This sense of magical control can be intoxicating and fun; it lends itself frequently to a sort of starry-eyed idealism. And it can also lead, particularly in younger coders—who’ve yet to be humbled by life and their own screw-ups—to some epic hubris. People who excel at programming, notes the coder and tech-culture critic Maciej Cegłowski, often “become convinced that they have a unique ability to understand any kind of system at all, from first principles, without prior training, thanks to their superior powers of analysis. Success in the artificially constructed world of software design promotes a dangerous confidence.” Or as the computer scientist Joseph Weizenbaum noted in 1976, “one would have to be astonished if Lord Acton’s observation that power corrupts were not to apply in an environment in which omnipotence is so easily achievable.”

It is accompanied by its close cousin, a fierce devotion to efficiency. Since they have, at their beck and call, machines that can repeat instructions with robotic perfection, coders take a dim view of doing things repetitively themselves. They have a dislike of inefficiency that is almost aesthetic—they recoil from it as if from a disgusting smell. Any opportunity they have to automate a process, to do something more efficiently, they will. (Sanghvi even extended this to her nuptials. Her mother wanted to arrange Sanghvi’s marriage in India, and Sanghvi agreed, because it struck her as far more efficient than dating—which you could regard, from a purely computer-scientific point of view, as a woefully resource-intensive sorting algorithm. “I was a big fan of arranged marriages,” as she said once in a speech. “It appealed to the engineer in me. They’re practical, and they had a higher probability of succeeding.”)

Code makes efficiency and scale easy, seductive, almost inevitable. That is also why programmers fit so easily into business building and part of why some slide so frequently into libertarian thinking. Their talents are torqued perfectly for capitalism’s central trick, which is, basically, “do something marginally more efficiently than before and then skim off the profit.” Mind you, software also, by its very nature, weird-ifies a lot of the assumptions of capitalism. A piece of software is a thing, a machine that does something, so you can own it; but because it’s also a form of speech, it can be easily shared. And so it is shared, almost incessantly. Coders are remarkably chatty and open about their everyday work, regularly posting their software problems to online forums and spending hours helping other people solve theirs. (A study in the ’80s concluded that coders were “less loyal to their employers than to their profession.”) Even in the bowels of the most rapaciously capitalistic Silicon Valley firm are coders who spend a lot of time—at their desk, at work—helping solve the bugs of other randos. And there’s often a communitarian spirit in the worlds of free and open source software, where coders often contribute work freely, to software that anyone can also use themselves, freely.

But crucially, nobody was telling them what to program or what not to program. They were the first group of coders who used the machines to do things that were simply whimsical or creative. They’d get the machines to play music by writing code that turned the vibrating speaker on and off at different frequencies. They’d write programs to calculate chess moves, one of which eventually beat an actual human. Russell wrote Spacewar!, one of the world’s first graphical computer games, in which two players each piloted a ship around a black hole, trying to shoot the other. Using a $120,000 machine to play a video game would likely have seemed, to computer-makers at the time, a madly frivolous thing to do. But the MIT hackers regarded themselves as liberating programming from its mundane history of mere bean counting and scientific problem-solving. Coding itself, they felt, was a playful, artistic act.

The Niagara of money in Silicon Valley, though, has been bringing in a new breed of coder that cared considerably less. By the late ’00s, the example of companies like Instagram—minting so many multimillionaires by making something that Facebook or Google might buy—caught the attention of a new breed of striver, one that we might call the Ivy League frat boys. In previous generations, they’d head for Wall Street, hungry to make quick millions. After the financial collapse of 2008, they needed a new field and found it in Silicon Valley. These “brogrammers” who began to show up, some straight from the frat house, weren’t even concerned about the impact of their code; they weren’t even necessarily interested in the intellectual thrill of the work, frankly. For them, the industry was purely a route to power. It’s safe to say that overall this new population has made less of a contribution to coding than to the overall culture of Silicon Valley.

This is the same sort of objective pride that coders often take when they’ve got something working. On the flip side, it’s also part of what can render them arrogant and dickish. You can convince yourself that what you’re doing is real work, and everyone else—the folks in marketing or sales or management—are just pencil pushers who don’t truly produce anything. (Ooooh, the marketing folks say they’ve increased the firm’s “mind share.” The coders will sit, unimpressed, arms crossed, asking: Can anyone really prove that’s true?) From the perspective of a really linear-minded coder, people who are involved in so-called soft-skills work are constantly hiding behind PowerPoint presentations because they can’t actually demonstrate that they’ve accomplished anything of merit. They’re just slinging buzzwords. This attitude can be a particular hazard among younger programmers fresh out of school, who haven’t yet realized the value of all their nontechnical colleagues—the others who are frantically selling and organizing and keeping the company from falling apart. (“I remember as a young programmer going to staff meetings, my eyes glazing over as some big-shot leader with whom I would never directly work showed chart after chart of numbers that I believed to be completely irrelevant to me,” as Chad Fowler, a longtime coder, wrote ruefully in his book The Passionate Programmer. “My teammates sat together, looking like a row of squirming children on a long car ride. None of us understood what was being presented, and none of us cared. We blamed what we felt was a complete waste of time on the incompetent managers who had called the meeting. Looking back on it, I realize how foolish we were.”)

“I tell people, you always take pride in your code. You should always be refactoring it, it should look like you’ve been working on it, when people see it,” he said. A single flabbily written function would convey something other than total commitment to the craft. “I’m a firm believer in the broken-windows theory. You find a bug, you hunt it down and kill it.” Indeed, when Cohen was working hard, he hated anything that took him out of the flow, even eating. While making himself a sandwich in his kitchen, back when I visited him for Wired, he complained that it was taking too long. “Sometimes I wish there were just some way to install energy in your body, like the Terminator putting a battery in his chest,” he said.

Many coders write “on the page,” as it were, working line by line, function by function, testing bits and slowly building up the program. Cohen back in 2004 wasn’t doing this. He’d wander around all day long lost in his head, pondering the weird timing issues of far-flung BitTorrent peers, modeling it in his mind. Then, after hours of this Romantic idyll, the code would come bursting out—and he’d sit down, composing so perfectly that it appeared to have been dictated. (He compared himself, matter-of-factly, to Mozart in Amadeus.) Jenna confirmed it when she wandered into the kitchen while breastfeeding their three-month-old son. “Bram will just pace around the house all day long, back and forth, in and out of the kitchen. Then he’ll suddenly go to his computer and the code just comes flowing out. And you can see by the lines that it’s clean,” she says. “It’s clean code!”

She pats Cohen affectionately on his head. “My sweet little autistic nerd boy.”

In 1976, the computer scientist Joseph Weizenbaum proclaimed that programmers were becoming defective in empathy, because they spent too much time in a tight loop with the machine. Weizenbaum had worked at MIT since the ’60s, and wandered into the AI lab, where he’d beheld the unkempt and often-fragrant original generation of hackers. In a famous passage from his book Computer Power and Human Reason, he described the lab as a world of hopeless addicts, cut off from humanity:

. . . bright young men of disheveled appearance, often with sunken glowing eyes, can be seen sitting at computer consoles, their arms tensed and waiting to fire their fingers, already poised to strike, at the buttons and keys on which their attention seems to be riveted as a gambler’s on the rolling dice. When not so transfixed, they often sit at tables strewn with computer printouts over which they pore like possessed students of a cabbalistic text. They work until they nearly drop, twenty, thirty hours at a time. Their food, if they arrange it, is brought to them: coffee, Cokes, sandwiches. If possible, they sleep on cots near the printouts. Their rumpled clothes, their unwashed and unshaven faces, and their uncombed hair all testify that they are oblivious to their bodies and to the world in which they move. These are computer bums, compulsive programmers . . .

Ho, as it turned out, had a very strict and peculiar itinerary planned for the trip. He’s particularly fond of ramen-noodle dishes, and his goal on this jaunt, he told her, was to visit as many Tokyo ramen shops as possible. To make sure they crammed in as many as they could, he’d created some custom code. Huh? she thought. He explained: First, he’d assembled a list of top Tokyo noodle places and plotted them on a Google Map. Then he’d written code that drew the optimum pathway that connected all the shops, so they could travel in the most efficient route between them. It was, he said, a “pretty traditional” algorithmic challenge, of the sort you learn in college, and he used tricks like this all the time to optimize the way he lived his life. He whipped out his phone to show her the map. He told her he was planning on keeping careful notes about the quality of each meal, too.