Categories
Books Writing

John McPhee Home Library

Im an avid fan of John McPhee having first been introduced to him when he profiled Ted Taylor in the New Yorker in 1973. I’ve collected a stack of his books in our home library. One useful query I’ve used with Gemini is this:

This is a stack of the John McPhee books in our home library. Give me a list with: title, year published; summary; how reviewed; an interesting story about the book.

Here’s the result – good fun!

John McPhee: Library Stack Directory

A detailed guide to the nine books by legendary narrative nonfiction writer John McPhee shown in the library stack. The list is organized in order from the top of the stack to the bottom.

1. Oranges

Year Published: 1967

Summary: An immersive, multi-layered look into the history, botany, and global trade of citrus. McPhee tracks the orange’s journey from its ancient Asian origins through Europe and the Americas, culminating in a detailed portrait of the highly industrialized orange juice concentration plants of 20th-century Florida.

How Reviewed: Celebrated for showing how a single, seemingly mundane topic can be transformed into compelling, poetic literature. Critics praised it as a hallmark text of the “New Journalism” movement and creative nonfiction.

An Interesting Story: McPhee originally intended to write a quick, single article for The New Yorker. However, he became so fascinated by the complex subculture of Florida orange growers and the science of the fruit that he stayed for months, ultimately producing enough rich material to fill this entire book.

2. Pieces of the Frame

Year Published: 1975

Summary: A diverse collection of eleven narrative essays covering eclectic topics, including a family search for the Loch Ness Monster, the landscape and history of Atlantic City, the art of fly-fishing, and the deep geology of the Appalachian basin.

How Reviewed: Warmly praised for its boundless curiosity and McPhee’s signature knack for weaving disparate human interests with environmental science.

An Interesting Story: For the title essay, McPhee brought his wife and young daughters to camp right on the shores of Loch Ness. Instead of writing a cynical piece about a local myth, he embedded with the genuinely dedicated, scientifically minded monster-hunters who spent months using sonar to sweep the deep waters.

3. Irons in the Fire

Year Published: 1997

Summary: A compilation of seven essays focusing on obscure, highly specialized worlds. It features pieces on modern cattle-rustling brand inspectors in Nevada, the lifespan of military cargo planes, the manufacture of forensic charcoal, and the historical journeys of Plymouth Rock.

How Reviewed: Reviewers warmly received the collection, highlighting McPhee’s unique talent for mastering technical jargon and making niche professions completely accessible and thrilling to general readers.

An Interesting Story: In the essay “The Gravel Page,” McPhee introduces the world of forensic geology. He follows an expert who can solve complex criminal cases, like kidnappings or murders, simply by analyzing the microscopic dust, pollen, and soil types caught in a suspect’s shoe treads or car tires.

4. A Sense of Where You Are

Year Published: 1965

Summary: McPhee’s brilliant debut book profiles Bill Bradley during his time as an All-American basketball star at Princeton University—long before Bradley became an NBA champion with the New York Knicks and a U.S. Senator.

How Reviewed: Widely celebrated for its exceptional character development and meticulous analysis of athletic grace, launching McPhee’s legendary literary career.

An Interesting Story: The famous title comes from a moment when Bradley demonstrated his flawless spatial awareness to McPhee. While walking backward away from the basket without looking, Bradley flipped the ball over his shoulder and sunk it. When McPhee asked how he did it, Bradley simply remarked that he just had “a sense of where you are.”

5. The Curve of Binding Energy

Year Published: 1974

Summary: A chilling profile of Theodore Taylor, a visionary nuclear physicist who designed some of the world’s smallest atomic weapons. The book details how alarmingly easy it would be for a motivated individual to steal nuclear material and build a homemade bomb using unclassified, public information.

How Reviewed: Nominated for a National Book Award, this work shocked readers and terrified policymakers by laying bare massive vulnerabilities in domestic nuclear facility security.

An Interesting Story: The book created an immediate national security panic. Because McPhee’s descriptions of security flaws were so detailed and accurate, it acted as a massive wake-up call that forced the U.S. government to dramatically overhaul and tighten security protocols at nuclear stockpiles.

6. The Control of Nature

Year Published: 1989

Summary: An epic three-part exploration of human hubris versus the elements. It profiles three intense battles: the Army Corps of Engineers trying to stop the Mississippi River from changing course, Icelanders fighting a volcanic eruption, and Los Angeles residents combating massive mountain mudslides.

How Reviewed: Frequently heralded as one of McPhee’s ultimate masterpieces, praised for its cinematic tension, incredible environmental writing, and deep philosophical look at humanity’s defiance of nature.

An Interesting Story: During the 1973 eruption on the island of Heimaey, Icelanders refused to let lava swallow their vital fishing harbor. They rigged up miles of plastic piping and pumped millions of gallons of icy ocean water directly onto the glowing molten rock for months, successfully freezing the advance and creating a natural rock breakwater.

7. The Patch

Year Published: 2018

Summary: A late-career compilation split into two sections: immersive outdoor essays covering fishing, bears, and golf courses, followed by “An Album Quilt,” a series of shorter, mosaic-like reflections on historical figures, celebrities, and fellow writers.

How Reviewed: Reviewed as a poignant, comforting, and delightfully nostalgic anthology that showcases a master writer looking back over a lifetime of keen observation.

An Interesting Story: The title essay, “The Patch,” refers to a hidden, pristine pocket of water lilies in a lake in eastern Canada. McPhee’s family kept its exact coordinates a closely guarded secret for generations because it was an unrivaled fishing spot for chain pickerel.

8. Silk Parachute

Year Published: 2010

Summary: An elegant essay collection ranging from the geometric intricacies of lacrosse and the geology of chalk to a loving profile of longtime New Yorker editor William Shawn and deeply personal memories of youth.

How Reviewed: Celebrated for its unique emotional warmth, with critics appreciating the rare, deeply personal glimpses into McPhee’s own childhood and family relationships.

An Interesting Story: The title essay is a tribute to McPhee’s mother. When she was a young woman in the early 20th century, she impulsively went up in a biplane and did a parachute jump just for the thrill of it. In her nineties, she would playfully drop a toy silk parachute out of her window down to her adult son.

9. Uncommon Carriers

Year Published: 2006

Summary: A fascinating look into the invisible freight network that keeps the American continent running. McPhee journeys across the country alongside long-haul truckers, towboat captains moving massive barges on rivers, and operators of cross-country coal trains.

How Reviewed: Highly praised as an eye-opening, deeply engaging look at the modern logistics industry and the eccentric, highly dedicated people who master it.

An Interesting Story: To write the opening chapter, McPhee spent days living in the cramped cab of a chemical tanker truck driven by Don Ainsworth. Ainsworth was an elite driver who treated long-haul trucking like a fine art, teaching McPhee the high-stakes rules, specific lane etiquette, and hidden subculture of the open road.

Categories
AI

The Transit Authority

Today SpaceX went public. The valuation target was $1.77 trillion — already the largest IPO in history, surpassing Saudi Aramco — and the market wanted more.

I was curious about the S-1, so I read the TAM section. SpaceX claims a total addressable market of $28.5 trillion. Rockets and Starlink together account for about $2 trillion of that. The rest — $26.5 trillion — is artificial intelligence. Enterprise AI applications alone: $22.7 trillion.

IDC analyst Arnal Dayaratna said the quiet part out loud: “To be crystal clear, its positioning there right now is basically nonexistent.”

That is an honest sentence. It describes most TAM claims in most S-1 filings. The market did not care. The stock was up 25% anyway.

But the $22.7 trillion number is interesting regardless of whether SpaceX captures it. It asks a real question: how large is the enterprise AI opportunity, really? And what does capturing it actually require?

The answer has something to do with transportation.

We do not travel the same way for every trip.

Walk to the coffee shop. Take a scooter to the office. Ride share to the airport. Commute by train. Drive your own car on weekends. Fly when you need to get somewhere fast and far.

Each mode has a different cost structure, a different latency, a different quality profile. Nobody takes a plane to buy milk. Nobody walks to a meeting in another city. We allocate the mode to the trip, instinctively, without much thought. The routing decision is invisible.

AI inference is arriving at exactly this moment. Until recently, there was one mode: you called the big frontier model. GPT-5.5. Claude Fable. Gemini 3 Pro. You paid the tolls, you waited, and you got what you needed. It was like renting a plane for every trip. Expensive, but simple. There was nothing else on the road.

That is no longer true.

The walk tier is a model running on your phone or laptop — no network, no cost, no data leaving the device. Google’s Gemma 4 and Microsoft’s Phi-4 now handle classification, autocomplete, document summarization. You do not even notice you are using AI.

The bike tier is a small model running on your own hardware — a workstation, a private server. Fast, cheap, data stays on-prem. These models can handle tasks that required GPT-4-class APIs eighteen months ago.

The rideshare tier is cheap cloud inference. You are not driving, not owning, but you get there quickly and cheaply. What cost $22,500 a month in 2025 runs for $405 today. That is not a gradual erosion. That is a structural break.

The car tier is dedicated hosted compute — reserved capacity, predictable performance, always available.

Frontier models are the airplane. Dense reasoning, long-context synthesis, genuinely hard problems. You use them when you need to get somewhere fast and far. You do not use them to classify customer support tickets.

Here is the problem nobody had two years ago.

Picture the IT director at a mid-size insurance company. She deployed a frontier model API last year. Smart decision at the time — one vendor, one contract, everything works. Now she’s gotten the quarterly invoice and done the math. Roughly 80% of the queries hitting that API are things like: extract the date from this document, categorize this claim, summarize this email thread. Tasks a much cheaper model handles just as well. She has been flying everyone to a meeting across town.

She is not alone. Most organizations that built on frontier APIs in 2023 and 2024 are now discovering they over-provisioned for the average query and under-thought the distribution. The expensive mode works. That’s the trap. You don’t look for alternatives when the thing you’re doing works.

The routing layer is where this resolves. A routing layer is need that sits between the application and the model tier and asks, for each incoming query: what does this actually require? Simple queries go to the cheap tier. Hard queries escalate to frontier.

Route 90% of requests to the cheap tier, 10% to frontier. You cut costs by 86%. The quality loss on the 90% is negligible, because most production queries are not frontier-hard. Most trips, you walk.

Back to the $22.7 trillion.

The number is real in the sense that enterprise software currently costs a lot. The global market — CRM, ERP, HR systems, supply chain, all of it — runs roughly $700 billion annually. If AI agents eventually do much of the work those systems mediate, and if the value gets priced into the AI layer, you can arithmetic your way toward very large numbers.

But the routing story embeds an uncomfortable question: if inference costs are collapsing, and if smart organizations route most of their traffic to free or near-free edge compute, who actually captures the value?

The model providers need volume. But enterprise routing gives sophisticated buyers a systematic exit from frontier pricing for the bulk of their workload. You call the expensive plane only when you need to cross an ocean.

This is why the routing layer matters more than it looks. The company that becomes the transit authority — the entity that sits between all the modes and makes the dispatch decision — is structurally positioned to matter as much as any individual model provider. The transit authority does not own the planes or the trains. It knows where you are going and picks the right mode. That intelligence, at scale, is a moat.

SpaceX is not that company. IDC is right about that. But the $22.7 trillion figure, even as a promotional artifact of an S-1, is pointing at something real: the opportunity is large enough that the infrastructure for consuming AI efficiently may be as valuable as the AI itself.

The frontier model providers are the airlines. Necessary, impressive, expensive to operate, essential for the long haul. Emerging routing solutions are building the booking platforms — the systems that decide when you actually need a plane, and make sure you are not buying a first-class ticket to go ten blocks.

In transportation, the booking platforms eventually captured enormous value. Expedia, Booking.com, Google Flights. The airlines, which had all the brand and all the infrastructure, found themselves competing for placement in someone else’s interface.

That story may be ahead of us in AI. The models are the planes. Someone else may be Expedia.

Categories
AI Startups

A New Reason to Launch

“Before you launch, the speed you can build is now mainly limited by your imagination in what you tell AI. After you launch, the AI can watch your users and make improvements on its own.”
— Jared Friedman, Y Combinator

Jared Friedman watches hundreds of founders a year navigate the gap between idea and launched product. He notices patterns the rest of us miss. And what he’s describing above is not an incremental improvement in how software gets built. It is a change in the nature of the advantage.

This is a different kind of liberation than founders have known before.

The old liberation was launch early and the market corrects your wrong assumptions. Humbling, but useful. You were still the one doing the correcting, late at night, rewriting the onboarding flow based on what the data told you.

The new liberation he’s describing is something closer to multiplication. You launch, and now there are effectively more of you. The AI is watching session replays you’ll never have time to watch. It’s noticing the drop-off after step three that you’d have caught in month four. It’s holding the pattern of a thousand user paths simultaneously and asking what they mean. Your imagination seeded the thing. Reality is now feeding it.

That observation redraws the map cleanly. Pre-launch and post-launch used to differ in degree — you knew more after than before. Now they differ in kind. Pre-launch you are the sensing organ. Post-launch you’ve grown new ones.

The founders who feel this most viscerally, I suspect, are the ones building alone or in pairs — the people for whom every previous era of building had a hard ceiling imposed by human hours. They could only read so many support tickets. They could only run so many experiments. The ceiling is lifting and the feeling is of a room getting larger.

The core advice hasn’t changed. Paul Graham was saying “launch early” twenty years ago and it was true then. What’s changed is the reason underneath it — the mechanism that makes it true now is nothing like the one he had in mind.

The advice is twenty years old. There is a new reason and it is brand new. Most people haven’t noticed the swap yet. But they will.

That window does not stay open long.

Categories
Bread California San Francisco/California

Larraburu

There were three sourdough breads in San Francisco and they were not the same thing. Boudin was at Fisherman’s Wharf, which told you everything. Parisian was on the better grocery shelves and at the airport, which told you the rest. Larraburu was in the neighborhood, which is to say it was not selling anything except bread.

I was living in Daly City when I found them. I was seventeen, or eighteen, which is the age when you begin to understand that the thing everyone points to is rarely the thing worth finding. I had eaten Boudin at the wharf, standing in the fog with everyone else who had just arrived somewhere. It was fine. It was what people meant when they said sourdough. Parisian was more serious, or wanted to be — the bread you bought at the airport to prove you’d really been here, to carry the city home in a bag. But there was something in both of them that felt like a performance, and I was at the age when performance was exactly what I was trying to see through.

Larraburu didn’t perform. The crust was softer than it had any right to be. The sour was there but it didn’t insist on itself. You tasted wheat and time and something faintly cool and creamy underneath. It was bread that assumed you already knew what you were doing.

They closed in 1976. Parisian lasted until 2007. Boudin is still on the wharf.

I have thought about this more than is strictly reasonable. What I keep coming back to is not the taste exactly, though the taste is there when I reach for it. What I keep coming back to is the distinction itself — the fact that I made it, that it mattered to me, that I was nineteen years old in Berkeley and buying bread from a neighborhood bakery in San Francisco because I had decided it was the real thing. You make these small declarations about who you are. Most of them dissolve. Some of them stay.

The two brothers who started Larraburu came from the Basque country in 1896 and brought their starter with them. By the time I was eating their bread the starter was already older than the state of California. They fed it three times a day, every day, for eighty years. That kind of commitment doesn’t announce itself. It just shows up in the bread.

In 1969 scientists from the United States Department of Agriculture began studying sourdough cultures from five San Francisco bakeries. They were trying to understand what made the bread taste the way it did, why you could not replicate it elsewhere, why bakers who moved away and took their starters with them found the flavor slowly changing, the sourness shifting, something essential escaping. They worked for years before a team at Oregon State University finally isolated what they were looking for — a previously unknown bacterium living inside the wild yeast, producing the lactic acid that gave the bread its character. They named it Lactobacillus sanfranciscensis. One of the five bakeries in the study was Larraburu.

The starter the brothers brought from the Basque country in 1896 was not simply old. It was a living record of every bakery it had passed through, every hand that had fed it, every climate it had survived. A sourdough starter is not a recipe. It is a culture in the biological sense — a community of organisms with a history, shaped by everything that has ever happened to it. You can write down the formula. You cannot write down what the starter knows.

Larraburu baked twenty-four hours a day. The sponge was rebuilt every eight hours, three times daily, without interruption. Two parts previous sponge, two parts high-gluten flour, one part water. Hold seven to eight hours. Rebuild. The rhythm was closer to farming than to cooking — less a process than a relationship, sustained across decades, across generations, across an ocean.

What I know now that I didn’t know then is that the starter survived the bakery. Someone saved a piece of it when they closed. It traveled to Hawaii, sat in a refrigerator on Maui, kept being fed. A culture that old doesn’t care about bankruptcy or lawsuits or whether the ovens are still running. It just wants flour and water and time.

I find something in that. Not consolation exactly. More like confirmation of something I already believed at seventeen, standing in the fog, learning to tell the difference.

Categories
Writing

The Grain Bin and the Ghost

Richard Rhodes published How to Write in 1995. In it, he offers practical advice about a writer’s reference shelf: keep a dictionary at home, own a one-volume encyclopedia. He mentions, almost in passing, that he just received the OED on CD-ROM as a birthday gift.

That sentence stops you cold in 2026.

Not because it’s quaint — though it is — but because of what it reveals about how a writing life was organized. Rhodes wasn’t describing luxury. He was describing infrastructure. The reference shelf was load-bearing. You kept facts at home the way you kept food in a pantry: because access wasn’t guaranteed, because the library closed, because the gap between not-knowing and knowing could be measured in trips and hours. A writer’s bookshelf was a personal hedge against scarcity.

Think about what it meant that someone’s birthday present was a reference tool. Not a novel. Not a bottle of wine. Twenty volumes of the most authoritative dictionary in the English language, compressed to a disc, given because a writer needed it and couldn’t otherwise have it on their desk. That’s what a writing life cost. That’s what it demanded of the people around you.

That scarcity is gone so completely it’s hard to reconstruct the phenomenology of it.

The bottleneck in Rhodes’s world was access. You either had the fact or you didn’t. Getting it required physical movement — to the shelf, to the library, to someone who knew. The reference book’s value was proximity: it collapsed the distance between the question and the answer. The OED on CD-ROM was remarkable precisely because it put those twenty volumes on your desk. No trip. No waiting. That was the gift.

The bottleneck now is entirely different. Access is solved, trivially, for anyone with a phone. The question isn’t where the facts are. The question is which facts to trust, how they were assembled, whether the source has an agenda, whether the model that synthesized them has introduced drift. We moved from a scarcity problem to a judgment problem, and most of our inherited intellectual habits were built for the former.

But something else happened too, something Rhodes couldn’t have framed because it didn’t exist: the infrastructure became generative. The reference shelf held facts. It didn’t think with you. It didn’t draft alongside you, or push back on your argument, or notice that the claim you just made contradicts something three paragraphs earlier. The CD-ROM OED was static; it waited to be consulted. The tools a writer reaches for now don’t wait. They participate.

This is the structural shift that the grain bin metaphor can’t contain. Rhodes was describing a writer’s relationship to stored knowledge — how you accumulate it, how you keep it close, how you move through it when you need it. That relationship was essentially curatorial. You built a collection. You maintained it. You drew from it.

What’s emerging now is something more like a collaboration with an infrastructure that has opinions. Not always right ones. Not always trustworthy ones. But opinions nonetheless — which means the writer’s job has changed in kind, not just in degree. You’re no longer managing a pantry. You’re managing a working relationship.

Where does it end up? Probably somewhere Rhodes would recognize at the level of the goal — clarity, the right word, the true sentence — and find almost unrecognizable at the level of method. The shelf is still there. But it talks back now. And figuring out what that means — whether to trust it, when to push against it, how to stay the one doing the writing — is the work no one has finished yet. Maybe no one can, while it’s still changing this fast.

Categories
AI

The Layers Don’t Hold

Stewart Brand drew the diagram in 1999, in The Clock of the Long Now, though he’d been developing the idea for years before that. Six concentric rings, each representing a layer of civilization, each moving at a different speed. Fashion at the outside, changing season to season. Commerce beneath it, slower. Infrastructure below that — roads, power grids, buildings. Then governance. Then culture. At the center, moving so slowly it seems not to move at all: nature.

The diagram is elegant, but Brand’s real insight is about the relationship between layers, not the layers themselves. He called the framework pace layers. The fast layers innovate. The slow layers stabilize. Fashion gets to be experimental and throwaway precisely because infrastructure doesn’t. Governance can afford to be deliberate because culture provides continuity underneath it. The whole system depends on this differential. Each layer absorbs shock from the one above it and passes only the most durable changes downward. It’s not inefficiency — it’s architecture.

Brand also had a name for what happens when the differential breaks down. He called it “layers crashing.” When a fast layer accelerates past the capacity of the layer beneath it to absorb and adapt, the system loses its self-correcting character. The fast layer doesn’t just move quickly anymore — it damages the slow layer’s ability to function. Infrastructure overwhelmed by commerce becomes fragile. Governance overwhelmed by technology becomes irrelevant. The stability that the slow layers provide isn’t guaranteed. It has to be continuously earned.

We are in a layers-crashing moment. The technology layer is moving faster than it has in any of our lifetimes, possibly faster than it ever has. And the layers below it — infrastructure, governance, culture — are discovering that the shock-absorption mechanisms they’ve refined over centuries weren’t designed for this.

Dario Amodei published a long policy essay recently. He opens with Treebeard — the ancient, slow-speaking tree from Lord of the Rings whom the Hobbits must somehow persuade to act quickly enough to matter. It’s the same intuition as Brand’s pace layers, arrived at from a different direction. The problem isn’t that governance is broken. The problem is that it was built for a different tempo, and the tempo has changed.

What’s new in Amodei’s essay — and it feels genuinely new — is the shift in register. For several years, Anthropic’s public posture on regulation has been: transparency first, binding rules later, once we understand the shape of the risks well enough to target them precisely. That posture made sense when the risks were theoretical. It makes less sense now. The pivot in the essay is Amodei’s own most advanced model, Claude Mythos Preview, which he describes as having “scrambled the global cybersecurity landscape.” He is using his own product as the evidence that the moment for incrementalism has passed.

The five policy areas he covers — regulation, macroeconomics, scientific innovation, civil liberties, geopolitics — each map onto a different pace-layer collision. The cybersecurity risk to financial infrastructure is commerce meeting governance too fast. The job displacement problem is commerce and culture in conflict, with governance lagging both. The civil liberties section is perhaps the most unsettling: the worry that AI hands governments tools of surveillance and coercion that the legal architecture of democracy — built for a slower world — simply cannot constrain.

The regulatory framework he proposes is modeled on the FAA: mandatory third-party testing of frontier models, government power to block deployment, four specific risk categories as scope limiters. It is more concrete than anything Anthropic has proposed publicly before. The FAA analogy is meant to reassure — we have regulated powerful technologies before, we know roughly how this works — and it largely does reassure. Though it’s worth holding alongside it a genuine open question: whether regulatory bodies can develop the expertise and independence to govern a technology this fast-moving before the technology moves again. The history of industry regulation suggests this is hard. It doesn’t suggest it’s impossible.

Brand’s diagram has one more feature worth noting. The arrows don’t only point downward, from fast layers shaping slow ones. They also point upward: the slow layers constrain what the fast layers can become. Culture shapes what commerce builds. Governance shapes what infrastructure gets funded. Nature sets limits that no other layer can override. The relationship is bidirectional, and the bidirectionality is the point. What Amodei is calling for — urgently — is for the slow layers to begin exerting upward pressure again, before the differential becomes so extreme that they lose the capacity to do so.

Whether they can move quickly enough is the question Brand’s diagram can’t answer. Treebeard wakes up, eventually. The forest burns faster than he walks.

Categories
AI

Hands He Can’t Feel

Note: a fictional story exploring how software development is changing in the world of Claude Code, Antigravity, etc.

The cursor blinks for maybe two seconds. Then the code appears, all of it, a function Pete Callahan had been turning over in his head for the better part of a morning, just there, complete and correct and formatted the way he would have formatted it himself. He reads it the way you read something you’re looking for an error in. There isn’t one. He leans back in his chair in a way that isn’t quite satisfaction and isn’t quite anything else he has a word for.

Bewildered, maybe.

Outside his window, Dayton is doing what Dayton does in February, which is endure. The city has always been good at that. The Wright Brothers built their first serious wind tunnel a few miles from here in a room above a bicycle shop, testing wing shapes that didn’t exist yet, failing in ways that taught them something. Pete grew up knowing that story the way you know the streets of the neighborhood you grew up in — not as history exactly, more as weather. Just a thing that was true about where you were from.

His father would have understood the wind tunnel. You build the thing to test the thing. You put in the hours. That’s how knowledge works.

Pete is no longer sure that’s how knowledge works.

His father, Ron Callahan, spent thirty-one years at Wright-Patterson keeping F-16s in the air. Not designing them, not flying them. Maintaining them. There is a difference and Ron has always understood it as a moral one. The pilot trusts you with his life in a way that is not metaphorical. You either know what you’re doing or you don’t. There is no almost.

He lives twenty minutes from Pete in a house that smells like coffee and WD-40, a combination Pete has never encountered anywhere else and that means, without his being able to say exactly why, that everything is okay. Ron is seventy-one now, still straight, still with the unhurried precision in his hands that Pete watched as a boy and tried to understand as a kind of language. On Sundays Pete drives over. They watch whatever game is on. Ron sets a mug in front of him without asking.

This particular Sunday Ron asks how work is going the way he always asks, with genuine interest and the slight remove of a man who has never quite been able to picture what his son actually does all day.

It’s great Dad. But it’s changing faster than ever before.

Ron nods. He has seen the F-4 give way to the F-16 give way to systems so sophisticated the maintenance manuals run to thousands of pages. He knows about change. You learn the new thing, he has always believed, or the new thing leaves you behind. Simple as that.

He hears his son’s sentence as a version of something he has said himself.

He’s not wrong, exactly. He’s just not quite right either.

Driving home Pete thinks about the kids he came up with, the ones from places like Dayton who found in code what the world didn’t always offer elsewhere — a domain where being right was demonstrable, where quality was real, where the machine didn’t care about your intentions. It had shaped him the way Dayton shaped him. Not as ideology. Just as weather.

He still believes that, mostly.

It’s just that the machine has changed its mind about what knowing means.

What Pete cannot explain, what he doesn’t have the language for yet, is that the change he is living through is not like learning a new aircraft. When the F-16 replaced the F-4, the mechanic’s relationship to the machine stayed intact. Hands on metal. Knowledge earned through repetition, through failure, through the slow accumulation of understanding what the thing wanted to do and what it didn’t. The new plane was more complex but the posture was the same. Man serving machine serving pilot. The chain held.

What is happening to Pete is something else. Something that doesn’t have a clean analogy in Ron’s world, or in the history of Dayton, or in the mythology of the American craftsman that Pete absorbed so completely he doesn’t even know he’s carrying it.

He is still building things. He is building better things, faster, than he ever has. But somewhere in the last eighteen months the relationship changed in a way he is still trying to locate. He used to be the one who knew. Now he is the one who directs something that knows, which sounds like a promotion and feels like something more complicated than that.

His father’s hands always knew what to do.

Pete is learning, at thirty-eight, to work with hands he can’t feel.

By ten o’clock the house has the particular quiet of a place that is usually fuller than this. Sarah’s coffee cup from this morning still on the counter. Her shoes by the door. The small evidence of a life that will resume at midnight when he hears her key in the lock, and until then it’s just Pete and the screen and whatever this is that he’s trying to figure out.

What he does, alone in the house on these nights, is push. He takes the thing further than the task requires. Asks harder questions. Builds something more complex than anyone asked for just to see where the edges are, just to understand what he’s actually working with. It is the same impulse that kept his father an extra hour on a Friday, checking something that had already been checked, because almost certain was not the same thing as certain and a pilot was going to trust this machine with his life.

The ethic transferred even when the medium changed.

Even now, when the medium is changing again.

He thinks about his father’s hands sometimes, late like this. The way they moved with that unhurried precision, never rushed, never uncertain, each motion the product of so much repetition it had passed through knowledge into something that lived below knowledge. Pete watched those hands as a boy the way you watch something you are trying to learn without knowing you are learning it.

He used to think he had built something like that himself. The ability to hold a system in his head, to feel where it wanted to go, to know. The hands that knew what to do.

What he is building now he cannot quite name yet. It is not that the knowledge is gone — if anything it matters more, sits heavier, earns its keep in ways it didn’t before. But the relationship is different in a way he is still trying to locate, still turning over on these quiet nights while Dayton endures outside the window and Sarah’s shoes wait by the door and the cursor blinks with the particular patience of something that does not need him to be ready.

He types. The code appears.

He reads it the way his father checked what had already been checked.

Not because he doesn’t trust it.

Because that’s what you do when it matters.

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
Writing

Still Learning

I never thought about rhythm in my writing. Not once.

A lifetime of writing. More essays than I can count. One book. And the sonic quality of my sentences — the way they moved, or failed to move, through a reader’s mind — simply wasn’t something I considered. I was too busy trying to say something true. I thought that was enough.

What changed was reading differently. Not for pleasure anymore, or not only for pleasure. David Perell conducts long interviews with writers about how they actually work — not what they believe about writing, but what they do, physically, at the desk, in the dark, before anyone sees it. He asks the same structural questions of very different writers and the patterns emerge slowly, the way patterns always emerge: first you see it once and think nothing of it, then you see it again, then you can’t stop seeing it. Rhythm came up constantly. Always in different language. Pacing. Breath. Music. Momentum. Always pointing at the same thing.

Then I found this from Susan Orlean:

My new preoccupation was on the sonic quality of my writing — the rhythm and tone of the sentences. I began reading all my work out loud, listening for places that lagged and dragged, that didn’t sparkle. I knew it was unlikely that anyone else was reading my stories out loud, but I was convinced that you do “hear” writing in your head as you read, and this pushes you (or stalls you) through the piece. I wanted the music — that is, this subconscious tonal effect — to match the subject.

I stopped. Read it again.

Because she was describing something real — something I had been doing wrong for twenty-five years without knowing it was wrong. You don’t know what you can’t hear. That’s the whole problem. The silence where the knowledge should be is itself silent.

I don’t read my work out loud. There’s something strange about it, something that breaks the spell — you stop being a writer and become an actor, hearing your own sentences hanging in the air, too exposed. But I do read and read again, more carefully now, looking for the wobble. Orlean’s point holds regardless of method: you hear writing in your head as you read it, and that hearing either carries you forward or it doesn’t. The ear that matters is the one inside.

George Saunders has a practice he describes in A Swim in a Pond in the Rain: he reads from the beginning of a piece over and over, and the moment something feels off — a word, a rhythm, a single syllable landing wrong — he stops and fixes it before moving forward. Never skips the trouble spot. Never tells himself he’ll come back. His opening pages accumulate dozens of passes before he ever reaches the end. What he’s really doing, underneath the technique, is training himself to feel the exact microsecond when a reader’s attention would start to drift. To catch the loss before it happens.

That’s not craft instruction. That’s building a new sensitivity where there wasn’t one before.

John McPhee works from the other direction entirely. His famous boxes — index cards, sorted into piles, piles arranged into sequences, nothing drafted until the structure is known — are about architecture before a single word is written. He’s deciding which rooms exist, and in what order, before he furnishes any of them. Where Saunders builds outward from one true sentence, McPhee builds downward from a blueprint.

But they’re asking the same question. McPhee: is this section in the right place? Saunders: is this word in the right place? Both listening for the moment the piece loses its hold on the reader. Both doing triage on something most writers never even examine.

What I’m still learning — slowly, and late — is that rhythm isn’t decoration. It isn’t the thing you tend to after the real work is done. It’s structural. A sentence moving at the wrong speed for what it’s carrying fails the thought itself, not just the ear.

There’s something else I’ve been thinking about. If rhythm is the thing that’s hardest to hear in your own work — if the ear takes years to develop — then maybe the most useful writing tool isn’t a grammar checker. Those are solved. What isn’t solved is the rhythm problem. An editor who listens for the wobble, explains what’s failing and why, and works through the fix with you rather than just patching it. Not a red pen. A teacher.

I’ve been experimenting with exactly that. An AI editor I call Clark. His job isn’t correctness. It’s the sonic quality of prose — the rhythm — the same thing Orlean was describing, the same sensitivity Saunders spent years training. Clark finds what’s working as hard as what isn’t. And when something fails, he explains what the reader’s inner ear is hitting and why. Helpful.

I didn’t know much about rhythm in writing when I was fifty. Didn’t know it at sixty.

I’m not entirely sure I know it now. But I know it more than I did, which might be the only kind of knowing that’s real.

A lifetime of writing. Still learning how to listen.

Categories
Creativity Photographers Photography Serendipity Writing

He Taught Us How to See

Michelangelo said he didn’t create his sculptures. He just removed the marble that wasn’t the statue.

I’ve been thinking about that lately. About what it means to have a collaborator whose job isn’t to add things but to help you find what’s already there. I’ve been doing that kind of work recently — the excavation kind — and it has changed how I write and honestly how much I enjoy the making of it.

But I’m getting ahead of myself. Start with Jay.

Continue reading “He Taught Us How to See”