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Reinvent yourself out of fear
Reinvention and relevance
Some people dominate in one domain for decades, as Steve Jobs and Jensen Huang did. The hurricane around them keeps changing their jobs, so they keep going. Remaking yourself repeatedly is the harder version, and the reason anyone does it is a deep, insecure need to remain relevant and to prove they aren't getting old or out of date.
Letting go of ego
Looking back, each time Doug Leone remade himself, fear of being gone was behind it, and vision and greatness had little to do with it. He still feels that fear at sixty-nine. The way through is to let go of ego, to assume you know nothing each time, and to start at the bottom.
Starting at the bottom
When he returned to Sequoia with the title of chairman, he called the title nonsense and described himself to investors as a low-level analyst who has to prove himself. Ninety days in, he felt good for nothing, with AI further from him than when he began. If he still feels as irrelevant nine months from now, a year after his return, he plans to take himself out.
Why do dominant companies struggle to reinvent themselves?
Clayton Christensen of Harvard Business School laid out the pattern in his 1997 book The Innovator's Dilemma. Successful companies listen closely to their best customers, who ask for improvements to what already exists, so they underinvest in new technologies that start out small and cheap. By the time those technologies improve enough to matter, the newcomers have a head start.
How did Steve Jobs remake his own career?
Jobs left Apple in 1985 after a power struggle and founded NeXT, then bought the computer graphics division of Lucasfilm in 1986 and turned it into Pixar. Apple acquired NeXT in 1997, which brought him back to the company he had co-founded. The iMac followed in 1998 and the iPod in 2001.
How did Jensen Huang keep Nvidia reinventing itself?
Huang co-founded Nvidia in 1993 and has been its chief executive since. In 2006 the company introduced CUDA, a programming platform that let developers run general-purpose software on graphics chips. In 2012, the AlexNet image-recognition system, which won the ImageNet competition, was trained on two Nvidia graphics cards.
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