As self-help workshops go, Applied Rationality’s is not especially accessible. The center’s three founders — Julia Galef, Anna Salamon and Smith — all have backgrounds in science or math or both, and their curriculum draws heavily from behavioral economics. Over the course of the weekend, I heard instructors invoke both hyperbolic discounting (a mathematical model of how people undervalue long-term rewards) and prospect theory (developed by the behavioral economists Daniel Kahneman and Amos Tversky to capture how people inaccurately weigh risky probabilities). But the premise of the workshop is simple: Our minds, cobbled together over millenniums by that lazy craftsman, evolution, are riddled with bad mental habits. ... Some of these problems are byproducts of our brain’s reward system. ... logical errors may be easy to spot in others, the group says, they’re often harder to see in ourselves. The workshop promised to give participants the tools to address these flaws, which, it hinted, are almost certainly worse than we realize. ... Most self-help appeals to us because it promises real change without much real effort, a sort of fad diet for the psyche. ... CFAR’s focus on science and on tiresome levels of practice can seem almost radical. It has also generated a rare level of interest among data-driven tech people and entrepreneurs who see personal development as just another optimization problem, if a uniquely central one. Yet, while CFAR’s methods are unusual, its aspirational promise — that a better version of ourselves is within reach — is distinctly familiar. The center may emphasize the benefits that will come to those who master the techniques of rational thought, like improved motivation and a more organized inbox, but it also suggests that the real reward will be far greater, enabling users to be more intellectually dynamic and nimble. ... CFAR’s original mandate was to give researchers the mental tools to overcome their unconscious assumptions. ... What makes CFAR novel is its effort to use those same principles to fix personal problems: to break frustrating habits, recognize self-defeating cycles and relentlessly interrogate our own wishful inclinations and avoidant instincts.

If you made a movie about a laid-off, sad-sack, fiftysomething guy who is given one big chance to start his career over, the opening scene might begin like this: a Monday morning in April, sunny and cool, with a brisk wind blowing off the Charles River in Cambridge, Mass. The man—gray hair, unstylishly cut; horn-rimmed glasses; button-down shirt—pulls his Subaru Outback into a parking garage and, palms a little sweaty, grabs his sensible laptop backpack and heads to the front door of a gleaming, renovated historic redbrick building. It is April 15, 2013, and that man is me. I’m heading for my first day of work at HubSpot, the first job I’ve ever had that wasn’t in a newsroom. ... Arriving here feels like landing on some remote island where a bunch of people have been living for years, in isolation, making up their own rules and rituals and religion and language—even, to some extent, inventing their own reality. This happens at all organizations, but for some reason tech startups seem to be especially prone to groupthink. Every tech startup seems to be like this. Believing that your company is not just about making money, that there is a meaning and a purpose to what you do, that your company has a mission, and that you want to be part of that mission—that is a big prerequisite for working at one of these places. ... Another thing I’m learning in my new job is that while people still refer to this business as the “tech industry,” in truth it is no longer really about technology at all. “You don’t get rewarded for creating great technology, not anymore,” says a friend of mine who has worked in tech since the 1980s, a former investment banker who now advises startups. “It’s all about the business model. The market pays you to have a company that scales quickly. It’s all about getting big fast. Don’t be profitable, just get big.”

In a searing investigation into the once lauded biotech start-up Theranos, Nick Bilton discovers that its precocious founder defied medical experts—even her own chief scientist—about the veracity of its now discredited blood-testing technology. She built a corporation based on secrecy in the hope that she could still pull it off. Then, it all fell apart. ... At Theranos, Holmes preferred that the temperature be maintained in the mid-60s, which facilitated her preferred daily uniform of a black turtleneck with a puffy black vest—a homogeneity that she had borrowed from her idol, the late Steve Jobs. ... Holmes had learned a lot from Jobs. Like Apple, Theranos was secretive, even internally. Just as Jobs had famously insisted at 1 Infinite Loop, 10 minutes away, that departments were generally siloed, Holmes largely forbade her employees from communicating with one another about what they were working on—a culture that resulted in a rare form of executive omniscience. At Theranos, Holmes was founder, C.E.O., and chairwoman. There wasn’t a decision—from the number of American flags framed in the company’s hallway (they are ubiquitous) to the compensation of each new hire—that didn’t cross her desk. ... And like Jobs, crucially, Holmes also paid indefatigable attention to her company’s story, its “narrative.” ... In a technology sector populated by innumerable food-delivery apps, her quixotic ambition was applauded. ... she is often surrounded by her security detail, which sometimes numbers as many as four men, who (for safety reasons) refer to the young C.E.O. as “Eagle 1”—and headed to the airport. (She has been known to fly alone on a $6.5 million Gulfstream G150.) ... it is impossible to get a precise result from the tip of a finger for most of the tests that Theranos would claim to conduct accurately. When a finger is pricked, the probe breaks up cells, allowing debris, among other things, to escape into the interstitial fluid. While it is feasible to test for pathogens this way, a pinprick is too unreliable for obtaining more nuanced readings. Furthermore, there isn’t that much reliable data that you can reap from such a small amount of blood.