Categories
AI China Youth

The Arithmetic of Youth

The first meeting was at one of the banks on a high floor somewhere in Shanghai, the kind of view that turns a city into an abstraction. It was 2005, and I was there the way American investors were there that year โ€” curious, a little jet-lagged, trying to read a country that was rewriting itself faster than anyone could print the new edition. Across the table sat a management team, and what struck me wasn’t anything they said. It was how young they were. Not junior-young. Running-the-company young.

Afterward โ€” in the hallway or the car, early in the trip, when I still had the confidence of someone who thought he could just ask โ€” I put the question to one of our local colleagues. Casually, expecting a casual answer. Something about a young country, a young economy, energy meeting opportunity.

The answer I got instead was the Cultural Revolution.

There was a generation, she explained, that simply wasn’t there. Sent to the countryside, pulled out of universities, handed shovels instead of textbooks. By the time China opened back up, that cohort had a hole in it โ€” a rung missing from the ladder. So the young people I’d just watched run that meeting weren’t there because anyone had bet on youth. They were there because there was no one older left to put in the chair. Youth, in that boardroom, wasn’t a strategy. It was a vacancy dressed up as one.

I have thought about that answer, off and on, for twenty years, without knowing what to do with it. Then a few weeks ago I read a summary of a conversation with Nathan Lambert โ€” an AI researcher who’d just spent time visiting the frontier labs in Beijing and Hangzhou โ€” and I found myself back in that room, except everything about the youth in it had flipped.

He describes teams at places like Moonshot AI as almost absurdly young, tight-knit, close to giddy about the work โ€” “the best vibes,” he calls it. Zhipu AI, he says, has built something close to an AGI showroom, a physical space engineered to perform confidence for whoever walks through the door. These aren’t companies with a hole where the experienced people should be. These are companies that went looking for twenty-five-year-olds because twenty-five-year-olds move at the speed frontier AI research demands, and installed them at the center of the room. The showroom isn’t hiding a vacancy. It’s staging a choice. That’s panel two.

Same demographic. Same first city โ€” Beijing both times โ€” with a high-speed rail line now running to Hangzhou instead of whatever second city I’d have named twenty years ago. Opposite cause. In 2005, youth in the room meant a generation had been taken from the labor force involuntarily. In 2026, youth in the room means a generation has been selected for it, deliberately, competitively, because being young is now the qualification rather than the disqualifier. The Cultural Revolution left a gap that youth filled by default. The AI boom left a door that youth is filling by design.

I would have stopped there, satisfied with the irony, except for a number I couldn’t get out of my head once I went looking for it: 15.6 percent. That’s China’s urban youth unemployment rate โ€” ages sixteen to twenty-four, university students excluded โ€” as of May 2026, and it counts as good news, down from 16.3 percent in April. A year earlier it had spiked to nearly nineteen percent in a single August, the month twelve million university graduates walked out of commencement and into a labor market that had no idea what to do with them. Some will sit for civil service exams, chasing what people there still call the iron rice bowl โ€” the illusion of permanence a state job used to guarantee, back when your grandparents didn’t choose their careers so much as get assigned them. Others will enroll in another degree, not because they want one, but because a classroom is a more dignified place to wait than an unemployment line.

So there is a third panel now, and it doesn’t fit neatly next to the other two. It isn’t a vacancy, and it isn’t a showroom. It’s just a very large number of young Chinese people who did everything they were told to do โ€” studied hard, got the degree โ€” and are standing outside a door that isn’t opening. And somewhere behind that door, in a much smaller room with much better lighting, another group of young Chinese people, maybe the same graduating class, are building the technology that a Silicon Valley researcher travels overseas to admire for its vibes.

I don’t think those two rooms are as separate as they look. I think the showroom is real, and I think the twelve million are real, and I think the mistake โ€” my mistake, sitting here in Menlo Park two decades removed from that conference table โ€” is letting either one stand in for “Chinese youth” as if it were a single sentence instead of a population. The Moonshot AI team is not a representative sample. It’s the visible sliver of a generation, selected with a precision that turns the unemployment numbers into part of the same mechanism โ€” one sorting process, not two unrelated stories. The best vibes in that lab and the worst numbers in that economy might just be describing the two ends of the same funnel.

I keep coming back to that hallway in 2005, and to how confident I was in the question I asked โ€” as if a generation’s youth could only ever be telling one story. It couldn’t then, and it can’t now. I got a true answer that day and thought I understood something. I understood one panel of a triptych I hadn’t seen the rest of yet โ€” and I’m still not sure I’ve seen all of it.

Categories
Aging AI Business Living

The Being Phase

There is a metric making the rounds in technology investing circles that is, on its face, about market share and revenue concentration. Alex Sacerdote of Whale Rock Capital calls it the New Rule of 40 for AI. The formula is simple: take the percentage of a companyโ€™s sales derived from AI, add its percentage market share in that AI category, and if the sum reaches 40, you have a winner. Celestica, a company most people have never heard of, scores extraordinarily well. It owns somewhere between half and sixty percent of the cloud Ethernet white-box switch market. NVIDIA doesnโ€™t need a formula. It simply is what it is.

Sacerdote designed the metric to cut through a specific kind of noise โ€” the companies claiming AI exposure they donโ€™t actually have, the giants whose AI revenue hovers at one or two percent of their base while their press releases suggest otherwise. The framework is a detector. It finds the companies that have stopped becoming AI infrastructure and started simply being it.

I found myself less interested in the companies than in that distinction.


I spent years at Visa watching a network that had long since crossed that threshold. By the time I arrived, Visa wasnโ€™t becoming the global payments infrastructure. It was the global payments infrastructure. The work was real โ€” fraud detection, modeling, the daily labor of keeping something enormous running โ€” but the existential question had been settled before I got there. The network existed. Merchants accepted it because cardholders carried it. Cardholders carried it because merchants accepted it. That loop had been closing for decades. We were custodians of a fait accompli.

Thereโ€™s a particular feeling to working inside something that has already won. Itโ€™s not complacency exactly. The problems are genuine and the stakes are high. But the uncertainty has a different quality โ€” itโ€™s operational uncertainty, not existential uncertainty. Youโ€™re not asking whether the thing will survive. Youโ€™re asking how to run it well.

I didnโ€™t have language for that distinction then. Sacerdoteโ€™s metric gives me some. The companies that score highest on his New Rule of 40 have resolved their existential question. Theyโ€™re not fighting for position. Theyโ€™re administering a position already held.


The question that has followed me out of that career, and out of several decades of watching technology cycles turn, is simpler and more personal than any investment framework.

When did I cross that line myself?


I have been writing at sjl.us since 2001. Thatโ€™s not a boast โ€” itโ€™s a data point. Twenty-five years of thinking out loud, of ideas arriving rather than being argued, of the specific memory as structural anchor. The blog is not becoming anything. It is what it is: a record of a mind moving through time, accumulated into something that has its own weight and shape.

The book on payments systems exists. The career at Visa exists. The photographs exist. The train journeys exist. The years in Dayton exist, and the years on the Peninsula, and the particular way the light falls on the California coast at Pescadero in the late afternoon โ€” when the fog is still offshore and the hills are improbably green and everything goes briefly, completely quiet, as if the world is deciding whether to continue.

These are not things I am building toward. They are things I am.

Sacerdote would say I have high market share in a specific category. The category is small โ€” one person, one particular configuration of experience and attention and accumulated knowing โ€” but the share is essentially total. There is no competitor for the position of having lived this particular life. The moat is absolute. The switching costs are infinite.

I used to find that thought melancholy. The narrowing as loss. The aperture closing on what remains.

Iโ€™m not sure I find it melancholy anymore.


The L-Curve, Sacerdote says, is a long flatline followed by a vertical explosion. The tinkering phase, then the moment of lift. He means it as a description of demand curves for technology infrastructure. But I recognize the shape from somewhere closer. The long middle of a life, building and becoming, and then the morning you wake up and realize the building is substantially done. What remains is the being.

Thatโ€™s not an ending. Itโ€™s a different kind of beginning.


Sacerdoteโ€™s metric will eventually stop working. All frameworks do. The AI infrastructure cycle will mature, the L-Curves will flatten, and some new measure will emerge to find the next thing that is just beginning to become what it will be. Thatโ€™s the nature of markets. The detector has to change as the signal changes.

But thereโ€™s a complication worth naming. Analysts at Citadel Securities published a note recently observing that even the most powerful technologies must pass through the prosaic discipline of cost curves, capacity constraints, and marginal returns. Token bills are arriving unexpectedly. Compute is scarce. The vision of AI as ubiquitous, frictionless, and immediate is colliding with physical reality. Their conclusion: asset prices will periodically be forced to reconcile ambition with physical constraint.

Thatโ€™s not a refutation of Sacerdote. Itโ€™s a reminder that feeling like youโ€™ve arrived and having actually arrived are different things. The being phase has to be load-tested. The position has to hold under pressure.

I think about the fiber optics Corning is laying into the massive data center clusters โ€” ultra-thin, bendable, carrying more light than anything that came before. The cable doesnโ€™t know itโ€™s infrastructure. It just carries what itโ€™s given, at the speed itโ€™s capable of, across whatever distance is required. It doesnโ€™t matter what the cable believes about itself. What matters is whether the light actually moves.

That seems right to me. You become what you are over a long time, largely without noticing. And then one day someone builds a metric that accidentally describes your life, and you recognize yourself in it, and you think: yes. Thatโ€™s the shape of it. High concentration. High share. A moat that deepened while you were looking elsewhere.

But the moat still has to hold.

The being phase, it turns out, is not the end of something. Itโ€™s the proof that something was built. And the daily question โ€” for companies, for infrastructure, for a person in his late seventies still writing, still paying attention โ€” is whether what was built is actually load-bearing.

You donโ€™t get to stop finding out.

Categories
Dayton Ohio Memories

The Mirror and the Boxcar

When the plane started circling, I needed to disappear.

I was just goofing around on my own with an army surplus signaling mirror in our treeless backyard in Kettering. A thick piece of bright rectangular glass with an opening in the middle where light could shine through a cross. To signal you had to line up the light shining through with the opening.

Living close to Wright-Patterson, C-119 Flying Boxcars were a common sight. I could hear one coming before I could see it. I turned and scanned the sky. There it was.

Maybe this was worth a try. What did it even mean?

I held it up, aimed and hoped.

Then I saw it. The plane started a turn to the left. Uh oh.

I didnโ€™t want to be reported. I ran into the woods behind our house. I watched and waited.

The circle completed. The boxcar flew on.

I walked back into the house and put the mirror back on the chest of drawers in my bedroom.

I never told anyone. Not even you.

Categories
Books

The Observer Observed

I first encountered Susan Orlean not in person, but in the ashes. Specifically, the ashes of the Los Angeles Central Library. Reading The Library Book was a masterclass in how to weave a forensic investigation with a love letter to a public institution. It was reportage, but it possessed a beating heart. She has spent decades at The New Yorker perfecting the art of the “curious observer”โ€”the person standing just to the side of the frame, noticing the detail everyone else missed.

That is why picking up Joyride felt different.

In a memoir, the observer must finally step in front of the lens. The transition from The Library Bookโ€”which is about the preservation of collective memoryโ€”to Joyrideโ€”which is about the fluidity of personal memoryโ€”is a fascinating shift. When a journalist writes a memoir, there is often a tension. They are used to looking outward, hunting for the story in orchids or arsonists. Turning that gaze inward requires a different kind of bravery.

“A commute has a destination; a joyride has only a duration.”

The title itself suggests a specific philosophy of living. It implies that the movement itself is the point. As I read, I found myself thinking about the difference between navigating a life and simply driving through it. Orlean captures that distinct feeling of the wind in your hair, the blur of the scenery, and the realization that the “plot” of our lives is often just the things that happen while we are busy steering.

We read writers like Orlean not just for what they saw, but for how they saw it. In Joyride, she reminds us that the most interesting routes are rarely the most direct ones. A great read!

Categories
Apple Living

Make It Great

In the car this morning, I listened to the 5by5 special podcast Thank You, Steve Jobs with its series of personal stories and tributes to the man. It’s a wonderful collection of reflections.

As I was listening, I was thinking back to the late 1980’s when, through some random combination of events, I ended up spending about a half hour with Steve Jobs one on one. The scene was a conference room at Steve’s then-new NeXT in Redwood City, down by the big salt pile off Seaport Boulevard. His purpose was to show me NeXTSTEP and how easy it was to develop applications in this new environment. I remember being blown away by the demo – just another one of his amazing performances. I never met him again.

Over the weekend, I came across a link to the Pixar home page and their tribute to Steve Jobs. It brought to mind perhaps the most recurring theme I’ve taken away from this man: Make it great. Or, with emphasis, make it insanely great.

A while back I wrote about “is this the best you can do?” Make it great ensures that it is. Great isn’t perfect – but it’s pretty darn close.