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Pluralistic: Critique and writing (23 Oct 2026) by Cory Doctorow
Saturday October 24th, 2026 at 4:25 PM

Pluralistic: Daily links from Cory Doctorow
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Today's links

  • Critique and writing: The most important part of a writing workshop is trying to fix other people's stories.
  • Hey look at this: Delights to delectate.
  • Object permanence: USPS nukes the mail; Enron Explorer; "Scored"; UAE's international hacker legion; NZ provides hacking tools to torturers; Truecrypt insecure; The Traitorous Eight.
  • Upcoming appearances: Vancouver, Ottawa, Vienna, Kilkenny, Courtenay, Vancouver, Oxford, Sheffield, Virtual, Oxford, Montreal.
  • Recent appearances: Where I've been.
  • Latest books: You keep readin' em, I'll keep writin' 'em.
  • Upcoming books: Like I said, I'll keep writin' 'em.
  • Colophon: All the rest.


A vast field of complicated machinery composed of many-times-overlaid 19th century printing presses. Caught in these gears are several figures who are all writing - a bearded Greek in a loincloth, a severe doge, a grande dame, a lady upon her settee, a recording angel, two drunken clerks at a table, a tormented poet in a wig. Invading the scene is a many-tentacled pulp robot.

Critique and writing (permalink)

Through my own writing life, nothing has done more to improve my writing than diligent participation in peer-based workshops; that's where a group of writers, all at about the same stage in their artistic development, gather to read one another's work and offer feedback specifically aimed at improving each other's stories.

This is a deceptively simple exercise, and the reasons it works so well are quite counter-intuitive. The most obvious benefit is the way that a workshop encourages you to write at all. When you're at the start of your writing career, you are almost totally reliant upon your own internal self-discipline to keep producing.

Acquiring that self-discipline is infinitely valuable, but it's also incredibly hard. Being part of a group of writers who expect you to regularly turn in new work adds a very useful bit of external motivation that augments your still nascent self-discipline. Knowing you have to turn in a story for the group by Friday can get you in gear when you feel discouraged or blocked.

Before you're getting published regularly (or at all), your critiquing circle might be the only source of validation you get for your work, so the knowledge that you're in for that validation if you get that story in on time is a great motivator. But this is where the counter-intuitive part comes in: as great as it feels to be the center of your peers' attention and to get close feedback on the work you sweated over, that's not the real value you get from a writing workshop, at least not at the start of your career.

Your peers' critiques can help you fix weaknesses in your story, and even teach you a little about how to avoid those weaknesses in future work. You might get feedback that turns an unpublishable story into a published one. But the point of a writing workshop isn't merely to make your stories better – it's to make you better at writing stories.

That's where critiquing other writers' stories comes in. The process of reading and re-reading someone else's imperfect work and devoting real mental energy to figuring out what's not working in it and how to fix it is how you develop the creative instincts that allow you to automatically and unconsciously avoid pitfalls and make breakthroughs in your own work.

Even if none of the feedback you offer is ever incorporated into the story you're critiquing, the act of preparing and delivering that critique is the most reliable fast-track to becoming a better writer yourself. There's something very valuable in the combination of thinking critically, being exposed to other workshop members' ideas about the story under discussion, and working with source material that you can look at with more objectivity because it didn't come out of your own head.

I bring all this up because I've now heard from a few beginning writers who tell me that they're finding LLMs to be good editorial feedback generators. They value the editorial suggestions they get from a chatbot after they finish their work, and use it to help them with a new draft. Without commenting on whether I think LLM feedback is editorially useful (I certainly wouldn't ever ask a chatbot for that kind of feedback), I want to point out that when it comes to improving your writing, getting editorial notes on your work is distinctly inferior to offering criticism of other writers' work.

The reality is that when you're starting out as a writer, the vast majority of work you produce will be artistically unsalvageable. The much-vaunted "million words of crap" you write on the way to becoming a publishable writer are about learning to marry technique to artistic vision and to sharpen both. Getting editorial feedback that helps you shore up the weakest spots in a story that is ultimately never published and constitutes a learning exercise has value, but it has far less value than applying the things you've learned from making and fixing those mistakes to your next story.

With vanishingly few exceptions, a commercially and artistically successful writer isn't someone who writes one great story or novel: a writing career is defined by a body of work, which means that you have to do more than rewrite. You have to write the next thing, and the next thing, and the next.

Having an editor-on-demand of highly variable (and often dubious) quality might help you improve your writing, but it's no substitute for participating in a peer workshop. The idea that an LLM might be able to stand in for a workshop is grounded in the fallacy that the point of a workshop is to have people tell you how to fix your story, rather than analyzing other people's writing in order to develop your own critical skills.

Look: it's a cliche to say "every writer is different," but I really believe that every writer is different, and that's down to the legibility of the writing process to other writers. If you're a painter or sculptor or other visual artist, you've likely spent many hours in a studio with many other practitioners while all of you work from the same life model or still life. If you're a musician, you've almost certainly played music with other musicians. If you're a dancer, you've definitely danced with other dancers.

But writers get precious little exposure to other writers' process. At best we might look at each other's drafts. A musician can listen to every note another musician produces while riffing or composing a new work or interpreting a work. Writers don't get to watch words emerge from each other's fingertips. Being observed that closely while you write would be ghastly and paralyzingly invasive.

I've taught a lot of writers over the years and I've had many discussions with my peers about their writing process, and I'm here to tell you that pretty much every writer finds every other writer's process baffling. We each of us invent an idiosyncratic process for ourselves that will never fully work for anyone else.

So if you value editorial feedback from a chatbot (ideally, a local one running on your computer and not one of the "foundation models" that are torching the planet and elevating the worst people on earth to positions of political, technical and commercial prominence), that's fine, you do you.

But even if that's the case, I still want you to know that whatever you're getting out of the chatbot is fundamentally different, and (I believe) much less useful than participating in a peer workshop.

That's what I wanted to say today, but I predict that an appreciable number of readers are about to email me to ask how these "peer workshops" work. There's a ton of variability in how these are conducted, but the basic shape of them is that in advance of each session, one or more writers submits a finished work to the other writers, who then read through the manuscript at least twice, making notes that include both minor copyedits and broader, thematic notes. They may write a brief editorial response as well, ranging from a paragraph to a couple of pages.

Then the workshop convenes. Each writer briefly expresses their views about the story under consideration, focusing on those thematic and structural notes on what worked and didn't work in the story, with suggestions for improving the latter. You don't need to point out every typo – they're noted on the manuscript. Critiquers don't need to repeat one another. If another workshop member says the thing you were planning to say, you can just say "Ditto what so-and-so said about whatever." If you have nothing to add when your turn comes about, it's fine to pass.

Those are pretty much universal characteristics of a peer workshop. Here are some variations that I am dogmatically committed to, but which other workshoppers might disagree with:

  • Every writer should submit regularly to the workshop. There is a serious risk that attending a workshop can become a substitute for actually writing. It is no kindness to your workshopmates to let them stay in the circle if it leads them to stop writing.

  • The subject of each session must not speak during the critiques, except to answer direct questions that are not related to the writing itself (e.g., "I couldn't figure out what word this was supposed to be – can you clarify?"). The subject can speak after all the other writers have spoken.

  • Each person in the critiquing circle speaks once, in turn, without being interrupted. No cross-talk allowed. It is useful to set a time-limit for critiques.

  • No partial manuscripts. It's not really possible to critique a story unless you have the complete tale. Novels can be workshopped as three chapters and an outline.

  • Stories should be distributed in advance and read in advance. Don't have writers read their work aloud for critique, as this can lead to critiquing the delivery rather than the material.

  • Critique the story, not the writer. It's fine to be offended by something in the story, but not OK to accuse your workshopmates of being bad people for having offended you.

  • Discourage resubmission of revised stories. Workshopping produces sharply diminishing returns. If you really want feedback on a rewrite, approach people individually and ask if they'll read the new draft.

Any group of three or more writers can start a workshop. You'll need to locate writers who are at about the same stage in their artistic and professional lives as you, and find a physical place (or a videoconference service) where you can meet. Library meeting rooms are a favorite, and so is rotating between workshop members' homes. Set a regular schedule – weekly, fortnightly, monthly, possibly quarterly – and stick to it.

If you write genre fiction and you are interested in attending a peer workshop that also has an instructor to guide the sessions, lecture, set exercises, etc, I can recommend the three workshops I've taught:

  • Clarion (UC San Diego, six weeks):

https://clarion.ucsd.edu/ (I'm also a 1992 Clarion grad)

  • Clarion West (Seattle, six weeks):

https://www.clarionwest.org/

  • Viable Paradise (Martha's Vineyard, one week):

https://viableparadise.com/

Hey look at this (permalink)


A shelf of leatherbound history books with a gilt-stamped series title, 'The World's Famous Events.'

Object permanence (permalink)

#25yrsago UK anti-terror laws could bankrupt ISPs https://web.archive.org/web/20011118143634/http://www.vnunet.com/News/1126338

#25yrsago What's an "iPod?" https://web.archive.org/web/20011024015856/http://www.apple.com/ipod/

#25yrsago Bible, Koran or Mein Kampf? https://web.archive.org/web/20011109123124/http://www.salon.com/people/feature/2001/10/24/book_quiz/index.html

#25yrsago Tongan court jester scam costs king millions https://web.archive.org/web/20011224034152/http://pidp.eastwestcenter.org/pireport/2001/October/10-23-01.htm

#25yrsago USPS irradiating the mail to fight anthrax attacks https://web.archive.org/web/20011109100316/http://www.newscientist.com/news/news.jsp?id=ns99991468

#20yrsago Enron Explorer mines Enron’s emails https://web.archive.org/web/20061106204850/http://enron.trampolinesystems.com/

#20yrsago Investigative journal: “Fair use is not applicable” https://archive.blogs.harvard.edu/shlep/2006/10/23/whaddayaknow-about-fair-use-and-copyright/

#20yrsago Warners stiffs African amputee film extras on prosthetics promise https://web.archive.org/web/20061105004400/http://www.nypost.com/seven/10232006/gossip/pagesix/pagesix.htm

#20yrsago Former FCC Chairman shills against Net Neutrality https://web.archive.org/web/20061028043416/http://www.lessig.org/blog/archives/003577.shtml

#15yrsago Plotting advice for fiction writers http://nielsenhayden.com/makinglight/archives/013243.html

#15yrsago DARPA wants vampire satellites to harvest parts from dead sats prior to decommissioning https://web.archive.org/web/20111022223128/http://www.darpa.mil/NewsEvents/Releases/2011/10/20.aspx

#15yrsago Understanding the hyperrich through the lens of tomorrow’s history http://www.antipope.org/charlie/blog-static/2011/10/a-cultural-experiment.html

#15yrsago Scored: pulse-pounding/thought-provoking YA novel about surveillance https://memex.craphound.com/2011/10/24/scored-pulse-pounding-thought-provoking-ya-novel-about-surveillance/

#10yrsago UAE surveillance contractor is recruiting an army of foreign hackers to break into its citizens’ devices https://web.archive.org/web/20161024141138/https://theintercept.com/2016/10/24/darkmatter-united-arab-emirates-spies-for-hire/

#10yrsago Publicly-funded NZ company sold mass surveillance tech to torturers and GCHQ https://web.archive.org/web/20161023101410/https://theintercept.com/2016/10/23/endace-mass-surveillance-gchq-governments/

#10yrsago RIP, Tom Hayden: Yippie, radical, politician, author https://www.bbc.co.uk/news/world-us-canada-37749127

#10yrsago Audit reveals significant vulnerabilities in Truecrypt and its successors https://www.helpnetsecurity.com/2016/10/18/veracrypt-security-audit/

#5yrsago Cyber-mercenaries helped Saudis hack an NYT reporter https://pluralistic.net/2021/10/24/breaking-the-news/#kingdom

#5yrsago The Traitorous Eight and the Battle of Germanium Valley https://pluralistic.net/2021/10/24/the-traitorous-eight-and-the-battle-of-germanium-valley/

#1yrago Checking in on the state of Amazon's chickenized reverse-centaurs https://pluralistic.net/2025/10/23/traveling-salesman-solution/#pee-bottles

Upcoming appearances (permalink)

A photo of me onstage, giving a speech, pounding the podium.


A screenshot of me at my desk, doing a livecast.

Recent appearances (permalink)


A grid of my books with Will Stahle covers..

Latest books (permalink)


A cardboard book box with the Macmillan logo.

Upcoming books (permalink)

  • "The Post-American Internet," a geopolitical sequel of sorts to Enshittification, Farrar, Straus and Giroux, 2027

  • "Unauthorized Bread": a middle-grades graphic novel adapted from my novella about refugees, toasters and DRM, FirstSecond, April 20, 2027

  • "Enshittification, Why Everything Suddenly Got Worse and What to Do About It" (the graphic novel), Firstsecond, 2027

  • "The Memex Method," Farrar, Straus, Giroux, 2027


Colophon (permalink)

Today's top sources:

Currently writing:

  • “Once Is Enemy Action,” a science fiction novel about the origins of modern technofascism. Today's words: 550 (28730 total).

  • "The Post-American Internet," a sequel to "Enshittification," about the better world the rest of us get to have now that Trump has torched America. Fourth draft completed. Submitted to editor.

  • A Little Brother short story about DIY insulin PLANNING

This work – excluding any serialized fiction – is licensed under a Creative Commons Attribution 4.0 license. That means you can use it any way you like, including commercially, provided that you attribute it to me, Cory Doctorow, and include a link to pluralistic.net.

https://creativecommons.org/licenses/by/4.0/

Quotations and images are not included in this license; they are included either under a limitation or exception to copyright, or on the basis of a separate license. Please exercise caution.

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"When life gives you SARS, you make sarsaparilla" -Joey "Accordion Guy" DeVilla

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ISSN: 3066-764X

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Why Frank O’Hara is Perfect For Introducing Poetry to Tweens by Catherine Sawoski
Thursday October 15th, 2026 at 2:52 PM

Craft and Criticism – Literary Hub
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frank o'hara

When I taught poetry, I always arrived with pencils, pieces of paper, and a printed out poem by Frank O’Hara. If my students, middle schoolers forced to cram into libraries and over-filled classrooms, had heard of any poets before, O’Hara wasn’t one of them. With his short declarations and excited exclamations, he was a far cry from Robert Frost, Shel Silverstein, or anyone else past teachers had forced upon them.

Here, finally, was a poet without the careful composition that made poetry feel stuffy, like some hidden language adults pretended to understand. I watched their faces screw up with little laughs reading about Lana Turner’s fainting spell—a room full of twelve-year-olds giggling about 1950s movie gossip and an actress they had never heard of before. It was like an inside joke.

Anyone familiar with O’Hara’s work will recognize this feeling of camaraderie—there’s an immediacy to his work, an off-the-cuff wit that makes you, almost immediately, co-conspirators. In his artistic manifesto (which he wrote, in typical O’Hara fashion, in a single hour while Donald Allen was on his way to pick it up), he described writing a poem for a single person: as if he just as easily could have picked up a phone instead of a pen. It was unlike anything my students had read before.

How, amidst the poetic structure and planning they were used to, could it not change their idea of what poetry was? They weren’t alone. In the 100 years since his birth, and 60 since his death, generations of writers have found inspiration in his casual profundity. In many ways, he never stopped being the king of the New York art scene.

I asked them to be like Frank O’Hara, noticing colors and sounds and people we encountered.

O’Hara is most famous for his collection Lunch Poems, written in his lunch break as a receptionist from the Museum of Modern Art—proving even future curators/art critics must begin at the front desk. He’s often been called a painter’s poet, and, rejected by the conventional literary scene, found himself faster friends with the Abstract Expressionists than the literary world. Lunch Poems—reviewed by Ted Berrigan, as, emphatically “a great book!” and one of the “most important documents in contemporary poetry”—includes some of his most famous works, including “The Day Lady Died,” “Ave Maria,” and “A Step Away From Them.” This last one was my usual classroom pick. Selecting an eager student to read it aloud, a school’s worth of seventh graders would follow along on their printouts, as they began:

It’s my lunch hour, so I go
for a walk among the hum-colored
cabs. First, down the sidewalk
where laborers feed their dirty
glistening torsos sandwiches
and Coca-Cola, with yellow helmets
They protect them from falling
bricks, I guess.

O’Hara called this style “I do this, I do that” poems. He had a name for it more broadly: Personism (“a movement which I recently founded and which nobody knows about”), marked not by the absence of ideas, but by the absence of thinking. “You just go on your nerve,” he wrote. “If someone’s chasing you down the street with a knife you just run, you don’t turn around and shout, ‘Give it up! I was a track star for Mineola Prep.’” You can picture him, walking down W 53rd, time ticking out on his lunch break, composing with a nerve so strong it poured out of him without trying.

Even when I hadn’t cleared it with the school administration, the next part of my lesson would be interactive. Heading out in more of a blob than a single-file line, I would gather the hordes of seventh graders out in the hallway, pens in hand, for a Poetry Walk. I asked them to be like Frank O’Hara, noticing colors and sounds and people we encountered. When we reconvened, they brought me details that they’d walked by for weeks without noticing—a crack in the wall, a spiderweb in the corner by the front door. Eight years later, and I still remember their specific examples.

I had taught them what Frank O’Hara had first taught me: poetry is not, as some may think, an arduous exercise in word choice and simile. Instead, it’s a way of looking, of noticing details we might have otherwise overlooked. It’s too tempting to get used to the sight of the hard hats, to no longer ask what, exactly, they’re protecting. The glistening torsos of the construction workers are all too easy to write off as sweaty. You need a fresh set of eyes to see. His poems sometimes took mere minutes to write in part, perhaps, because he was writing them every time he looked around. As he wrote in Autobiographia Literaria:

And here I am, the
center of all beauty!
writing these poems!
Imagine!

The best O’Hara acolytes are the ones who encourage us to see the beauty in the world, attuned to torsos on a New York Street or the majesty of making eggs for a loved one. The So-Called Second New York School (following behind O’Hara, John Ashbery, James Schuyler, and Kenneth Koch) spent their early days studying this like they were cheating on a test. Bill Berkson and O’Hara’s joint chapbook, Hymns of St Bridget, began with Berkson attempting to copy O’Hara’s way of seeing in a poem about a church steeple, what he called a “cheap imitation” of his style. “It is to you, bending limp and ridiculous, on Ninth / Street, that I turn,” he writes, finding the personality and humor to recast a landmark he walked by everyday. It’s easy to take a church seriously; it’s much harder to see it for all of its bent absurdity. (A posthumous journal of Berkson’s lists / thoughts / reflections on O’Hara—A Frank O’Hara Notebook—was published in 2019.)

O’Hara’s literary influence has been, in a word, enormous.

Ron Padgett: “reading poems like [A Step Away From Them] by Frank let me realize I could relax… and say anything I wanted.”

Alice Notley: “I was often working out in what I conceived to be O’Hara’s forms…I wanted to make work like that.”

Poets in his circle each took something different from O’Hara, adding up elements of his work to create the bedrock foundation of contemporary poetry. You can hear him in the humor that peppers literary magazines, and each literary pop culture reference. The short, conversational colloquialisms that he proved could be poetic.

The simplicity of O’Hara’s work means it’s just as exciting as it is accessible.

Nothing, however, has lived on quite like his appreciation for the mundane. While O’Hara wasn’t the first champion of the quotidian, the years following his sudden death (he was tragically hit by a jeep on a Fire Island beach at the age of 40) have made his work a blueprint for capturing modern life. This past summer, 60 years after his death, I came across a work by Pip McGough in The Brooklyn Rail that seethed with a matter-of-factness, an I-do-this, I-do-that quality that observed thick bus glass I had never thought to notice before. I see O’Hara’s influence often when I open the pages of a publication. In 2024, for instance, I remember reading Alex Dimitrov’s “Everything Always” in The New Yorker, where he writes

A man dangles a cigarette
over a fire escape on Crosby.
It’s so early, I am still in last night.
All of life honks.
The streets steam.

O’Hara is all over this, like he’s the unspoken other end of Dimitrov’s telephone call.  In car honks and steaming concrete, he sees in a way that would make O’Hara proud. He’s slightly sadder, less exuberant, but he picks out details—unglamorous, unspecial, seemingly unimportant—that make you feel the NOW-ness of being alive. In a lesson plan for The Poetry Foundation, Dimitrov wrote about how O’Hara can teach students how to see the beauty in the everyday. “A poem has already happened to you today,” he begins. A poem is happening to students, poets, teachers, everyone every hour, every minute.

It’s easy to like Frank O’Hara. There’s a reason I started my students off with him: unlike his friend and New York School colleague, the famously inscrutable John Ashbery, the simplicity of his work means it’s just as exciting as it is accessible. A friend told me recently her MFA professor, a prominent documentary poet, read O’Hara when she wanted to be reminded of the “pleasure of poetry.”

This must be a contributing factor to why he’s been so much in vogue in popular culture—his rhapsodic observations are understood and enjoyed by anyone who can share in the experience of being alive. Don Draper, in Mad Men, reads a copy of Meditations in an Emergency, and “Mayakovsky” (perhaps my favorite O’Hara poem) is read aloud in an episode. Ada Calhoun’s, in her much-discussed memoir Also a Poet, uses O’Hara as the peg that an exploration of her father/daughter relationship hangs on. As Sophia Stewart writes in The LA Review of Books: Frank O’Hara is everywhere, in TV and books and articles and epigraphs.

To anyone who has spent any time with O’Hara, finding a favorite Lunch Poem or looking up his references to 1950s culture, it makes sense. I believe there are two types of enjoyment in poetry: one in the deeply analytical work, cataloguing the sheer expansiveness of references, finding a poem open wider and wider to you until you lose sight of the bottom. T.S. Eliot’s “The Waste Land,” for example, or Edmund Spensers’s “The Faerie Queen.” O’Hara’s is the second kind. He’s felt rather than understood.

When O’Hara died, he left behind hundreds of unpublished poems in every nook and cranny of his apartment. I like to think about the ones stuffed in the back of his desk drawer, jotted down as if he were possessed, freed only when the errant thought hit the page. There’s no pretension to his work: just a poet, seeing the world, telling you about it. 100 years after his birth, we’re hungry for authenticity. Frank O’Hara, with each glistening torso, never fails to tell you something true.

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Pluralistic: Model collapse (12 Aug 2026) by Cory Doctorow
Wednesday August 26th, 2026 at 1:01 AM

Pluralistic: Daily links from Cory Doctorow
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Today's links


A collage made of architectural features from 'Variae Architecturae Formae' (1636), a collection of engravings. The architectural arches, buildings, fountains, etc, are layered atop each other and placed around each other to create an infinite, recombinant built environment.

Model collapse (permalink)

One of my favorite rhetorical and analytical moves is joining things together (showing that two different, seemingly unrelated ideas are aspects of the same phenomenon) and taking them apart (resolving a paradox by demonstrating that what appears to be one, contradictory thing is actually two different things that have been lumped together).

"Taking things apart" is a very useful framework for understanding AI. How do we resolve the (seeming) paradox that some skilled workers report wonderful results from their work with AI, while others are full of dire warnings about the lurking defects in their AI-assisted outputs? Simple: the first group are "centaurs" (humans who are assisted by machines) and the second are "reverse centaurs" (humans who have been pressed into service as peripherals for machines):

https://pluralistic.net/2025/12/05/pop-that-bubble/#u-washington

What are we to make of the people who've been fired by bosses who replaced them with AI, in light of the fact that AI is demonstrably not able to do their (former) jobs? Again, it's simple if you separate out two distinct phenomena: "AI can do your job" is the first. The second is: "Your boss is a credulous dolt who is infinitely horny for replacing lippy workers with pliable machines, which made him an easy mark for an AI salesman who convinced him to fire you and replace you with an AI that can't do your job":

https://pluralistic.net/2025/03/18/asbestos-in-the-walls/#government-by-spicy-autocomplete

This is also a useful move for understanding the AI investment bubble. It's not just billionaires who don't think other people are as real as they are and consequently their jobs can be done by chatbots. It's also billionaires who believe that bosses can be sold AI and don't care if the AI is defective, because that's your boss's problem after he buys the AI and fires you. They don't have to believe in AI in order to think it's a good investment: like an investor betting that Joe Rogan can sell millions of dollars' worth of peptides to desperate young men, they are assessing the sales potential, not the merits of the thing for sale:

https://pluralistic.net/2026/08/03/andor/#either

As useful as "taking things apart" is, "putting things together" is also a very important technique for assessing, critiquing and improving AI. In a stellar essay entitled "Temperature Zero for Culture: Why Everything Is Starting to Look the Same" by the data scientist Lauren Leek, we get a top-notch example of "putting things together":

https://laurenleek.substack.com/p/temperature-zero-for-culture-why

Leek's essay is one of those fabulous, wide-ranging, cross-disciplinary pieces, touching on urban design, music trends, synthetic LLM crowds, Netflix recommendation algorithms, and several other subjects, all seeking to resolve a(nother) (seeming) paradox: how is it that we have so much potential variety, but everything is so manifestly the same?

The answer is complicated and nuanced, but Leek's foundational point is that in a data-driven society, "predictions" are self-fulfilling prophecies. As Leek puts it: "Once prediction shapes the choices in front of us, we lose the ability to tell the difference between what people wanted and what the system made easy to want."

This is a pervasive issue across many domains. Leek says that economists call it "performativity," while machine learning researchers call it "model collapse" and urbanists call it "placelessness."

"Performativity" describes how, once a market has been modeled by economists, that model becomes the foundation for economic policy, which pushes the market to conform to the model:

https://press.princeton.edu/books/paperback/9780691138497/do-economists-make-markets

"Model collapse" describes how machine learning models that are trained on their own predictions become incredibly bland, with all variety disappearing from the system's predictions:

https://pluralistic.net/2024/03/14/inhuman-centipede/#enshittibottification

This is hugely consequential: it's why bias proliferates through predictive policing algorithms: train a model with data from racist stop-and-frisks and it will predict that all the weapons and drugs in a city are to be found in Black and brown peoples' pockets. Turn those predictions into recommendations telling cops where to go look for weapons and drugs and they will double down on racist stops, producing even more biased training data, which turns into still more bias in the predictions:

https://hrdag.org/2016/10/10/predictive-policing-reinforces-police-bias/

"Placelessness" is the urbanist's name for "when everywhere optimises toward the same template." I think of it as Flinstones Syndrome, where the same background is looped behind Fred and Barney as they drive through Bedrock. In New York City, it's Citibank-bodega-Chipotle-Walgreens; in the Chicago suburbs, it's the strip malls with a Chili's, a gas station, and a big box store.

Leek proposes that these are all expressions of the same underlying phenomenon, a failure mode of data science that takes a world of "granular personal data" and arrives at a world where "personalisation produc[es] more sameness."

To these excellent examples, I'd add another one, from the world of monetary policy: Goodhart's Law, which holds that "When a measure becomes a target, it ceases to be a good measure":

https://en.wikipedia.org/wiki/Goodhart%27s_law

Goodhart's Law captures a wide variety of phenomena. When Google first deployed Pagerank, they showed that by counting the inbound links to all the pages on the web, you could extract a signal about which pages were most important (because there was no reason to link to a page unless you found it noteworthy).

But once Pagerank became the dominant means by which web users found pages, counting links stopped being useful: first, because people used Pagerank to find the best pages and link to them, making it impossible for new pages to get the inbound links needed to supersede incumbent pages; and second, because it's easy for fraudsters to create inbound links for low-quality pages in bulk, once there's a reason to do so.

Counting inbound links was a world-beating retrospective way of predicting which page would best match a searcher's query, but once it shaped the world it sought to analyze, it ceased to be a good prospective way to predict which page would best match your queries.

Leek is a brilliant data scientist and an even better science communicator, with a knack for crisp, readily understood explanations. How can a world of granular, highly varied data turn into a world of homogeneous choices? Simple: start with a set of items ("cuisines, genres, shop types") and a standard algorithm for sorting them. Let users choose from those recommendations. The mode (average) of those choices "gets shown more, so it gets picked more, so the model grows more confident the mode is what people want, and the tails starve." Run this for a few rounds and the evenly distributed catalog of choices "collapses onto one dominant option."

This is intrinsic in the choices we make in designing recommendation algorithms, tilting them towards the likelihood of a successful recommendation. A recommender that wants to succeed every time will make the safest possible recommendations, "so an algorithm that is uncertain about you, and it is always at least a little uncertain, hedges toward the average."

Then she busts out a beautiful, perfect little statistics aphorism: "Personalisation under a standard loss function is regression to the collective mean with extra steps." That is to say, "regression to the mean" (the tendency of varied things to become more standardized) cannot be avoided with the standard personalization algorithm. That algorithm is going to play it safe, showing you things that are broadly palatable, and because your choices are constrained to the average, you will choose average things.

This is how recommendation systems – and other analytical tools that produce predictions that are then turned into action – force so many diverse phenomena (streets, markets, media recommendations) into sameness. The fact that these recommenders are self-fulfilling prophecies means that "they don't have to be right," only "listened to."

This explains the sameness of so many of London's high streets. Leek examines 640 shopping streets, characterizing 18,000 food places spread out across them, flagging all the chain restaurants. Her analysis shows that any two London streets will, on average, share about half of their "food profile."

Obviously, this is most pronounced on streets with chain outlets, and it doesn't take that many chain outlets before a street's sameness shoots up: "A relatively small number of repeated names is enough to make otherwise different streets resemble one another more." So why do streets with chains resemble one another so much? Because the chains use an algorithm (weighting footfall, proximity to train stations, demographics, and competitors) to decide where to put their restaurants. If a street with a Gail's Bakery on it feels like every other street with a Gail's Bakery, that's because Gail's only puts its restaurants in places that have highly similar characteristics, measured to a high degree of accuracy and controlled by a narrow set of tolerances.

In other words, every street that feels like it should have a Gail's will eventually get a Gail's, whereupon that street will feel even more like all the other streets that have a Gail's, because it will share one more common factor with those other streets (a Gail's).

Leek points here to her earlier work on pub closures in the UK. The UK has experienced an epidemic of pub closures, with thousands of pubs disappearing since 2016:

https://laurenleek.substack.com/p/britain-lost-14000-third-places-they

Her research found that the biggest predictor of a pub surviving was its similarity to the median pub; which is to say that the more distinctive a pub was, the more "character" it had, the more likely it was to close. Pubs that are different from the average pub are harder to categorize, which means they're harder for a bank manager to assess for creditworthiness or for a landlord to justify extending a long-term lease to. The algorithms used to allocate capital and real estate are also recommenders, and they also drive variety out of the system.

This same phenomenon acts on culture. In an age of music recommendation algorithms, hit songs are changing; today's songs use a smaller vocabulary of unique words and repeat those words more often:

Vocabulary richness, distinct words relative to length, has fallen by more than a quarter since the early 1960s, while the share of repeated lines has climbed by nearly a third. The modern hit says less and says it more often, because the hook that works gets repeated.

But that's not the whole story! While each song resembles itself more ("saying less more often"), within that constraint, there's far more variety today than before: a given song's (constrained) vocabulary has grown more distinct when compared to all the other songs' vocabularies. Songs repeat the words they use, but the words repeated in songs are getting more different.

For Leek, this is the key to understanding the whole phenomenon and (more importantly) doing something about it. Music recommendation systems optimized for a singable hook, but did not optimize on any of the other variables in songs, so those dimensions acquired a broader range, even as the optmized variable got flatter and narrower.

This means that the tendency of recommenders to "flatten the world" isn't a single blunt outcome: it depends on which dimension we choose to flatten through recommendation, and who chooses to flatten that dimension.

A media recommender optimizes for consumption, showing you a tractable set of things it believes you'll watch, read or listen to. When you choose from among this limited set, the recommender takes note of that fact and shows you more of the same, pushing everything to a greige median. All the movies, books and songs you might have liked that were omitted from that initial set are excluded from being recommended in the future. The features of that media that you might have appreciated "decay out of consideration." They are never tested for desirability. The model collapses.

How badly does it collapse? Leek cites Movietweetings' data on which movies people watch: out of a million public movie ratings, half relate to the top 2% of movies in the set. There's 38,000 films in the set, but just 380 titles account for 40% of the ratings. Leek argues (persuasively) that this isn't because recommenders are good at "knowing your taste" – rather, they are good at "narrowing the menu."

Leek relates this to her work on creating LLM "personas" – synthetic populations meant to mimic the tastes and proclivities of real groups of people, that you can interrogate "before you spend money asking actual humans." While this would be useful for many applications, "it fails in exactly the way this whole essay is about."

Leek went to enormous lengths to reproduce the traits that make people interesting to study in aggregate, painstakingly replicating the ways that social connections, psychological outlook and demographic factors predict people's beliefs. The result was a set of LLM personas with "elaborate stories" about how they differed from one another, but whose survey responses about planned actions were homogeneous in a way that real populations are not.

This, Leek writes, is the same force that homogenizes other data-driven predictors. Because she'd ordered her LLM to reproduce the statistically validated relationships between different factors that predict a person's beliefs, each synthetic persona was a homogenized average. It's like the paradox of "The Average Man," where military uniforms sized to the average of all service personnel fit no one, because no one is average:

https://archive.org/details/DTIC_AD0010203

The thing is (as Leek points out) the idea that synthetic personas are a good way to understand the preferences of a real population is not a harmless delusion: it's a product that's being actively sold to governments, campaigning politicians and marketers. It's a self-fulfilling prophecy that drives governance, political campaigns and product design to the same homogeneous median that is making every shopping street in London feel the same.

This matters. As Leek writes, ecologists have long understood the importance of variety for systemic resilience: they call it "the insurance value of biodiversity." A diverse system has reservoirs of species and variation that may not be optimized for how things stand now, but that can move into niches created when things change in ways that lay waste to the previously dominant organisms. As anyone whose favorite banana went extinct can tell you, homogeneity works well, but diversity fails well:

https://en.wikipedia.org/wiki/Gros_Michel

The brittleness of algorithm-induced homogeneity is compounded by the fact that recommenders obscure the true preferences of people. If you watch two Scandinavian crime dramas after Netflix recommends them to you, it will keep showing you more Scandy crime for the next decade – even if there's another kind of programming that you'd vastly prefer (if only you knew about it). This means that decision-makers who choose which shows will get made in the future will keep on funding their safe Danish detectives, to the exclusion of whatever might emerge from the same weird attractor that produced the K-Pop Demon Hunter fortune.

Transpose this failure mode onto states, bank managers and landlords, and we see whole ranges of policies, businesses and activities that never come into existence, despite the popularity, prosperity and joy they might bring us.

But Leek doesn't end with this worrisome note. Instead, she identifies this whole thing – model collapse, placelessness, performativity, even Goodhart's Law – as an expression of one of the best-understood tradeoffs in computer science: "exploration vs exploitation":

Any system learning from feedback has to divide its effort between exploiting what already scores well and exploring options it hasn’t tried, in case they’re better.

Computer scientists have long understood that focusing on exploitation to the exclusion of exploration is a trap that locks you into "the first decent option" so you can never discover the best one.

Which means that this algorithmic homogeneity has a well-understood corrective: "forcing exploration back in." The problem is that markets hate this kind of exploration. A company that lives and dies by how many clicks it gets is never going to sacrifice 20% of its traffic by showing its users weird, untested options that score worse than the median because these weird things have never had a chance to prove that they are desirable.

This is a classic market failure, and, as Leek points out, there are regulatory responses in the UK (the Digital Markets, Competition and Consumers Act) and the EU (the Digital Services Act), both of which require the largest platforms to open up their recommendation systems, but so far, regulators have focused on "online harms" rather than variety (though the DSA does require platforms to offer algorithmic recommendations that are not based on your personal traits).

Leek identifies this willingness of states to set conditions for algorithm design as a means by which "exploration" can be forced back into the system. She's also bullish on interoperability, so that users can leave platforms with bad recommenders, without losing access to their media or social circles. As she writes, "the deepest discipline on a feed that has trapped you is the credible ability to leave it and take your data with you." I couldn't agree more:

https://pluralistic.net/2023/01/08/watch-the-surpluses/

She's less hopeful about individual responses. Demanding that you be an "adventurous consumer" is a way of letting systems off the hook. When every street has the same restaurants and every bookshop has the same books and the people in your life are all locked into one of two social media platforms, "choosing wisely" only gets you so far. Shopping isn't politics!

https://pluralistic.net/2026/05/21/purity-culture/#stop-fucking-that-chicken

Leek is a superb writer. After reading this piece yesterday, I sent it to half a dozen people and then read everything else in Leek's newsletter archives. Not only is it all brilliant, but I also realized that she'd written one of the most memorable articles about cities and platforms I've read in the last year, "How Google Maps quietly allocates survival across London’s restaurants – and how I built a dashboard to see through it":

https://laurenleek.substack.com/p/how-google-maps-quietly-allocates

I should have added Leek's newsletter to my RSS reader when I read that last December. I've rectified that oversight! What a fantastic thinker, scientist and communicator! If she isn't being relentlessly pestered by editors and literary agents offering her a book deal, then it really does prove that the recommender systems are elevating the bland median over the thoroughly, delightfully spiky outliers.

Hey look at this (permalink)


A shelf of leatherbound history books with a gilt-stamped series title, 'The World's Famous Events.'

Object permanence (permalink)

#25yrsago Awful, stupid Wired report on Dutch hacker camp https://web.archive.org/web/20011007084604/https://www.wired.com/news/culture/0,1284,46033,00.html

#25yrsaog Excellent NYT story about the internal contradictions of the DMCA https://memex.craphound.com/2001/08/13/excellent-nyt-story-about-the/

#20yrsago Our faulty intuition about open systems https://www.ft.com/content/64167124-263d-11db-afa1-0000779e2340

#20yrsago Defending against the last plot won’t save us from the next one https://www.schneier.com/blog/archives/2006/08/terrorism_secur.html

#20yrsago NBC: Hair-gel terrorists posed no risk last week https://web.archive.org/web/20060813194630/http://www.msnbc.msn.com/id/14320452/

#15yrsago AT&T merger leak: it’s all about raising prices and reducing competition https://web.archive.org/web/20110920222524/http://www.broadbandreports.com/shownews/Leaked-ATT-Letter-Demolishes-Case-For-TMobile-Merger-115652

#10yrsago What’s inside a Tiki Bird? https://miehana.blogspot.com/2016/08/fancy-feathers-restoring-tiki-room-birds.html

#5yrsago End of the line for Reaganomics https://pluralistic.net/2021/08/13/post-bork-era/#manne-down

#5yrsago Smart cities are neither, 2021 edition https://pluralistic.net/2021/08/13/post-bork-era/#our-streets

#1yrago Maga's boss class think they are immune to American carnage https://pluralistic.net/2025/08/13/then-they-came-for-me/#boss-politics

Upcoming appearances (permalink)

A photo of me onstage, giving a speech, pounding the podium.


A screenshot of me at my desk, doing a livecast.

Recent appearances (permalink)


A grid of my books with Will Stahle covers..

Latest books (permalink)


A cardboard book box with the Macmillan logo.

Upcoming books (permalink)

  • "The Post-American Internet," a geopolitical sequel of sorts to Enshittification, Farrar, Straus and Giroux, 2027

  • "Unauthorized Bread": a middle-grades graphic novel adapted from my novella about refugees, toasters and DRM, FirstSecond, April 20, 2027

  • "Enshittification, Why Everything Suddenly Got Worse and What to Do About It" (the graphic novel), Firstsecond, 2027

  • "The Memex Method," Farrar, Straus, Giroux, 2027


Colophon (permalink)

Today's top sources:

Currently writing:

  • “Once Is Enemy Action,” a science fiction novel about the origins of modern technofascism. Today's words: 546 (4161 total).

  • "The Post-American Internet," a sequel to "Enshittification," about the better world the rest of us get to have now that Trump has torched America. Fourth draft completed. Submitted to editor.

  • A Little Brother short story about DIY insulin PLANNING

This work – excluding any serialized fiction – is licensed under a Creative Commons Attribution 4.0 license. That means you can use it any way you like, including commercially, provided that you attribute it to me, Cory Doctorow, and include a link to pluralistic.net.

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Reading Code Considered Helpful by Kira Howe
Tuesday August 25th, 2026 at 4:13 PM

Planet Clojure
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It&aposs difficult to find reasonable, pragmatic takes on using coding agents these days. Ray Myers is a good voice in that space right now and I thought this was a great survey of what people in the industry are actually saying about reading AI-generated code.

but those seem like weak-sauce countermeasures [my addition for clarity: (training employees to recognize LLM manipulation and deploying judge agents)] if you mean to help someone “fight back” against a “bombing”. They suggest pushing workarounds onto the user and adding more agents. Think for a second. What’s missing?

We could use fewer agents!

This always drives me crazy. More or less every week at work now people are complaining about some negative effect of AI, and the standard answer from leadership is universally and consistently "use more AI". Instead of trying to use more AI to solve our AI-generated problems, what if we just tried using less AI in the first place? Why is nobody asking that?

I understand why the LLM companies don&apost want us to use less AI. But so far I do not understand why executives who are paying through the nose for their ever-increasing LLM inference bills do not want us to use less AI.

Where are the women?

When we find ourselves citing exclusively men, something may have gone wrong.

I appreciate this take. Most industry conversations are male dominated. My take on this is that it&aposs mostly because being female in public really, really sucks, and speaking up in these conversations is almost never worth the inevitable harassment, bullying, and gatekeeping you&aposre in for. Men simply do not understand what it&aposs like to have their very reasonable technical opinions regularly met with "you should not exist in this industry". I know that&aposs not true, but hearing it too often is bad for my mental health, so I mostly stick to my read-only corner of the internet over here and do not engage in public conversations. I&aposve been bullied my whole life and learned a long time ago that the best way to deal with bullies is to just remove their access to you. You can&apost get bullied if the bullies can&apost contact you.

Frowning on those who live in the present is a luxury that evaporates with proximity to the pager.

This is the first time I&aposve seen this "proximity to the pager" phrase, but I love it. I think it cuts to the core of what is so divisive in the industry right now. In my experience, the people who are most enthusiastic about "AI" and agentic coding and all of that stuff are the ones who are nowhere to be found when prod goes down. Conversely, everyone I know who has ever had to work after hours to fix a downed system that people are paying for is much more realistic and honest about the current capabilities of coding agents.

They then hand those constraints down to our department to do their homework for them work out the details.

It does feel strange that OpenAI and Anthropic constantly claim they are building a Superintelligence capable of doing real work, yet most of the industry is now spending most of its time doing the real engineering work of making the LLMs they produce do anything actually useful. Un-guided and unrestrained, LLMs do far more harm than good, but we&aposve all been effectively mandated to use them day in and day out, so now we spend most of our time just learning how to build better harnesses, guardrails, and systems to try to cajole them into doing meaningful work.

Rigorous automated testing is much more feasible than is generally realized. This is largely a failure to budget for coaching and training.

This is definitely true in my experience. At the risk of sounding like a gatekeeping asshole, I do believe that people who write poorly tested code (or did before AI could do it all for them), both fundamentally misunderstand how to write good test-driven software and dramatically underestimate the cost of all the manual verification steps they do instead. All the engineers I know who write bad or inadequate tests spend ridiculous amounts of time manually QAing their own software. There are some true agents of chaos out there who just yolo code into production, but I would say most software engineers, even very mid ones, do want to confidently answer the question "does this code work" before they ship it. I think the people who don&apost believe that automated testing is the fastest way to do that just don&apost really know how to do it well and at this point are too embarrassed or set in their ways to admit they need to upskill.

They emphasize speed of code gen as a proxy for value.

This is a really deeply embedded misunderstanding in the industry. The velocity at which your software is produced doesn&apost tell you anything at all about the value it delivers to users. But because it is easy to measure many teams have massively over-indexed on it and mistake velocity for productivity, which is unfortunate because it&aposs really easy to juice your own velocity metrics while actually causing damage to project outcomes. But that doesn&apost matter when nobody is measuring outcomes and only velocity is rewarded.

link / raymyers.org (via) / #ai #coding-agents #quality #reflections #society #software-engineering #tech-industry #testing

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Tea as a Cure For Brainrot by absurdpirate (hidden)
Tuesday August 25th, 2026 at 4:07 PM

Absurd Pirate's Internet Blog
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I've recently become something of a tea junkie. I've always liked tea, but rarely did I ever go farther than a simple tea bag, which is basically the instant coffee of the tea world. If you asked me if I preferred coffee or tea, I'd usually say coffee. My primary tea drinks were either matcha lattes, or Americanized Masala chai.

After watching Avatar: The Last Airbender with my wife and really loving Uncle Iroh, I decided to look a bit more into tea. I decided to make actual matcha, the non-latte way. I think something in my brain changed and so too did my relationship with tea.

I have since began to learn about Chinese Gongfu tea. I purchased a small starter kit that came with a gaiwan, a gong dao bei, some tea cups, a tray, and a small dragon tea pet I've named after the Dragon of the West. Nothing too fancy, something nice enough to not hate the process, but cheap enough to where if I don't like it or something breaks due to my inexperience, it's no big deal. I also purchased some tea from Harney & Sons, specifically their dragon pearl jasmine. Obviously starting with jasmine because of Iroh.

I've realized there's beauty in the simple experience of tea making. Something relaxing about sitting their, brewing tea, and enjoying the taste and aroma. Going through the ritual of gongfu tea making, and the social nature of it. Jasmine tea specifically has a very nice, floral aroma. Very light on the palette, no bitterness at all when brewed right (which was about 10-20 seconds at 175degrees Fahrenheit for my gaiwan). Gongfu tea brewing is one that commands full attention, and is very difficult to multitask with lest you break your gaiwan or burn your fingers.

I tried making some of the bag teas, the sweeter fruit-infused teas that my wife likes. It kinda sucks if I'm being honest. It's incredibly bitter by comparison, I just thought that's what tea tasted like, but no. I've learned that loose leaf tea is really where it's at.

So how does this more meticulous style of tea making (not exclusive to gongfu mind you) act as a possible cure for brain rot? I'm glad you asked... or didn't.

When we talk about brainrot, it's usually due to an excess of low-quality stimulation. With tea brewing, or really any form of drink making that requires a sort of methodical ritual to it (pour over coffee also comes to mind), it's on the complete opposite end of the spectrum. When you're dealing with onset brainrot, it's due to rapid-fire, high-intense, visual stimuli.

A lot of us, myself included, find it really hard to not be able to do something without some background stimulation. Be it music while cleaning the house, a podcast while doing homework, a youtube video while eating. It's important to be able to sit with yourself. A mind that can't be alone in the quite is a mind that misses subtle beauties.

Hobbies/interests that force you to really slow down override that tendency for your brain to pull a Sonic. "Gotta go fast" and all that. Vinyl, espresso coffee making, gongfu tea, all of these require you to take a moment and slow the fuck down. It also gives that instant gratification reward when the ritual is over. After you've brushed your record and carefully set the needle, you're rewarded with your favorite music. After you've gone through the ritual of brewing espresso, you're rewarded with a delicious cup of coffee. You get the point.

One of the main coping mechanisms I was taught to deal with my ADHD is mindfulness. Often this comes in the form of meditation, or just simply slowing down and really thinking through your steps so you don't blink and wonder how you got from the inside of your house to your car (that can't just be me right?).

Gongfu tea brewing isn't a fast process really. Not nearly as fast and simple as just pouring hot water over a tea bag. It's just as much a science as it is an art. I won't drone on with the details of what goes into gongfu tea, so if you want to look it up there's plenty of videos on Youtube (the one by Jesse's Teahouse is what got me started).

Anyway that's my yap session for today. I encourage you to find a hobby that exercises mindfulness. Can be anything really, from tea, to music, to meditation. Do it with care and do it in peace. Your spirit will thank you for it.

tea

|

Reply via email: me@absurdpirate.com

as of writing this...

I've been kinda away from blogging for a bit. My mom was diagnosed with stage 3 carcinoma and have been taking time to process all that. It's serious, obviously, but the odds are very much in her favor. Wishing her all the best and offering support where I can. I started a new beta 1.7.3 minecraft world that I want to treat as a sort of long-term evolving project. Starting with 1.7.3 and then slowly upgrading over time to newer versions, capping off at silver age (probably release 1.8).

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Writing with AI is Stupid by Ashton Wiersdorf
Saturday August 8th, 2026 at 1:45 AM

Lambda Land
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Regardless of how you feel about generative AI—love it or hate it—the worst thing you can do with it is use it to write for you.

Imagine, for the sake of argument, that there was an LLM entirely free from any ethical, ecological, or economic baggage: it had been trained on public domain text using fusion energy and could run inference on Raspberry Pi-tier hardware. Everyone in the world had access to it, it never hallucinated, and was fully aligned with doing good for humanity. This would be very exciting and useful—I’ve found LLMs to be amazing for translation and accessibility and having a cheap, ubiquitous, and reliable tool to aid those goals would be phenomenal.

It would still be a bad idea to use it to write for you. Why?

Writing is thinking

I am not the first person to suggest that writing is a critical mode of thinking. Rose Horowitch writes in The Atlantic:

Writing is hard. Orwell likened the experience to a “long bout of some painful illness.” AI promises a simple remedy. The trouble is that writing is not merely the act of transcribing fully formed thoughts—if it were, it wouldn’t be hard. Writing is the way people figure out what they think, and how to convey those thoughts to someone who doesn’t already share them. Cal Newport, a computer-science professor at Georgetown University, argues that the process of writing forces people to think in an orderly, linear fashion. It exposes flabby thoughts and shoddy reasoning. And the time and focus it takes to form thoughts into words, sentences, and paragraphs allow the author to make new connections and discover new insights.

This feels true to me. My job is to write. …The writing process is how I refine and formalize inchoate ideas and gain new understanding. By evaluating my arguments and discarding those that aren’t convincing, I find the ones that are. Writing is hard because the writer is learning. If AI eliminates the challenge, it also eliminates the learning.

— Horowitch, The End of Reading is Here

I agree entirely with that passage. When I have a hard problem at work, the best thing for me to do is to describe the problem in writing and then to “narrate” my thought process on the page a little. This helps me to know what I think about something.

Writing is hard. I’m struggling to write this blog post right now. I keep revising and revising in my head and in my editor—and that takes work. But at the end of this I’m going to be better able to articulate exactly why I think using AI to write something for you is stupid, and I’m going to have a much clearer understanding of it myself. I could have, of course, dropped a prompt into $LLM_OF_THE_WEEK and gotten a polished essay. I could have read it carefully, nodded my head in agreement—but my mind wouldn’t be the same.

AI is like a forklift: it can be steered by a single individual and accomplish tasks that would have hitherto taken a team. That’s great. But we don’t take our forklifts over to the benchpress at the gym and start busting out reps. The gym is for us to improve, and that takes personal struggle. Writing changes our brains and that is half the point. (The other half being able to communicate your idea to someone else, of course. This is optional in many circumstances!)

Writing fluff

I get that there’s a certain amount of writing that people do in the course of their work that’s just busywork: maybe your boss wants daily status updates on a project or something a rather. I still think it’s better to write by hand. Maybe it’ll be quick and sloppy—that’s fine, an LLM is better employed in cleaning up prose, but not composing it in the first place. If a human is going to read something, I don’t think there’s any excuse to have a bot do the writing.

Last year I had an experience with “work slop”, though that term hadn’t been invented yet, I think. It was awful. It was degrading and disrespectful. Foisting slop onto someone else is terrible.

Programming can be writing sometimes

With that in mind, I feel like programming can function like writing prose sometimes. If I’m sussing out a new problem domain, programming by hand helps me get intimately acquainted with the terrain. A lot of code written in the corporate world—at least in my experience—has been pretty uncreative and frequently tear-inducing boring. Most code exists to expose business patterns and protocols to automation, and there is a lot of overlap between companies in what kinds of things need to be automated. LLMs excel and writing this kind of stuff.

But there’s still that piece here and there where the domain isn’t well-known to the people maintaining the software. These are the places where working something out by hand can be more beneficial than running blindly ahead with an LLM because of the understanding that you build up in your own mind. You might even encounter new information that changes how you see and approach the problem entirely. I’ve seen this happen in my work, and I sure I’m not the only one to experience this.

Minds and machines

I’ve been impressed with some of the coding that an LLM-backed agent can do. I will still write code by hand when I need deep contact with the problem domain because it helps me think.

I think writing with an LLM is completely stupid. Writing is thinking. If something isn’t worth thinking about enough to write manually, it probably isn’t worth writing at all.

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joka__
79 days ago
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