The job has never really changed.
I go hands-on first. I learn a new technology deeply, figure out where it is headed, and carry what I find to CEOs and boards so they can move before the market does. The technology keeps changing. The discipline does not. Right now that technology is AI, and I am more convinced by it than by anything I have worked on before.
I went to MIT at sixteen to become an astronaut.
Two months into the Navy ROTC flight program, my eyesight washed me out. I was certain my life was over, the way a teenager is certain of things. Then I wandered into an open house at the MIT Artificial Intelligence Laboratory, and I fell in love. I spent the next four years there, teaching and building robots, and eventually earned a PhD in AI.
It took decades for that training to become the center of the story. It finally has. Everything I learned about approximation, computation, and learning machines turned out to be the foundation of the era we are now living through.
I have been in the room for four of these shifts.
I advised Lou Gerstner as IBM bet the company on the internet; that work grew into a $15B business. I was Chief Technology Advisor to Bob Moritz as PwC moved 6,000 partners and 160 territories to the cloud. I founded Google Cloud's Applied AI business and grew it across NASA, healthcare, and genomics into one of Cloud's fastest segments. I scaled Photobucket to 50 million users before it was acquired for $300M. Today, at Alphabet, I work on generative AI, where the same pattern is playing out in content and advertising.
Every day I write down one thing AI actually did.
One verified deployment that moved a real number. When I ran out of hand-picked examples, I built a scanner that reads every earnings call and SEC filing across the major indexes and validates each deployment against independent sources. That became The Ledger: 5,000+ verified deployments and counting.
The pattern underneath the data became a thesis I have spent a decade working through. I call it the Approximation Era. The short version: AI is a universal approximator, we are trading calculus for compute, and one industry after another is becoming computable. It is not a tech trend. It is a phase change.
Why I count.
All of it points at one thing.
My mother died of cancer at 57. Before she went, she made my brother and me promise to find a better way. He became an oncologist. I became the AI guy. The Approximation Era is how we finally keep the promise.
That promise is why I sit on the tumor board at Stanford Medicine, why I serve on the board of the Lustgarten Foundation for pancreatic cancer research, and why I started the AI Cancer Forum with my mentor Lee Hood. Lee and I have been circling an idea we call Clearome: the same approximation engine pointed squarely at cancer, phenomics read like a movie of the body. It is early. It is a conversation between two people who have been at this a long time, not a company and not a plan. But it is the direction the evidence keeps pointing, and the one I care about most.
Katherine Johnson did the math by hand because there was no other way. We have other ways now. The work is the same. Show up. Take the next step. Keep stepping.