Tag: craft

Categories
Memories Music

The Engineering of Feeling

You’re always captive when it happens. A stoplight in the rain. A straightaway with nothing to look at but the white lines. Eight lanes of brake lights and nowhere to be but exactly where you are. The riff starts, and you’re not driving anymore so much as being driven — pinned by something that arrived four decades before you got in the car.

It happened once near Havana. You were there with a camera, working the old cars — fat-fendered Chevys and Buicks, kept running past the embargo by Cuban mechanics who became, out of necessity, a nation of engineers, scavenging parts and refusing to let something good die just because the factory that made it no longer existed. You didn’t think about Tom Scholz once, photographing a ’57 Bel Air held together by stubbornness. But the two belong in the same sentence. A man in a basement in Watertown, Massachusetts, kept a song alive the same way — building the tools himself when the tools that existed weren’t good enough.

Scholz had a master’s from MIT and a day job at Polaroid, designing the instant camera that would eventually lose to the VCR. He was an engineer — the kind who solves problems by taking them apart. What he did nights and weekends for five years instead was build a recording studio in his basement and use it to construct a song about a girl he’d loved in school, inspired by an old Left Banke single that used to ambush him with longing every time it came on. He played almost every instrument himself, layering twelve-string acoustic over electric over more electric, take after take, through amplifiers he’d built because the ones on the market couldn’t get the sound in his head. By the time Epic signed the band, the label assumed the demo was already a finished master. It was — just not one made anywhere near a studio.

An engineer built the least mechanical-sounding record of 1976. Every track is stacked with the precision of someone who understood signal paths better than he understood how to be a rock star. None of it sounds calculated when it hits you. The quiet drifts a few bars, then the chorus arrives like a held breath let go — the same structural trick Kurt Cobain would later borrow, half-consciously, for “Smells Like Teen Spirit.” Scholz built the explosion out of engineering. What you feel is the girl, the ache, the years.

The song is about the way music smuggles you back into a memory without asking permission. Scholz built that experience the way memory actually works — not in one clean take, but in fragments, layered over years, until the whole thing cohered into something that felt, impossibly, spontaneous. The method is the meaning. He didn’t just write a song about the past ambushing you. He built the ambush, piece by piece, until it was good enough to catch strangers in cars forty years later who never loved the same girl and never will.

Another song does this to you too, and it got there by the opposite road. “Listen to the Music” arrived almost the way lightning does. Tom Johnston wrote it in his bedroom on 12th Street in San Jose, brought it to his producer half-finished, and the band recorded it without changing a thing — no five years, no basement, no solitary engineer stacking takes until three in the morning. Its density comes from somewhere else: Patrick Simmons’ loose fingerpicking threading against Johnston’s percussive strumming, two drummers locking into a groove that shouldn’t work this easily, and one bold studio choice — a phasing effect, that underwater jet-swirl, laid over the vocals as well as the guitars, which almost nobody does. It sounds less like a song someone assembled than a room full of people who fell into the same current at once, then got bent sideways by one effect and printed.

Two songs, same seat, same stretch of road, opposite methods — one built alone across five years by a man who wouldn’t let go of a track until it was right, the other built in days by musicians whose parts happened to interlock, finished by a single flourish nobody else was doing quite that way. There’s more than one route to the kind of complexity that outlasts you. Refuse to stop. Or know exactly when to.

Categories
AI Business

The Wage of Knowing

In 1973 the Los Angeles Public Library installed a telephone line that worked while the building was dark. Dial H-O-O-T-O-W-L on a rotary phone, nine at night until one in the morning, and a librarian would answer. Somebody wanted to know the boiling point of mercury, or who wrote a poem they half remembered, or how many wives Henry VIII actually had, and a person on the other end of a cord found out. This went on for years. Nobody thought of it as data collection. It was just a service, a courtesy, a woman at a desk with a card catalog in her head.

I worked, in another life, in the payments industry, back when a merchant who wanted to charge your card had to call in and ask permission. There were rooms for this. Banks of phones, a bulletin of stolen numbers updated by hand, a floor limit past which a supervisor had to be found. The people answering the phones were, more often than you would guess, college students. Twenty years old, minimum wage, deciding in real time whether a stranger’s card was good. Nobody trained them for six months first. They learned the bulletin, they learned to listen for something wrong in a voice, and they said yes or no.

I have been driven, recently, by a car with nobody driving it. I noticed the wheel turning on its own and I braced for the wrongness of it. Thirty seconds later I was not bracing. I was looking out the window. The data says I was right to relax: across two hundred and twenty million miles, the cars involved in this experiment cause a small fraction of the serious crashes a human would have caused over the same roads. I did not need the data. I needed thirty seconds.

None of these people knew what they were doing. That is the thing about the librarian and the college student and, for that matter, about me learning to trust a wheel that moves by itself. The librarian was not building a search engine. The clerk was not training a fraud model. He was making rent. Their competence was not evidence, to them. It was just Tuesday. It became evidence later, to someone else, in a room they never saw — the accident logs, the chargeback data, the accumulated record of a million correct guesses that turned out to be exactly the material a system needed to learn the job and take it.

This is the part that is easy to get wrong. It is not that the human failed and the machine succeeded. It is that the human succeeding, over and over, in full view, was the demonstration that the job could be learned. You do not automate a task nobody can do. You automate the one being done well enough, often enough, for long enough that the pattern becomes visible. Doing the job right was never neutral. It was the case being built.

Which brings me to a woman I will call the lawyer, because there are thousands of her and none of them are exactly her. She has a laptop open at her kitchen table. She logs into a dashboard belonging to a company that pairs credentialed people with the AI labs that need them — a doctor here, a banker there, a corporate attorney with fifteen years of contract law behind her. She reads a model’s draft of a merger agreement and marks where it reasons like a first-year associate instead of a partner. She rewrites a clause. She explains, in the margin, why the model’s version would get laughed out of a negotiation. She is paid well for this. More, some weeks, than she billed certain clients.

She knows exactly what she is doing. That is the difference between her and the other three. The librarian did not know she was leaving a trail. The clerk did not know his good judgment would become someone else’s weights. I did not know, thirty seconds into that ride, that I was participating in anything at all. The lawyer knows. She is being paid, by the hour, at a rate that respects her expertise, to make her expertise legible enough that it no longer requires her. The company she works for has a name for this. They call it the reinforcement learning economy, which is a tidy way of saying: teach it everything, and then it will not need to call you back.

She does the work anyway. The rate is good. The work is interesting, in the way that teaching is interesting — you learn what you know by trying to say it clearly enough for someone else to use. Nobody is lying to her. The dashboard does not pretend to be anything other than what it is. She logs off at the end of the session the way anyone logs off after a long day of being excellent at something, tired in the specific way that comes from careful work, and she does not, from what I understand, spend the evening thinking about what she has just fed into the machine.

I keep coming back to the rotary dial. Somebody dialing H-O-O-T-O-W-L at midnight in 1973 could not have imagined the lawyer at her kitchen table. But the shape is the same, if you look at it long enough. A person answers a question well. The answering becomes a record. The record becomes a system. The system answers next time. Nobody in the room ever decided this was the plan. It just turned out, every time, to be the plan.

Categories
AI Apple Bicycles History

The Best Lathe in the Shop

Part 3 of 3…

There is a version of this story where Apple is the Wright Brothers.

It is not an unreasonable version. Apple has done the safety bicycle move more times than almost any company in history — taken a technology the engineers built for engineers and brought it down to earth, made it a machine for everyone. The Mac. The iPod. The iPhone. Each one was a wheel coming down. Each one arrived after a period of apparent slowness, of critics saying Apple had lost its edge, of the industry having already moved on to the next thing. Each one was, in retrospect, obvious. Apple had been in the bicycle shop the whole time. You just couldn’t see what they were building.

So when Apple showed its hand at WWDC this week — a rebuilt Siri operating at the OS level, accessing your messages and mail and photos in real time, understanding context across apps, doing things the old Siri could only approximate — it is tempting to read it as Kitty Hawk. The long preparation made visible. The brothers finally leaving the shop.

It might be. It also might not be. That is the only honest thing to say.

What Apple showed was real. The new Siri, built on Apple’s own Foundation Models with help from Google’s Gemini, is not the Siri that became a punchline. It holds context. It moves across apps without being asked. It knows what you were doing five minutes ago and connects it to what you are doing now. It can surface a photo without opening Photos, build a navigation route from an image, draft a message in the tone of the conversation it is joining. These are not features. They are the beginning of an operating system that understands you, which is a different thing from an operating system that executes your commands.

The structure of the keynote said more than the words did. Apple led with fixes before features. iOS 27 is a Snow Leopard update — performance, reliability, the underlying machinery — and Siri AI was presented as one item on a long list rather than the main event. This is Apple’s tell. When they are doing something foundational they tend to understate it, the way a craftsman doesn’t announce the quality of his work but simply does it and lets you find it. The penny-farthing riders called their machine the ordinary. They didn’t think they needed to explain.

But here is the thing about the bicycle shop analogy that the optimistic version leaves out. The Wright Brothers knew what they were trying to build. They had been thinking about flight for years before Kitty Hawk. The bicycle shop gave them the craft knowledge, the physical intuition, the hands-on education in how machines move through space. What it did not give them was the destination. They brought the destination themselves.

The question Apple has not answered for me — the question this week’s keynote raised rather than resolved — is whether they know where they are going. Or whether this has only been a partial reveal and there’s much more behind the curtain?

The OS-level integration is the chain drive. Decoupling AI from the app, letting it run through the substrate the way a chain runs through a drivetrain, is exactly the kind of architectural insight that changes what a machine can do. It is not a feature you add. It is a rethinking of what the machine is for. Every previous AI assistant lived above the operating system, looking down at your data from a remove. Apple’s new architecture lives inside it, which is a different relationship entirely — the difference between a mechanic who reads about your car and one who has driven it for a year.

That is the Coventry precision. The tight tolerances. The discipline of making things that have to work at the level where failure is not an option.

What nobody knows, including Apple, is what you build with it.

There is also this: Tim Cook will not be driving this evolution. He announced that John Ternus takes over in September, which means this WWDC — this particular showing of the hand — is the last one Cook owns. Ternus is a hardware engineer, the man who built the Apple Silicon transition, the person most responsible for the Neural Engine that makes on-device inference possible. He is, in the bicycle shop metaphor, the craftsman who built the lathe. Whether he knows how to use it to make something that flies is the question the next several years will answer.

History is patient about these things. It lets the work speak.

In 1892, two brothers opened a shop on West Third Street in Dayton and started fixing bicycles. They were not trying to change the world. They were trying to make a living, to learn a machine, to understand in their hands what the books couldn’t teach them. The flying came later, and it came because of the shop, not despite it. The shop was the point. They just didn’t know it yet.

Apple has the best lathe in the bicycle shop. They have the chain drive architecture, the on-device precision, the installed base of two billion devices that will carry whatever they build into more hands than any other platform on earth. They have a new set of hands on the wheel starting in September, hands that know the metal intimately, that built the engine the whole thing runs on.

What they do not have yet — or if they have it, they are not showing it — is the image of what they are flying toward.

Maybe that’s the ordinary part. Maybe that’s always been the ordinary part. You don’t know what you’re building until you’ve built it, and by then the world has already changed, and everyone says it was obvious, and they are right, and they are also completely wrong about when the decision was made.

The shop is open. The lathe is running. Work is underway.

What happens when someone finally knows what to make?

Categories
AI Bicycles History

The Bicycle Shop

Part 2 of 3…

It is eleven-thirty on a Tuesday night and she is arguing with a language model about a spreadsheet.

Not arguing, exactly. That’s not the right word. She is coaxing. She is debugging. She is reading error messages that tell her almost nothing and rewriting prompts that almost work, and she has been doing this for two hours, and the spreadsheet still isn’t right, and she is going to try one more thing before she gives up and does it by hand. She is a data analyst at a mid-sized logistics company in Columbus, Ohio. She is not a researcher. She is not a founder. Nobody is writing about her. She is just a person trying to get a machine to do something useful, and the machine keeps almost doing it, and she keeps learning, in the gap between almost and done, something she couldn’t have learned any other way.

She doesn’t know what she’s learning. That’s the important part.

In 1892, two brothers opened a bicycle repair shop on West Third Street in Dayton, Ohio. The bicycle craze was at its peak — the safety bicycle, with its two equal wheels and chain drive, had just replaced the penny-farthing, that absurd high-wheeler everybody called loose change and the riders, with complete seriousness, called the ordinary. The brothers fixed flats and adjusted brakes and built custom frames and ordered parts from Coventry and kept the books and swept the floor. It was ordinary work. Nobody was writing about them either. What they were doing was accumulating, without knowing they were accumulating, a physical understanding of how machines move through space — the gyroscopic principles, the weight distribution, the thousand small calibrations that kept a rider from falling. They were learning in their hands what no university taught and no book fully contained.

Eleven years later they flew.

We tell the Wright Brothers story as a story about flight. It makes sense — flight is the thing, the miracle, the moment the world changed. But the actual story, the one that explains how Kitty Hawk was possible, is a story about a bicycle shop. It is a story about unglamorous preparatory work, about the education that hides inside the constraint, about what you learn in the gap between the machine that exists and the machine that should exist. Orville and Wilbur didn’t go to Kitty Hawk despite the bicycle shop. They went because of it. The shop was the point. They just didn’t know it yet.

We are in the bicycle shop right now.

The people building with AI today — the prompt engineers, the fine-tuners, the agent builders, the data analysts in Columbus arguing with spreadsheets at midnight — are doing work that looks, from the outside, like mere tinkering. Unglamorous. Iterative. Full of failure. The tools are awkward. The models hallucinate. The context windows run out at the wrong moment. Every solution opens three new problems. It feels like the penny-farthing: powerful enough to be useful, constrained enough to be maddening, requiring a kind of practiced vault just to get started.

But that awkwardness is the education.

Every time a prompt fails, the person writing it learns something about how the model thinks — about what it responds to, what it resists, where it gets confused, where it surprises you. Every agent that breaks in production teaches its builder something about the gap between what a model can do in a demo and what it can do under load, with real data, with users who don’t behave the way you expected. Every context window that runs out forces a decision about what actually matters, what is essential, what can be cut. These are not just technical lessons. They are epistemic ones. They are lessons about the nature of intelligence, about how meaning gets encoded and retrieved, about what it means for a machine to understand something versus to pattern-match on the surface of understanding.

The people learning these lessons right now don’t have a name for what they know. They just know it in their hands.

This is how it always works. James Starley’s craftsmen in Coventry bent and brazed bicycle frames by feel and experience, knowing things in their hands they couldn’t fully explain on paper. That embodied knowledge — the tight tolerances, the interchangeable parts, the discipline of making things that had to work — migrated into every bicycle shop that followed, crossed the Atlantic, and ended up in a shed in Ohio. The Wright Brothers didn’t invent precision manufacturing. They inherited it, absorbed it, and applied it to a problem nobody else had solved because nobody else had brought those particular hands to that particular problem.

The chain drive was the hinge. Before it, the bicycle’s design was locked — bigger wheel for more speed, higher and higher off the ground, until the machine teetered at the edge of what a human could survive. The chain drive broke the constraint. It decoupled the pedals from the wheel, let the gearing do what only size had done before, brought the rider back to earth. What had been a machine for athletes became a machine for everyone. What had been the ordinary became, almost overnight, something new.

We are waiting for the chain drive.

Not waiting passively — it is being built right now, in a hundred places at once, by people who mostly don’t know they’re building it. It might be the interface that finally makes AI genuinely accessible to people who can’t do the running vault. It might be the memory architecture that lets a model carry context the way a human carries context, not in a window but in something more like experience. It might be something nobody has named yet, something that will seem obvious afterward, the way all elegant solutions seem obvious after the fact.

What it will not be is the product of people who stayed away from the bicycle shop.

The analyst in Columbus closes her laptop at midnight. The spreadsheet is still not right. She has learned three things about how the model handles date formatting, two things about how it interprets ambiguous column headers, and one thing about her own assumptions that she didn’t know she was making. Tomorrow she will try again. She will get closer. At some point — not tomorrow, maybe not this year — she will get it right, and the thing she learned in the gap will be available to her for the next problem, and the one after that, and she will carry it forward without knowing she’s carrying it, the way craft always travels, in hands that have done the work.

She doesn’t know what she’s riding toward.

That’s the ordinary part. That’s always been the ordinary part.

Categories
Aircraft Bicycles Dayton Ohio History

The Ordinary

Part 1 of 3…

The man sitting atop a penny-farthing in the summer of 1879 is five feet off the ground. He weighs maybe one hundred and fifty pounds. The wheel beneath him is fifty-four inches across — taller than most of the children who stop to watch him pass. He got up there by running alongside the machine, hooking a foot on a small peg above the rear wheel, and vaulting himself upward in a single practiced motion. He will dismount the same way: a controlled fall forward, a hop, gravity made manageable by repetition. He has done this so many times that he no longer thinks about it. He thinks about the road ahead.

He is not a daredevil. He is a commuter.

The people on the sidewalk call his machine a penny-farthing, which is a joke dressed up as a name. A penny was the largest British coin; a farthing the smallest, worth one quarter of a penny. Seen from the street, the big front wheel and its tiny rear companion looked exactly like the two coins set side by side. Some wit had noticed, and the name stuck. The riders themselves refused it. They called their machine the ordinary — because to them, it was exactly that, the standard form, the rational machine, the obvious answer. They said ordinary with complete seriousness while everyone else was calling it loose change.

This tells you something about the people who rode it. And about the machine they thought they were riding.

The penny-farthing was not a circus prop. It was the highest expression of an engineering logic that had no other options. The pedals connected directly to the front axle. One rotation of the legs meant one rotation of the wheel. If you wanted to go faster, you needed a bigger wheel. It was that simple. It was that brutal. The geometry of human ambition ran directly through the circumference of that front wheel, and the front wheel kept getting bigger, and the riders kept climbing higher, until the whole enterprise teetered at the edge of what a human being could reasonably mount and survive.

The high-wheeler was not a mistake. It was the answer to a question no one yet knew how to ask differently.

The machines were built in Coventry, England, by craftsmen who bent and brazed steel frames by hand, fitted wire spokes under tension — a Starley innovation that made the wheel lighter than anyone expected — and pressed solid rubber tires onto rims by feel and experience. James Starley had essentially invented the industry in 1871, and Coventry became its Detroit: a concentration of metalworking skill that fed on itself, that knew things in its hands it couldn’t fully explain on paper.

Then, in the mid-1880s, someone put a chain on it.

The chain-and-sprocket drive seems obvious now, the way all elegant solutions seem obvious after the fact. Decouple the pedals from the wheel. Run a chain from a sprocket near the rider’s feet to a smaller sprocket at the rear axle. Suddenly the wheel didn’t have to be enormous — the gearing could do what only size had done before. The front wheel came down. The rear wheel came up to match it. The rider dropped five feet closer to the earth. The machine that emerged from this rearrangement was called, without any particular irony, the safety bicycle. It was safe. It was fast. It was something a woman in a skirt could ride, something a child could learn on, something that didn’t require a running vault to mount.

The ordinary had been a machine for athletes. The safety bicycle was a machine for everyone.

By the 1890s it had become something close to a religious phenomenon. Factories couldn’t keep up with demand. Doctors wrote approvingly of its effects on the nervous system, the cardiovascular system, the general disposition of the modern soul. Roads were improved because cyclists demanded it. The bicycle arrived before the automobile and prepared the world for it — softened the ground, culturally speaking, for the idea that ordinary people might move through space under their own mechanical power, faster than their feet could carry them, farther than their legs could take them. It was the first technology to feel like freedom to people who had never felt that way before.

In Dayton, Ohio, two brothers watched all of this happen and decided to get into the business.

Orville and Wilbur Wright were not, in the beginning, aviation pioneers. They were bicycle mechanics. They opened their shop in 1892, right at the peak of the craze, and what they learned there — the feel of a machine in motion, the gyroscopic principles of balance and control, the importance of getting the weight right, the importance of understanding what a human body can and cannot do at speed — was an education no university offered and no book could fully provide. They learned it with their hands. They learned it in the gap between the machine that existed and the machine that should exist.

The Wrights were not the only ones in Dayton thinking about bicycles. The Huffman Manufacturing Company had opened its doors the same year as the Wright Cycle Company — 1892, the peak of the craze, the same fever in the same city. Huffman would eventually become Huffy, and Huffy would eventually become the bicycle every American child found under the Christmas tree. Dayton was doing something in those years. It was a city that couldn’t stop thinking about how people move. The precision those Coventry craftsmen had developed — interchangeable parts, tight tolerances, the discipline of making things that had to work — migrated into every bicycle shop that followed, including a small one on West Third Street.

The chain drive had taught the world that the right mechanical insight could make an impossible thing ordinary. You didn’t have to accept the constraints you were handed. You could re-ask the question.

Orville and Wilbur had been paying attention.

When they went to Kitty Hawk in 1903, they brought with them a bicycle chain. It connected the engine to the propellers. The same principle — a sprocket, a chain, a transferred force — that had brought the penny-farthing rider down from his absurd perch now lifted two men off the ground for the first time in human history.

The man on the high-wheeler in 1879 did not know he was riding toward the Wright Brothers. He was just going to work. But the machine beneath him, the one everybody called loose change and he called ordinary, was already asking the question that would take twenty years to answer.

What happens when you finally get the wheel the right size?

The roller chain — the specific form that connected pedal to wheel and made the safety bicycle possible — was invented in Manchester in 1879 by a Swiss engineer named Hans Renold. He was refining a design that Leonardo da Vinci had sketched in a notebook around 1500. Leonardo could imagine it. He couldn’t make it. The world needed four hundred years of improving machine tools before anyone could hold the tolerances tight enough to build what Leonardo had already seen. The idea arrived centuries before the craft caught up. It is always this way.

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

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
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”