I found Huang to be an elusive subject, in some ways the most difficult I’ve ever reported on. He hates talking about himself and once responded to one of my questions by physically running away. Before this book was commissioned, I had written a magazine profile of Huang for The New Yorker. Huang told me he hadn’t read it, and had no intention of ever doing so. Informed that I was writing a biography of him, he responded, “I hope I die before it comes out.”

Still, Huang offered me access to a great number of people to report this book. I spoke with almost two hundred people, including his employees, his cofounders, his rivals, and several of his oldest friends. The beloved and even somewhat goofy family man who emerged from these interviews bore little resemblance to the unapologetically carnivorous executive who made Nvidia succeed, but it is these same attachments that spur Huang’s ambition: he spoke frankly with me of his insecurities, his fear of letting his employees down, his fear of bringing shame to the family name. Some executives speak of profit as “keeping score,” but not Huang; for him, the money is only temporary insurance against some future calamity. There was something a little touching about hearing a man worth a hundred billion dollars talk in this way.

From both men, Altman also learned the importance of building relationships and creating “network effects” as an individual. “I’ve heard a lot of different theories about how things get done,” he wrote on his blog in 2013. “Here’s the best one: a combination of focus and personal connections. Charlie Rose said this to Paul Graham, who told it to me.” Altman would later add a third ingredient: self-belief. “For startups I think it’s really important to add this,” he said. “You actually have to believe you might do it.”

Through the course of my reporting, I would come to conclude something even more startling. Not even in Silicon Valley did other companies and investors move until after ChatGPT to funnel unqualified sums into scaling. That included Google and DeepMind, OpenAI’s original rival. It was specifically OpenAI, with its billionaire origins, unique ideological bent, and Altman’s singular drive, network, and fundraising talent, that created a ripe combination for its particular vision to emerge and take over. “I get the sense that Sam is the most ambitious person on the planet,” a former employee says. In other words, everything OpenAI did was the opposite of inevitable; the explosive global costs of its massive deep learning models, and the perilous race it sparked across the industry to scale such models to planetary limits, could only have ever arisen from the one place it actually did.

Early in his career, Altman observed that new CEOs only succeeded if they “refounded” the company. He did this with conviction at YC when he inherited the presidency. He created new programs, including a new fund, to expand the accelerator’s support for startups at different stages. He moved into hard technologies—those that required ambitious scientific innovation, including nuclear fusion, quantum computing, and self-driving cars. Already a prestigious name brand, YC’s sphere of influence grew from a couple hundred companies to thousands a year, turning it into a center of gravity in Silicon Valley. “The thing that I’m most proud of is we really built an empire,” Altman said after stepping down as president.

With every team stretched dangerously thin, managers begged Altman for more head count. There was no shortage of candidates. After ChatGPT, the number of job applicants clamoring to join the rocket ship had rapidly multiplied. But Altman worried about what would happen to company culture and mission alignment if the company scaled up its staff too quickly. He believed firmly in maintaining a small staff and high talent density. “We are now in a position where it’s tempting to let the organization grow extremely large,” he had written in his 2020 vision memo, in reference to Microsoft’s investment. “We should try very hard to resist this—what has worked for us so far is being small, focused, high-trust, low-bullshit, and intense.

“The overhead of too many people and too much bureaucracy can easily kill great ideas or result in sclerosis. Unlike the big-iron engineering projects of the past, we could fulfill our mission with a surprisingly small number of great people.”