Months of trying to make a machine write something Tolstoy-tier. Here’s where it works, where it falls apart, and what surprised me.
Okay, so. For the past few months I’ve been doing something kind of ridiculous. I’ve been trying to use AI to write fiction. Not a parody, not a clone. Real literature. The kind of book that gets read in two hundred years, and could stand its own against the likes of Dostoevsky, Shakespeare, Tolstoy, Faulkner, Hemingway, and so on.
I know how that sounds. I’m not under the illusion that I cracked it. But the experiment was never really about producing the masterpiece on attempt one. It was about figuring out where exactly this stuff breaks. Where’s the seam? At what point does it stop being writing and start being a very smooth impression of writing?
This is just me sharing notes from the trenches. No hot takes, no manifestos. Just stuff I’ve actually noticed, in the order I noticed it. If you’re playing with this too, I’d love to hear what you’re seeing.
AI is a mirror, not a muse
This is the biggest thing, and honestly the thing I tell every writer friend who asks. AI doesn’t write your story. It writes your story back at you, in your voice, but only if you give it enough of your voice to work with.
First time I sat down with Claude Opus 4.7 and just asked it cold to write me an opening, the result was fine. Like, technically fine. Clean prose. It moved. It also belonged to nobody. It was the literary equivalent of stock photography. Looked good, said nothing, could’ve been written for anyone.
Then I tried something different. I wrote the first three to four pages myself first, and only then handed it over. Completely different result. Suddenly the model was picking up my rhythm, my weird pacing habits, the way I lean on certain kinds of clauses. It started feeling less like a co-author and more like a really attentive friend who’d been reading my drafts for years and was trying to keep me sounding like me while I stepped away.
Which reframes the whole thing for me. AI isn’t generating original literature. It’s amplifying voice you already have. If you don’t have a voice yet, it can’t help you find one. It’ll just give you back the average of every voice it has ever read, which is exactly what generic AI prose feels like.
So if you’re trying to write fiction with AI, my advice is dead simple: write the opening yourself. Write enough that the model has something real to grip onto. Then iterate. And expect to push back. A lot. Five, six rounds on tone, on a phrase that feels off, on a beat that came out wrong. The voice doesn’t survive on autopilot. You’re constantly correcting drift.
Where it absolutely shines: structural editing
If voice is where the model has gotten weirdly good, structure is where it’s just flat-out useful. Right now. Today. This is the unglamorous strength nobody writes essays about, but it’s probably the most valuable thing this tech does for a working writer.
Hand the model a messy draft. Tangled plot, two arcs that contradict each other, a subplot that goes nowhere, a scene you kept only because the dialogue was funny. It will find all of it in one read. It’ll tell you which threads are doing real work and which are decorative. It’ll suggest cuts that hurt to make and are basically always right. It catches the inconsistencies you’ve stopped seeing because you’ve read your own thing thirty times.
It’s not creative work in the romantic sense. It’s editorial work. But editorial work is what turns a draft into a book, and most of us don’t have access to a sharp, patient editor who’ll read the whole thing in one go and tell us the truth. The model is that editor. Three a.m., never tired, never offended.
One trap though. Don’t confuse “structurally cleaner” with “actually better.” The model can give you a more polished, more coherent version of your draft. That’s not always a better one. Some of the greatest novels in the canon are messy on purpose. Make sure you’re accepting cuts because they serve the story, not because the manuscript looks tidier afterward. Coherence isn’t the same as art.
Where it still struggles: actual human emotion
Now the harder part. The part I’m least optimistic about in the short term.
AI doesn’t really get human emotion the way a great novelist does. The newer models are surprisingly good at the surface of feeling. They can write grief, jealousy, longing, shame. The prose looks right. What they struggle with, and what every revision pass exposes, is the gravitational pull between two people.
Here’s the failure mode I keep hitting. The model writes two characters who are supposed to love each other, or be quietly destroying each other, and the words on the page are technically correct, but something is off. The dialogue is plausible. The interiority is plausible. The relationship isn’t. It feels like two people performing a relationship instead of being inside one. You can read it and tell.
When I push back, it usually improves on the second or third pass, but the improvement has a particular flavor. It starts borrowing moves from existing literature. The held silence, the betraying gesture, the line of dialogue that says one thing and means three. Sophisticated recombination of techniques rather than a fresh act of feeling. Sometimes that’s enough. A lot of the time, the seam shows if you’re paying attention.
The deeper version of this problem: AI is bad at subtext. It’s bad at what’s left unsaid. Half of what makes Tolstoy or Chekhov great lives in the gap between what a character says and what they mean. The silences. The misread look. The line that ends one beat too early. Models trained to be helpful and complete are basically biased against withholding. You have to fight them constantly to let a scene stay ambiguous, let a character stay unknowable, let a conversation just end without resolving.
Same problem shows up with endings. The model wants to close loops. It wants to land beats. It wants every chapter to feel earned. But great literature regularly refuses to do that. The Brothers Karamazov doesn’t really tie itself off. Hamlet leaves you with a corpse and a bunch of unresolved interior. Left alone, AI ties the bow every single time. You have to keep telling it not to.
The architecture problem
Here’s a failure that only shows up in long work, and it took me a while to catch.
The model can write a beautiful chapter. It can write a beautiful run of chapters. What it can’t reliably do, even with a ton of context, is the kind of architectural patience that defines a great novel. By that I mean the way Dostoevsky plants a tiny detail in chapter two that detonates in chapter forty. The way Tolstoy lets one image come back, transformed, three hundred pages later. The way you finish a novel and realize the whole thing was secretly about something the first chapter only hinted at.
That kind of long-range intentionality requires holding the entire book in your head as one object. The model holds context, sometimes a lot of it, but it doesn’t seem to hold the work as an object the way a writer does. It writes locally. It nails the next great paragraph. It doesn’t seem to know which paragraph is doing load-bearing work for a payoff three hundred pages out.
Until that changes, the architectural soul of a long novel has to come from a person. The model can help you execute. It can’t yet hold the whole thing.
Voice vs. worldview (these are not the same thing)
Quick distinction worth making, because people collapse these and they shouldn’t.
Voice, at the sentence level, is the texture. Diction, syntax, rhythm, the small recurring habits. Models pick this up fast. Three to five pages and Claude is producing sentences that sound like mine.
Worldview is something else. Worldview is the moral and philosophical lens that holds a body of work together. Tolstoy isn’t great because of his syntax. He’s great because of his lifelong obsession with moral awakening, with how to live, with the specific weight he gives to dying men and peasants and aristocrats. That worldview is inseparable from his actual life. His crises. His late-life religious turn.
Models don’t have a worldview. They have a statistical absorption of every worldview they’ve ever read. Ask one to write inside a worldview and it performs one. Sometimes the performance is excellent. It’s rarely the kind of unified moral vision that animates a real book from inside, because that vision tends to come from somebody who actually lived a life and arrived at convictions about it.
This isn’t obviously a problem you fix with bigger models or more data. It might be a different kind of limitation.
The “necessity” problem
There’s a thing critics call necessity. The feeling that a sentence had to exist exactly this way. That if you swapped it out, something would be lost.
AI prose, even the good stuff, mostly doesn’t have it. It’s well-formed. It’s appropriate. It moves the plot. But you can usually picture ten other versions of the same paragraph that would do basically the same job. The sentence doesn’t feel inevitable. It feels picked from a menu.
Great writers do something else. They write sentences that, once you’ve read them, you can’t unread. There’s almost a fingerprint at the level of word choice. AI tends to produce sentences that feel like a consensus of fingerprints. That gap, between inevitable and merely appropriate, is now the main thing I look for when I’m editing model output. I cut everything appropriate. I keep only what feels like it had to be there.
It always sounds like 2026
One more thing on style. AI defaults to contemporary literary fiction voice. Even when you ask it for nineteenth-century cadence or Elizabethan diction, the gravity pulls back toward something polished and present-day. You can win individual battles. You can feel it resisting the whole time. On its own, it doesn’t write like Melville or Faulkner or Woolf. It writes like a thoughtful contemporary writer doing an impression of them.
This matters more than it sounds. Part of why the canon is the canon is that those books are stylistically irreducible to any other era. They couldn’t have been written at any other time, by any other person. AI tends to produce work that feels like right now, which is a strange thing to say about a model trained on centuries of literature, but that’s what I see.
The friction question (this is the one that keeps me up)
Last thing, and the one I genuinely don’t have an answer for.
A lot of what we call great literature was made under absurd amounts of friction. Dostoevsky wrote in debt, in mourning, sometimes mid-seizure, sometimes for his life. Tolstoy revised War and Peace by hand for years. Shakespeare worked under commercial pressure inside an industry. The friction wasn’t incidental to the work. It shaped it.
AI removes friction. That’s the whole point. Blank page is less scary. Fifth draft arrives faster. Structural problems get diagnosed in minutes instead of months.
So here’s the question I keep circling: can art survive the removal of friction? Maybe friction was always romantic mythology and the work is what matters, full stop. Maybe shorter feedback loops just mean better art, faster, because we get more iterations per lifetime. That’s a totally defensible read.
But maybe not. Maybe some of what makes great literature great is the trace of a person who paid for every paragraph in years of their life. Maybe readers can feel that cost without being able to name it. Maybe a frictionless work, however polished, lacks the specific gravity that comes from being wrung out of someone.
I don’t know which is right. I suspect both are partly right. What I know is the question isn’t going away, and anyone using these tools seriously is going to have to come up with their own answer.
Where this leaves us
After all of it, here’s where I’ve landed for now.
AI cannot, today, write a novel that belongs next to Tolstoy. Voice is shallow without a writer behind it. Emotional connection between characters is performed, not felt. Subtext gets suppressed by training that wants clarity. Long-range architecture is beyond the model’s grip. Necessity is missing. Worldview is borrowed. The era keeps leaking through.
AI can, today, make a serious writer faster, sharper, less stuck, and more structurally rigorous than they would otherwise be. That’s not nothing. That’s actually a huge deal. It just turns out to be a different deal than producing literature that lasts.
My current bet: the great novels of the next twenty years will still be written by people. People who use AI heavily, in ways earlier writers didn’t have access to, but the central acts, the voice, the worldview, the emotional truth, the architectural intention, will stay stubbornly human. If that ever stops being true, that’s going to be one of the more interesting boundaries this technology crosses. I’m watching for it. I’ll keep poking at it.
Experiment continues. If you’re doing this too, message me. Genuinely curious what you’re seeing.
Leave a Reply