Deep Work: Rules for Focused Success in a Distracted World

by Cal Newport

Deep Work: Professional activities performed in a state of distraction-free concentration that push your cognitive capabilities to their limit. These efforts create new value, improve your skill, and are hard to replicate.

Microsoft CEO Bill Gates famously conducted “Think Weeks” twice a year, during which he would isolate himself (often in a lakeside cottage) to do nothing but read and think big thoughts.

Shallow Work: Noncognitively demanding, logistical-style tasks, often performed while distracted. These efforts tend to not create much new value in the world and are easy to replicate.

Spend enough time in a state of frenetic shallowness and you permanently reduce your capacity to perform deep work.

The Shallows was just the first in a series of recent books to examine the Internet’s effect on our brains and work habits. These subsequent titles include William Powers’s Hamlet’s BlackBerry, John Freeman’s The Tyranny of E-mail, and Alex Soojung-Kim Pang’s The Distraction Addiction—all of which agree, more or less, that network tools are distracting us from work that requires unbroken concentration, while simultaneously degrading our capacity to remain focused.

Our work culture’s shift toward the shallow (whether you think it’s philosophically good or bad) is exposing a massive economic and personal opportunity for the few who recognize the potential of resisting this trend and prioritizing depth—an

This was a good idea, but Benn had a problem: “I couldn’t stay focused.” There were days during this period, he now admits, when he spent almost every minute (“98 percent of my time”) surfing the Web. The business plan project—a chance to distinguish himself early in his career—fell to the wayside.

By the time he quit, Benn was well aware of his difficulties with deep work, so when he dedicated himself to learning how to code, he knew he had to simultaneously teach his mind how to go deep. His method was drastic but effective. “I locked myself in a room with no computer: just textbooks, notecards, and a highlighter.” He would highlight the computer programming textbooks, transfer the ideas to notecards, and then practice them out loud. These periods free from electronic distraction were hard at first, but Benn gave himself no other option: He had to learn this material, and he made sure there was nothing in that room to distract him. Over time, however, he got better at concentrating, eventually getting to a point where he was regularly clocking five or more disconnected hours per day in the room, focused without distraction on learning this hard new skill. “I probably read something like eighteen books on the topic by the time I was done,” he recalls.

The deep work paid off. Benn quickly landed a job as a developer at a San Francisco tech start-up with $25 million in venture funding and its pick of employees. When Benn quit his job as a financial consultant, only half a year earlier, he was making $40,000 a year. His new job as a computer developer paid $100,000—an amount that can continue to grow, essentially without limit in the Silicon Valley market, along with his skill level.

When I last spoke with Benn, he was thriving in his new position. A newfound devotee of deep work, he rented an apartment across the street from his office, allowing him to show up early in the morning before anyone else arrived and work without distraction. “On good days, I can get in four hours of focus before the first meeting,” he told me. “Then maybe another three to four hours in the afternoon. And I do mean ‘focus’: no e-mail, no Hacker News [a website popular among tech types], just programming.” For someone who admitted to sometimes spending up to 98 percent of his day in his old job surfing the Web, Jason Benn’s transformation is nothing short of astonishing.

Deep work is not some nostalgic affectation of writers and early-twentieth-century philosophers. It’s instead a skill that has great value today.

To remain valuable in our economy, therefore, you must master the art of quickly learning complicated things. This task requires deep work. If you don’t cultivate this ability, you’re likely to fall behind as technology advances.

To succeed you have to produce the absolute best stuff you’re capable of producing—a task that requires depth.

But as we shift to an information economy, more and more of our population are knowledge workers, and deep work is becoming a key currency—even if most haven’t yet recognized this reality.

The Deep Work Hypothesis: The ability to perform deep work is becoming increasingly rare at exactly the same time it is becoming increasingly valuable in our economy. As a consequence, the few who cultivate this skill, and then make it the core of their working life, will thrive.

Not surprisingly, I soon developed a similar commitment to depth. To the chagrin of both my friends and the various publicists I’ve worked with on my books, I’ve never had a Facebook or Twitter account, or any other social media presence outside of a blog. I don’t Web surf and get most of my news from my home-delivered Washington Post and NPR. I’m also generally hard to reach: My author website doesn’t provide a personal e-mail address, and I didn’t own my first smartphone until 2012 (when my pregnant wife gave me an ultimatum—“you have to have a phone that works before our son is born”). On the other hand, my commitment to depth has rewarded me. In the ten-year period following my college graduation, I published four books, earned a PhD, wrote peer-reviewed academic papers at a high rate, and was hired as a tenure-track professor at Georgetown University. I maintained this voluminous production while rarely working past five or six p.m. during the workweek.

I build my days around a core of carefully chosen deep work, with the shallow activities I absolutely cannot avoid batched into smaller bursts at the peripheries of my schedule. Three to four hours a day, five days a week, of uninterrupted and carefully directed concentration, it turns out, can produce a lot of valuable output.

My commitment to depth has also returned nonprofessional benefits. For the most part, I don’t touch a computer between the time when I get home from work and the next morning when the new workday begins (the main exception being blog posts, which I like to write after my kids go to bed). This ability to fully disconnect, as opposed to the more standard practice of sneaking in a few quick work e-mail checks, or giving in to frequent surveys of social media sites, allows me to be present with my wife and two sons in the evenings, and read a surprising number of books for a busy father of two.

“We are in the early throes of a Great Restructuring,” Brynjolfsson and McAfee explain early in their book. “Our technologies are racing ahead but many of our skills and organizations are lagging behind.”

Though an increasing number of people will lose in this new economy as their skill becomes automatable or easily outsourced, there are others who will not only survive, but thrive—becoming more valued (and therefore more rewarded) than before.

Advances such as robotics and voice recognition are automating many low-skilled positions, but as these economists emphasize, “other technologies like data visualization, analytics, high speed communications, and rapid prototyping have augmented the contributions of more abstract and data-driven reasoning, increasing the values of these jobs.” In other words, those with the oracular ability to work with and tease valuable results out of increasingly complex machines will thrive. Tyler Cowen summarizes this reality more bluntly: “The key question will be: are you good at working with intelligent machines or not?”

It no longer makes sense, for example, to hire a full-time programmer, put aside office space, and pay benefits, when you can instead pay one of the world’s best programmers, like Hansson, for just enough time to complete the project at hand. In this scenario, you’ll probably get a better result for less money, while Hansson can service many more clients per year, and will therefore also end up better off.

Hearing a succession of mediocre singers does not add up to a single outstanding performance.” In other words, talent is not a commodity you can buy in bulk and combine to reach the needed levels: There’s a premium to being the best. Therefore, if you’re in a marketplace where the consumer has access to all performers, and everyone’s q value is clear, the consumer will choose the very best. Even if the talent advantage of the best is small compared to the next rung down on the skill ladder, the superstars still win the bulk of the market.

The final group that will thrive in our new economy—the group epitomized by John Doerr—consists of those with capital to invest in the new technologies that are driving the Great Restructuring. As we’ve understood since Marx, access to capital provides massive advantages.

In this new economy, three groups will have a particular advantage: those who can work well and creatively with intelligent machines, those who are the best at what they do, and those with access to capital.

Two Core Abilities for Thriving in the New Economy 1. The ability to quickly master hard things. 2. The ability to produce at an elite level, in terms of both quality and speed.

To join the group of those who can work well with these machines, therefore, requires that you hone your ability to master hard things. And because these technologies change rapidly, this process of mastering hard things never ends: You must be able to do it quickly, again and again.

If you want to become a superstar, mastering the relevant skills is necessary, but not sufficient. You must then transform that latent potential into tangible results that people value. Many developers, for example, can program computers well, but David Hansson, our example superstar from earlier, leveraged this ability to produce Ruby on Rails, the project that made his reputation. Ruby on Rails required Hansson to push his current skills to their limit and produce unambiguously valuable and concrete results.

If you don’t produce, you won’t thrive—no matter how skilled or talented you are.

It’s here that we arrive at a central thesis of this book: The two core abilities just described depend on your ability to perform deep work.

This task of formalization began in earnest in the 1970s, when a branch of psychology, sometimes called performance psychology, began to systematically explore what separates experts (in many different fields) from everyone else. In the early 1990s, K. Anders Ericsson, a professor at Florida State University, pulled together these strands into a single coherent answer, consistent with the growing research literature, that he gave a punchy name: deliberate practice.

Instead, we argue that the differences between expert performers and normal adults reflect a life-long period of deliberate effort to improve performance in a specific domain.”

To master a cognitively demanding task requires this specific form of practice—there are few exceptions made for natural talent.

“Men of genius themselves were great only by bringing all their power to bear on the point on which they had decided to show their full measure.”

This brings us to the question of what deliberate practice actually requires. Its core components are usually identified as follows: (1) your attention is focused tightly on a specific skill you’re trying to improve or an idea you’re trying to master; (2) you receive feedback so you can correct your approach to keep your attention exactly where it’s most productive. The first component is of particular importance to our discussion, as it emphasizes that deliberate practice cannot exist alongside distraction, and that it instead requires uninterrupted concentration. As Ericsson emphasizes, “Diffused attention is almost antithetical to the focused attention required by deliberate practice” (emphasis mine).

As the journalist Daniel Coyle surveys in his 2009 book, The Talent Code, these scientists increasingly believe the answer includes myelin—a layer of fatty tissue that grows around neurons, acting like an insulator that allows the cells to fire faster and cleaner. To understand the role of myelin in improvement, keep in mind that skills, be they intellectual or physical, eventually reduce down to brain circuits. This new science of performance argues that you get better at a skill as you develop more myelin around the relevant neurons, allowing the corresponding circuit to fire more effortlessly and effectively. To be great at something is to be well myelinated.

By focusing intensely on a specific skill, you’re forcing the specific relevant circuit to fire, again and again, in isolation. This repetitive use of a specific circuit triggers cells called oligodendrocytes to begin wrapping layers of myelin around the neurons in the circuits—effectively cementing the skill. The reason, therefore, why it’s important to focus intensely on the task at hand while avoiding distraction is because this is the only way to isolate the relevant neural circuit enough to trigger useful myelination. By contrast, if you’re trying to learn a complex new skill (say, SQL database management) in a state of low concentration (perhaps you also have your Facebook feed open), you’re firing too many circuits simultaneously and haphazardly to isolate the group of neurons you actually want to strengthen.

To learn hard things quickly, you must focus intensely without distraction.

Though Grant’s productivity depends on many factors, there’s one idea in particular that seems central to his method: the batching of hard but important intellectual work into long, uninterrupted stretches.

During these periods, which can last up to three or four days, he’ll often put an out-of-office auto-responder on his e-mail so correspondents will know not to expect a response. “It sometimes confuses my colleagues,” he told me. “They say, ‘You’re not out of office, I see you in your office right now!’” But to Grant, it’s important to enforce strict isolation until he completes the task at hand.

the following law of productivity: High-Quality Work Produced = (Time Spent) x (Intensity of Focus)

when you switch from some Task A to another Task B, your attention doesn’t immediately follow—a residue of your attention remains stuck thinking about the original task. This residue gets especially thick if your work on Task A was unbounded and of low intensity before you switched, but even if you finish Task A before moving on, your attention remains divided for a while.

Leroy studied the effect of this attention residue on performance by forcing task switches in the laboratory. In one such experiment, for example, she started her subjects working on a set of word puzzles. In one of the trials, she would interrupt them and tell them that they needed to move on to a new and challenging task, in this case, reading résumés and making hypothetical hiring decisions. In other trials, she let the subjects finish the puzzles before giving them the next task. In between puzzling and hiring, she would deploy a quick lexical decision game to quantify the amount of residue left from the first task.* The results from this and her similar experiments were clear: “People experiencing attention residue after switching tasks are likely to demonstrate poor performance on that next task,” and the more intense the residue, the worse the performance.

The concept of attention residue helps explain why the intensity formula is true and therefore helps explain Grant’s productivity. By working on a single hard task for a long time without switching, Grant minimizes the negative impact of attention residue from his other obligations, allowing him to maximize performance on this one task. When Grant is working for days in isolation on a paper, in other words, he’s doing so at a higher level of effectiveness than the standard pro...

It might seem harmless to take a quick glance at your inbox every ten minutes or so. Indeed, many justify this behavior as better than the old practice of leaving an inbox open on the screen at all times (a straw-man habit that few follow anymore). But Leroy teaches us that this is not in fact much of an improvement. That quick check introduces a new target for your attention. Even worse, by seeing messages that you cannot deal with at the moment (which is almost always the case), you’ll be forced to turn back to the primary task with a secondary task left unfinished.

To produce at your peak level you need to work for extended periods with full concentration on a single task free from distraction. Put another way, the type of work that optimizes your performance is deep work. If you’re not comfortable going deep for extended periods of time, it’ll be difficult to get your performance to the peak levels of quality and quantity increasingly necessary to thrive professionally. Unless your talent and skills absolutely dwarf those of your competition, the deep workers among them will outproduce you.

Jack Dorsey is important to our discussion because he’s an exemplar of a group we cannot ignore: individuals who thrive without depth. When I titled the motivating question of this section “What About Jack Dorsey?,” I was providing a specific example of a more general query: If deep work is so important, why are there distracted people who do well? To conclude this chapter, I want to address this question so it doesn’t nag at your attention as we dive deeper into the topic of depth in the pages ahead.

Indeed, many software companies now deploy the Scrum project management methodology, which replaces a lot of this ad hoc messaging with regular, highly structured, and ruthlessly efficient status meetings (often held standing up to minimize the urge to bloviate). This approach frees up more managerial time for thinking deeply about the problems their teams are tackling, often improving the overall value of what they produce.

It’s bad enough that so many trends are prioritized ahead of deep work, but to add insult to injury, many of these trends actively decrease one’s ability to go deep. Open offices, for example, might create more opportunities for collaboration,* but they do so at the cost of “massive distraction,”

In a well-cited study, Mark and her co-authors observed knowledge workers in real offices and found that an interruption, even if short, delays the total time required to complete a task by a significant fraction. “This was reported by subjects as being very detrimental,” she summarized with typical academic understatement.