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AI Bicycles History

The Bicycle Shop

Part 2 of 3โ€ฆ

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

Not arguing, exactly. Thatโ€™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 isnโ€™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 couldnโ€™t have learned any other way.

She doesnโ€™t know what sheโ€™s learning. Thatโ€™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 โ€” 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 โ€” 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 โ€” 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 didnโ€™t go to Kitty Hawk despite the bicycle shop. They went because of it. The shop was the point. They just didnโ€™t know it yet.

We are in the bicycle shop right now.

The people building with AI today โ€” the prompt engineers, the fine-tuners, the agent builders, the data analysts in Columbus arguing with spreadsheets at midnight โ€” 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 โ€” 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 donโ€™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 donโ€™t have a name for what they know. They just know it in their hands.

This is how it always works. James Starleyโ€™s craftsmen in Coventry bent and brazed bicycle frames by feel and experience, knowing things in their hands they couldnโ€™t fully explain on paper. That embodied knowledge โ€” the tight tolerances, the interchangeable parts, the discipline of making things that had to work โ€” migrated into every bicycle shop that followed, crossed the Atlantic, and ended up in a shed in Ohio. The Wright Brothers didnโ€™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 bicycleโ€™s design was locked โ€” 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 โ€” it is being built right now, in a hundred places at once, by people who mostly donโ€™t know theyโ€™re building it. It might be the interface that finally makes AI genuinely accessible to people who canโ€™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 didnโ€™t know she was making. Tomorrow she will try again. She will get closer. At some point โ€” not tomorrow, maybe not this year โ€” 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 sheโ€™s carrying it, the way craft always travels, in hands that have done the work.

She doesnโ€™t know what sheโ€™s riding toward.

Thatโ€™s the ordinary part. Thatโ€™s always been the ordinary part.

Categories
AI Business IBM Management

Making It Up As We Went Along

There was a building along Route 270 in Gaithersburg, Maryland where people kept secrets for a living. Not the cloak and dagger kind. The corporate kind, which in its own way requires just as much discipline. The IBM Washington Systems Center occupied a two-story modern building that looked, from the outside, like any other outpost of late twentieth century American business. Inside it was something else. It was where IBM sent its hardest problems, and where the largest IBM customers in the world โ€” the ones whose names you would recognize immediately โ€” sent their most urgent ones back.

I worked there as a manager. But before I was a manager there, I was a hire. And before I was a hire, I was like every other IBM professional on the outside of a particular line โ€” a line I didnโ€™t fully understand until I crossed it.


At IBM there was a protocol so embedded in the culture it had almost ceased to be a rule and become something closer to a religious observance. New products were not discussed until they were announced. Not hinted at. Not alluded to. Not whispered about with a favored customer over lunch. The announcement came in the form of something called a Blue Letter โ€” a formal communication from senior leadership that functioned as the official moment a product entered the world. Before the Blue Letter, the product did not exist in any conversation you were permitted to have. After it, you could talk about nothing else.

Violation was not a career setback. It was a firing offense. Full stop.

That clarity had a kind of elegance to it. You didnโ€™t have to calibrate how much you could say or navigate gray areas. The line was absolute. And because it was absolute, and because everyone knew the consequence of crossing it, the culture enforced itself. You didnโ€™t need surveillance. You needed people to understand the stakes, and they did.


What I didnโ€™t understand, from the outside, was what that line was doing to my imagination.

When you canโ€™t see the roadmap โ€” when the strategy and the unannounced products and the long arc of where the company is going are all behind a wall you have no access to โ€” you donโ€™t experience that as absence. You experience it as depth. The things you donโ€™t know feel like they must be there for a reason. The gaps in the announced picture feel like the gaps in a great iceberg โ€” whatโ€™s visible is impressive, but whatโ€™s below the surface must be more impressive still.

I had faith in IBMโ€™s strategic intelligence the way you have faith in things you canโ€™t fully see. And faith, uncontradicted by evidence, tends toward beauty. The hidden roadmap wasnโ€™t just unknown โ€” it was, in my imagination, a thing of coherence and intention and vision. It had to be. The alternative was too unsettling to consider.

Then I got hired into the Washington Systems Center and crossed the line.


There was no single moment of disillusionment. No specific product that shattered the dream, no strategy document that read like a disappointment. It was more like a gradual adjustment of the eyes โ€” the way they adapt when you move from bright sunlight into a room lit quite differently than you expected. The room isnโ€™t dark. Itโ€™s just not what you anticipated. And once your eyes adjust you can see perfectly well, but you can never quite recover the image you had of the room before you entered it.

The reality on the inside was messier than the dream on the outside. More improvised. More human. We were, in ways I hadnโ€™t anticipated, almost making it up as we went along. Not carelessly โ€” the people at WSC were extraordinary, the work was serious, the commitment was real. But the beautiful coherent roadmap I had constructed in my imagination from the outside bore only a partial resemblance to the actual thing. Strategy, it turned out, looked different up close. Less like architecture. More like weather.

I absorbed this alone. Nobody sat me down and named what I was experiencing. Nobody had the conversation with me that I would later learn to have with others. I found my way through it by degrees, the way you find your way through most things that donโ€™t come with instructions.

What came out the other side wasnโ€™t cynicism. It was something more useful โ€” a clearer eye, a more grounded relationship to the institution I was part of. The faith hadnโ€™t been wrong exactly. It had just been innocent. And innocence, once lost, canโ€™t be recovered. But what replaces it, if youโ€™re lucky, is something steadier.


Years later I was the manager. And I was hiring IBMers โ€” good ones, experienced ones, people who had spent serious careers on the other side of the blue line. They knew the products cold. They knew the customers. They knew how to work. What they didnโ€™t know, couldnโ€™t know, was what waited for them on the inside of the wall they were about to cross.

I knew it. Because I had been them.

There is a particular expression that crosses a personโ€™s face when the actual roadmap becomes visible for the first time. It isnโ€™t dramatic. It doesnโ€™t announce itself. Itโ€™s more like a subtle recalibration โ€” a slight stillness, a momentary adjustment behind the eyes. The person in front of you is doing quiet interior work, reconciling what they imagined with what theyโ€™re now seeing. The gap between those two things is doing something to them, and theyโ€™re not sure yet what to do with it.

I learned to watch for that expression. And when I saw it I knew what was coming if I didnโ€™t get ahead of it.


The danger wasnโ€™t disappointment. Disappointment is temporary, and smart people move through it. The danger was what disappointment hardens into when it isnโ€™t named and worked through โ€” a corrosive cynicism that poisons not just the person carrying it but everyone around them. A talented IBMer who had invested a career in faith, discovered the faith was misplaced, and decided the whole enterprise was therefore hollow โ€” that person could do real damage to a team. I had seen it happen, or the early stages of it, which was enough.

So I developed what I came to think of as the god is dead conversation.

The name came from Nietzsche, though the application was strictly practical. What Nietzsche meant โ€” or one of the things he meant โ€” was that when the organizing faith of a civilization collapses, the collapse doesnโ€™t leave nothing. It leaves a vacancy that has to be filled with something else, something built rather than inherited. The god is dead conversation was about helping someone through that vacancy quickly, before they filled it with the wrong thing.

It wasnโ€™t a long conversation. It didnโ€™t need to be. What it needed to be was honest, and direct, and delivered before the cynicism had time to set.

I would tell them what I saw happening. I would tell them it was normal, expected, that everyone who crossed this particular line felt some version of it. I would tell them the dream theyโ€™d carried on the outside wasnโ€™t foolish โ€” it was a reasonable response to incomplete information, and the information had been incomplete by design, and the design had served real purposes. None of that made them naive. It made them human.

And then I would tell them what Iโ€™d learned on my own, without anyone to guide me through it. That the messiness on the inside wasnโ€™t a failure of IBMโ€™s intelligence or intention. It was just what strategy actually looks like when youโ€™re close enough to see the seams. Every institution looks more coherent from the outside than it does from the inside. Thatโ€™s not a scandal. Thatโ€™s organizational life.


The conversations were tricky. There was real care required. You were asking someone to grieve something โ€” the beautiful imagined roadmap, the faith in a hidden coherence โ€” without tipping them into bitterness about what replaced it. You were trying to accelerate a process that, left alone, might drag on for months and quietly corrode their effectiveness. And you were doing it while also being their manager, which meant you needed them functional and engaged on the other side of the conversation, not just unburdened.

What I had going for me was credibility. I wasnโ€™t delivering a message from outside the experience. I had made the same crossing. I knew the specific texture of what they were feeling because I had felt it myself โ€” the diffuse quality of it, the absence of a single dramatic moment, the gradual adjustment of the eyes. When I told them I understood what was happening to them, I actually did. I think they could tell.

Trial and error had taught me the shape of it. What didnโ€™t work I had found out the hard way, at some cost, early on. What I arrived at had been load tested by real people in real situations. It wasnโ€™t a framework from a leadership seminar. It was something I owned completely, which meant I could adapt it in the moment rather than execute a script.


Most of them came through it well. Better than well, actually.

What I hadnโ€™t fully anticipated โ€” though in retrospect it makes complete sense โ€” was what replaced the faith once it was gone. It wasnโ€™t the steadier, clearer-eyed pragmatism I had found my way to alone. It was something more potent than that. Something that surprised me the first time I saw it and then became one of the things I quietly counted on.

They came out the other side feeling superior.

Not arrogant. Not dismissive of colleagues still on the outside. But quietly, privately elevated โ€” because they were now keepers of the secrets they had once only believed in. The blue line that had shaped their entire professional identity, that had defined the boundary of what they could know and say and imagine, was now behind them. They were on the inside. They had access. They had been trusted with the actual roadmap, the real strategy, the unannounced products that the rest of the world was still constructing faith-based pictures of.

The believer had become the keeper. And keeping, it turned out, was a more powerful identity than believing. The believer is passive โ€” sustained by what they imagine. The keeper is active, responsible, trusted. They carry something real rather than something projected.

It solved my practical problem neatly, though that wasnโ€™t why it moved me. What moved me was watching people find their footing on the other side of a genuine loss and discover that the ground there was solid โ€” different from what theyโ€™d imagined, but solid. They hadnโ€™t just survived the crossing. Theyโ€™d been changed by it in a way that made them more valuable, more grounded, more fully present to the actual work.

Which was, I suppose, what the god is dead conversation had been for all along.


I think about that blue line often these days.

We are living through a moment when artificial intelligence is advancing faster than most people can track, and the organizations building it โ€” the labs, the research teams, the companies placing enormous bets on where this technology is going โ€” have their own version of the wall. Not identical to IBMโ€™s. The competitive and legal architecture is different. The culture is different. But the basic structure is the same: there is what has been announced, and there is everything else, and most people are working entirely from the announced side.

Which means most people are doing what I did before I crossed the line at WSC. They are filling the gaps with faith. And faith, uncontradicted by evidence, tends toward beauty.


The unrevealed AI roadmap looks, from the outside, like a thing of coherence and intention. The capabilities that havenโ€™t been announced yet must be more impressive than the ones that have. The strategy must be more considered than whatโ€™s visible. The gaps in the public picture feel like depth rather than uncertainty โ€” like the part of the iceberg below the surface, which must be vast because the part above is already remarkable.

I am not saying this faith is wrong. I held the same faith about IBM and it wasnโ€™t wrong exactly โ€” it was innocent. The people constructing faith-based pictures of where AI is going are doing a reasonable thing with incomplete information. The information is incomplete partly by design, for reasons that make competitive and strategic sense, just as IBMโ€™s secrecy made sense. None of that makes the faith naive.

But Iโ€™ve been inside enough walls to know what the inside tends to look like. And I think itโ€™s worth saying, clearly and without cynicism, that the reality is probably messier than the dream. More improvised. More uncertain. More human. The people building these systems are extraordinary โ€” the work is serious, the commitment is real โ€” but they are also, in ways that might surprise you, almost making it up as they go along. Not carelessly. But without the complete map that the outside imagines must exist somewhere, fully drawn, waiting to be revealed.

Strategy, up close, looks less like architecture and more like weather.


This isnโ€™t a counsel of despair. Itโ€™s almost the opposite.

The IBMers who crossed the line and survived the god is dead conversation didnโ€™t end up with less than they started with. They ended up with more โ€” a clearer eye, a more grounded relationship to the institution, a more useful kind of engagement with the actual work. The faith they lost was the innocent kind. What replaced it was steadier and more durable.

I suspect something similar is available to anyone willing to look at the AI moment with clear eyes. Not the disappointed cynicism of someone who expected a beautiful coherent roadmap and found a human institution instead. Not the breathless faith of someone still on the outside of the wall, filling gaps with generous assumptions. Something in between โ€” harder to sustain, more honest, ultimately more useful.

The technology is real. The progress is real. The stakes are real. None of that requires the roadmap to be a thing of beauty. It just requires it to be worked on seriously by people who understand what they donโ€™t yet know โ€” which, from everything I can observe, it is.


What I couldnโ€™t give those IBMers, and what nobody can give you, is the experience of crossing the line yourself. The god is dead conversation only works because the crossing has already happened โ€” because the person sitting across from you has already seen the actual roadmap and is already processing the gap between what they imagined and what they found. You canโ€™t have the conversation in advance. The disillusionment has to be real before it can be worked through.

Most of us will never cross the line into the AI labs. Weโ€™ll stay on the outside of the wall, working from the announced picture, filling the gaps as best we can. Thatโ€™s not a failure โ€” itโ€™s just the condition most of us are in, the same condition those IBMers were in for their entire careers before I hired them.

But knowing the wall exists, and knowing what walls do to imagination, seems like it ought to change something about how we hold our faith. Not abandon it. Just hold it a little more lightly. Stay curious about the seams. Remain open to the possibility that the most important thing about the unrevealed roadmap isnโ€™t whatโ€™s in it โ€” but what weโ€™ve projected onto it.

The blue line is still there. Most of us are still on the outside of it.

And the hidden roadmap still looks, from here, like a thing of beauty.