Tag: semiconductors

Categories
AI Semiconductors

The Margin of the Weather

A company that has sold memory chips for forty years — memory, one of the most humiliatingly commoditized products in capitalism, a business that has bankrupted entire Korean and Japanese conglomerates teaching each other lessons about discipline — is about to make more money in twelve months than in the previous four decades combined.

Samsung’s chip chief told a room of his own employees: this year’s profit will exceed everything the division has earned since the 1970s. Forty years of grinding, erased by one fiscal year. You’d think they’d invented something.

They hadn’t. Everyone building an AI data center needs memory. Nobody built enough factories. Samsung was one of three companies on earth able to supply the shortfall, and the price of a chip that costs what it always cost went up fifty percent. Samsung kept the difference. Not innovation. What happens to a farmer when the drought hits every field but his.

We don’t credit the lucky farmer with genius. We say: good year. And we don’t expect the good year to repeat. Rain comes back. The price falls. Scarcity is weather, not a personality trait.

There’s a real achievement in this story too, and it has nothing to do with the weather. A year ago Samsung failed to qualify its most advanced memory for Nvidia’s systems — performance problems, a rival getting the business instead. The engineers went back and fixed it. That’s the actual skill in this company’s year: unglamorous, uncelebrated at the town hall, worth nothing next to the number that got the confetti. The competence arrived quietly, on a different chip, in a different meeting, and nobody’s putting that on a plaque.

The stock market didn’t put it on one either, but it seemed to know the difference. Best quarter in Samsung’s history — profit nineteen times the year before — and the shares fell seven percent. Not despite the earnings. The gain had already been priced in, the shares having run up a hundred and fifty percent on the expectation of exactly this number, so the number’s arrival became a ceiling instead of a floor. A market rewards discovery. It does not reward weather. Had investors believed Samsung built something durable — the Nvidia qualification, the years of engineering behind it — the stock would have ripped, the way See’s Candies or Apple gets rewarded quarter after quarter, because everyone agrees the thing generating the money isn’t going anywhere. Instead the market glanced at the record harvest and asked, politely, whether it would rain again next year.

Analysts insist the shortage holds through next year. Someone always insists that, right before it doesn’t. Fabs get built. Capacity catches the demand that summoned it, the way it always has, and the cycle ends the way memory cycles end — too much supply chasing too little demand, margins reverting toward the number they were always going to revert toward. Nobody knows if this time is different. A company just posted the best year of its life, on a windfall it didn’t earn and a fix it did, and the market — which has seen droughts end before — hasn’t decided yet which one it’s watching.

Categories
AI AI: Inference Semiconductors Uncategorized

5 Critical Management Lessons from the Founders at Etched

How two young founders are building what could become one of the most important companies in the AI era — and what their story teaches about leadership, execution, and building at the edge of the possible.

I recently listened to the latest Invest Like the Best podcast from Patrick O’Shaughnessey which was a remarkable conversation with Gavin and Rob, the founders of Etched, the company building specialized AI inference hardware that’s aiming to be radically better than existing solutions. Their story — starting as very young founders against massive skepticism, raising serious capital, and now shipping full rack-scale systems — is packed with hard-earned wisdom.

One of the comments Patrick makes at the beginning was how during his due diligence on the company he kept being told that semiconductor technology wasn’t a place for young people. You need seasoned, middle age experts to master this domain. Exactly not these founders.

Note: the following is based upon an AI’s analysis of the conversation transcript with me asking “What are the five most important management lessons from this conversation?” These lessons are relevant whether you’re leading a team, building a product, or simply trying to do meaningful work in our fast-moving world.

1. Velocity Compounds — Prioritize Speed Ruthlessly

In hardware, and increasingly in any deep-tech endeavor, speed isn’t just an advantage; it’s often the deciding factor.

Etched didn’t just design a chip — they built the full inference solution (chip, board, power delivery, interconnects, cold plates, and production processes) in parallel. They sent engineers to live in Bangalore for months to unblock vendors. They ran 24/7 shifts and did massive pre-work (including putting full chip designs on FPGA clusters) so that when the silicon finally arrived, they had working inference in racks in just 40 days.

Key takeaway: Look for every opportunity to parallelize. Accept higher short-term costs if they buy meaningful time. As they put it, “You win by shipping.” The best part is often no part — and the best vendor is no vendor, when vertical integration lets you move faster. Velocity, velocity, velocity.

2. Build Teams with Legends + High-Drive Talent

One of the most distinctive parts of their approach is how they recruit. They seek out “Legends” — people who have done the hardest versions of the problem before (like the engineer who built Nvidia’s HGX and DGX systems) — and pair them with exceptionally driven, somewhat naive high-performers who refuse to accept conventional limits.

They use “project-based recruiting,” mapping the hardest technical problems ever solved and persistently pursuing the actual people who did the real work. Their culture self-selects for people willing to move their families to San Jose to bet on two young founders taking on the world.

Key takeaway: For breakthrough work, average talent doesn’t suffice. The combination of deep experience and raw, first-principles energy creates magic. Invest heavily in finding and retaining these people — even if it takes 20 conversations. You can also learn a lot if the best in the world talent turns down the opportunity to work with you!

3. Assume It’s Possible, Then Solve the “Unsolvable” Problems

Repeatedly in their story, experts told them certain things were impossible. Their response? Assume it is possible and figure out how.

The most striking example was a clock domain crossing issue that required aligning signals to within 50 picoseconds — something many engineers said couldn’t be done. People quit. They solved it in about two weeks during a very dark period.

Key takeaway: When you hear “impossible,” treat it as the beginning of the investigation, not the end. Cultivate a “find a way” mindset across the team. The moments when things feel hopeless are often when the most important progress happens. I’m constantly struck by how often persistence results from simply realizing (or assuming) that something is actually possible.

4. Production Is the Real Product

Etched’s mantra is “Production is the product.” They obsess over not just technical performance but manufacturability, supply chain resilience, serviceability, and the ability to scale to gigawatts.

They made deliberate choices around process nodes and memory to avoid zero-sum competition. They built their own factory processes and test infrastructure early. Future designs are being simplified specifically for faster production cycles and higher reliability at massive scale.

Key takeaway: In any business that hopes to reach real scale, think end-to-end from the beginning. Technical excellence without production excellence is just a prototype. Optimize for output (tokens, units, whatever your metric is) at volume. There’s a lot of “zero to one” thinking here.

5. Bet Big and Stay Existentially Focused

Building in semiconductors requires enormous capital. Etched raised roughly $100 million early on when they were still very young and pre-tapeout — after most traditional investors had passed. They knew half-measures wouldn’t work.

This existential focus (this one product determines whether the company lives or dies) creates a different level of intensity that attracts talent, suppliers, and customers who believe.

Key takeaway: Match your ambition with appropriate resources and commitment. Clear existential stakes help filter for the right people and partners. In a world of distractions, singular focus on what truly matters is a superpower.

Final Thoughts

Gavin and Rob’s story is the combination of technical sophistication and deep human resilience. They faced a tough personal battle with cancer (in Rob’s case), widespread doubt, brutal technical challenges, and fundraising pressure — and kept moving forward with curiosity, determination, and humility.

In an age of AI and accelerating technology, the ability to build teams that can solve seemingly impossible problems at speed may be one of the most valuable capabilities a leader can develop. Their example reminds us that the future belongs not just to the smartest, but to those who can execute with urgency while maintaining clear principles. Velocity, velocity, velocity.

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 company’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 doesn’t need a formula. It simply is what it is.

Sacerdote designed the metric to cut through a specific kind of noise — the companies claiming AI exposure they don’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 wasn’t becoming the global payments infrastructure. It was the global payments infrastructure. The work was real — fraud detection, modeling, the daily labor of keeping something enormous running — 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.

There’s a particular feeling to working inside something that has already won. It’s not complacency exactly. The problems are genuine and the stakes are high. But the uncertainty has a different quality — it’s operational uncertainty, not existential uncertainty. You’re not asking whether the thing will survive. You’re asking how to run it well.

I didn’t have language for that distinction then. Sacerdote’s metric gives me some. The companies that score highest on his New Rule of 40 have resolved their existential question. They’re not fighting for position. They’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. That’s not a boast — it’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 — 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 — one person, one particular configuration of experience and attention and accumulated knowing — 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.

I’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.

That’s not an ending. It’s a different kind of beginning.

Sacerdote’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. That’s the nature of markets. The detector has to change as the signal changes.

But there’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.

That’s not a refutation of Sacerdote. It’s a reminder that feeling like you’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 — ultra-thin, bendable, carrying more light than anything that came before. The cable doesn’t know it’s infrastructure. It just carries what it’s given, at the speed it’s capable of, across whatever distance is required. It doesn’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. That’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. It’s the proof that something was built. And the daily question — for companies, for infrastructure, for a person in his late seventies still writing, still paying attention — is whether what was built is actually load-bearing.

You don’t get to stop finding out.

Categories
Chemicals Petroleum Semiconductors

The Invisible Layer Beneath the Chip

At the edge of a semiconductor fab, nothing looks dramatic.

No flames. No smoke. No sense of weight.

Just pipes, valves, and a silence so controlled it feels artificial.

It’s easy, standing there, to believe that oil—the old engine of the economy—has been replaced by something cleaner, lighter, more abstract. Software, maybe. Or data. The kinds of things that don’t spill.

But step a little closer, and the illusion breaks.

A modern fab is less like a factory and more like a chemistry experiment that never ends. Gases move through stainless steel arteries. Liquids are mixed, spun, deposited, stripped away. Surfaces are etched and re-etched until what remains is measured in atoms, not microns. The machines—Applied Materials, Lam Research—are precise, but they are not the story. The story is what flows through them.

Chemicals are doing the real work.

Not in bulk, the way oil once did. Not with force. But with specificity.

A barrel of oil is valuable because of its density—how much energy it contains. A liter of photoresist is valuable because of its selectivity—what it allows to exist and what it removes. One powers motion. The other defines structure.

Structure is where the modern economy hides its value.

A semiconductor is not impressive because of what it consumes. It’s impressive because of what it constrains. Billions of transistors, each one placed, shaped, and insulated with a chemical discipline that borders on obsession. The difference between a working chip and a useless one is often a contaminant you cannot see.

This is a different kind of industrialism.

The 20th century scaled by adding more—more fuel, more steel, more throughput. The 21st century scales by removing everything that shouldn’t be there. Purity is the limiting factor. Not how much you can move, but how precisely you can control.

From a distance, it can look like oil has become less important. The headlines have shifted. The glamour has moved on.

But the truth is more entangled.

Most of the chemicals inside a fab begin their lives as hydrocarbons. The solvents, the polymers, even some of the specialty gases—downstream of the same geological inheritance. Oil didn’t disappear. It changed roles. It moved from the foreground to the substrate.

The question, then, isn’t whether chemicals have replaced oil. It’s whether the economy has learned to express value differently.

Less in how much energy we can release. More in how carefully we can shape matter.

Semiconductors are the clearest example, but not the only one. Pharmaceuticals follow the same logic. Advanced materials, too. In each case, the breakthrough isn’t scale—it’s control. The ability to operate at the edge of what’s physically possible, and to do it repeatedly.

Which raises a quieter possibility.

That the defining resource of the next era isn’t oil, or even chemicals.

It’s precision.

And chemistry is simply the language we use to achieve it.