Categories
Writing

The Grain Bin and the Ghost

Richard Rhodes published How to Write in 1995. In it, he offers practical advice about a writerโ€™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 itโ€™s quaint โ€” though it is โ€” but because of what it reveals about how a writing life was organized. Rhodes wasnโ€™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 wasnโ€™t guaranteed, because the library closed, because the gap between not-knowing and knowing could be measured in trips and hours. A writerโ€™s bookshelf was a personal hedge against scarcity.

Think about what it meant that someoneโ€™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 couldnโ€™t otherwise have it on their desk. Thatโ€™s what a writing life cost. Thatโ€™s what it demanded of the people around you.

That scarcity is gone so completely itโ€™s hard to reconstruct the phenomenology of it.

The bottleneck in Rhodesโ€™s world was access. You either had the fact or you didnโ€™t. Getting it required physical movement โ€” to the shelf, to the library, to someone who knew. The reference bookโ€™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 isnโ€™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 couldnโ€™t have framed because it didnโ€™t exist: the infrastructure became generative. The reference shelf held facts. It didnโ€™t think with you. It didnโ€™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 donโ€™t wait. They participate.

This is the structural shift that the grain bin metaphor canโ€™t contain. Rhodes was describing a writerโ€™s relationship to stored knowledge โ€” 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.

Whatโ€™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 โ€” which means the writerโ€™s job has changed in kind, not just in degree. Youโ€™re no longer managing a pantry. Youโ€™re managing a working relationship.

Where does it end up? Probably somewhere Rhodes would recognize at the level of the goal โ€” clarity, the right word, the true sentence โ€” 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 โ€” whether to trust it, when to push against it, how to stay the one doing the writing โ€” is the work no one has finished yet. Maybe no one can, while itโ€™s still changing this fast.

Categories
AI Technology

The Bathwater Problem

Gary Kamiya was writing about the Tenderloin when he said it, but the line has been following me around: โ€œThe problem is that by saving the baby, you also save the bathwater.โ€

The pattern is remarkably consistent across every major information technology. Each one arrives promising to liberate the deserving โ€” the faithful, the learned, the civic-minded โ€” and each one immediately, inevitably, arms everyone else too. Gutenbergโ€™s press was understood by its champions as a device for spreading the true Word; within decades it was the primary infrastructure for Protestant schism, Catholic counter-propaganda, astrological almanacs, and pornography. The reformers got their Bible. They also got their pamphlet wars.

The telegraph was greeted as a force for peace โ€” shared information would make war irrational, commerce would bind nations. It also became the nervous system of commodity speculation, financial manipulation, and the first truly industrial-scale news hoaxes. The telephone: connection and the crank call, the crisis line and the threatening voice in the dark. Radio: FDRโ€™s fireside chats and Father Coughlin. Television: Murrow taking down McCarthy, and also fifty years of manufactured consent. The internet: the largest library ever assembled and the largest sewer.

The pattern isnโ€™t coincidental. Itโ€™s structural. Each technology expands whatโ€™s possible for human expression and coordination โ€” and human expression and coordination contain both the noblest and the worst of us in roughly fixed proportion. The tool doesnโ€™t change the ratio. It scales both sides of it.

Whatโ€™s interesting historically is how each generation believes their technology will be different โ€” that this time the architecture can be designed to select for the good. The internet era produced the most elaborate version of this belief: algorithmic curation would surface truth, network effects would reward quality, the wisdom of crowds would outcompete misinformation. Instead it turned out that engagement was the attractor, and outrage was the highest-engagement content. The bath got hotter.

The AI moment is the same belief system, restated with more technical sophistication. But the Kamiya line stands. You are saving a baby, and you are saving bathwater, and no one has yet designed a tub that can tell the difference.

The question isnโ€™t whether the bathwater comes with the baby. It always does. The question is whether you turn on the tap.

Categories
Living Serendipity Travel

The Conditions of the Unexpected

There is a flight I took in 2001 that I have never fully stopped thinking about. Not the flight itself โ€” a forgettable three-hour hop in a middle seat โ€” but the two-hour delay that preceded it. The gate agentโ€™s apologetic crackling over the intercom. The way I surrendered to the terminal, found a bar stool, ordered something I didnโ€™t need. The man next to me was reading a book I recognized. We talked for two hours. He told me about a job. I didnโ€™t take it โ€” but I spent three months considering it, which is its own kind of detour. I came out the other side different in ways I still canโ€™t fully account for.

I have told this story before as a story about luck. Iโ€™m not sure thatโ€™s what it is.


Alexander Krauss spent years going through the records of scienceโ€™s major discoveries โ€” Nobel Prize winners, the landmark non-Nobel findings, more than 750 in all โ€” looking for the mechanism behind what everyone had been calling serendipity. The telescope trained on an unexpected patch of sky. Flemingโ€™s contaminated petri dish. The chance observation that shouldnโ€™t have meant anything but did.

What he found upended the romance of the story. The discoveries that seemed most accidental, most shaped by the caprice of an unlucky sneeze or a mislabeled sample, turned out to follow a pattern. Nearly all of them happened shortly after a researcher gained access to a new tool. The accidental observation of cells under an improved microscope. X-rays discovered through a discharge tube nobody had pointed in that direction before. The first planet beyond our solar system, caught by a spectrograph that hadnโ€™t existed a few years earlier. What looked like lightning striking the same improbable spot again and again was actually the same thing each time: a new instrument creating the conditions under which something unexpected could be seen.

Krauss calls this โ€œengineering serendipity.โ€ The phrase stops me every time I read it, because it sounds like a contradiction and turns out to be the most practical sentence in the philosophy of discovery. You canโ€™t engineer the specific surprise. But you can engineer the conditions that make surprise likely. You can build the lens before you know what it will show you.

This distinction โ€” between engineering an unexpected discovery and engineering the conditions for unexpected discovery โ€” is one Iโ€™ve been carrying around like a stone in my pocket. Because I think it applies far outside the laboratory. I think itโ€™s one of the central design problems of a life.


The book trend critics are calling โ€œDigital Nostalgiaโ€ is, depending on how you read it, either the most sentimental or the most diagnostic thing happening in literary culture right now. The novels topping lists this spring are full of people losing their recordings, waking up in centuries without algorithms, mourning the weight of analog things. Ben Lernerโ€™s new novel begins with a dropped phone in a hotel sink โ€” the recording gone, the moment unrecoverable. Caro Claire Burkeโ€™s Yesteryear sends a social-media influencer back to an 1855 that is nothing like the one she curated for her followers: cold, filthy, unfiltered, and somehow more real.

What readers are reaching for in these books is not the past per se. Itโ€™s the texture of a life that wasnโ€™t predicted in advance. The feeling of not knowing what came next because nothing had pre-sorted the possibilities. Nostalgia, in its root meaning, is pain at being far from home. What Digital Nostalgia seems to be mourning is something more specific: the disappearance of accident from everyday life.

I notice this in small ways. My phone knows where Iโ€™m going before Iโ€™ve decided to leave. The algorithm has predicted, with unsettling accuracy, what I will want to read next. The coffee shop I found by walking down an unfamiliar street now gets recommended to me, which is useful and also somehow diminishes the thing I found. The city I live in has become a more efficient version of itself. Less of it surprises me than used to.

This is not entirely bad. But something is lost in the smoothing. And the books people are buying tell you what.


The urbanist argument for cities has always included, at some level, an argument for density as a serendipity engine. You put people in proximity. You make them share transit and sidewalks and bars and parks. Intersections happen. Ideas cross. The great creative explosions of modern history โ€” Florentine painting, Viennese psychoanalysis, the Bell Labs cafeteria โ€” were products less of individual genius than of designed proximity. People who wouldnโ€™t have met each other kept meeting each other.

Whatโ€™s interesting about Kraussโ€™s argument is that it generalizes this principle to the history of science in a way that makes it quantifiable. Itโ€™s not just that cities were generative because they were dense. Itโ€™s that they were generative because they were full of new tools โ€” printing presses, coffeehouses, salons โ€” that created new surfaces where minds could collide and refract in new ways. The tool doesnโ€™t make the discovery. It makes the discovery possible, and likely, and reproducible by others.

Which brings me back to the airport bar.

The two-hour delay created an unstructured interval I hadnโ€™t planned for. I didnโ€™t know what to do with it, so I sat somewhere I wouldnโ€™t normally have sat. The man next to me had a book that served as an opening. We were both temporarily outside our routines, which is another way of saying: we were both in a new instrument, looking at something we hadnโ€™t known to look for.

What Iโ€™ve been slow to admit is that this kind of moment doesnโ€™t just happen. It happens to people who are outside their routines. It happens in places where unlike people are forced into proximity. It happens when you sit down somewhere without your headphones, without a screen to retreat into, in the condition of being briefly unoptimized. The delay was the tool. The discovery followed.


So here is the tension I keep returning to: you can engineer the conditions for serendipity, but you cannot engineer serendipity itself, and the engineering has to be genuinely open-ended or it stops working. If you design a system that produces specific surprises, you havenโ€™t built a serendipity engine. Youโ€™ve built a surprise dispenser, which is a different and lesser thing. Amazonโ€™s โ€œyou might also likeโ€ feature is not serendipity. It is prediction wearing serendipityโ€™s clothes.

The difference is whether the system preserves its capacity to show you something it didnโ€™t know you needed to see. A new microscope could reveal anything. A recommendation algorithm reveals only a constrained neighborhood of the space of things youโ€™ve already wanted. The former is a lens. The latter is a mirror.

I think this is what the Digital Nostalgia readers are grieving, without quite being able to name it: not the analog past itself, but the unoptimized interval. The moment between knowing what you wanted and finding it, when anything might happen. That space has been shrinking for twenty years, and the algorithmโ€™s promise โ€” to eliminate friction, to anticipate, to smooth โ€” has turned out to be partly a promise to eliminate possibility.

The question Iโ€™m sitting with is whether itโ€™s recoverable. Not globally โ€” Iโ€™m not interested in the manifesto version of this argument, the call to smash the phones or return to the forest. But personally. Whether I can design my own life to include enough genuine aperture โ€” enough unoptimized intervals, enough new tools, enough places where I am briefly outside my routine and available to be surprised โ€” to keep the surprises coming.

I have some guesses about what this looks like. Reading outside my field. Saying yes to the conversation I donโ€™t have time for. Choosing the longer route. Leaving earlier so the delay doesnโ€™t feel like a crisis.

These are small things. They are also, if Krauss is right, approximately how all the important discoveries get made.


The flight eventually boarded. I didnโ€™t take the job. But I thought about it for three months, which means I thought about my actual life for three months โ€” what I wanted from it, what I was settling for, what I hadnโ€™t been willing to name. The man at the bar didnโ€™t change my path. He changed my angle of view, briefly, enough. Iโ€™ve been a little suspicious of smooth trips ever since.

Categories
AI Work

The Digital Beast of Burden

A friend of mine recently cut through the noise of the current AI discourse with a comment that felt surprisingly grounding. We were talking about the breathless predictions of AGIโ€”superintelligence, sentient machines, the technological singularityโ€”when he shrugged and said, “I don’t need any of that. I just want AI to do the donkey work.”

He wasn’t asking for a god in the machine; he was asking for a better tractor. He didn’t want a synthetic philosopher to debate the meaning of life; he wanted the next evolution of “Claude Cowork”โ€”a reliable, tireless entity to handle the drudgery so he could get back to the actual business of thinking.

There is something profound in that phrase: donkey work. It evokes the image of the beast of burdenโ€”the creature that carries the heavy packs up the mountain so the traveler can focus on the path and the view. For thousands of years, humans have sought tools to offload physical exertion. We domesticated animals, we built water wheels, we invented the steam engine. We outsourced the calorie-burning, back-breaking labor to preserve our bodies.

“The ‘donkey work’ of the information age isn’t hauling stone; it is the cognitive load of bureaucracy, formatting, sorting, scheduling, and synthesizing endless streams of data.”

Now, we are looking to preserve our minds.

The friction that exists between having an idea and executing it is often composed entirely of this “donkey work.” When my friend says he wants AI for this, he isn’t being lazy. He is expressing a desire to reclaim his cognitive bandwidth.

There is a fear that if we hand over these tasks, we become less capable. But I suspect the opposite is true. If you are no longer exhausted by the logistics of your work, you are free to be consumed by the meaning of it.

We often talk about AI as if itโ€™s destined to replace the artist or the architect. But the most valuable version of this technology might just be the humble assistantโ€”the digital mule that quietly processes the mundane in the background. Itโ€™s the difference between a tool that tries to be you, and a tool that helps you be you.

We don’t need AGI to solve the human condition. We just need the “donkey work” handled so we have the time and energy to experience it.

What do you think?

  1. Is there a danger that in handing over the “donkey work,” we accidentally hand over the friction required to build mastery?
  2. If your daily cognitive load dropped by 50% tomorrow, would you actually use that space for “higher thinking,” or would you just fill it with more noise?
  3. Where exactly is the line between “drudgery” and the “process”โ€”and are we risking erasing the latter to solve the former?
Categories
AI

The Second Fire: From Finding to Forming

There is a specific kind of vertigo that comes with a paradigm shift. Itโ€™s the feeling of standing on the edge of a map that has just been unrolled to reveal twice as much territory as you thought existed. Lately, as I navigate the vast, generative landscape of AI, that old vertigo has returned. Itโ€™s a hauntingly familiar resonance, a structural echo of the late nineties and early 2000s when we first encountered the Google search bar.

Back then, the world was a series of closed doors. Information was siloed in physical libraries, expensive encyclopedias, or the unreliable oral histories of our social circles. Then came that clean, white interface with a single blinking cursor. Suddenly, the friction of “not knowing” began to evaporate. We weren’t just browsing the web; we were suddenly endowed with a collective memory. It felt like a superpowerโ€”the ability to summon any fact from the digital ether in milliseconds.

“Google is not just a search engine; it is a way of life. It is the way we find out who we are, where we are going, and what we are doing.”

Today, the sensation is different in texture but identical in weight. If Google gave us the power to find, AI is giving us the power to form.

The “Aha!” moment of 2026 isn’t about locating a PDF or a Wikipedia entry; itโ€™s the realization that the distance between a thought and its realization has shrunk to almost nothing. When I prompt a model to synthesize a complex theory or visualize a dream, I feel that same electric jolt I felt twenty years ago when I realized Iโ€™d never have to wonder about a trivia fact ever again.

But there is a philosophical weight to this new “awesome.” With Google, the challenge was discernmentโ€”filtering the flood of information to find the truth. With AI, the challenge is intent. When the “how” becomes effortless, the “why” becomes the only thing that matters. We are moving from the era of the Librarian to the era of the Architect.

We are once again holding a new kind of fire. Itโ€™s warm, itโ€™s brilliant, and just like the first time we saw that search bar, we know that the world we lived in yesterday is gone, replaced by a version where our reach finally matches our imagination.