Think Like a Rocket Scientist: Simple Strategies You Can Use to Make Giant Leaps in Work and Life

by Ozan Varol

The most elegant solutions, the rocket scientist David Murray writes, “use the least number of components to solve the greatest number of problems.”

“The more we understand something,” Peter Attia explained to me, “the less complicated it becomes. This is classic Richard Feynman teaching.”

Simple also has fewer points of failure. Complicated things break more easily. This principle is as true in rocket science as it is in business, computer programming, and relationships. Every time you introduce complexity to a system, you’re giving it one more aspect that can fail.

Simplicity also reduces costs.

The noise in any system—whether it’s a rocket, a business, or your résumé—reduces its value. There’s a temptation to always add more, but the taller the Jenga tower, the more fragile it gets. “Any intelligent fool can make things bigger and more complex,” economist E. F. Schumacher said in a quote often misattributed to Einstein. “It takes a touch of genius and a lot of courage to move in the opposite direction.”

Rocket scientists have to constantly ask themselves, How can we possibly make this fit into that? They get the right fit by cutting out the junk, reducing the system to its irreducible minimums, and making everything as simple as possible without compromising the mission.

Even as you seek to simplify, remain open to new facts that complicate matters. As the English mathematician and philosopher Alfred North Whitehead put it, “Seek simplicity and distrust it.”56

Bernard Shaw once said, “Few people think more than two or three times a year. I’ve made an international reputation for myself by thinking once or twice a week.”15 As Shaw knew, hustle and creativity are antithetical to each other. You can’t generate breakthroughs while clearing out your inbox. You must dig the well before you’re thirsty and become curious now—not when a crisis inevitably presents itself. Curiosity may have killed Schrödinger’s cat. But it just might save you.

The purple crayon was Einstein’s favorite scientific tool, one that he carried with him even as an adult.18 As he wrote to a friend, “You and I never cease to stand like curious children before the great mystery into which we were born.”19 Centuries earlier, Isaac Newton purportedly used similar words in describing himself as “a boy playing on the seashore… whilst the great ocean of truth lay all undiscovered before me.”

We view intelligent urges as a virtue and playful urges as a vice. But play and intelligence should be complements, not competitors. Play, put differently, can be a portal to intelligence. In his seminal article “The Technology of Foolishness,” James March writes that “playfulness is a deliberate, temporary relaxation of rules in order to explore the possibilities of alternative rules.”21 He argues that individuals and organizations “need ways of doing things for which they have no good reason. Not always. Not usually. But sometimes.” Only by taking a playful attitude toward our own beliefs can we challenge and change them.

“We are drowning in information,” biologist E. O. Wilson said, “while starving for wisdom.”

Falling into boredom allows our brain to tune out the external world and tune into the internal.

Specialization is all the rage these days. In the English-speaking world, a generalist is a Jack or Jill of all trades, but the master of none. The Greeks caution that a person “who knows a lot of crafts lives in an empty house.”55 The Koreans believe a person of “12 talents has nothing to eat for dinner.”56 This attitude comes at a cost. It stifles the cross-pollination of ideas from different disciplines.

“Art training alone,” the study suggests, “can help to teach medical students to become better clinical observers.”

In developing his theory of evolution, Darwin was inspired by two very different fields—geology and economics. In Principles of Geology, Charles Lyell argued in the 1830s that mountains, rivers, and canyons had been formed through a slow, evolutionary process that took place over eons as erosion, wind, and rain chipped away at the Earth. Lyell’s theory bucked conventional wisdom, which attributed these geological features solely to catastrophic or supernatural events like Noah’s flood.66 Darwin read Lyell’s book while sailing on the Beagle and applied the geological idea to biology. As rocket scientist David Murray explains, Darwin argued that organic material “evolves just as inorganic material does: with minute changes in each descendant that, over time, accumulate to form new biological appendages like eyes, hands, or wings.”67 Darwin also drew inspiration from the late-eighteenth-century economist Thomas Malthus. Malthus argued that humans tend to outgrow resources like food, creating a competition for survival. This competition, Darwin believed, drove the evolutionary process, leading the species best adapted to their environment to survive.

Optimal creativity doesn’t happen in complete isolation. Breakthroughs almost always involve a collaborative component. “If I have seen further,” Newton famously said, “it is by standing upon the shoulders of giants.” These giants come to the table with diverse perspectives, bringing their own apples and oranges for the collective body to compare and connect. Entrepreneur and writer Frans Johansson calls this phenomenon the Medici effect. It refers to the fifteenth-century creative explosion that occurred when the wealthy Medici family brought together in Florence many accomplished individuals from different walks of life—scientists, poets, sculptors, philosophers, and more. As these individuals connected, new ideas blossomed, paving the way for the Renaissance (the word means “rebirth” in French).

Opposites don’t always attract. On each mission, there’s a tension between “the idealistic, impractical scientists” and “the stubborn, practical engineers,” as Squyres writes. On the good missions, this tension turns into a creative dance that brings out the best in both disciplines. But on the bad missions, “it’s an acid that eats away at the collaboration until it’s rotten.”77 The key to making the relationship work is combinatory play. The scientists learn some engineering, and the engineers learn some science. This approach was a top priority for Squyres. “If you came in,” he explains, “and you sat in on one of our daily tactical planning sessions where we have a team of a dozen scientists and a dozen engineers sitting together in a room, you could sit there for an hour and still not quite figure out who were the scientists and who were the engineers.” The team was blended so well—with the scientists and the engineers well versed in each other’s language and objectives—that you could hardly tell the difference.

Most of us don’t do what Dumas did. We instinctively dismiss the opinions of amateurs like Pasteur. They don’t know what they’re talking about. They haven’t attended the relevant meetings. They don’t have the necessary background. They’re out of their element. Yet it’s precisely for these reasons that outsider opinions hold value. First-principles thinking, as Dumas’s answer implies, often has an inverse relationship to expertise. Unlike the insiders, whose identity or salary can depend on the existing state of affairs, outsiders have no stake in the status quo. Conventional wisdom is easier to tune out when you’re not smothered by it.

Einstein’s secret to success was escaping the intellectual prison that confined other physicists. When he published his paper on special relativity, he was an unknown clerk in a Swiss patent office. As an outsider to the physics establishment, he was able to move beyond the collective body of knowledge—which, in his case, was a Newtonian perspective that treated time and space as absolute. His revolutionary paper on special relativity, “On the Electrodynamics of Moving Bodies,” looks nothing like a typical physics paper. It cites the names of only a handful of scientists and contains virtually no citations to existing works—a highly unconventional move by academic standards.86 In Einstein’s case, creating a revolution meant searching beyond incremental improvement, untethered by citations to works past. Other examples abound. Musk was a latecomer to rocket science, which he picked up by reading textbooks. Bezos came to retail from the finance world, and Hastings was a software developer before he cofounded Netflix. Standing outside the establishment, these gate-crashers were in a better position to see its flaws and recognize its outdated methods.

moonshot—a breakthrough technology that brings a radical solution to an enormous problem.

“We choose to go to the moon in this decade and do the other things,” Kennedy said, “not because they are easy, but because they are hard.” He simply refused to let the existing reality drive his country’s future.

Moonshots force you to reason from first principles. If your goal is 1 percent improvement, you can work within the status quo. But if your goal is to improve tenfold, the status quo has to go. Pursuing a moonshot puts you in a different league—and often an entirely different game—from that of your competitors, making the established plays and routines largely irrelevant.

The political strategists James Carville and Paul Begala tell a story about the choice a lion faces in deciding to hunt for a mouse or an antelope. “A lion is fully capable of capturing, killing, and eating a field mouse,” they explain. “But it turns out that the energy required to do so exceeds the caloric content of the mouse itself.” Antelopes, in contrast, are much bigger animals, so “they take more speed and strength to capture.” But once captured, an antelope can provide days of food for the lion.12 The story, as you may have guessed, is a microcosm for life. Most of us go after the mice instead of the antelopes. We think the mouse is a sure thing, but the antelope is a moonshot. Mice are everywhere; antelopes are few and far between. What’s more, everyone around us is busy hunting mice. We assume that if we decide to go for antelopes, we might fail and go hungry. So we don’t launch a new business, because we think we don’t have what it takes. We hesitate to apply for a promotion, assuming that someone far more competent will get it. We don’t ask people on a date if they seem out of our league. We play not to lose instead of playing to win. “The story of the human race,” psychologist Abraham Maslow wrote in 1933, “is the story of men and women selling themselves short.”

“Not many people believe that they can move mountains,” David Schwartz says in The Magic of Thinking Big. “So, as a result, not many people do.”

The story we choose to tell ourselves about our capabilities is just that: a choice. And like every other choice, we can change it. Until we push beyond our cognitive limits and stretch the boundaries of what we consider practical, we can’t discover the invisible rules that are holding us back. There are tremendous benefits to taking moonshots even where—or particularly where—real-life conditions are out of sync with our imagination.

The flies and the bees, respectively, represent what’s known as divergent and convergent thinking. The flies are the divergent thinkers, fluttering freely until they find the exit. The bees are the convergent thinkers, zeroing in on the seemingly most obvious exit path with a behavior that is ultimately their undoing. Divergent thinking is a way of generating different ideas in an open-minded and free-flowing manner—like flies bouncing around in a glass bottle. During divergent thinking, we don’t think about constraints, possibilities, or budgets. We just throw around ideas, open to whatever might present itself. We become optimists in the way that physicist David Deutsch defines the term—as someone who believes that anything permitted by the laws of physics is doable.25 The goal is to create a flurry of options—both good and bad—not prematurely judging them, limiting them, or choosing among them.

Because of the differences between idea generation and idea evaluation, many authors separate their drafting from their editing. Drafting is better suited for divergent thinking, and editing for convergent.

Jaime Waydo, who led the design of Curiosity’s mobility system, is a fan of far-fetched solutions. “I worry that we are programming people to do the safe thing,” she told me. “But safe answers will never change the world.”

Regular makes vulnerable. Irregular makes nimble.

When we are exposed to what psychologists call a meaning threat—something that doesn’t make sense—the resulting sense of disorientation can prompt us to look for meaning and association elsewhere.

“Anything that one man can imagine,” Jules Verne said, “another man can make real.”

Musk credits Asimov’s books for spurring his thinking about the future (so much so that SpaceX launched Asimov’s Foundation trilogy aboard the Falcon Heavy vehicle in February 2018). In the Foundation series, a visionary named Hari Seldon foresees dark ages lurking for humankind and devises a plan to colonize distant planets. “The lesson I drew from that,” Musk says, is that humans should “prolong civilization, minimize the probability of a dark age and reduce the length of a dark age if there is one.”

So Felten came on board to think about the practical problems. X may be a moonshot factory, but it’s still a factory. It must produce profitable products. “When I came here,” Felten explained, “X was this amazing place full of deep, deep, deep geeks, most of whom had never taken a product out into the world.”60 Pure idealists don’t make for great entrepreneurs. Consider Tesla, one of the greatest inventors of all time. “It’s a sad, sad story,” Larry Page, Google’s cofounder explains. “He couldn’t commercialize anything, he could barely fund his own research.”61 Although Tesla—whom Edison pejoratively called a “poet of science”—left behind a legacy of three hundred patents, he died penniless in a New York hotel.62 Reflecting on this story, Page says, “You’ve got to actually get [your invention] into the world; you’ve got to produce, [and] make money doing it.”

For most of us, planning for the future means forecasting. In our businesses, we review the current supply and demand for widgets and extrapolate them into the future. In our personal lives, we let our current skill set drive our vision for who we might become. But forecasting, by definition, doesn’t start with first principles. With forecasting, we look in the rearview mirror and at the raw materials in front of us, rather than the possibilities ahead. When we forecast, we ask, “What can we do with what we have?” Often, the status quo itself is part of the problem. Forecasting takes all our problematic assumptions and biases and propels them into the future. In so doing, it artificially restricts our vision of what is feasible, given the current circumstances. Backcasting flips the script. Rather than forecasting the future, backcasting aims to determine how an imagined future can be attained. “The best way to predict the future,” Alan Kay says, “is to invent it.”83 Instead of letting our resources drive our vision, backcasting lets our vision drive the resources. When we backcast, we take our bold ambition and introduce actionable steps. We visualize our ideal job and sketch out a roadmap to get there. We picture the perfect product and ask what it takes to build it. Only when you face the real prospect of sketching a blueprint for success—now, not later—will you be forced to separate fact from fiction.

Amazon takes a similar backward perspective on its products.84 Amazonians write internal press releases for products that don’t yet exist. Each press release functions as a thought experiment—the initial vision of a breakthrough idea. The document describes the “customer problem, how current solutions (internal or external) fail, and how the new product will blow away existing solutions.” The press release is then presented to the company with the same enthusiasm that accompanies the public launch of a finished product. “We only fund things that we can articulate crisply,” explained Amazon’s Jeff Wilke. The articulation is so crisp that the press releases include a six-page list of hypothetical frequently asked questions from customers. This exercise forces the team of experts at Amazon to put themselves in the position of nonexperts and view the product from their perspective. It requires them to ask “stupid” questions and come up with answers—even before the product is built.

You’ve just been put in charge of a particularly audacious project at work. Your boss says you have to get a monkey to stand on a pedestal and train it to recite passages from Shakespeare. How do you begin? If you’re like most people, you begin with building a pedestal.

The monkey-first attitude requires developing a set of “kill metrics,” as X calls them, a set of go/no-go criteria for determining when to press ahead and when to quit.88 The criteria must be defined at the outset—when you’re relatively clearheaded—before your emotional and financial investments might trigger the sunk-cost fallacy and cloud your judgment.

There’s far more certainty in building a pedestal than in getting a monkey to talk. We don’t know how to train a monkey, but we know how to build pedestals, so we build them. In our lives, we spend our time doing what we know best—writing emails, attending endless meetings—instead of tackling the hardest part of a project.

Here’s the thing: What’s easy often isn’t important, and what’s important often isn’t easy. In the end, we have a choice. We can keep building pedestals and wait for a magical monkey to show up reciting Shakespeare (spoiler: there are no magical monkeys). Or we can focus on the important instead of the easy, and try to teach that monkey to talk, one syllable at a time.

When we’re familiar with a problem, and when we think we have the right answer, we stop seeing alternatives. This tendency is known as the Einstellung effect. In German, einstellung means “set,” and in this context, the term refers to a fixed mental set or attitude. The initial framing of the question—and the initial answer—both stick. The Einstellung effect is partly a relic of our education system. In schools, we’re taught to answer problems, not to reframe them. The problems are handed to—well, more like forced on—students in the form of problem sets. The phrase problem set makes this approach clear. The problems have been set (einstellung), and the student’s job is to solve them—not change or question them. A typical problem declares “all of its constraints, all of its given information, comprehensively and in advance,” as high-school teacher Dan Meyer explains.5 The students then take the prepackaged and preapproved problem and plug it into a formula they memorized, which, in turn, spits out the right answer. This approach is wildly disconnected from reality. In our adult lives, problems often aren’t handed to us fully formed. We have to find, define, and redefine them ourselves. But once we find a problem, our educational conditioning kicks in, launching us into answer mode rather than asking whether there’s a better problem to solve. Although we pay lip service to the importance of finding the right problem, we double down on the same tactics that have failed us in ...

When the Einstellung effect gets in the way—when we can’t see the better move—we can change our definition of the problem by questioning the question.

“Every answer,” Harvard Business School professor Clayton Christensen says, “has a question that retrieves it.”11 The answer is often embedded within the question itself, so the framing of the question becomes crucial to the solution. Charles Darwin would agree. “Looking back,” he wrote in a letter to a friend, “I think it was more difficult to see what the problems were than to solve them.”

Goldin’s solution for this uncertainty was to use a strategy we encountered earlier in the book: introduce a redundancy. Instead of putting all our eggs in one spacecraft’s basket and crossing our fingers that nothing bad would happen along the way, we decided to send two rovers instead of one. Even if one failed, the other might make it.

In the end, two questions that reframed the problems ended up producing one of the most successful interplanetary missions of all time: What if we used airbags instead of a three-legged lander? What if we sent two rovers instead of one? These questions may appear obvious, but they were obvious only in hindsight. How do you do what Adler and Goldin did and see the problem from a perspective others miss? One approach is to distinguish between two concepts—strategy and tactics—that are often conflated.

A strategy is a plan for achieving an objective. Tactics, in contrast, are the actions you take to implement the strategy.

To find the strategy, ask yourself, What problem is this tactic here to solve? This question requires abandoning the what and the how and focusing on the why.

Once you identify the strategy, it becomes easier to play with different tactics. If you frame the problem more broadly as one of gravity—not as a flawed three-legged lander—airbags can present a better alternative.

The barometer story is a good example of functional fixedness. As psychologist Karl Duncker explains, the concept refers to a “mental block against using an object in a new way that is required to solve a problem.” Just as we treat problems and questions as fixed, we do the same with tools. Once we learn that a barometer measures pressure, we blind ourselves to other uses for it. Like the chess players whose eyes kept darting to the familiar solution on the chess board, our minds fixate on the function we know.

The switch from function to form is also helpful in reframing the resources at your disposal. Consider, for example, the development of Amazon Web Services (AWS).41 As Amazon grew from an online bookstore to an “everything” store, it built up an immense electronic infrastructure, including storage and databases. The company realized that its infrastructure wasn’t simply an internal resource. It could also be sold to other companies as a cloud-computing service, to be used for storage, networking, and databases. AWS eventually became a cash cow for Amazon, generating roughly $17 billion in revenue in 2017—more than Amazon’s retail division.

Drury knows a secret missed by many business leaders: The low-hanging fruit has already been picked. You can’t beat a stronger competitor by copying them. But you can beat them by doing the opposite of what they’re doing. Instead of adopting a common best practice or the industry standard, reframe the question by asking, “What if I did the reverse?” Even if you don’t execute, the simple process of thinking through the opposite will make you question your assumptions and jolt you out of your current perspective.