unintentionally creating another one that’s even worse. The best way to examine the long-term consequences of our decisions is to use second-order thinking.

It’s often easier to identify when people didn’t adequately consider the second and subsequent order impacts. For example, consider a country that, wanting to inspire regime change in another country, funds and provides weapons to a group of “moderate rebels.” Only it turns out that those moderate rebels will become powerful and then go to war with the sponsoring country for decades. Whoops.

“Failing to consider second- and third-order consequences is the cause of a lot of painfully bad decisions, and it is especially deadly when the first inferior option confirms your own biases. Never seize on the first available option, no matter how good it seems, before you’ve asked questions and explored.”

—Ray Dalio

The ability to think through problems to the second, third, and nth order—or what we will call second-order thinking for short—is a powerful tool that supercharges your thinking.

Second-Order Thinking

In his exceptional book, The Most Important Thing, Howard Marks explains the concept of second-order thinking, which he calls second-level thinking.

First-level thinking is simplistic and superficial, and just about everyone can do it (a bad sign for anything involving an attempt at superiority). All the first-level thinker needs is an opinion about the future, as in “The outlook for the company is favorable, meaning the stock will go up.” Second-level thinking is deep, complex and convoluted.

First-order thinking is fast and easy. It happens when we look for something that only solves the immediate problem without considering the consequences. For example, you can think of this as I’m hungry so let’s eat a chocolate bar.

Second-order thinking is more deliberate. It is thinking in terms of interactions and time, understanding that despite our intentions our interventions often cause harm. Second order thinkers ask themselves the question “And then what?” This means thinking about the consequences of repeatedly eating a chocolate bar when you are hungry and using that to inform your decision. If you do this you’re more likely to eat something healthy.

First-level thinking looks similar. Everyone reaches the same conclusions. This is where things get interesting. The road to out-thinking people can’t come from first-order thinking. It must come from second-order thinking. Extraordinary performance comes from seeing things that other people can’t see.


Second order thinking graph

Improving Your Ability To Think

Here are three ways you can use to put second order thinking into practice today.

  1. Always ask yourself “And then what?”
  2. Think through time — What do the consequences look like in 10 minutes? 10 months? 10 Years? 1
  3. Create templates like the second image above with 1st, 2nd, and 3rd order consequences. Identify your decision and think through and write down the consequences. If you review these regularly you’ll be able to help calibrate your thinking.
  4. (Bonus) If you’re using this to think about business decisions, ask yourself how important parts of the ecosystem are likely to respond. How will employees deal with this? What will my competitors likely do? What about my suppliers? What about the regulators? Often the answer will be little to no impact, but you want to understand the immediate and second-order consequences before you make the decision.

A lot of extraordinary things in life are the result of things that are first-order negative, second order positive. So just because things look like they have no immediate payoff, doesn’t mean that’s the case. All it means is that you’ll have less competition if the second and third order consequences are positive because everyone who thinks at the first order won’t think things through.

Second-order thinking takes a lot of work. It’s not easy to think in terms of systems, interactions, and time. However, doing so is a smart way to separate yourself from the masses.

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    From Suzy Welsh

Shane Parrish on Mental Models, Decision Making, Charlie Munger, Farnam Street, And More

An interview I gave that I think you’ll enjoy as I talk about reading, mental models, investing, learning and more.


Shane Parrish is the curator for the popular Farnam Street Blog, an intellectual hub of curated interestingness that covers topics like human misjudgment, decision making, strategy, and philosophy. Shane is a strategist for both individuals and organizations and is dedicated to mastering the best of what other people have already figured out.


Can you discuss your background and the origins of Farnam Street?
Farnam Street started as a byproduct of my MBA. As I was going through that program it became evident that we were being taught to regurgitate material in a way that made marking easier. We weren’t honing our critical thinking skills or integrating multiple disciplines. We couldn’t challenge anything.

Eventually, I got frustrated. I didn’t give up on the MBA, but I did start using the time that I was previously investing in homework and started to focus on my own learning and development. At first it was mostly academic. I started going back to the original Kahneman and Tversky papers, and other material that was journal based, because I figured I’d probably never have access to such a wealth of journals again outside of school.

So I started the website and it was really just for me, not for anybody else. The original URL of the website was the zipcode for Berkshire Hathaway. I didn’t think anyone would find it. It eventually grew into a community of people interested in continuous learning, applying different models to certain problems, and developing ways to improve our minds in a practical way. The strong reception surprised me at first, but now the community has become very large, stimulating, and encouraging. I should point out that I don’t come up with anything original myself—I’m just trying to master the best of what other people like Buffett, Kaufman, Bevelin, and Munger have already figured out. In fact, that’s our tagline. It reminds me of something Munger said once when asked what he learned from Einstein, and he replied, only half-jokingly, “Well he taught me relativity. I wasn’t smart enough to figure that out on my own.” That seems like a bit of a wiseass remark, but there’s some untapped wisdom there.

What are your motivations for Farnam Street?
I want to embrace the opportunity I have, which has been created largely through luck, and I want to give readers and subscribers enormous value in three ways.

First, I want to help them make better decisions. To do our best to figure out how the world really works. Second, I want to help people discover new interests and connections across disciplines. Finally, I want to help people explore what it means to live a good life and how we should live. I hope by sharing my intellectual and personal journey I can help people better navigate theirs.

It seems pretty clear that you have a profound admiration for investors. Farnam Street is the street Berkshire Hathaway is located on, and you discuss Charlie Munger’s views quite a bit. What appeals to you about investing?

For Munger and Buffett specifically, it’s not necessarily that they’re just investors, it is that they’ve modeled a path of life that resonates with me. I also appreciate the values that are associated with their investment success. I think what they’ve done is they’ve taken other people’s ideas, stood on the shoulders of giants, so to speak, and applied those ideas in better ways than the people who came up with the ideas. For example, with regard to psychological biases and Kahneman’s work, Munger and Buffett have found a way to institutionalize this to a point where they can actually avoid most of these biases.

Whereas Kahneman himself just says something along the lines of, “I’ve studied biases all my life, but I’m not better.” Yet, these two guys from Omaha actually figured out how to be better.

It’s not just Kahneman and human biases. They’ve done it in a variety of disciplines like Michael Porter’s work on Competitive Strategy. They separately derived the same basic ideas, except in a way that gives them an enormous investing advantage. To my knowledge, Michael Porter has not done that. Of course, he may not have been trying to do so. Another great example is Ben Graham. He provided the bedrock that Warren Buffett built his brain on, but if you really think about it, Buffett was and is a much better investor. And lastly, regarding Munger, in my opinion, his method of organizing practical psychology is a lot better than the actual residents of that discipline, even the people who “taught” him the ideas through books.

Returning to investing, the field resonates with me because investors have skin in the game. Investors have clear accountability and measurable performance. That contrasts with many other types organizations. For the most part, investors are searching for the truth and constantly looking for ways they could be wrong and that they could be fooling themselves. There’s a pretty clear scoreboard.

Are you an investor yourself?
Yes. I used to be involved with a small registered investment advisor based in Massachusetts. I still invest personally and hope to return more of my focus to investing in the future. (Which, I’ve now done at Syrus Partners) Right now I’m focused on Farnam Street, which I see as the biggest opportunity ahead of me and the opportunity that I’m most excited about. There’s a lot to do.

Can you talk about what you have planned for Farnam Street?
I just hired somebody to help out at Farnam Street for the first time. It’s become more of a sustainable business. We are developing products. We have two courses coming out next year that we’re incredibly excited about (Update: These two are part of the learning community now). I think we have put over a year’s effort into one of the products, and we’re just starting the other one right now which will be released next fall.

Adapting your reading style to consider the type of material you are reading and why you are reading it makes you much more effective at skimming, understanding, synthesizing, and connecting ideas. If you take the same approach to reading everything, you will end up overwhelmed and frustrated.

We are launching “The Art of Reading” early in the year. That course is aimed at adapting Mortimer Adler’s theory of reading to the modern age, and giving people a structured way of going about learning from books, as opposed to simply reading them. Seems simple, but most of us never really pick it up.

Today we are bombarded constantly with information, and we often read all types of material in the same way. But that’s pretty ineffective. We don’t have to read everything the same way.

Reading is something you seem to know quite a lot about, but in a recent post, you discussed that you are purposefully reading fewer books. What is your thinking around that decision?
I fell into a trap with reading. It almost became a personal challenge that you can easily get wrapped up in. In 2014, I was basically reading a book every few days. I think I ended the year with over 140 books read, but I must have started at least 300. I realized I was reading just to finish the book. That meant I wasn’t getting as much out of it as I should. I ended up wasting a lot of time using that approach and it also impacted what I read. You have these subtle pressures to read smaller books and to digest things in a really quick way. I wasn’t spending enough time synthesizing the material with what I already knew and honing my understanding of an idea.

It’s not about how many books you read but what you get out of the books you read.

It’s not about how many books you read but what you get out of the books you read. One great book, read thoroughly and understood deeply, can have a more profound impact on your life than reading 300 books without really understanding the ideas in depth and having them available for practical problem-solving.

Can you discuss some of your techniques for absorbing and synthesizing as much information as possible?
There is a lot that can be done after simply finishing a chapter. I like to summarize the chapter in my own words. I also like to apply any learnings from the chapter to my life, either by looking backward to see where concepts may have applied or by looking forward to seeing if it might make sense to incorporate something into my daily routine. I think the reason to do that is twofold. One is to give me a better understanding of that learning, and two is really a check and balance, and a feedback loop. Have you ever watched TV and somebody comes in on a commercial and says, “What are you watching,” and you’re like, “I have no idea,” but you’ve been sitting there 20 minutes? Well, we can do that with books too. You’ll start reading, and paragraphs will fly by, and then you’ll have no idea what you were reading. It’s fine if you’re reading for entertainment, you might be able to catch up later, but if you’re reading for understanding, that’s something you want to avoid.

Part of what I want to do is develop a feedback process to make sure that I’m not doing that.

I try to make extensive use of book covers for notes about areas to revisit, potential connections to other concepts, and outlining the structure of the author’s argument. After I’ve finished a book, I usually put it on my desk for a week or two, let it sit, and then I come back to it. I reread all of my margin notes, my underlines, and highlights. Then I apply a different level of filtering to it and make a decision about what I want to do with the information now.

You also talk about the Feynman technique in some of your posts.

The Feynman technique is essentially explaining a concept or idea to yourself, on a piece of paper, as if you were teaching it to someone else with little background knowledge. When you’re learning something new, it’s all about going back and making sure you understand it.

Can you explain it in simple, jargon-free, language? Can you explain it in a way that is complete and demonstrates understanding? Can you take an idea and apply it to a problem outside of the original domain? Take out a piece of paper and find out.

I think that being able to do this at the end of a book is really important, especially if it’s a new subject for you. The process of doing that shows you where your gaps are; this is important feedback. If you have a gap in your understanding, you can circle back to the book to better understand that point. If you can’t explain it to somebody else, then you probably don’t understand it as well as you think you do. It doesn’t mean you don’t understand it, but the inability to articulate it is definitely a flag that it’s something you need to circle back to, or pay more attention to.

“Most geniuses—especially those who lead others—prosper not by deconstructing intricate complexities but by exploiting unrecognized simplicities.”

— Andy Benoit

It seems like feedback mechanisms are a key part of your approach.

I think at the heart of it, you want to be an active reader. You want to selectively be an active reader and not a passive reader. These types of activities make sure that you’re reading actively. Writing notes in a book, for example, is really just a way to pound what you’re reading into your brain. You need engagement.

In a recent post, you brought up Peter Thiel’s concept of a “secret”. Essentially, what important truth do very few people agree with you on? I’d be really curious if you have something in mind that would fit this concept.

Ever since I came across this question I’ve been toying with it over and over in my head. I’m not sure I have a decent answer, but I’ll offer one of the things that I run into a lot but couldn’t really describe until Peter Kaufman pointed me to a quote by Andy Benoit, who wrote a piece in Sports Illustrated a while back. Benoit said “Most geniuses—especially those who lead others—prosper not by deconstructing intricate complexities but by exploiting unrecognized simplicities.” I think he nailed it. This explains Berkshire Hathaway, the New England Patriots, Costco, Glenair, and a host of amazing organizations.

I’ve long had a feeling about this but couldn’t really pull it out of my subconscious into my conscious mind before. Benoit gave me the words. I think we generally believe that things need to be complicated but in essence, there is great value in getting the simple things right and then sticking with them, and that takes discipline. As military folks know, great discipline can beat great brainpower.

I know of many companies that invest millions of dollars into complicated leadership development programs, but they fail to treat their people right so the return on this investment isn’t even positive it’s negative because it fosters cynicism. Or consider companies that focus on complicated incentive plans—they never work. It’s very simple. If you relentlessly focus on the basics and develop a good corporate culture—like the one Ken Iverson mentions in his book Plain Talk—you surpass people who focus on the complex. Where I might disagree with Benoit a little is that I don’t think these are unrecognized as much as under-appreciated. People think the catechism has to be more complicated.

You discuss the power of multidisciplinary learning. Do you have any example where the multidisciplinary learning has been especially powerful for you? Munger has a number of examples of him arriving at a solution faster than an expert in a field as a virtue of Munger using concepts from other fields.

If you were a carpenter you wouldn’t want to show up for a job with an empty toolbox or only a hammer. No, you’d want to have as many different tools at your disposal as possible.

Nothing sucks up your time like poor decisions.

Furthermore, you’d want to know how to use them. You can’t build a house with only a hammer. And there is no point in having a saw in your toolbox if you don’t know how to use it. In this sense, we’re all carpenters. Only, our tools are the big ideas from multiple academic disciplines. If we have a lot of mental tools and the knowledge of how to wield them properly, we can start to think rationally about the world.

These tools allow us to make better initial decisions, help us better scramble out of bad situations, and think critically about what other people are telling us. You can’t overestimate the value of making good initial decisions. Nothing sucks up your time like poor decisions and yet, perversely, we often reward people for solving the very problems they should have avoided in the first place.

It’s a little weird, but in some organizations, you’re better off screwing up and fixing it than making a simple, correct, decision the first time. Think about portfolio managers trumpeting how they’ve “smartly sold” a stock at a loss of 20%, saving them a loss of 50%, but which a wiser person never would have purchased in the first place. The sale looks smart, but the easier decision would have been avoiding misery from the get-go. That kind of thing happens all over the place.

Multidisciplinary thinking also helps with cognitive diversity. In our annual workshop on decision making, Re:Think Decision Making, we talk about the importance of looking at a problem in multiple dimensions to better understand reality and identify the variables that will govern the situation—whether it’s incentives, adaptation, or proximity effects. But the only way you’re going to get to this level of understanding is to hold up the problem and look at it through the lens of multiple disciplines. These models represent how the world really works. Why wouldn’t you use them?

One important thing, for example, we can learn from ecology, is second-order thinking—“and then what?” I think that a lot of people forget that there’s a next phase to your thinking, and there’s a second and third order effect. I’ve been in a lot of meetings where decisions are made and very few people think to the second level. They get an idea that sounds good and they simply stop thinking. The brain shuts down. For example, we change classification systems or incentive systems in a way that addresses the available problems, but we rarely anticipate the new problems that will arise. It’s not easy. This is hard work.

Another example is when a salesman comes into a company and offers you some software program he claims is going to lower your operating costs and increase your profits. He’s got all these charts on how much more competitive you’ll be and how it will improve everything. You think this is great. You’re sold. Well, the second order thinking is to ask, how much of those cost savings are going to go to you and how much will be passed on to the customer? Well to a large extent that depends on the business you’re in. However, you can be damn sure the salesman is now knocking on your competitors’ door and telling them you just bought their product. We know thanks to people like Garrett Hardin, Howard Marks, and disciplines like ecology that there are second and third order effects. This is how the world really works.

Munger’s got a brain that I don’t have. I have to deal with what I’ve got. I’m not trying to come up with the fastest solution to a problem. It’s great to have a 30-second mind, but it’s not a race. Part of the issue I see over and over again is not that people don’t have the cognitive tools, but rather they don’t have time to actually think about a problem in a three-dimensional way.

If you think you’re going to come up with good solutions to complicated problems in 30 seconds and your name is not Charlie Munger, I wish you luck.

The rest of us should learn to say “I don’t know” or “Let me think about it” about ten times more frequently than we do.

It makes sense that second-order and third-order effects are underappreciated.
I think a lot of people get incentives wrong and it has disastrous implications on corporate culture. Let’s look at it from another angle – how would you intentionally design an incentive system that functioned horribly? You’d make it so complicated that few people understood it. You’d make everyone measured on individual and not team success. You’d have different variables and clauses and sub-clauses. No one would understand how their work impacts someone else. To make it even worse, you’d offer infrequent and small rewards. You’d offer a yearly bonus of maybe 5% of salary or something. And of course, you’d allow the people in it to game the system and the people running it to turn it into politics. I think we can all agree those are not desired outcomes and yet that is how many incentive systems work.

I think it’s important to focus on getting better at making decisions over time. It is about making the process slightly better than it was last time.

Do you have any thoughts on particularly powerful concepts or process implementations that can help investment organizations pursue investment excellence?
I think it’s important to focus on getting better at making decisions over time. It is about making the process slightly better than it was last time. These improvements compound like money. You really have to flip it on its head. What’s likely to not work well? Generally speaking, analysts tend to have a focused view of the world and they stay in their lane. Specialization certainly helps develop specific knowledge, but it also makes it hard to learn from the guy or girl next to you who has knowledge in a different industry, so you’re not improving your intuition as much as you’d probably want. It’s like chess. People once thought great chess players were great thinkers, but they’re not any better at general problem-solving than the rest of us. They’re just great chess players. Investment analysis is often the same way, especially if you’re siloed in some industry analyst position. It’s probably not making you a great thinker, but you are learning more about your industry.

have the organization learn and get better, we need to expose our decision-making process to others.

In order to have the organization learn and get better, we need to expose our decision making process to others. One way to do this is to highlight the variables we think are relevant. Start making clear why we made our decisions and the range of outcomes we thought were possible. It needs to be done in advance. A lot of people do this through a decision journal. Some accomplish this through a discussion that flushes out which variables you think will dominate the outcome and most importantly, why. Not only does that facilitate an environment where others can challenge your thought process, but over time it enables them to get a good feel for what you think are the key variables in that particular industry. That helps me expand my circle of competence. You don’t want an organization where the automobile analyst knows nothing about banking and the chemicals guy knows little about consumer products, and then a portfolio manager with a little surface knowledge of everything is pulling the trigger. I have never seen that work, but I’ve seen a lot of people try. The “everyone’s a generalist” approach has its own limitations, like a crippling lack of specialized knowledge.

So, obviously, any investment organization has to find a middle ground. How could it be otherwise? You must start with this basic and obvious truth to solve the problem.

Another challenge in the investment world is dealing with the sheer volume of the information. I get questions from portfolio managers all the time about how best to keep up with the information flow. They say “I get 500 emails a day. I have researchers’ work come to me at all hours. I have thousands of pages of material to read.”

Clearly, Berkshire Hathaway has done a really good job with this, with basically two guys doing all of the information processing—two really smart guys, but only two.

How do they do that?

Well, part of the answer is that Buffett and Munger are continuously learning about companies that do not change rapidly. They’re learning about companies that change slowly. That in and of itself is a major advantage. They also are operating in industries in which they know the key variables of determining an organization’s success or failure, and more importantly, ignoring the industries where they don’t. It’s a huge step to be able say to yourself “Look, I’m going to miss some enormous winners that were incredibly hard to see ahead of time. I’m OK with that.” Buffett and Munger can do it, but most struggle. So they stretch and invest in things where they really cannot accurately predict the odds of success or failure, all forces considered.

Probabilities being what they are, if you consistently invest in things with middling odds, you’ll have middling results. Again, how could it be otherwise? The key is knowing the difference between an obviously attractive situation and a difficult-to-predict one and being able to act on the former and sit on the latter. Of course, I’m over-simplifying a bit, but you can’t get around the fact that reality is reality. You have to find a way. And this will help you solve your information flow problem, because you’ll be tossing a lot of ideas out very quickly.

It seems like you would prefer the Buffett and Munger model over the approach of the average hedge fund with specialists?
If my job is being a neurosurgeon, I need to keep up-to-date with all the latest neurosurgery papers, academic articles, books, and talks because I’m very specialized in that one particular area and it’s relevant to my job and relevant to my livelihood.

If you look at investing holistically you can’t do that for every company in every industry. In my understanding, part of the reason Buffett and Munger have accumulated so much knowledge is that they focus on learning things that change slowly. That makes it easier to identify potential outcomes and determine the relevant variables. David Foster Wallace had this great quote, “Bees have to move very fast to stay still.” And that’s what most of us do. We move a lot to stay in the same place. Buffett and Munger are getting further ahead each day.

Unless physics changes, for example, it’s unlikely that we’ll see the development of more efficient ways to move bulk freight. It doesn’t seem subject to technological disruption, but instead will likely be aided by technology. Technology helps improve the management of your rail network, but it’s not going to replace the entire network anytime soon. I think that Berkshire is actually moving away from uncertainty by pursuing companies like this. If you don’t know the range of outcomes, you will have a hard time assessing probabilities. One of the things that decision journals help identify is outcomes outside of what we expected. That’s a very humbling experience. After identifying possible outcomes and applying confidence levels, it’s humbling to get it so wrong

You have also studied an investment firm that’s probably as different from Berkshire Hathaway as possible with your most recent podcast with Chris Dixon of Andreessen Horowitz. What are your thoughts on good decision making as applied in the venture capital world and how is it different than Berkshire Hathaway?

Chris was an excellent guest to have on The Knowledge Project. He operates in Venture Capital—a world I don’t get much exposure to. He has insight on things I know very little about: venture funding, how to structure a venture capital firm so that you are adding value, etc. And they’ve been very successful.

I think we’re largely operating in unprecedented territory given the magnitude of private valuations. In past decades, companies IPO’d at much lower valuations so public market investors could more easily participate in their success. I don’t know how this plays out, but talking to Chris was fascinating.

Andreessen Horowitz has a very different operational approach as compared to Berkshire Hathaway. As I understood it, they are trying to add value to the entrepreneurs. Also, they’ve moved away from a business or idea based sourcing process to one that is almost exclusively focused on the entrepreneur. That directly contradicts some of Buffett’s thoughts on the relative importance of a management team versus the underlying business.

It makes sense that they would have different approaches. I think it’s important to understand that there are things that we want to have in our mental tool box. But part of being an effective craftsman is knowing when they work and when they don’t. You can’t just pull out random tools and expect them to work.

In 2013, I did some consulting work on improving innovation in organizations and the most common thing that people were doing at the time to solve the innovation problem was copying Google’s 20% of time spent on independent innovative ideas.

You need to understand how that fits with the company culture.

I found this interesting for a number of reasons. It surprised me that every executive had it on the tip of their tongue, but there’s no large sample size for a successful innovation like this 20% idea. Google and, I think, 3M are the two most prominent examples. Google, at the time, I think they had only been around for 15 years. That’s a pretty small sample size for continuous innovation. Also, you need to understand how that fits with the company culture, and why it works even if you’re seeing it work. Why does it work at Google? Is it because of how it fits in the overall culture? The problem I see is that people are taking one piece of a large puzzle and thinking that it’s going to solve their problem. It might help. It might not. It’s just a tool. It reminds me of the group of blind people touching the different parts of the elephant.

Also, some of these innovation projects get done for the wrong reasons, and with the wrong incentives. If my boss asks me for ideas to help the company innovate and I give him an idea that sounds good, one that subconsciously reminds him of an article he read in Fortune about innovation, isn’t that basically good enough for me as an employee? Does it even matter if it works? In most organizations, am I really going to be held responsible for the success or failure of my innovation prescription? The organization might suffer, but will I suffer personally? Probably not. My lack of ability to think the problem through will probably be forgotten in time if the idea sounded good and relevant at the time. If it was defensible via Powerpoint. This is one reason hiring consultants rarely works as well as hoped.

So, we copy Google’s twenty percent innovation time. They’re an innovative company; they’re hip; they’re cool; we’re going to copy them. Okay, well, we can do that. It’s a good story. What gets lost is a potentially useful discussion like, “Maybe we should remove the things in our environment that take away from natural innovation, like all these meetings.” That’s a much tougher conversation, but just like taking away sugar works better than adding broccoli to your diet, taking things out of the corporate culture is often a better solution than adding new stuff. Munger has us paying attention to incentives because they really are driving the train. You have to get it right.

One big theme for you is the concept of life-long learning. What is your motivation to pursue it? Munger has called it a moral duty. Do you have similar feelings?
I wish I were as eloquent as him. I’ve always had to work harder. You just have to keep getting better every day. You have to keep learning. If you’re going to accomplish what you want to accomplish, it’s probably not through going home and watching Netflix every night, right? You have to learn how the world works. We have a huge statistical sample size of things that aren’t changing. There is an excellent letter by Chris Begg at East Coast Asset Management that discusses Peter Kaufman’s thoughts on this. Physics, math, and biology are things that change very, very slowly, if at all. Learning things in those disciplines is good. It’s practical, because that’s how the world works. Those are things that don’t change over time.

I think that, for me, it’s just become “How can I pass people that are smarter than me?” I think if I can get incrementally better every day, compounding will kick in and over a long enough time, I’m going to achieve the things that I want in life.

What could be better than constantly learning new things and discovering that you’re still curious? Most of us forget what it’s like to be six years old and asking “why?” all the time and trying to understand why things operate the way they do. It’s hard to still do that, but you can still carry that wonder with you into life and try to understand why things are happening and why success or failure happens.

Avoiding stupidity is easier than seeking brilliance. But that by itself is suboptimal. You also want to copy models of success.

We don’t necessarily have to come up with all of this stuff ourselves. We can see a better model and adopt it or, the parts of it that will help us along. Giving up on holding on to our own ideas is really important.

I don’t come up with almost anything that’s original. I aggregate and synthesize other people’s thoughts and put it into context for people. I think that those are things that I like to focus on, I have a passion for doing that. I’m doing it anyway because I get a lot of value out of reading, learning, and exploring the world, and I share that with people.

With regard to Mental Models, you spend a lot of time discussing their importance, but you also highlight their shortcomings. Can you discuss your view of the value of mental models?

It’s important to understand how we are likely to fool ourselves. Aside from the psychological factors, which Munger and Bevelin talk about extensively, there are other ways.

For example, we run organizations based on dashboards and metrics and we make decisions based on these numbers. Investors look at financial reports to make investment decisions.

We think that those numbers tell a story and, to some extent, they do. However, they don’t tell the full story. They are limited. For example, a strike-out can be a good thing in baseball. Players who suck statistically in one system can thrive as a part of another – the whole “Moneyball” idea lives here, and the Patriots have been extremely successful with a wide variety of talent. In business, reported depreciation can be widely off. The accounting could be gamed. A tailwind could be benefitting a business temporarily, soon to dissipate. Many companies look their absolute best, on historical figures, just before the big denouement.

“All models are false but some are useful.”

— George Box

There is a great quote by George Box who said “All models are false but some are useful.” Practically speaking, we have to work with reductions—like maps. A map with a scale of one foot to one foot wouldn’t be useful, would it? Knowing that we’re working with reductions of reality, not reality itself, should give us pause. We recently wrote a piece on Farnam Street called “The Map is Not the Territory,” which is a more in-depth exploration of the nuances behind this.

Knowing how to dig in and understand these maps and their limitations is important. A lot of models are core – they don’t change very much. Social proof is real. Incentives do drive human behavior, financial and otherwise. The margin of safety approach from engineering works across many, many practical areas of life. Those are the types of huge, important models you want to focus on as a part of becoming a generally wise person. You need to learn them and learn how to synthesize with them. From there, you layer in the models that are specific to your job or your area of desired expertise. If you’re a bank investor, you’re going to look to attain a deep fluency in bank accounting that a neurosurgeon wouldn’t need. But both the analyst and the surgeon can understand and use the margin of safety idea practically and profitably.

Essentially, they can be powerful if used correctly, but we can also over apply them in some ways?

They work sometimes and not other times. You need to be aware of limitations. The point here is just to be cautious—the map is not the terrain. It doesn’t tell the full story.

Do you have any other investors or companies outside of Berkshire Hathaway that really have some profound thinking or you really love reading their shareholder letters or you’ve learned a lot from? Anything like that that we can talk about?

Berkshire has an incredibly unique model of writing to shareholders, and frankly no one else is as good. One that’s slightly off the beaten path, although it’s become a lot better known over the past few years, is a Canadian company called Constellation Software (CSU). The CEO there is truly doing God’s work as far as how he reports to shareholders. Very clear presentation of the financial performance of the business, and a lucid and honest discussion of what’s going on.

There are two key components to reporting to shareholders well, as I see it. One is presenting, in as clear a way as possible, the results in the prior periods. Presented consistently and honestly over time. The second is being extremely forthcoming about why these figures came out the way they did; good or bad, warts and all. When Blue Chip Stamps was still a reporting company, Munger would write about See’s Candy. What did his summary table show every year? Pounds of candy sold, stores open, total revenue, total profits. The key variables. Then he explained in clear language why See’s was a good business and what had occurred in the most recent period, and if possible, what he foresaw in general for the following year. That’s what we need more of: give investors an updated report of the major drivers and then tell us what happened. Leave out the fluff. You don’t need to write essays like Buffett. Just help us understand the business and what’s going on.

This has been great, Shane. Thanks so much for your time.

How Darwin Thought: The Golden Rule of Thinking

In his 1986 speech at the commencement of Harvard-Westlake School in Los Angeles (found in Poor Charlie’s Almanack) Charlie Munger gave a short Johnny Carson-like speech on the things to avoid to end up with a happy and successful life. One of his most salient prescriptions comes from the life of Charles Darwin:

It is my opinion, as a certified biography nut, that Charles Robert Darwin would have ranked in the middle of the Harvard School graduating class if 1986. Yet he is now famous in the history of science. This is precisely the type of example you should learn nothing from if bent on minimizing your results from your own endowment.

Darwin’s result was due in large measure to his working method, which violated all my rules for misery and particularly emphasized a backward twist in that he always gave priority attention to evidence tending to disconfirm whatever cherished and hard-won theory he already had. In contrast, most people early achieve and later intensify a tendency to process new and disconfirming information so that any original conclusion remains intact. They become people of whom Philip Wylie observed: “You couldn’t squeeze a dime between what they already know and what they will never learn.”

The life of Darwin demonstrates how a turtle may outrun a hare, aided by extreme objectivity, which helps the objective person end up like the only player without a blindfold in a game of Pin the Tail on the Donkey.

Charles Darwin (Via Wikipedia)

The great Harvard biologist E.O. Wilson agreed. In his book, Letters to a Young Scientist, Wilson argued that Darwin would have probably scored in the 130 range on a standard IQ test. And yet there he is, buried next to the calculus-inventing genius Isaac Newton in Westminster Abbey. (As Munger often notes.)

I had, also, during many years, followed a golden rule, namely, that whenever a published fact, a new observation or thought came across me, which was opposed to my general results, to make a memorandum of it without fail and at once; for I had found by experience that such facts and thoughts were far more apt to escape from memory than favorable ones.

What can we learn from the working and thinking habits of Darwin?

Extreme Focus Combined with Attentive Energy

The first clue comes from his own autobiography. Darwin was a hoover of information related to a topic he was interested in. After describing some of his specific areas of study while aboard the H.M.S. Beagle, Darwin concludes in his Autobiography:

The above various special studies were, however, of no importance compared with the habit of energetic industry and of concentrated attention to whatever I was engaged in, which I then acquired. Everything about which I thought or read was made to bear directly on what I had seen and was likely to see; and this habit of mind was continued during the five years of the voyage. I feel sure that it was this training which has enabled me to do whatever I have done in science.

This habit of pure and attentive focus to the task at hand is, of course, echoed in many of our favorite thinkers, from Sherlock Holmes, to E.O. Wilson, Feynman, Einstein, and others. Munger himself remarked that “I did not succeed in life by intelligence. I succeeded because I have a long attention span.”

In Darwin’s quest, there was almost nothing relevant to his task at hand — the problem of understanding the origin and development of species — which might have escaped his attention. He had an extremely broad antenna. Says David Quammen in his fabulous The Reluctant Mr. Darwin:

One of Darwin’s great strengths as a scientist was also, in some ways, a disadvantage: his extraordinary breadth of curiosity. From his study at Down House he ranged widely and greedily, in his constant search for data, across distances (by letter) and scientific fields. He read eclectically and kept notes like a pack rat. Over the years he collected an enormous quantity of interconnected facts. He looked for patterns but was intrigued equally by exceptions to the patterns, and exceptions to the exceptions. He tested his ideas against complicated groups of organisms with complicated stories, such as the barnacles, the orchids, the social insects, the primroses, and the hominids.

Not only was Darwin thinking broadly, taking in facts at all turns and on many subjects, but he was thinking carefully, This is where Munger’s admiration comes in: Darwin wanted to look at the exceptions. The exceptions to the exceptions. He was on the hunt for truth and not necessarily to confirm some highly-loved idea. Simply put, he didn’t want to be wrong about the nature of reality. To get the theory whole and correct would take lots of detail and time, as we will see.


The habit of study and observation didn’t stop at the plant and animal kingdom for Darwin. In a move that might seem strange by today’s standards, Darwin even opened a notebook to study the development of his own newborn son, William. This is from one of his notebooks:

Natural History of Babies

Do babies start (i.e., useless sudden movement of muscles) very early in life. Do they wink, when anything placed before their eyes, very young, before experience can have taught them to avoid danger. Do they know frown when they first see it?

From there, as his child grew and developed, Darwin took close notes. How did he figure out that the reflection in the mirror was him? How did he then figure out it was only an image of him, and that any other images that showed up (say, Dad standing behind him) were mere images too – not reality? These were further data in Darwin’s mental model of the accumulation of gradual changes, but more importantly, displayed his attention to detail. Everything eventually came to “bear directly on what I had seen and what I was likely to see.”

And in a practical sense, Darwin was a relentless note-taker. Notebook A, Notebook B, Notebook C, Notebook M, Notebook N…all filled with observations from his study of journals and texts, his own scientific work, his travels, and his life. Once he sat down to write, he had an enormous amount of prior written thought to draw on. He could also see gaps in his understanding, which he diligently filled in.

Become an Expert

You can learn much about Darwin (and truthfully about anyone) by who he studied and admired. If Darwin held anyone in high esteem, it was Charles Lyell, whose Principles of Geology was his faithful companion on the H.M.S. Beagle. Here is his description of Lyell from his autobiography, which tells us something of the traits Darwin valued and sought to emulate:

I saw more of Lyell than of any other man before and after my marriage. His mind was characterized, as it appeared to me, by clearness, caution, sound judgment and a good deal of originality. When I made any remark to him on Geology, he never rested until he saw the whole case clearly and often made me see it more clearly than I had done before. He would advance all possible objections to my suggestions, and even after these were exhausted would long remain dubious. A second characteristic was his hearty sympathy with the work of other scientific men.

Studying Lyell and geology enhanced Darwin’s (probably natural) suspicion that careful, detailed, and objective work was required to create scientific breakthroughs. And once Darwin had expertise and grounding in the level of expertise required by Lyell to understand and explain the theory of geology, he had a basis for the rest of his scientific work. From his autobiography:

After my return to England, it appeared to me that by following the example of Lyell in Geology, and by collecting all facts which bore in any way on the variation of animals and plants under domestication and nature, some light might perhaps be thrown on the whole subject.

In fact, it was Darwin’s study and understanding of geology itself that gave him something to lean on conceptually. Lyell’s, and his own, theory of geology was of a slow-moving process that accumulated massive gradual changes over time. This seems like common knowledge today, but at the time, people weren’t so sure that the mountains and the islands could have been created by such slow moving and incremental processes.

Wallace & Gruber’s book Creative People at Work, an analysis of a variety of thinkers and artists, argues that this basic mental model carried Darwin pretty far:

Why was the acquisition of expert knowledge in geology so important to the development of Darwin’s overall thinking? Because in learning geology Darwin ground a conceptual lens — a device for bringing into focus and clarifying the problems to which he turned his attention. When his attention shifted to problems beyond geology, the lens remained and Darwin used it in exploring new problems.


(Darwin’s) coral reef theory shows that he had become an expert in one field…(and) the central idea in Darwin’s understanding of geology was “gradualism” — that great things could be produced by long, continued accumulation of very small effects. The next phase in the development of this thought-form would involve his use of it as the basis for the construction of analogies between geology and new, unfamiliar subjects.


Darwin wrote his most explicit and concise statement of the nature and utility of his gradualism thought-form: “This multiplication of little means and brinigng the mind to grapple with great effect produced is a most laborious & painful effort of the mind.” He recognized that it took patience and discipline to discover the “little means” that were responsible for great effects. With the necessary effort, however, this gradualism thought-form could become the vehicle for explaining many remarkable phenomena in geology, biology, and even psychology.

It is amazing to note that Darwin did not write The Origin of Species until 1859 even though his notebooks show he had been pretty close to the correct idea at least 15 or 20 years prior. What was he doing in all that time? Well, for eight years at least, he was studying barnacles.


One of the reasons Darwin went on a crusade of classifying and studying the barnacles in minute detail was his concern that if he wasn’t a primary expert on some portion of the natural world, his work on a larger and more general thesis would not be taken seriously, and that it would probably have holes. He said as much to his friend Frederic Gerard, a French botanist, before he had begun his barnacle work: “How painfully (to me) true is your remark that no one has hardly a right to examine the question of species who has not minutely described many.” And, of course, Darwin being Darwin, he spent eight years remedying that unfathomable situation.

It seemed like extraordinarily tedious work, unrelated to anything a scientist would consider important on a grand scale. It was taxonomy. Classification. Even Darwin admitted later on that he doubted it was worth the years he spent on it. Yet, in his detail-oriented journey for expertise on barnacles, he hit upon some key ideas that would make his theory of natural selection complete. Says Quammen:

He also found notable differences on another categorical level; within species. Contrary to what he’d believed all along about the rarity of variation in the wild, barnacles turned out to be highly variable. A species wasn’t a Platonic essence or a metaphysical type. A species was a population of differing individuals.

He wouldn’t have seen that if he hadn’t assigned himself the trick job of drawing lines between one species and another. He wouldn’t have seen it if he hadn’t used his network of contacts and his good reputation as a naturalist to gather barnacle specimens, in quantity, from all over the world. The truth of variation only reveals itself in crowds. He wouldn’t have seen it if he hadn’t examined multiple individuals, not just single representatives, of as many species as possible….Abundant variation among barnacles filled a crucial role in his theory. Here they were, the minor differences on which natural selection works.

Darwin was so diligent it could be breathtaking at times. Quammen describes him gathering up various species to assess the data about their development and their variation. Birds, dead or alive, as many as possible. Foxes, dogs, ducks, pigeons, rabbits, cats…nothing escaped his purview. As many specimens as he could get his hands on. All while living in a secluded house in Victorian England, beset by constant illness. He was Big Data before Big Data was a thing, trying to suss out conclusions from a mass of observation.

The Golden Rule

Eventually, his work led him to something new: Species are not immutable, they are all part of the same family tree. They evolve through a process of variation — he didn’t know how; that took years for others to figure out through the study of genetics — and differential survival through natural selection.

Darwin was able to put his finger on why it took so long for humanity to come to this correct theory: It was extremely counter-intuitive to how one would naturally see the world. He admitted as much in the Origin of Species‘ concluding chapter:

The chief cause of our natural unwillingness to admit that one species has given birth to other and distinct species, is that we are always slow in admitting any great changes of which we do not see the steps. The difficulty is the same as that felt by so many geologists, when Lyell first insisted that long lines of inland cliffs had been formed, and great valleys excavated, by the agencies which we still see at work. The mind cannot possibly grasp the full meaning of the term of even a million years; it cannot add up and perceive the full effects of many slight variations, accumulated during an almost infinite number of generations.

Counter-intuition was Darwin’s specialty. And the reason he was so good was he had a very simple habit of thought, described in the autobiography and so cherished by Charlie Munger: He paid special attention to collecting facts which did not agree with his prior conceptions. He called this a golden rule.

I had, also, during many years, followed a golden rule, namely, that whenever a published fact, a new observation or thought came across me, which was opposed to my general results, to make a memorandum of it without fail and at once; for I had found by experience that such facts and thoughts were far more apt to escape from memory than favorable ones. Owing to this habit, very few objections were raised against my views which I had not at least noticed and attempted to answer.

So we see that Darwin’s great success, by his own analysis, owed to his ability to see, note, and learn from objections to his cherished thoughts. The Origin of Species has stood up in the face of 157 years of subsequent biological research because Darwin was so careful to make sure the theory was nearly impossible to refute. Later scientists would find the book slightly incomplete, but not incorrect.

This passage reminds one of, and probably influenced, Charlie Munger‘s prescription on the work required to hold an opinion: You must understand the opposite side of the argument better than the person holding that side does. It’s a very difficult way to think, tremendously unnatural in the face of our genetic makeup (the more typical response is to look for as much confirming evidence as possible). Harnessed properly, though, it is a powerful way to beat your own shortcomings and become a seeing man amongst the blind.

Thus, we can deduce that, in addition to good luck and good timing, it was Darwin’s habits of completeness, diligence, accuracy, and habitual objectivity which ultimately led him to make his greatest breakthroughs. It was tedious. There was no spark of divine insight that gave him his edge. He just started with the right basic ideas and the right heroes, and then worked for a long time and with extreme focus and objectivity, always keeping his eye on reality.

In the end, you can do worse than to read all you can find on Charles Darwin and try to copy his mental habits. They will serve you well over a long life.

Peter Thiel on the End of Hubris and the Lessons from the Internet Bubble of the Late 90s

The best interview question — what important truth do very few people agree with you on?— is tough to answer. Just think about it for a second.

In his book Zero to One, Peter Thiel argues that it might be easier to start with what everyone seems to agree on and go until you disagree.

If you can identify a delusional popular belief, you can find what lies hidden behind it: the contrarian truth.

Consider the proposition that companies should make money for their shareholders and not lose it. This seems self-evident, but it wasn’t so obvious to many in the late 90s. Remember back then? No loss was too big. (In my interview with Sanjay Bakshi he suggested that to some extent this still exists today.)

Making money? That was old school. In the late 1990s, it was all about the new economy. Eyeballs first, profits later.

Conventional beliefs only ever come to appear arbitrary and wrong in retrospect; whenever one collapses, we call the old belief a bubble. But the distortions caused by bubbles don’t disappear when they pop. The internet craze of the ’90s was the biggest bubble since the crash of 1929, and the lessons learned afterward define and distort almost all thinking about technology today. The first step to thinking clearly is to question what we think we know about the past.

There’s really no need to rehash the 1990s in this article. You can google it. Or you can read the summary in chapter two of Zero to One.

Where things get interesting, at least in the thinking context, are the lessons we drew from the late 90s. Thiel says the following were lessons most commonly learned:

The entrepreneurs who stuck with Silicon Valley learned four big lessons from the dot-com crash that still guide business thinking today:

1. Make incremental advances. Grand visions inflated the bubble, so they should not be indulged. Anyone who claims to be able to do something great is suspect, and anyone who wants to change the world should be more humble. Small, incremental steps are the only safe path forward.

2. Stay lean and flexible. All companies must be “lean,” which is code for “unplanned.” You should not know what your business will do; planning is arrogant and inflexible. Instead you should try things out, “iterate,” and treat entrepreneurship as agnostic experimentation.

3. Improve on the competition. Don’t try to create a new market prematurely. The only way to know you have a real business is to start with an already existing customer, so you should build your company by improving on recognizable products already offered by successful competitors.

4. Focus on product, not sales. If your product requires advertising or salespeople to sell it, it’s not good enough: technology is primarily about product development, not distribution. Bubble-era advertising was obviously wasteful, so the only sustainable growth is viral growth.

These lessons, Thiel argues, are now dogma in the startup world. Ignore them at your peril and risk near-certain failure. In fact, many private companies I’ve worked with have adopted the same view. Governments too are attempting to replicate these ‘facts’ — they have become conventional wisdom.

And yet … the opposites are probably just as true if not more correct.

1. It is better to risk boldness than triviality.
2. A bad plan is better than no plan.
3. Competitive markets destroy profits.
4. Sales matters just as much as product.

Such is the world of messy social science — hard and fast rules are difficult to come by, and frequently, good ideas lose value as they gain popularity. (This is the “everyone on their tip-toes at a parade” idea.) Just as importantly, what starts as a good hand tends to be overplayed by man-with-a-hammer types.

And so the lessons which have been culled from the tech crash are not necessarily wrong, they are just context-dependent. It is hard to generalize with them.

According to Thiel, we must learn to use our brains as well as our emotions:

We still need new technology, and we may even need some 1999-style hubris and exuberance to get it. To build the next generation of companies, we must abandon the dogmas created after the crash. That doesn’t mean the opposite ideas are automatically true: you can’t escape the madness of crowds by dogmatically rejecting them. Instead ask yourself: how much of what you know about business is shaped by mistaken reactions to past mistakes? The most contrarian thing of all is not to oppose the crowd but to think for yourself.

In a nutshell, when everyone learns the same lessons, applying them to the point of religious devotion, there can be an opportunity in the opposite. If everyone is thinking the same thing, no one is really thinking.

As Alfred Sloan, the heroic former CEO of General Motors, once put it:

If we are all in agreement on the decision – then I propose we postpone further discussion of this matter until our next meeting to give ourselves time to develop disagreement and perhaps gain some understanding of what the decision is all about.

How to Think: The Skill You’ve Never Been Taught

“I’ve spent my life trying to undo habits—especially habits of thinking. They narrow your interaction with the world. They’re the phrases that come easily to your mind, like: ‘I know what I think,’ or ‘I know what I like,’ or ‘I know what’s going to happen today.’ If you just replace ‘know’ with ‘don’t know,’ then you start to move into the unknown. And that’s where the interesting stuff happens.”  — Humans of New York


No skill is more valuable and harder to come by than the ability to critically think through problems. And schools don’t teach you a method of thinking, you have to do the work yourself. Those who do it well get an advantage and those that do it poorly pay a tax.

Poor initial decisions are one of the reasons we’re so busy. With poor thinking, a large chunk of your time is spent correcting mistakes. Good thinking, on the other hand, produces better initial decisions and frees up time and energy.

I’ve read Solitude and Leadership, an essay by William Deresiewicz before. In fact, I even pointed out some of its leadership lessons. However, after Peter Kaufman prompted a re-visit to the very same essay, I realized that I missed a key part.

How do you learn to think?

Let’s start with how you don’t learn to think. A study by a team of researchers at Stanford came out a couple of months ago. The investigators wanted to figure out how today’s college students were able to multitask so much more effectively than adults. How do they manage to do it, the researchers asked? The answer, they discovered—and this is by no means what they expected—is that they don’t. The enhanced cognitive abilities the investigators expected to find, the mental faculties that enable people to multitask effectively, were simply not there. In other words, people do not multitask effectively. And here’s the really surprising finding: the more people multitask, the worse they are, not just at other mental abilities, but at multitasking itself.

One thing that made the study different from others is that the researchers didn’t test people’s cognitive functions while they were multitasking. They separated the subject group into high multitaskers and low multitaskers and used a different set of tests to measure the kinds of cognitive abilities involved in multitasking. They found that in every case the high multitaskers scored worse. They were worse at distinguishing between relevant and irrelevant information and ignoring the latter. In other words, they were more distractible. They were worse at what you might call “mental filing”: keeping information in the right conceptual boxes and being able to retrieve it quickly. In other words, their minds were more disorganized. And they were even worse at the very thing that defines multitasking itself: switching between tasks.

Multitasking, in short, is not only not thinking, it impairs your ability to think. Thinking means concentrating on one thing long enough to develop an idea about it. Not learning other people’s ideas, or memorizing a body of information, however much those may sometimes be useful. Developing your own ideas. In short, thinking for yourself. You simply cannot do that in bursts of 20 seconds at a time, constantly interrupted by Facebook messages or Twitter tweets, or fiddling with your iPod, or watching something on YouTube.

I find for myself that my first thought is never my best thought. My first thought is always someone else’s; it’s always what I’ve already heard about the subject, always the conventional wisdom. It’s only by concentrating, sticking to the question, being patient, letting all the parts of my mind come into play, that I arrive at an original idea. By giving my brain a chance to make associations, draw connections, take me by surprise. And often even that idea doesn’t turn out to be very good. I need time to think about it, too, to make mistakes and recognize them, to make false starts and correct them, to outlast my impulses, to defeat my desire to declare the job done and move on to the next thing.

I used to have students who bragged to me about how fast they wrote their papers. I would tell them that the great German novelist Thomas Mann said that a writer is someone for whom writing is more difficult than it is for other people. The best writers write much more slowly than everyone else, and the better they are, the slower they write. James Joyce wrote Ulysses, the greatest novel of the 20th century, at the rate of about a hundred words a day—half the length of the selection I read you earlier from Heart of Darkness—for seven years. T. S. Eliot, one of the greatest poets our country has ever produced, wrote about 150 pages of poetry over the course of his entire 25-year career. That’s half a page a month. So it is with any other form of thought. You do your best thinking by slowing down and concentrating.

The best way to improve your ability to think is to spend time thinking.

“It’s only by concentrating, sticking to the question, being patient, letting all the parts of my mind come into play, that I arrive at an original idea. By giving my brain a chance to make associations, draw connections, take me by surprise”

— William Deresiewicz