So Good They Can't Ignore You

by Cal Newport

According to Johnson’s theory, Sarah would have been better served by first mastering a promising niche—a task that may take years—and only then turning her attention to seeking a mission.

Most people who love their work got where they are by first building up career capital and then cashing it in for the types of traits that define great work. Getting to the cutting edge of a field can be understood in these terms: This process builds up rare and valuable skills and therefore builds up your store of career capital. Similarly, identifying a compelling mission once you get to the cutting edge can be seen as investing your career capital to acquire a desirable trait in your career. In other words, mission is yet another example of career capital theory in action. If you want a mission, you need to first acquire capital. If you skip this step, you might end up like Sarah and Jane: with lots of enthusiasm but very little to show for it.

“I think you do need passion to be happy,” Pardis Sabeti told me. At first this sounds like she’s supporting the passion hypothesis that I debunked in Rule #1. But then she elaborated: “It’s just that we don’t know what that passion is. If you ask someone, they’ll tell you what they think they’re passionate about, but they probably have it wrong.” In other words, she believes that having passion for your work is vital, but she also believes that it’s a fool’s errand to try to figure out in advance what work will lead to this passion.

To use my terminology, this long period of training, starting with her undergraduate biology classes and continuing through her PhD and then postdoctoral work at the Broad Institute, was when she was building up her stores of career capital. When she took a professorship at Harvard, she was finally ready to cash in this capital to obtain the mission-driven career she enjoys today.

Advancing to the cutting edge in a field is an act of “small” thinking, requiring you to focus on a narrow collection of subjects for a potentially long time. Once you get to the cutting edge, however, and discover a mission in the adjacent possible, you must go after it with zeal: a “big” action.

Sarah and Jane, by contrast, reversed this order. They started by thinking big, looking for a world-changing mission, but without capital they could only match this big thinking with small, ineffectual acts. The art of mission, we can conclude, asks us to suppress the most grandiose of our work instincts and instead adopt the patience—the style of patience observed with Pardis Sabeti—required to get this ordering correct.

Once you have the capital required to identify a mission, you must still figure out how to put the mission into practice. If you don’t have a trusted strategy for making this leap from idea to execution, then like me and so many others, you’ll probably avoid the leap altogether.

I tell these stories because they emphasize that Kirk is someone who is not afraid to try something bold if it holds out the promise of making his life more interesting.

As Kirk explained to me, in an academic field like archaeology, you get a lot of these types of calls—“people who think they found a dinosaur footprint, or whatever”—and there’s just not time, with the pressure of research and teaching, to keep up with them. But Kirk saw an opportunity here that would support his mission. “This type of public outreach is exactly what we archaeologists should be doing,” he realized.

When Sims studied a variety of successful innovators, from Steve Jobs to Chris Rock to Frank Gehry, as well as innovative companies, such as Amazon and Pixar, he found a strategy common to all. “Rather than believing they have to start with a big idea or plan out a whole project in advance,” he writes, “they make a methodical series of little bets about what might be a good direction, learning critical information from lots of little failures and from small but significant wins” [emphasis mine]. This rapid and frequent feedback, Sims argues, “allows them to find unexpected avenues and arrive at extraordinary outcomes.”

The important thing about little bets is that they’re bite-sized. You try one. It takes a few months at most. It either succeeds or fails, but either way you get important feedback to guide your next steps. This approach stands in contrast to the idea of choosing a bold plan and making one big bet on its success. If Kirk had done this—for example, deciding in advance to dedicate years to popularizing the Land and Water documentary—he would not have had nearly as much success with his mission.

A career untamed, he realized, can bring you into dangerous territory, such as being bored while writing computer code for an investment bank. He needed a mission to actively guide his career or he would end up trapped again and again. He decided that a good mission for him would somehow combine the artistic and technical sides of his life, but he didn’t know how to make this general idea into a money-making reality, so he went searching for answers.

Remarkable marketing is the art of building things worth noticing.”

“At this point I basically just put two and two together,” Giles told me. “The synthesis of Purple Cow and My Job Went to India is that the best way to market yourself as a programmer is to create remarkable open-source software. So I did.” Following Godin’s advice, Giles came up with the idea for Archaeopteryx, his AI-driven music creator. “I don’t think there was anybody else with my combined background,” he said. “Plenty of Ruby programmers love dance music, but I don’t think any of them has sacrificed the same ridiculous number of hours to tweaking breakbeats and synth patches over and over again, releasing white-label records that never made a dime, and studying music theory.” In other words, Giles’s ability to produce a Ruby program that produced real music was unique: If he could pull it off, it would be a purple cow.

What Giles discovered, I decided, is that a good mission-driven project must be remarkable in two different ways. First, it should be remarkable in the literal sense of compelling people to remark about it.

There’s also, however, a second type of remarkability at play. Giles didn’t just find a project that compels remarks, but he also spread the word about the project in a venue that supports these remarks. In his case, this venue was the open-source software community. As he learned from Chad Fowler, there’s an established infrastructure in this community for noticing and spreading the word about interesting projects. Without this conduciveness to chatter, a purple cow, though striking, may never be seen.

The Law of Remarkability For a mission-driven project to succeed, it should be remarkable in two different ways. First, it must compel people who encounter it to remark about it to others. Second, it must be launched in a venue that supports such remarking.

If you’re a scientist with a remarkable idea, there’s little doubt about how best to spread it: publish!

With Kirk French, we also see the law of remarkability in action. His general mission was to popularize modern archaeology. There are lots of non-remarkable ways to pursue this mission. For example, he could have worked on making the archaeology curriculum at Penn State more appealing to undergraduates, or published articles on the field in general-interest science magazines. But these projects would not have generated the type of attention-grabbing success that can transform your career into something compelling. Instead, Kirk decided to head straight into people’s homes and use archaeological techniques to help them uncover the significance (if any) of family treasures. This approach is remarkable—an observation reinforced by the number of speaking invitations Kirk now receives, including a recent opportunity to address the largest conference in his field about lessons learned as a popularizer.

the best ideas for missions are found in the adjacent possible—the region just beyond the current cutting edge.

To encounter these ideas, therefore, you must first get to that cutting edge, which in turn requires expertise. To try to devise a mission when you’re new to a field and lacking any career capital is a venture bound for failure.

Once you identify a general mission, however, you’re still left with the task of launching specific projects that make it succeed. An effective strategy for accomplishing this task is to try small steps that generate concrete feedback—little bets—and then use this feedback, be it good or bad, to help figure out what to try next. This systematic exploratio...

In sum, mission is one of the most important traits you can acquire with your career capital. But adding this trait to your working life is not simple. Once you have the capital to identify a good mission, you must still work to make it succeed. By using little bets and the law of remarkability, you greatly increase your chances of finding ways to transform your mission from a compelling idea into a compelling career.

We were bored, available, and ambitious—a dangerous combination

When Michael and I left for college—he to NYU and I to Dartmouth—I decided I was done with website design and moved on to more pressing interests, such as girls.

Once Michael and I figured out how to keep the business humming, however, this skill turned out to be rare and valuable (especially for people our age).

When it later came time for me to decide what to do after college, I had two offers in hand, one from Microsoft and the other from MIT. This is the type of decision that would paralyze my classmates. I, however, didn’t see any reason to worry. Both paths, I was sure, would yield numerous opportunities that could be leveraged into a remarkable life.

The things that make great work great, it argued, are rare and valuable. If you want them in your career, you need rare and valuable skills to offer in return. In other words, if you’re not putting in the effort to become, as Steve Martin put it, “so good they can’t ignore you,” you’re not likely to end up loving your work—regardless of whether or not you believe it’s your true calling.

A graduate-level mathematics problem set—something I have plenty of experience with—is about as pure an exercise in deliberate practice as you’re likely to find. You’re given a problem that you have no idea how to solve, but you have to solve it or you’ll get a bad grade, so you dive in and try as hard as you can, repeatedly failing as different avenues lead you to dead ends. The mental strain of mustering every last available neuron toward solving a problem, driven by the fear of earning zero points on the assignment, is a nice encapsulation of exactly what the deliberate-practice literature says is necessary to improve. This is why, early in their careers, graduate students experience great leaps in their abilities.

But at a research-oriented program like the one offered by MIT’s computer science department, your course work winds down after the first two years. Soon after, your research efforts are expected to release themselves from your advisor’s orbit and follow a self-directed trajectory. It’s here that if you’re not careful to keep pushing forward, your improvement can taper off to what the performance scientist Anders Ericsson called an “acceptable level,” where you then remain stuck.

Here was my first lesson: This type of skill development is hard. When I got to the first tricky gap in the paper’s main proof argument, I faced immediate internal resistance. It was as if my mind realized the effort I was about to ask it to expend, and in response it unleashed a wave of neuronal protest, distant at first, but then as I persisted increasingly tremendous, crashing over my concentration with mounting intensity.

To combat this resistance, I deployed two types of structure. The first type was time structure: “I am going to work on this for one hour,” I would tell myself. “I don’t care if I faint from the effort, or make no progress, for the next hour this is my whole world.” But of course I wouldn’t faint and eventually I would make progress. It took, on average, ten minutes for the waves of resistance to die down. Those ten minutes were always difficult, but knowing that my efforts had a time limit helped ensure that the difficulty was manageable. The second type of structure I deployed was information structure—a way of capturing the results of my hard focus in a useful form. I started by building a proof map that captured the dependencies between the different pieces of the proof. This was hard, but not too hard, and it got me warmed up in my efforts to understand the result. I then advanced from the maps to short self-administered quizzes that forced me to memorize the key definitions the proof used. Again, this was a relatively easy task, but it still took concentration, and the result was an understanding that was crucial for parsing the detailed math that came next. After these first two steps, emboldened by my initial successes in deploying hard focus, I moved on to the big guns: proof summaries. This is where I forced myself to take each lemma and walk through each step of its proofs—filling in missing steps. I would conclude by writing a detailed summary in my own words. ...

More important than these small successes, however, was the new mindset this test case introduced. Strain, I now accepted, was good. Instead of seeing this discomfort as a sensation to avoid, I began to understand it the same way that a body builder understands muscle burn: a sign that you’re doing something right. Inspired by this insight, I accompanied a promise to do more large-scale paper deconstructions of this type with a trio of smaller habits designed to inject even more deliberate practice into my daily routine.

Here’s the routine: Once a week I require myself to summarize in my “bible” a paper I think might be relevant to my research. This summary must include a description of the result, how it compares to previous work, and the main strategies used to obtain it. These summaries are less involved than the step-by-step deconstruction I did on my original test-case paper—which is what allows me to do them on a weekly basis—but they still induce the strain of deliberate practice.

Another deliberate-practice routine was the introduction of my hour tally—a sheet of paper I mounted behind my desk at MIT, and plan on remounting at Georgetown. The sheet has a row for each month on which I keep a tally of the total number of hours I’ve spent that month in a state of deliberate practice.

By having these hour counts stare me in the face every day I’m motivated to find new ways to fit more deliberate practice into my schedule. Without this routine, my total amount of time spent stretching my abilities would undoubtedly be much lower.

It’s much easier to redesign your graduate-student Web page than it is to grapple with a mind-melting proof. The result for me was that my career capital stores, initially built up during the forced strain of my early years as a graduate student, were dwindling as time went on. Researching Rule #2, however, changed this state of affairs by making me much more “craft-centric.” Getting better and better at what I did became what mattered most, and getting better required the strain of deliberate practice. This is a different way of thinking about work, but once you embrace it, the changes to your career trajectory can be profound.

as my postdoctoral advisor told me, “If it’s not in writing, it doesn’t count.”

When you study the type of careers that make others remark, “That’s the type of job I want,” this trait almost always plays a central role. Once you understand this value of control, it changes the way you evaluate opportunities, leading you to consider a position’s potential autonomy as being as important as its offered salary or the institution’s reputation.

That is, the safest route to tenure is to take a robust research topic that already has lots of interest and then outwork your peers. If you want to innovate, wait until later in your career. In his famed “Last Lecture,” the late Carnegie Mellon computer science professor Randy Pausch captured this reality well when he quipped, “Junior faculty members used to come up to me and say, ‘Wow, you got tenure early; what’s your secret?’ I said, ‘It’s pretty simple, call me any Friday night in my office at ten o’clock and I’ll tell you.’

During my quest, for example, I discovered two traps that typically trip people up in their search for control. The first trap was having too little career capital. If you go after more control in your working life without a rare and valuable skill to offer in return, you’re likely pursuing a mirage.

This was the trap tripped, for example, by the many fans of lifestyle design, who left their traditional jobs to try to make a living on passive income-generating websites. Many of these contrarians quickly discovered that the income-generating piece of that plan doesn’t work well if you don’t have something valuable to offer in exchange for people’s money.

But there were certainly those farther out in my professional orbit who were more resistant to this decision. To them, pounding a well-trod path at a well-established university was the safest route to the desired outcome of tenure and a good research reputation. The personal benefits of having more control over my work were not on their professional radar, so any decision outside the safe decision was deemed alarming.

“When deciding whether to follow an appealing pursuit that will introduce more control into your work life, ask yourself whether people are willing to pay you for it. If so, continue. If not, move on.”

True missions, it turns out, require two things. First you need career capital, which requires patience. Second, you need to be ceaselessly scanning your always-changing view of the adjacent possible in your field, looking for the next big idea. This requires a dedication to brainstorming and exposure to new ideas. Combined, these two commitments describe a lifestyle, not a series of steps that automatically spit out a mission when completed.

We now dive from the top level of the pyramid to the bottom level, where we find my dedication to background research. Here’s my rule: Every week, I expose myself to something new about my field. I can read a paper, attend a talk, or schedule a meeting. To ensure that I really understand the new idea, I require myself to add a summary, in my own words, to my growing “research bible” (which I introduced earlier in this conclusion when discussing how I applied Rule #2). I also try to carve out one walk each day for free-form thinking about the ideas turned up by this background research (I commute to work on foot and have a dog to exercise, so I have many such walks to choose from in my schedule). The choice of what material to expose myself to is guided by my mission description at the top of the pyramid.

As you might recall, a little bet, in the setting of mission exploration, has the following characteristics: It’s a project small enough to be completed in less than a month. It forces you to create new value (e.g., master a new skill and produce new results that didn’t exist before). It produces a concrete result that you can use to gather concrete feedback.

After leaving the monastery, Thomas returned to the banking job he had left two years earlier when he moved to the Catskills to pursue his passion. This time, however, he approached his working life with a new awareness. His experience at the monastery had freed him from the escapist thoughts of fantasy jobs that had once dominated his mind. He was able instead to focus on the tasks he was given and on accomplishing them well. He was free from the constant, draining comparisons he used to make between his current work and some magical future occupation waiting to be discovered. This new focus, and the output it produced, was appreciated by management. Nine months into his job he was promoted. Then he was promoted again. And then again! Within two years he had moved from a lowly data-entry position to being put in charge of a computer system that managed over $6 billion of investment assets. By the time I met him, he had been put in charge of a system that manages five times that amount. His work is challenging, but Thomas enjoys the challenge. It also provides him with a sense of respect, impact, and autonomy—exactly the kind of rare and valuable traits, as you might recall, that I argued back in Rule #2 are needed for creating work you love. Thomas acquired these traits not by matching his work to his passion, but instead by doing his work well and then strategically cashing in the capital it generated.

Don’t obsess over discovering your true calling. Instead, master rare and valuable skills. Once you build up the career capital that these skills generate, invest it wisely. Use it to acquire control over what you do and how you do it, and to identify and act on a life-changing mission. This philosophy is less sexy than the fantasy of dropping everything to go live among the monks in the mountains, but it’s also a philosophy that has been shown time and again to actually work.