This is the last part of a four-part series on Elon Musk’s companies. For an explanation of why this series is happening and how Musk is involved, start with Part 1.11 ← also click these
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Welcome to the last post in the series on the world of Elon Musk.
It’s been a long one, I know. A long series with long posts and a long time between posts. It turns out that when it comes to Musk and his shit, there was a lot to say.
Anyone who’s read the first three posts in this series is aware that I’ve not only been buried in the things Musk is doing, I’ve been drinking a tall glass of the Elon Musk Kool-Aid throughout. I’m very, very into it.
I kind of feel like that’s fine, right? The dude is a steel-bending industrial giant in America in a time when there aren’t supposed to be steel-bending industrial giants in America, igniting revolutions in huge, old industries that aren’t supposed to be revolutionable. After emerging from the 1990s dotcom party with $180 million, instead of sitting back in his investor chair listening to pitches from groveling young entrepreneurs, he decided to start a brawl with a group of 900-pound sumo wrestlers—the auto industry, the oil industry, the aerospace industry, the military-industrial complex, the energy utilities—and he might actually be winning. And all of this, it really seems, for the purpose of giving our species a better future.
Pretty Kool-Aid worthy. But someone being exceptionally rad isn’t Kool-Aid worthy enough to warrant 90,000 words over a string of months on a blog that’s supposed to be about a wide range of topics.
During the first post, I laid out the two objectives for the series:
1) To understand why Musk is doing what he’s doing.
2) To understand why Musk is able to do what he’s doing.
So far, we’ve spent most of the time exploring objective #1. But what really intrigued me as I began thinking about this was objective #2. I’m fascinated by those rare people in history who manage to dramatically change the world during their short time here, and I’ve always liked to study those people and read their biographies. Those people know something the rest of us don’t, and we can learn something valuable from them. Getting access to Elon Musk gave me what I decided was an unusual chance to get my hands on one of those people and examine them up close. If it were just Musk’s money or intelligence or ambition or good intentions that made him so capable, there would be more Elon Musks out there. No, it’s something else—what TED curator Chris Anderson called Musk’s “secret sauce”—and for me, this series became a mission to figure it out.
The good news is, after a lot of time thinking about this, reading about this, and talking to him and his staff, I think I’ve got it. What for a while was a large pile of facts, observations, and sound bites eventually began to congeal into a common theme—a trait in Musk that I believe he shares with many of the most dynamic icons in history and that separates him from almost everybody else.
As I worked through the Tesla and SpaceX posts, this concept kept surfacing, and it became clear to me that this series couldn’t end without a deep dive into exactly what it is that Musk and a few others do so unusually well. The thing that tantalized me is that this secret sauce is actually accessible to everyone and right there in front of us—if we can just wrap our heads around it. Mulling this all over has legitimately affected the way I think about my life, my future, and the choices I make—and I’m going to try my best in this post to explain why.
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Two Kinds of Geology
In 1681, English theologian Thomas Burnet published Sacred Theory of the Earth, in which he explained how geology worked. What happened was, around 6,000 years ago, the Earth was formed as a perfect sphere with a surface of idyllic land and a watery interior. But then, when the surface dried up a little later, cracks formed in its surface, releasing much of the water from within. The result was the Biblical Deluge and Noah having to deal with a ton of shit all week. Once things settled down, the Earth was no longer a perfect sphere—all the commotion had distorted the surface, bringing about mountains and valleys and caves down below, and the whole thing was littered with the fossils of the flood’s victims.
And bingo. Burnet had figured it out. The great puzzle of fundamental theology had been to reconcile the large number of seemingly-very-old Earth features with the much shorter timeline of the Earth detailed in the Bible. For theologians of the time, it was their version of the general relativity vs. quantum mechanics quandary, and Burnet had come up with a viable string theory to unify it all under one roof.
It wasn’t just Burnet. There were enough theories kicking around reconciling geology with the verses of the Bible to today warrant a 15,000-word “Flood Geology” Wikipedia page.
Around the same time, another group of thinkers started working on the geology puzzle: scientists.
For the theologian puzzlers, the starting rules of the game were, “Fact: the Earth began 6,000 years ago and there was at one point an Earth-sweeping flood,” and their puzzling took place strictly within that context. But the scientists started the game with no rules at all. The puzzle was a blank slate where any observations and measurements they found were welcome.
Over the next 300 years, the scientists built theory upon theory, and as new technologies brought in new types of measurements, old theories were debunked and replaced with new updated versions. The science community kept surprising themselves as the apparent age of the Earth grew longer and longer. In 1907, there was a huge breakthrough when American scientist Bertram Boltwood pioneered the technique of deciphering the age of rocks through radiometric dating, which found elements in a rock with a known rate of radioactive decay and measured what portion of those elements remained intact and what portion had already converted to decay substance.
Radiometric dating blew Earth’s history backwards into the billions of years, which burst open new breakthroughs in science like the theory of Continental Drift, which in turn led to the theory of Plate Tectonics. The scientists were on a roll.
Meanwhile, the flood geologists would have none of it. To them, any conclusions from the science community were moot because they were breaking the rules of the game to begin with. The Earth was officially less than 6,000 years old, so if radiometric dating showed otherwise, it was a flawed technique, period.
But the scientific evidence grew increasingly compelling, and as time wore on, more and more flood geologists threw in the towel and accepted the scientist’s viewpoint-maybe they had had the rules of the game wrong.
Some, though, held strong. The rules were the rules, and it didn’t matter how many people agreed that the Earth was billions of years old—it was a grand conspiracy.
Today, there are still many flood geologists making their case. Just recently, an author named Tom Vail wrote a book called Grand Canyon: A Different View, in which he explains:
Contrary to what is widely believed, radioactive dating has not proven the rocks of the Grand Canyon to be millions of years old. The vast majority of the sedimentary layers in the Grand Canyon were deposited as the result of a global flood that occurred after and as a result of the initial sin that took place in the Garden of Eden.
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If the website analytics stats on Chartbeat included a “Type of Geologist” demographic metric, I imagine that for Wait But Why readers, the breakdown would look something like this:
It makes sense. Whether religious or not, most people who read this site are big on data, evidence, and accuracy. I’m reminded of this every time I make an error in a post.
Whatever role faith plays in the spiritual realm, what most of us agree on is that when seeking answers to our questions about the age of the Earth, the history of our species, the causes of lightning, or any other physical phenomenon in the universe, data and logic are far more effective tools than faith and scripture.
And yet—after thinking about this for a while, I’ve come to an unpleasant conclusion:
When it comes to most of the way we think, the way we make decisions, and the way we live our lives, we’re much more like the flood geologists than the science geologists.
And Elon’s secret? He’s a scientist through and through.
Hardware and Software
The first clue to the way Musk thinks is in the super odd way that he talks. For example:
Human child: “I’m scared of the dark, because that’s when all the scary shit is gonna get me and I won’t be able to see it coming.”
Elon: “When I was a little kid, I was really scared of the dark. But then I came to understand, dark just means the absence of photons in the visible wavelength—400 to 700 nanometers. Then I thought, well it’s really silly to be afraid of a lack of photons. Then I wasn’t afraid of the dark anymore after that.”2
Or:
Human father: “I’d like to start working less because my kids are starting to grow up.”
Elon: “I’m trying to throttle back, because particularly the triplets are starting to gain consciousness. They’re almost two.”3
Or:
Human single man: “I’d like to find a girlfriend. I don’t want to be so busy with work that I have no time for dating.”
Elon: “I would like to allocate more time to dating, though. I need to find a girlfriend. That’s why I need to carve out just a little more time. I think maybe even another five to 10 — how much time does a woman want a week? Maybe 10 hours? That’s kind of the minimum? I don’t know.”4
I call this MuskSpeak. MuskSpeak is a language that describes everyday parts of life as exactly what they actually, literally are.
There are plenty of instances of technical situations when we all agree that MuskSpeak makes much more sense than normal human parlance—
—but what makes Musk odd is that he thinks about most things in MuskSpeak, including many areas where you don’t usually find it. Like when I asked him if he was afraid of death, and he said having kids made him more comfortable with dying, because “kids sort of are a bit you. At least they’re half you. They’re half you at the hardware level, and depending on how much time you have with them, they’re that percentage of you at the software level.”
When you or I look at kids, we see small, dumb, cute people. When Musk looks at his five kids, he sees five of his favorite computers. When he looks at you, he sees a computer. And when he looks in the mirror, he sees a computer—his computer. It’s not that Musk suggests that people are just computers—it’s that he sees people as computers on top of whatever else they are.
And at the most literal level, Elon’s right about people being computers. At its simplest definition, a computer is an object that can store and process data—which the brain certainly is.
And while this isn’t the most poetic way to think about our minds, I’m starting to believe that it’s one of those areas of life where MuskSpeak can serve us well—because thinking of a brain as a computer forces us to consider the distinction between our hardware and our software, a distinction we often fail to recognize.
For a computer, hardware is defined as “the machines, wiring, and other physical components of a computer.” So for a human, that’s the physical brain they were born with and all of its capabilities, which determines their raw intelligence, their innate talents, and other natural strengths and shortcomings.
A computer’s software is defined as “the programs and other operating information used by a computer.” For a human, that’s what they know and how they think—their belief systems, thought patterns, and reasoning methods. Life is a flood of incoming data of all kinds that enter the brain through our senses, and it’s the software that assesses and filters all that input, processes and organizes it, and ultimately uses it to generate the key output—a decision.
The hardware is a ball of clay that’s handed to us when we’re born. And of course, not all clay is equal—each brain begins as a unique combination of strengths and weaknesses across a wide range of processes and capabilities.
But it’s the software that determines what kind of tool the clay gets shaped into.
When people think about what makes someone like Elon Musk so effective, they often focus on the hardware—and Musk’s hardware has some pretty impressive specs. But the more I learn about Musk and other people who seem to have superhuman powers—whether it be Steve Jobs, Albert Einstein, Henry Ford, Genghis Khan, Marie Curie, John Lennon, Ayn Rand,2 or Louis C.K.—the more I’m convinced that it’s their software, not their natural-born intelligence or talents, that makes them so rare and so effective.
So let’s talk about software—starting with Musk’s. As I wrote the other three posts in this series, I looked at everything I was learning about Musk—the things he says, the decisions he makes, the missions he takes on and how he approaches them—as clues to how his underlying software works.
Eventually, the clues piled up and the shape of the software began to reveal itself. Here’s what I think it looks like:
Elon’s Software
The structure of Musk’s software starts like many of ours, with what we’ll call the Want box:
This box contains anything in life where you want Situation A to turn into Situation B. Situation A is currently what’s happening and you want something to change so that Situation B is what’s happening instead. Some examples:
Next, the Want box has a partner in crime—what we’ll call the Reality box. It contains all things that are possible:
Pretty straightforward.
The overlap of the Want and Reality boxes is the Goal Pool, where your goal options live:3
So you pick a goal from the pool—the thing you’re going to try to move from Point A to Point B.
And how do you cause something to change? You direct your power towards it. A person’s power can come in various forms: your time, your energy (mental and physical), your resources, your persuasive ability, your connection to others, etc.
The concept of employment is just Person A using their resources power (a paycheck) to direct Person B’s time and/or energy power toward Person A’s goal. When Oprah publicly recommends a book, that’s combining her abundant power of connection (she has a huge reach) and her abundant power of persuasion (people trust her) and directing them towards the goal of getting the book into the hands of thousands of people who would have otherwise never known about it.
Once a goal has been selected, you know the direction in which to point your power. Now it’s time to figure out the most effective way to use that power to generate the outcome you want—that’s your strategy:
Simple right? And probably not that different from how you think.
But what makes Musk’s software so effective isn’t its structure, it’s that he uses it like a scientist. Carl Sagan said, “Science is a way of thinking much more than it is a body of knowledge,” and you can see Musk apply that way of thinking in two key ways:
1) He builds each software component himself, from the ground up.
Musk calls this “reasoning from first principles.” I’ll let him explain:
I think generally people’s thinking process is too bound by convention or analogy to prior experiences. It’s rare that people try to think of something on a first principles basis. They’ll say, “We’ll do that because it’s always been done that way.” Or they’ll not do it because “Well, nobody’s ever done that, so it must not be good.” But that’s just a ridiculous way to think. You have to build up the reasoning from the ground up—“from the first principles” is the phrase that’s used in physics. You look at the fundamentals and construct your reasoning from that, and then you see if you have a conclusion that works or doesn’t work, and it may or may not be different from what people have done in the past.5
In science, this means starting with what evidence shows us to be true. A scientist doesn’t say, “Well we know the Earth is flat because that’s the way it looks, that’s what’s intuitive, and that’s what everyone agrees is true,” a scientist says, “The part of the Earth that I can see at any given time appears to be flat, which would be the case when looking at a small piece of many differently shaped objects up close, so I don’t have enough information to know what the shape of the Earth is. One reasonable hypothesis is that the Earth is flat, but until we have tools and techniques that can be used to prove or disprove that hypothesis, it is an open question.”
A scientist gathers together only what he or she knows to be true—the first principles—and uses those as the puzzle pieces with which to construct a conclusion.
Reasoning from first principles is a hard thing to do in life, and Musk is a master at it. Brain software has four major decision-making centers:
1) Filling in the Want box
2) Filling in the Reality box
3) Goal selection from the Goal Pool
4) Strategy formation
Musk works through each of these boxes by reasoning from first principles. Filling in the Want box from first principles requires a deep, honest, and independent understanding of yourself. Filling in the Reality box requires the clearest possible picture of the actual facts of both the world and your own abilities. The Goal Pool should double as a Goal Selection Laboratory that contains tools for intelligently measuring and weighing options. And strategies should be formed based on what you know, not on what is typically done.
2) He continually adjusts each component’s conclusions as new information comes in.
You might remember doing proofs in geometry class, one of the most mundane parts of everyone’s childhood. These ones:
Given: A = B
Given: B = C + D
Therefore: A = C + D
Math is satisfyingly exact. Its givens are exact and its conclusions are airtight.
In math, we call givens “axioms,” and axioms are 100% true. So when we build conclusions out of axioms, we call them “proofs,” which are also 100% true.
Science doesn’t have axioms or proofs, for good reason.
We could have called Newton’s law of universal gravitation a proof—and for a long time, it certainly seemed like one—but then what happens when Einstein comes around and shows that Newton was actually “zoomed in,” like someone calling the Earth flat, and when you zoom way out, you discover that the real law is general relativity and Newton’s law actually stops working under extreme conditions, while general relativity works no matter what. So then, you’d call general relativity a proof instead. Except then what happens when quantum mechanics comes around and shows that general relativity fails to apply on a tiny scale and that a new set of laws is needed to account for those cases.
There are no axioms or proofs in science because nothing is for sure and everything we feel sure about might be disproven. Richard Feynman has said, “Scientific knowledge is a body of statements of varying degrees of certainty—some most unsure, some nearly sure, none absolutely certain.” Instead of proofs, science has theories. Theories are based on hard evidence and treated as truths, but at all times they’re susceptible to being adjusted or disproven as new data emerges.
So in science, it’s more like:
Given (for now): A = B
Given (for now): B = C + D
Therefore (for now): A = C + D
In our lives, the only true axiom is “I exist.” Beyond that, nothing is for sure. And for most things in life, we can’t even build a real scientific theory because life doesn’t tend to have exact measurements.
Usually, the best we can do is a strong hunch based on what data we have. And in science, a hunch is called a hypothesis. Which works like this:
Given (it seems, based on what I know): A = B
Given (it seems, based on what I know): B = C + D
Therefore (it seems, based on what I know): A = C + D
Hypotheses are built to be tested. Testing a hypothesis can disprove it or strengthen it, and if it passes enough tests, it can be upgraded to a theory.
So after Musk builds his conclusions from first principles, what does he do? He tests the shit out of them, continually, and adjusts them regularly based on what he learns. Let’s go through the whole process to show how:
You begin by reasoning from first principles to A) fill in the Want box, B) fill in the Reality box, C) select a goal from the pool, and D) build a strategy—and then you get to work. You’ve used first principles thinking to decide where to point your power and the most effective way to use it.
But the goal-achievement strategy you came up with was just your first crack. It was a hypothesis, ripe for testing. You test a strategy hypothesis one way: action. You pour your power into the strategy and see what happens. As you do this, data starts flowing in—results, feedback, and new information from the outside world. Certain parts of your strategy hypothesis might be strengthened by this new data, others might be weakened, and new ideas may have sprung to life in your head through the experience—but either way, some adjustment is usually called for:
As this strategy loop spins and your power becomes more and more effective at accomplishing your goal, other things are happening down below.
For someone reasoning from first principles, the Want box at any given time is a snapshot of their innermost desires the last time they thought hard about it. But the contents of the Want box are also a hypothesis, and experience can show you that you were wrong about something you thought you wanted or that you want something you didn’t realize you did. At the same time, the inner you isn’t a statue—it’s a shifting, morphing sculpture whose innermost values change as time passes. So even if something in the Want box was correct at one point, as you change, it may lose its place in the box. The Want box should serve the current inner you as best possible, which requires you to update it, something you do through reflection:
A rotating Want loop is called evolution.
On the other side of the aisle, the Reality box is also going through a process. “Things that are possible” is a hypothesis, maybe more so than anything else. It takes into account both the state of the world and your own abilities. And as your own abilities change and grow, the world changes even faster. What was possible in the world in 2005 is very different from what’s possible today, and it’s a huge (and rare) advantage to be working with an up-to-date Reality box.
Filling in your Reality box from first principles is a great challenge, and keeping the box current so that it matches actual reality takes continual work.
For each of these areas, the box represents the current hypothesis and the circle represents the source of new information that can be used to adjust the hypothesis. It’s our duty to remember that the circles are the boss, not the boxes—the boxes are only trying their best to do the circles proud. And if we fall out of touch with what’s happening in the circles, the info in the boxes becomes obsolete and a less effective source for our decision-making.
Thinking about the software as a whole, let’s take a step back. What we see is a goal formation mechanism below and a goal attainment mechanism above. One thing goal attainment often requires is laser focus. To get the results we want, we zoom in on the micro picture, sinking our teeth into our goal and honing in on it with our strategy loop.
But as time passes, the Want box and Reality box adjust contents and morph shape, and eventually, something else can happen—the Goal Pool changes.
The Goal Pool is just the overlap of the Want and Reality boxes, so its own shape and contents are totally dependent on the state of those boxes. And as you live your life inside the goal attainment mechanism above, it’s important to make sure that what you’re working so hard on remains in line with the Goal Pool below—so let’s add in two big red arrows for that:
Checking in with the large circle down below requires us to lift our heads up from the micro mission and do some macro reflection. And when enough changes happen in the Want and Reality boxes that the goal you’re pursuing is no longer in the goal pool, it calls for a macro life change—a breakup, a job switch, a relocation, a priority swap, an attitude shift.
All together, the software I’ve described is a living, breathing system, constructed on a rock solid foundation of first principles, and built to be nimble, to keep itself honest, and to change shape as needed to best serve its owner.
And if you read about Elon Musk’s life, you can watch this software in action.
How Musk’s software wrote his life story
Getting started
Step 1 for Elon was filling in the contents of the Want box. Doing this from first principles is a huge challenge—you have to dig deep into concepts like right and wrong, good and bad, important and trivial, valuable and frivolous. You have to figure out what you respect, what you disdain, what fascinates you, what bores you, and what excites you deep in your inner child. Of course, there’s no way for anyone of any age to have a clear cut answer to these questions, but Elon did the best thing he could by ignoring others and independently pondering.
I talked with him about his early thought process in figuring out what to do with his career. He has said many times that he cares deeply about the future well-being of the human species—something that is clearly in the center of his Want box. I asked how he came to that, and he explained:
The thing that I care about is—when I look into the future, I see the future as a series of branching probability streams. So you have to ask, what are we doing to move down the good stream—the one that’s likely to make for a good future? Because otherwise, you look ahead, and it’s like “Oh it’s dark.” If you’re projecting to the future, and you’re saying “Wow, we’re gonna end up in some terrible situation,” that’s depressing.
Fair. Honing in on his specific path, I brought up the great modern physicists like Einstein and Hawking and Feynman, and I asked him whether he considered going into scientific discovery instead of engineering. His response:
I certainly admire the discoveries of the great scientists. They’re discovering what already exists—it’s a deeper understanding of how the universe already works. That’s cool—but the universe already sort of knows that. What matters is knowledge in a human context. What I’m trying to ensure is that knowledge in a human context is still possible in the future. So it’s sort of like—I’m more like the gardener, and then there are the flowers. If there’s no garden, there’s no flowers. I could try to be a flower in the garden, or I could try to make sure there is a garden. So I’m trying to make sure there is a garden, such that in the future, many Feynmans may bloom.
In other words, both A and B are good, but without A there is no B. So I choose A.
He went on:
I was at one point thinking about doing physics as a career—I did undergrad in physics—but in order to really advance physics these days, you need the data. Physics is fundamentally governed by the progress of engineering. This debate—“Which is better, engineers or scientists? Aren’t scientists better? Wasn’t Einstein the smartest person?”—personally, I think that engineering is better because in the absence of the engineering, you do not have the data. You just hit a limit. And yeah, you can be real smart within the context of the limit of the data you have, but unless you have a way to get more data, you can’t make progress. Like look at Galileo. He engineered the telescope—that’s what allowed him to see that Jupiter had moons. The limiting factor, if you will, is the engineering. And if you want to advance civilization, you must address the limiting factor. Therefore, you must address the engineering.
A and B are both good, but B can only advance if A advances. So I choose A.
In thinking about where exactly to point himself to best help humanity, Musk says that in college, he thought hard about the first principles question, “What will most affect the future of humanity?” and put together a list of five things: “the internet; sustainable energy; space exploration, in particular the permanent extension of life beyond Earth; artificial intelligence; and reprogramming the human genetic code.”6
Hearing him talk about what matters to him, you can see up and down the whole stack of Want box reasoning that led him to his current endeavors.
He has other reasons too. Next to wanting to help humanity in the Want box is this quote:
I’m interested in things that change the world or affect future in wondrous new technology where you see it and you’re like, “How did that even happen? How is that possible?”7
This follows a theme of Musk being passionate about super-advanced technology and the excitement it brings to him and other people. So given all of the above, an ideal endeavor for Musk would be something involving engineering, something in an area that will be important for the future, and something to do with cutting-edge technology. Those broad, basic Want box items alone narrow down the goal pool considerably.
Meanwhile, he was a teenager with no money, reputation, or connections, and limited knowledge and skills. In other words, his Reality box wasn’t that big. So he did what many young people do—he focused his early goals not around achieving his Wants, but expanding the Reality box and its list of “things that are possible.” He wanted to be able to legally stay in the US after college, and he also wanted to gain more knowledge about engineering, so he killed two birds with one stone and applied to a PhD program at Stanford to study high energy density capacitors, a technology aimed at coming up with a more efficient way than traditional batteries to store energy.
U-turn to the internet
Musk had gone into the Goal Pool and picked the Stanford program, and he moved to California to get started. But there was one thing—it was 1995. The internet was in the early stages of taking off and moving much faster than people had anticipated. It was also a world Musk could dive into without money or a reputation. So he added a bunch of internet-related possibilities into his Reality box. The early internet was also more exciting than he had anticipated—so getting involved in it quickly found its way into his Want box.
These rapid adjustments caused big changes in his Goal Pool, to the point where the Stanford PhD was no longer what his software’s goal formation center was outputting.
Most people would have stuck with the Stanford program—because they had already told everyone about it and it would be weird to quit, because it was Stanford, because it was a more normal path, because it was safer, because the internet might be a fad, because what if he were 35 one day and was a failure with no money because he couldn’t get a good job without the right degree.
Musk quit the program after two days. The big macro arrow of his software came down on the right, saw that what he was embarking on wasn’t in the Goal Pool anymore, and he trusted his software—so he made a macro change.
He started Zip2 with his brother, an early cross between the concepts of the Yellow Pages and Google Maps. Four years later, they sold the company and Elon walked away with $22 million.
As a dotcom millionaire, the conventional wisdom was to settle down as a lifelong rich guy and either invest in other companies or start something new with other people’s money. But Musk’s goal formation center had other ideas. His Want box was bursting with ambitious startup ideas that he thought could have major impact on the world, and his Reality box, which now included $22 million, told him that he had a high chance of succeeding. Being leisurely on the sidelines was nowhere in his Want box and totally unnecessary according to his Reality box.
So he used his newfound wealth to start X.com in 1999, with the vision to build a full-service online financial institution. The internet was still young and the concept of storing your money in an online bank was totally inconceivable to most people, and Musk was advised by many that it was a crazy plan. But again, Musk trusted his software. What he knew about the internet told him that this was inside the Reality box—because his reasoning told him that when it came to the internet, the Reality box had grown much bigger than people appreciated—and that was all he needed to know to move forward. In the top part of his software, as his strategy-action-results-adjustments loop spun, X.com’s service changed, the team changed, the mission changed, even the name changed. By the time eBay bought it in 2002, the company was called PayPal and it was a money transfer service. Musk made $180 million.
Following his software to space
Now 31 years old and fabulously wealthy, Musk had to figure out what to do next with his life. On top of the “whatever you do, definitely don’t risk losing that money you have” conventional wisdom, there was also the common logic that said, “You’re awesome at building internet companies, but that’s all you know since you’ve never done anything else. You’re in your thirties now and it’s too late to do something big in a whole different field. This is the path you chose—you’re an internet guy.”
But Musk went back to first principles. He looked inwards to his Want box, and having reflected on things, doing another internet thing wasn’t really in the box anymore. What was in there was his still-burning desire to help the future of humanity. In particular, he felt that to have a long future, the species would have to become much better at space travel.
So he started exploring the limits of the Reality box when it came to getting involved in the aerospace industry.
Conventional wisdom screamed at the top of its lungs for him to stop. It said he had no formal education in the field and didn’t know the first thing about being a rocket scientist. But his software told him that formal education was just another way to download information into your brain and “a painfully slow download” at that—so he started reading, meeting people, and asking questions.
Conventional wisdom said no entrepreneur had ever succeeded at an endeavor like this before, and that he shouldn’t risk his money on something so likely to fail. But Musk’s stated philosophy is, “When something is important enough, you do it even if the odds are not in your favor.”
Conventional wisdom said that he couldn’t afford to build rockets because they were too expensive and pointed to the fact that no one had ever made a rocket that cheaply before—but like the scientists who ignored those who said the Earth was 6,000 years old and those who insisted the Earth was flat, Musk started crunching numbers to do the math himself. Here’s how he recounts his thoughts:
Historically, all rockets have been expensive, so therefore, in the future, all rockets will be expensive. But actually that’s not true. If you say, what is a rocket made of? It’s made of aluminum, titanium, copper, carbon fiber. And you can break it down and say, what is the raw material cost of all these components? And if you have them stacked on the floor and could wave a magic wand so that the cost of rearranging the atoms was zero, then what would the cost of the rocket be? And I was like, wow, okay, it’s really small—it’s like 2% of what a rocket costs. So clearly it would be in how the atoms are arranged—so you’ve got to figure out how can we get the atoms in the right shape much more efficiently. And so I had a series of meetings on Saturdays with people, some of whom were still working at the big aerospace companies, just to try to figure out if there’s some catch here that I’m not appreciating. And I couldn’t figure it out. There doesn’t seem to be any catch. So I started SpaceX.8
History, conventional wisdom, and his friends all said one thing, but his own software, reasoning upwards from first principles, said another—and he trusted his software. He started SpaceX, again with his own money, and dove in head first. The mission: dramatically lower the cost of space travel to make it possible for humanity to become multi-planetary.
Tesla and beyond
Two years later, while running a growing SpaceX, a friend brought Elon to a company called AC Propulsion, which had created a prototype for a super-fast, long-range electric car. It blew him away. The Reality box of Musk’s software had told him that such a thing wasn’t yet possible, but it turns out that Musk wasn’t aware of how far lithium-ion batteries had advanced, and what he saw at AC Propulsion was new information about the world that put “starting a top-notch electric car company” into the Reality box in his head.
He ran into the same conventional wisdom about battery costs as he had about rocket costs. Batteries had never been made cheaply enough to allow for a mass-market, long-range electric car because the cost of making a battery was simply too high. He used the same first principles logic and a calculator to determine that most of the problem was the cost of middlemen, not raw materials, and decided that actually, conventional wisdom was wrong and batteries could be much cheaper in the future. So he co-founded Tesla with the mission of accelerating the advent of a mostly-electric-vehicle world—first by pouring in resources power and funding the company, and later by contributing his time and energy resources as well and becoming CEO.
Two years after that, Musk co-founded SolarCity with his cousins, a company whose goal was to revolutionize energy production by creating a large, distributed utility that would install solar panel systems on millions of homes. Musk knew that his time/energy power, the one kind of power that has hard limits, no matter who you are, was mostly used up, but he still had plenty of resources power—so he put it to work on another goal in his Goal Pool.
Most recently, Musk has jumpstarted change in another area that’s important to him—the way people transport themselves from city to city. His idea is that there should be an entirely new mode of transport that will whiz people hundreds of miles by zinging them through a tube. He calls it the Hyperloop. For this project, he’s not using his time, energy, or resources. Instead, by laying out his initial thoughts in a white paper and hosting a competition for engineers to test out their innovations, he’s leveraging his powers of connection and persuasion to create change.
___________
There are all kinds of tech companies that build software. They think hard, for years, about the best, most efficient way to make their product. Musk sees people as computers, and he sees his brain software as the most important product he owns—and since there aren’t companies out there designing brain software, he designed his own, beta tests it every day, and makes constant updates. That’s why he’s so outrageously effective, why he can disrupt multiple huge industries at once, why he can learn so quickly, strategize so cleverly, and visualize the future so clearly.
This part of what Musk does isn’t rocket science—it’s common sense. Your entire life runs on the software in your head—why wouldn’t you obsess over optimizing it?
And yet, not only do most of us not obsess over our own software—most of us don’t even understand our own software, how it works, or why it works that way. Let’s try to figure out why.
Most People’s Software
You always hear facts about human development and how so much of who you become is determined by your experiences during your formative years. A newborn’s brain is a malleable ball of hardware clay, and its job upon being born is to quickly learn about whatever environment it’s been born into and start shaping itself into the optimal tool for survival in those circumstances. That’s why it’s so easy for young children to learn new skills.
As people age, the clay begins to harden and it becomes more difficult to change the way the brain operates. My grandmother has been using a computer as long as I have, but I use mine comfortably and easily because my malleable childhood brain easily wrapped itself around basic computer skills, while she has the same face on when she uses her computer that my tortoise does when I put him on top of a glass table and he thinks he’s inexplicably hovering two feet above the ground. She’ll use a computer when she needs to, but it’s not her friend.
So when it comes to our brain software—our values, perceptions, belief systems, reasoning techniques—what are we learning during those key early years?
Everyone’s raised differently, but for most people I know, it went something like this:
We were taught all kinds of things by our parents and teachers—what’s right and wrong, what’s safe and dangerous, the kind of person you should and shouldn’t be. But the idea was: I’m an adult so I know much more about this than you, it’s not up for debate, don’t argue, just obey. That’s when the cliché “Why?” game comes in (what MuskSpeak calls “the chained why”).
A child’s instinct isn’t just to know what to do and not to do, she wants to understand the rules of her environment. And to understand something, you have to have a sense of how that thing was built. When parents and teachers tell a kid to do XYZ and to simply obey, it’s like installing a piece of already-designed software in the kid’s head. When kids ask Why? and then Why? and then Why?, they’re trying to deconstruct that software to see how it was built—to get down to the first principles underneath so they can weigh how much they should actually care about what the adults seem so insistent upon.
The first few times a kid plays the Why game, parents think it’s cute. But many parents, and most teachers, soon come up with a way to cut the game off:
Because I said so.
“Because I said so” inserts a concrete floor into the child’s deconstruction effort below which no further Why’s may pass. It says, “You want first principles? There. There’s your floor. No more Why’s necessary. Now fucking put your boots on because I said so and let’s go.”
Imagine how this would play out in the science world.
In fairness, parents’ lives suck. They have to do all the shit they used to have to do, except now on top of that there are these self-obsessed, drippy little creatures they have to upkeep, who think parents exist to serve them. On a busy day, in a bad mood, with 80 things to do, the Why game is a nightmare.
But it might be a nightmare worth enduring. A command or a lesson or a word of wisdom that comes without any insight into the steps of logic it was built upon is feeding a kid a fish instead of teaching them to reason. And when that’s the way we’re brought up, we end up with a bucket of fish and no rod—a piece of installed software that we’ve learned how to use, but no ability to code anything ourselves.
School makes things worse. One of my favorite thinkers, writer Seth Godin (whose blog is bursting with first principles reasoning wisdom), explains in a TED Talk about school that the current education system is a product of the Industrial Age, a time that catapulted productivity and the standard of living. But along with many more factories came the need for many more factory workers, so our education system was redesigned around that goal. He explains:
The deal was: universal public education whose sole intent was not to train the scholars of tomorrow—we had plenty of scholars. It was to train people to be willing to work in the factory. It was to train people to behave, to comply, to fit in. “We process you for a whole year. If you are defective, we hold you back and process you again. We sit you in straight rows, just like they organize things in the factory. We build a system all about interchangeable people because factories are based on interchangeable parts.”
Couple that concept with what another favorite writer of mine, James Clear, explained recently on his blog:
In the 1960s, a creative performance researcher named George Land conducted a study of 1,600 five-year-olds and 98 percent of the children scored in the “highly creative” range. Dr. Land re-tested each subject during five year increments. When the same children were 10-years-old, only 30 percent scored in the highly creative range. This number dropped to 12 percent by age 15 and just 2 percent by age 25. As the children grew into adults they effectively had the creativity trained out of them. In the words of Dr. Land, “non-creative behavior is learned.”
It makes sense, right? Creative thinking is a close cousin of first principles reasoning. In both cases, the thinker needs to invent his own thought pathways. People think of creativity as a natural born talent, but it’s actually much more of a way of thinking—it’s the thinking version of painting onto a blank canvas. But to do that requires brain software that’s skilled and practiced at coming up with new things, and school trains us on the exact opposite concept—to follow the leader, single-file, and to get really good at taking tests. Instead of a blank canvas, school hands kids a coloring book and tells them to stay within the lines.4
What this all amounts to is that during our brain’s most malleable years, parents, teachers, and society end up putting our clay in a mold and squeezing it tightly into a preset shape.
And when we grow up, without having learned how to build our own style of reasoning and having gone through the early soul-searching that independent thinking requires, we end up needing to rely on whatever software was installed in us for everything—software that, coming from parents and teachers, was probably itself designed 30 years ago.
30 years, if we’re lucky. Let’s think about this for a second.
Just say you have an overbearing mother who insists you grow up with her values, her worldview, her fears, and her ambitions—because she knows best, because it’s a scary world out there, because XYZ is respectable, because she said so.
Your head might end up running your whole life on “because mom says so” software. If you play the Why? game with something like the reason you’re in your current job, it may take a few Why’s to get there, but you’ll most likely end up hitting a concrete floor that says some version of “because mom says so.”
But why does mom say so?
Mom says so because her mom said so—after growing up in Poland in 1932, where she was from a home where her dad said so because his dad—a minister from a small town outside Krakow—said so after his grandfather, who saw some terrible shit go down during the Siberian Uprising of 1866, ingrained in his children’s heads the critical life lesson to never associate with blacksmiths.
Through a long game of telephone, your mother now looks down upon office jobs and you find yourself feeling strongly about the only truly respectable career being in publishing. And you can list off a bunch of reasons why you feel that way—but if someone really grilled you on your reasons and on the reasoning beneath them, you end up in a confusing place. It gets confusing way down there because the first principles foundation at the bottom is a mishmash of the values and beliefs of a bunch of people from different generations and countries—a bunch of people who aren’t you.
A common example of this in today’s world is that many people I know were raised by people who were raised by people who went through the Great Depression. If you solicit career advice from someone born in the US in the 1920s, there’s a good chance you’ll get an answer pumped out by this software:
The person has lived a long life and has made it all the way to 2015, but their software was coded during the Great Depression, and if they’re not the type to regularly self-reflect and evolve, they still do their thinking with software from 1930. And if they installed that same software in their children’s heads and their children then passed it on to their own children, a member of Generation Y today might feel too scared to pursue an entrepreneurial or artistic endeavor and be totally unaware that they’re actually being haunted by the ghost of the Great Depression.
When old software is installed on new computers, people end up with a set of values not necessarily based on their own deep thinking, a set of beliefs about the world not necessarily based on the reality of the world they live in, and a bunch of opinions they might have a hard time defending with an honest heart.
In other words, a whole lot of convictions not really based on actual data. We have a word for that.
Dogma
I don’t know what’s the matter with people: they don’t learn by understanding, they learn by some other way—by rote or something. Their knowledge is so fragile! —Richard Feynman
Dogma is everywhere and comes in a thousand different varieties—but the format is generally the same:
X is true because [authority] says so. The authority can be many things.
Dogma, unlike first principles reasoning, isn’t customized to the believer or her environment and isn’t meant to be critiqued and adjusted as things change. It’s not software to be coded—it’s a printed rulebook. Its rules may be originally based on reasoning by a certain kind of thinker in a certain set of circumstances, at a time far in the past or a place far away, or it may be based on no reasoning at all. But that doesn’t matter because you’re not supposed to dig too deep under the surface anyway—you’re just supposed to accept it, embrace it, and live by it. No evidence needed.
You may not like living by someone else’s dogma, but you’re left without much choice. When your childhood attempts at understanding are met with “Because I said so,” and you absorb the implicit message “Your own reasoning capability is shit, don’t even try, just follow these rules so you don’t fuck your life up,” you grow up with little confidence in your own reasoning process. When you’re never forced to build your own reasoning pathways, you’re able to skip the hard process of digging deep to discover your own values and the sometimes painful experience of testing those values in the real world and learning you want to adjust them—and so you grow up a total reasoning amateur.
Only strong reasoning skills can carve a unique life path, and without them, dogma will quickly have you living someone else’s life. Dogma doesn’t know you or care about you and is often completely wrong for you—it’ll have a would-be happy painter spending their life as a lawyer and a would-be happy lawyer spending their life as a painter.
But when you don’t know how to reason, you don’t know how to evolve or adapt. If the dogma you grew up with isn’t working for you, you can reject it, but as a reasoning amateur, going it alone usually ends with you finding another dogma lifeboat to jump onto—another rulebook to follow and another authority to obey. You don’t know how to code your own software, so you install someone else’s.
People don’t do any of this intentionally—usually if we reject a type of dogma, our intention is to break free of a life of dogmatic thinking altogether and brave the cold winds of independent reasoning. But dogmatic thinking is a hard habit to break, especially when it’s all you know. I have a friend who just had a baby, and she told me that she was so much more open-minded than her parents, because they wanted her to have a prestigious career, but she’d be open to her daughter doing anything. After a minute, she thought about it, and said, “Well actually, no, what I mean by that is if she wanted to go do something like spend her life on a farm in Montana, I’d be fine with that and my parents never would have been—but if she said she wanted to go work at a hedge fund, I’d kill her.” She realized mid-sentence that she wasn’t free of the rigid dogmatic thinking of her parents, she had just changed dogma brands.
This is the dogma trap, and it’s hard to escape from. Especially since dogma has a powerful ally—the group.
Tribes
Some things I think are very conservative, or very liberal. I think when someone falls into one category for everything, I’m very suspicious. It doesn’t make sense to me that you’d have the same solution to every issue. —Louis C.K.
What most dogmatic thinking tends to boil down to is another good Seth Godin phrase:
People like us do stuff like this.
It’s the rallying cry of tribalism.
There’s an important distinction to make here. Tribalism tends to have a negative connotation, but the concept of a tribe itself isn’t bad. A tribe is just a group of people linked together by something they have in common—a religion, an ethnicity, a nationality, family, a philosophy, a cause. Christianity is a tribe. The US Democratic Party is a tribe. Australians are a tribe. Radiohead fans are a tribe. Arsenal fans are a tribe. The musical theater scene in New York is a tribe. Temple University is a tribe. And within large, loose tribes, there are smaller, tighter, sub-tribes. Your extended family is a tribe, of which your immediate family is a sub-tribe. Americans are a tribe, of which Texans are a sub-tribe, of which Evangelical Christians in Amarillo, Texas is a sub-sub-tribe.
What makes tribalism a good or bad thing depends on the tribe member and their relationship with the tribe. In particular, one simple distinction:
Tribalism is good when the tribe and the tribe member both have an independent identity and they happen to be the same. The tribe member has chosen to be a part of the tribe because it happens to match who he really is. If either the identity of the tribe or the member evolves to the point where the two no longer match, the person will leave the tribe. Let’s call this conscious tribalism.
Tribalism is bad when the tribe and tribe member’s identity are one and the same. The tribe member’s identity is determined by whatever the tribe’s dogma happens to say. If the identity of the tribe changes, the identity of the tribe member changes with it in lockstep. The tribe member’s identity can’t change independent of the tribal identity because the member has no independent identity. Let’s call this blind tribalism.
With conscious tribalism, the tribe member and his identity comes first. The tribe member’s identity is the alpha dog, and who he is determines the tribes he’s in. With blind tribalism, the tribe comes first. The tribe is the alpha dog and it’s the tribe that determines who he is.
This isn’t black and white—it’s a spectrum—but when someone is raised without strong reasoning skills, they may also lack a strong independent identity and end up vulnerable to the blind tribalism side of things—especially with the various tribes they were born into. That’s what Einstein was getting at when he said, “Few people are capable of expressing with equanimity opinions which differ from the prejudices of their social environment. Most people are even incapable of forming such opinions.”
A large tribe like a religion or nation or political party will contain members who fall across the whole range of the blind-to-conscious spectrum. But some tribes themselves will be the type to attract a certain type of follower. It makes logical sense that the more rigid and certain and dogmatic the tribe, the more likely it’ll be to attract blind tribe members. ISIS is going to have a far higher percentage of blind tribe members than the London Philosophy Club.
The allure of dogmatic tribes makes sense—they appeal to very core parts of human nature.
Humans crave connection and camaraderie, and a guiding dogma is a common glue to bond together a group of unique individuals as one.
Humans want internal security, and for someone who grows up feeling shaky about their own distinctive character, a tribe and its guiding dogma is a critical lifeline—a one-stop shop for a full suite of human opinions and values.
Humans also long for the comfort and safety of certainty, and nowhere is conviction more present than in the groupthink of blind tribalism. While a scientist’s data-based opinions are only as strong as the evidence she has and inherently subject to change, tribal dogmatism is an exercise in faith, and with no data to be beholden to, blind tribe members believe what they believe with certainty.
We discussed why math has proofs, science has theories, and in life, we should probably limit ourselves to hypotheses—but blind tribalism proceeds with the confidence of the mathematician:
Given (because the tribe says so): A = B
Given (because the tribe says so): B = C + D
Therefore, with certainty: A = C + D
And since so many others in the tribe feel certain about things, your own certainty is reassured and reinforced.
But there’s a heavy cost to these comforts. Insecurity can be solved the hard way or the easy way—and by giving people the easy option, dogmatic tribes remove the pressure to do the hard work of evolving into a more independent person with a more internally-defined identity. In that way, dogmatic tribes are an enabler of the blind tribe member’s deficiencies.
The sneaky thing about both rigid tribal dogma and blind membership is that they like to masquerade as open-minded thought with conscious membership. I think many of us may be closer to the blind membership side of things with certain tribes we’re a part of than we recognize—and those tribes we’re a part of may not be as open-minded as we tend to think.
A good test for this is the intensity of the us factor. That key word in “People like us do stuff like this” can get you into trouble pretty quickly.
Us feels great. A major part of the appeal of being in a tribe is that you get to be part of an Us, something humans are wired to seek out. And a loose Us is nice—like the Us among conscious, independent tribe members.
But the Us in blind tribalism is creepy. In blind tribalism, the tribe’s guiding dogma doubles as the identity of the tribe members, and the Us factor enforces that concept. Conscious tribe members reach conclusions—blind tribe members are conclusions. With a blind Us, if the way you are as an individual happens to contain opinions, traits, or principles that fall outside the outer edges of the dogma walls, they will need to be shed—or things will get ugly. By challenging the dogma of your tribe, you’re challenging both the sense of certainty the tribe members gain their strength from and the clear lines of identity they rely on.
The best friend of a blind Us is a nemesis Us—Them. Nothing unites Us like a collectively hated anti-Us, and the blind tribe is usually defined almost as much by hating the dogma of Them as it is by abiding by the dogma of Us.
Whatever element of rigid, identity-encompassing blindness is present in your own tribal life will reveal itself when you dare to validate any part of the rival Them dogma.
Give it a try. The next time you’re with a member of a tribe you’re a part of, express a change of heart that aligns you on a certain topic with whoever your tribe considers to be Them. If you’re a religious Christian, tell people at church you’re not sure anymore that there’s a God. If you’re an artist in Boulder, explain at the next dinner party that you think global warming might actually be a liberal hoax. If you’re an Iraqi, tell your family that you’re feeling pro-Israel lately. If you and your husband are staunch Republicans, tell him you’re coming around on Obamacare. If you’re from Boston, tell your friends you’re pulling for the Yankees this year because you like their current group of players.
If you’re in a tribe with a blind mentality of total certainty, you’ll probably see a look of horror. It won’t just seem wrong, it’ll seem like heresy. They might get angry, they might passionately try to convince you otherwise, they might cut off the conversation—but there will be no open-minded conversation. And because identity is so intertwined with beliefs in blind tribalism, the person actually might feel less close to you afterwards. Because for rigidly tribal people, a shared dogma plays a more important role in their close relationships than they might recognize.
Most of the major divides in our world emerge from blind tribalism, and on the extreme end of the spectrum—where people are complete sheep—blind tribalism can lead to terrifying things. Like those times in history when a few charismatic bad guys can build a large army of loyal foot soldiers just by displaying strength and passion. Because blind tribalism is the true villain behind our grandest-scale atrocities:
Most of us probably wouldn’t have joined the Nazi party, because most of us aren’t on the extreme end of the blind-to-conscious spectrum. But I don’t think many of us are on the other end either. Instead, we’re usually somewhere in the hazy middle—in the land of cooks.5
The Cook and the Chef
The difference between the way Elon thinks and the way most people think is kind of like the difference between a cook and a chef.
The words “cook” and “chef” seem kind of like synonyms. And in the real world, they’re often used interchangeably. But in this post, when I say chef, I don’t mean any ordinary chef. I mean the trailblazing chef—the kind of chef who invents recipes. And for our purposes, everyone else who enters a kitchen—all those who follow recipes—is a cook.
Everything you eat—every part of every cuisine we know so well—was at some point in the past created for the first time. Wheat, tomatoes, salt, and milk go back a long time, but at some point, someone said, “What if I take those ingredients and do this…and this…..and this……” and ended up with the world’s first pizza. That’s the work of a chef.
Since then, god knows how many people have made a pizza. That’s the work of a cook.
The chef reasons from first principles, and for the chef, the first principles are raw edible ingredients. Those are her puzzle pieces, her building blocks, and she works her way upwards from there, using her experience, her instincts, and her taste buds.
The cook works off of some version of what’s already out there—a recipe of some kind, a meal she tried and liked, a dish she watched someone else make.
Cooks span a wide range. On one end, you have cooks who only cook by following a recipe to the T—carefully measuring every ingredient exactly the way the recipe dictates. The result is a delicious meal that tastes exactly the way the recipe has it designed. Down the range a bit, you have more of a confident cook—someone with experience who gets the general gist of the recipe and then uses her skills and instincts to do it her own way. The result is something a little more unique to her style that tastes like the recipe but not quite. At the far end of the cook range, you have an innovator who makes her own concoctions. A lamb burger with a vegetable bun, a peanut butter and jelly pizza, a cinnamon pumpkin seed cake.6
But what all of these cooks have in common is their starting point is something that already exists. Even the innovative cook is still making an iteration of a burger, a pizza, and a cake.
At the very end of the spectrum, you have the chef. A chef might make good food or terrible food, but whatever she makes, it’s a result of her own reasoning process, from the selection of raw ingredients at the bottom to the finished dish at the top.
In the culinary world, there’s nothing wrong with being a cook. Most people are cooks because for most people, inventing recipes isn’t a goal of theirs.
But in life—when it comes to the reasoning “recipes” we use to churn out a decision—we may want to think twice about where we are on the cook-chef spectrum.
On a typical day, a “reasoning cook” and a “reasoning chef” don’t operate that differently. Even the chef becomes quickly exhausted by the mental energy required for first principles reasoning, and usually, doing so isn’t worth his time. Both types of people spend an average day with their brain software running on auto-pilot and their conscious decision-making centers dormant.
But then comes a day when something new needs to be figured out. Maybe the cook and the chef are each given the new task at work to create a better marketing strategy. Or maybe they’re unhappy with that job and want to think of what business to start. Maybe they have a crush on someone they never expected to have feelings for and they need to figure out what to do about it.
Whatever this new situation is, auto-pilot won’t suffice—this is something new and neither the chef’s nor the cook’s software has done this before. Which leaves only two options:
Create. Or copy.
The chef says, “Ugh okay, here we go,” rolls up his sleeves, and does what he always does in these situations—he switches on the active decision-making part of his software and starts to go to work. He looks at what data he has and seeks out what more he needs. He thinks about the current state of the world and reflects on where his values and priorities lie. He gathers together those relevant first principles ingredients and starts puzzling together a reasoning pathway. It takes some hard work, but eventually, the pathway brings him to a hypothesis. He knows it’s probably wrong-ish, and as new data emerges, he’ll “taste-test” the hypothesis and adjust it. He keeps the decision-making center on standby for the next few weeks as he makes a bunch of early adjustments to the flawed hypothesis—a little more salt, a little less sugar, one prime ingredient that needs to be swapped out for another. Eventually, he’s satisfied enough with how things are going to move back into auto-pilot mode. This new decision is now part of the automated routine—a new recipe is in the cookbook—and he’ll check in on it to make adjustments every once in a while or as new pertinent data comes in, the way he does for all parts of his software.
The cook has no idea what’s going on in the last paragraph. The reasoning cook’s software is called “Because the recipe said so,” and it’s more of a computerized catalog of recipes than a computer program. When the cook needs to make a life decision, he goes through his collection of authority-written recipes, finds the one he trusts in that particular walk of life, and reads through the steps to see what to do—kind of like WWJD, except the J is replaced by whatever authority is most trusted in that area. For most questions, the authority is the tribe, since the cook’s tribal dogma covers most standard decisions. But in this particular case, the cook leafed through the tribe’s cookbook and couldn’t find any section about this type of decision. So he needs to get a hold of a recipe from another authority he trusts with this type of thing. Once the cook finds the right recipe, he can put it in his catalog and use it for all future decisions on this matter.
First, the cook tries a few friends. His catalog doesn’t have the needed info, but maybe one of theirs does. He asks them for their advice—not so he can use it as additional thinking to supplement his own, but so it can become his own thinking.
If that doesn’t yield any strongly-opinionated results, he’ll go to the trusty eternal backstop—conventional wisdom.
Society as a whole is its own loose tribe, often spanning your whole nation or even your whole part of the world, and what we call “conventional wisdom” is its guiding dogma cookbook—online and available to the public. Typically, the larger the tribe, the more general and more outdated the dogma—and the conventional wisdom database runs like a DMV website last updated in 1992. But when the cook has nowhere else to turn, it’s like a trusty old friend.
And in this case—let’s say the cook is thinking of starting a business and wants to know what the possibilities are—conventional wisdom has him covered. He types the command into the interface, waits a few minutes, and then the system pumps out its answer:
The cook, thoroughly discouraged, thanks the machine and updates his Reality box accordingly.
With the decision made (not to start a business), he switches his software back into auto-pilot mode. Done and done.
Musk calls the cook’s way of thinking “reasoning by analogy” (as opposed to reasoning by first principles), which is a nice euphemism. The next time a kid gets caught copying answers from another student’s exam during the test, he should just explain that he was reasoning by analogy.
If you start looking for it, you’ll see the chef/cook thing happening everywhere. There are chefs and cooks in the worlds of music, art, technology, architecture,7 writing, business, comedy, marketing, app development, football coaching, teaching, and military strategy. And in each case, though both parties are usually just on autopilot, mindlessly playing the latest album again and again at concerts, it’s in those key moments when it’s time to write a new album—those moments of truth in front of a clean canvas, a blank Word doc, an empty playbook, a new sheet of blueprint paper, a fresh whiteboard—that the chef and the cook reveal their true colors. The chef creates while the cook, in some form or another, copies.
And the difference in outcome is enormous. For cooks, even the more innovative kind, there’s almost always a ceiling on the size of the splash they can make in the world, unless there’s some serious luck involved. Chefs aren’t guaranteed to do anything good, but when there’s a little talent and a lot of persistence, they’re almost certain to make a splash. Sometimes the chef is the one brave enough to go for something big—but other times, someone doesn’t feel the desire to make a splash and the chef is the one with the strength of character to step out of the game and in favor of keeping it small. Being a chef isn’t being like Elon Musk—it’s being yourself.
No one talks about the “reasoning ...
