Be Prepared To Lose Your Job In The Future… If You Don’t Learn This One Skill Now

Jeff Bezos, Warren Buffett, and Elon Musk all take this one approach.

One question Jeff Bezos is often asked is one we all need to ask ourselves, “What’s going to change in the next 10 years?”

It’s a profound question because the world is changing so rapidly, and because the decisions we make now will determine our destiny.

Decide wrong, and you might find yourself on a sinking ship, watching as your whole industry goes bankrupt and the skills you spent years honing become obsolete. Millions of people from journalists to financial analysts now find themselves in this position.

Decide right, and you could be set for life. The top artificial intelligence programmers, for example, make as much as NFL superstars. These programmers have suddenly found that the skill set they spent years honing has become incredibly valuable.

These two groups, top AI programmers and people whose skills have become devalued, might have spent the same amount of time learning and be equally smart. But selecting different fields took them down completely different paths.

Over the last few years, I’ve come across a group of people who have spent their whole careers expertly predicting the future, investing based off of their predictions, and then massively profiting decade after decade. What I’ve noticed is that they share a common and completely counterintuitive approach toward investing their money and time that bucks conventional wisdom. In this article, I’ll share how you can copy the approaches of self-made billionaire entrepreneurs and investors like Jeff Bezos, Ray Dalio, Howard Marks, and Warren Buffett so that you too can ‘win’ your future.

“What’s Going to Change?” Is The Wrong Question

Like I said above, Jeff Bezos is often asked, “What’s going to change in the next 10 years?” That’s actually not the key question though. Listen to how he reframes it (emphasis mine):

That is a very interesting question; it’s a very common one. I almost never get the question: ‘What’s NOT going to change in the next 10 years?’

And I submit to you that that second question is actually the more important of the two — because you can build a business strategy around the things that are stable in time.

He then goes on to explain how Amazon has profited from focusing on the second question (emphasis mine):

[I]n our retail business, we know that customers want low prices, and I know that’s going to be true 10 years from now. They want fast delivery; they want vast selection. It’s impossible to imagine a future 10 years from now where a customer comes up and says, ‘Jeff, I love Amazon; I just wish the prices were a little higher,’ [or] ‘I love Amazon; I just wish you’d deliver a little more slowly.’ Impossible.

And so the effort we put into those things, spinning those things up, we know the energy we put into it today will still be paying off dividends for our customers 10 years from now. When you have something that you know is true, even over the long term, you can afford to put a lot of energy into it.

I remember the thoughts running through my head the first time I read this quote. It felt intuitive and counterintuitive at the same time. On the one hand, I thought to myself, “This makes so much sense! Why not just focus on what’s guaranteed to be valuable rather than speculating?” On the other hand, Bezos’ response flies in the face of conventional wisdom and was jarring. The typical approach to planning for the future resembles betting at the roulette wheel:

• Identify what you think is going to be really important (i.e., artificial intelligence, virtual reality, blockchain, synthetic biology, nanotechnology).
• Pick one of those areas to invest in and master.
• Hope it hits big and that you have the right timing so that you can profit.

While the conventional approach does sometimes work, it’s not a dependable strategy. It’s not what I’d tell my kids to do. A 2012 study from the Kauffman Foundation shows that “The [venture capital] industry hasn’t returned the cash invested since 1997.” And if you take out a few companies like Uber, Amazon, Google, and Facebook, the returns are abysmal. In other words, the odds of you investing in, starting, or being an early employee at a billion-dollar company are like the odds of winning a lottery. Just 200 out of all the startups out there are valued at $1 billion or more right now! You have a tenfold better chance of being hit by lightning.

Why doesn’t focusing on trends work as well as you might think?

Why Future Prediction Doesn’t Work

“You can’t predict, you can prepare.” — Howard Marks

Self-made billionaire, entrepreneur, and investor Howard Marks runs the investment firm Oaktree Capital and has $100 billion under management, making it one of the largest hedge funds in the world. Each year, Marks writes a widely-circulated letter to shareholders. One of these memos gives a masterclass in how investing in future trends isn’t always smart:

1. The seemingly sure bets will have the most competition, which will make them less profitable. Marks writes: “Most great investments begin in discomfort. The things most people feel good about — investments where the underlying premise is widely accepted, the recent performance has been positive and the outlook is rosy — are unlikely to be available at bargain prices. Rather, bargains are usually found among things that are controversial, that people are pessimistic about, and that have been performing badly of late.”
2. Luck and randomness are big, unavoidable factors. ”It’s far from certain that even ‘right’ decisions will be successful, since every decision requires assumptions about what the future will look like, and even reasonable assumptions can be thwarted by the world’s randomness,” says Marks. There are certain random events that are so influential that they completely change the game for everyone. Nassim Taleb calls these events “Black Swans.” (A great example is the 2008 financial crisis.)
3. It’s much harder than you think to be consistently right. “It’s hard to consistently make decisions that correctly factor in all of the relevant facts and considerations (i.e., it’s hard to be right),” Marks notes with humility, a key trait of many of the world’s top-performing investors. Self-made billionaire Ray Dalio, the founder of the largest hedge fund in the world, drives home how hard investing is in the first sentence of his new book: “Before I begin telling you what I think, I want to establish that I’m a ‘dumb shit’ who doesn’t know much relative to what I need to know.”
4. Even if you get the prediction right, you are likely to get the timing wrong. Marks says: “Even well-founded decisions that eventually turn out to be right are unlikely to do so promptly. This is because not only are future events uncertain, their timing is particularly variable.” And the problem with this is that having the wrong timing is functionally equivalent to making the wrong decision.

The field of artificial intelligence is a case in point for Marks’ argument. While artificial intelligence sounds like a sure bet now, it wasn’t always that way. From 1974–1980 and 1987–1993, the field went through “AI winters.” In these periods, AI reeled from being overhyped and lost credibility and funding. Talented young programmers left in droves. Many of the most successful people in the field now are those who survived these winters and kept going even when it didn’t seem smart to do so. Now, someone entering the AI field has to compete against droves of the smartest people in the world.

My point is that picking which fields will be hot in 20 years is not as simple as it sounds. Predicting third-, fourth-, and fifth-order consequences is almost impossible. Who would’ve predicted in the early 1900s that the invention of the automobile would ultimately lead to the creation of suburban sprawl, the hotel industry (because of the Interstate highway system), and the insurance industry.

Notice how Warren Buffett, the best investor in history, doesn’t invest in the hottest tech startups of the day. Instead, he has made his career by identifying businesses whose rock-solid fundamentals don’t change, or which change very slowly. As a result, Buffett is able to invest in companies for the long-term. He’s held stock in companies like Geico, Coca-Cola, and American Express for decades.

So if predicting the future isn’t the answer, what can you do instead?

Introducing The Trunk Technique

“Predicting rain doesn’t count. Building arks does.” — Warren Buffett

At the heart of the methods used by Buffett, Dalio, Marks, Taleb, and Bezos is a common theme: focus on areas that are virtually guaranteed to be valuable in the future no matter what happens.

Bezos talks about how focusing on stable customer preferences is a powerful foundation to build a company around. I’d take that a step further: focusing on stable knowledge is a powerful approach to build a life around. I call this skill the Trunk Technique…

Some forms of knowledge arise quickly and then just as quickly become obsolete. Other forms stay relevant for a very long time. In my article, Why Being Great Is So Much Harder Than People Realize, I share how the rate at which information goes obsolete is increasing:

One academic study, for example, found that the decay rate in the accuracy of clinical knowledge about cirrhosis and hepatitis was 45 years. In other words, if you’re talking to a 70-year-old liver specialist who hasn’t updated his skills, you have a 50 percent chance of getting bad information. Engineering degrees went from a half life of 35 years in 1930 to about 10 years in 1960.

Source: New Scientist

So what’s the difference between knowledge that expires relatively quickly versus knowledge with staying power?

Broadly speaking, “transitional” or quickly-expiring knowledge is the kind that helps us navigate a specific environment (such as the specialized field of liver medicine). Whereas “pillar” or longer-lasting knowledge is based on fundamental principles and mental models that can be applied in many contexts including unforeseen future ones.

Let me explain. As I share in How Elon Musk Learns Faster and Better Than Everyone Else, when most people think about knowledge, they think about it horizontally, viewing knowledge across different subjects. The problem with this is that when you look at things in one dimension, you miss important connections:

What many miss is that knowledge is vertical as well. Great thinkers and doers, I have noticed, view reality this way. There are deeper principles and mental models that connect the various subjects that we study:

In the example above, by learning the universal mental models of network science that apply to all networks, you can more easily understand specific patterns in how the brain functions and how social networks work.

And it’s not just one layer deep. There are many layers. In one of Elon Musk’s Reddit AMAs he explains it like this:

It is important to view knowledge as sort of a semantic tree — make sure you understand the fundamental principles, i.e. the trunk and big branches, before you get into the leaves/details or there is nothing for them to hang onto.

Here’s one way of visualizing Musk’s semantic tree:

People who use the Trunk Technique focus on mastering the fundamental mental models or first principles first and then move on to the leaves second. By doing this, they build a more stable and adaptable tree, and therefore career. Trees lose their leaves every winter, but they thrive for decades (and sometimes hundreds of years) because they have strong trunks and roots.

Let’s take the topic of experimentation as an example. Understanding the 10,000-experiment rule is crucial for success at an individual, company, and societal level. The Leave Approach to getting better at experimentation would be to first focus on hacks like understanding how to A/B test a button on your website. The Trunk Technique would be to understand what the scientific method is first (i.e., controlled experimentation; peer-reviewed refereed journals; blind, randomized design; falsifiability; controlled placebo; double blind experimentation; computer simulations; and meta-analysis). By understanding the few core principles that make up the scientific method, one can then create thousands of experiments across every area of life and career forever. As new hacks and software tools arise, you’d be able to quickly understand their significance and use them. Then, when those specific tools become obsolete, you’d still have your trunk to grow new branches and leaves from. I attribute a large part of any success I’ve had as a writer to applying the scientific method to the creation of ideas.

Another example: I’m obsessed with health, so I’ve learned hacks for getting micronutrients, intermittent fasting, cold showers, saunas, and interval training. These are fine, but even more fundamental to my health has been learning the underlying principle of post-traumatic growth. All of the hacks above can be derived by understanding that systems grow by being stressed and then being given time to recover.

I share more details on how they specifically apply the Trunk Technique to your life in How Elon Musk Learns Faster And Better Than Everyone Else, How One Life Hack From A Self-Made Billionaire Leads To Exceptional Success, and How To Tell If Someone Is Truly Smart Or Just Average, which have collectively been read over 1 million times.

In summary, the Trunk Technique allows you to:

• Build a knowledge tree that lasts forever. Winston Churchill once said: “The farther back you can look, the farther forward you are likely to see.” More recently, this phenomenon has been called the Lindy Effect: “The future life expectancy of some non-perishable things like a technology or an idea is proportional to their current age, so that every additional period of survival implies a longer remaining life expectancy.” The corollary of this for the information age is: “The more you focus on fundamental knowledge, the longer your knowledge tree will last.”
• Adapt to any future fast and thrive. The nature of fundamental mental models is that they appear across all fields. Therefore, when you go into an emerging field, you’ll enter with a head start, because you’ll immediately see how the principles you already know are relevant.
• Better understand what’s happening and what it means. Similar to how an expert chess player can see several moves ahead, mental models will allow you to put what’s happening in context so you can react appropriately and think farther ahead.
• Reduce the risk of investing in an area that turns out to not be a winner. In this article, I’m not suggesting that you ignore the future completely. What I’m saying is that you balance your understanding of trends with what is never going to change: timeless principles and mental models. In his book, Antifragile, Nassim Taleb, a very successful investor rumored to be worth hundreds of millions of dollars, suggests an approach to investing resources that maximizes returns while eliminating losses. He calls it the Barbell Strategy: the idea of building a portfolio of extremes (extremely safe assets + high risk-reward assets) rather than building a big mix with everything in the middle.

Source: Nassim Taleb

The Trunk Technique functions in the same way as Taleb’s Barbell Strategy. By building a strong base of risk-free knowledge, we cap our downside while also giving ourselves more flexibility and confidence to make speculative bets on the future that might hit it big. That’s why I argue that learning how to apply the Trunk Technique is one of the main skills that anyone should learn in order to create the future they want.

Want To Apply The Trunk Technique To Your Life Today?

Are you convinced of the power of Mental Models? I’ve learned from personal experience that it literally takes years to develop true mastery of these. Therefore, I created two resources for you:

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• Every month, you’ll master one new mental model.
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• A 101 Overview of the mental model (why it’s important, how it works, its vocabulary, etc.)
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This article was written with love and care using the blockbuster mental model.

If there’s a link to an Amazon book, it’s an affiliate link, which means I get a small amount of compensation when you buy the book. This compensation does not influence the specific books I recommend, as I only recommend books that I read and love.