They called me Spock in 7th grade. Some still do.
What sounded like a jab turned out to be a job description.
Most people don’t get paid for seeing the system. They get paid for maintaining it.
I’ve been on this curve my whole life. And it feels like the right moment to start writing it down.
I read Isaac Asimov before I understood he was training me to think in systems. I absorbed Ray Kurzweil early, and The Age of Spiritual Machines didn’t feel speculative to me. It felt directional. Less prediction than belief. A statement about where intelligence was headed and what that would do to us once it arrived at scale.
I came up on William Gibson not as science fiction, but as signal — Neuromancer, Pattern Recognition — stories about how culture mutates around technology long before institutions notice.
I learned COBOL in 6th grade. I wrote a term paper on a Commodore 64. I watched the world go from Pong to PS5, from “a computer” to “a network,” from “a website” to “a life.”
What mattered wasn’t the hardware. It was watching abstractions collapse into behavior.
I had an early Mac. I was on email when it still felt like a strange new language. I carried one of the first Motorola cell phones. I made one of the first online ad banners. I watched connectivity move from novelty to necessity, from convenience to infrastructure.
Then I did what my generation of builders did: I translated new technology into culture. I built a company around helping brands not just “go digital,” but be digital. I sat in rooms where transformations were approved, funded, delayed, reshaped, and sometimes killed by fear. I watched “impossible” become infrastructure more than once.
Somewhere in there, Marshall McLuhan clicked for me. Technology isn’t just a tool. It’s an environment. And at HBS, sitting in Clayton Christensen’s classroom, disruption stopped being abstract. I could map the theory directly to what I’d already watched happen inside real organizations: smart people, well-resourced institutions, losing not because they lacked intelligence, but because they misread the curve.
I once sat in a boardroom with Andy Grove. As the meeting opened, he looked at me and said:
“I’ve noticed that the quality of your ideas is usually in inverse proportion to the amount of setup you do. So let’s just get to the ideas.”
That line never left me. Not as a critique, but as a discipline. Clarity doesn’t need ceremony. Good judgment doesn’t need theatrics. When the thinking is sound, the signal carries on its own.
So no, I’m not surprised by AI.
Not because this is the first time machines have learned, but because this is the first time intelligence has spread this fast, this cheaply, and this unevenly.
This wave isn’t a new channel. It’s intelligence becoming widely accessible. When intelligence becomes accessible at scale, leverage changes.
You don’t just get faster writing.
You get faster planning.
Faster synthesis.
Faster persuasion.
Faster creation.
Faster mistakes.
Faster confusion.
Faster everything.
It collapses the distance between intention and execution.
Which is exhilarating — until you realize how much bad intent and unclear thinking already existed.
This isn’t about to happen. It already has.
Which means the organizations still “preparing for AI” are already late. The tools are already in the room. Access has already spread. Speed is already becoming the default.
That’s not a reason to panic. It’s a reason to get disciplined.
Because when speed becomes default, the scarcity shifts.
The scarcity is no longer tools.
The scarcity becomes judgment.