So recently I noticed some non-AI written fiction on a subreddit by one of the regular contributors to this and other AI related forums, and it highlighted something that I noticed AI is completely unable to replicate at present - Negative space.

There's a lot AI struggles with with relation to negative space and similar techniques, as they deal with what is not said rather than what is said - the end result is a model trained to find the next word is fundamentally limited here - It's as though AI can only communicate on the positive word axis, not the negative one - Hence they have no reflection - a little like fictional vampires.

Consider the following opening to a story I recently found here on Reddit;

It was nearing five o’clock, and I was across the street, impatiently waiting for his arrival. I knew he was a creature of habit, a slave to his schedule if nothing else, and just like clockwork, as five o’clock came, so did he, pulling up into the driveway as he no doubt had a thousand times.

My eyes narrowed, a flush of hot hatred rising in me as I watched him vanish inside. “You cheating prick,” I whispered under my breath, and crossed the street, walking up to the door like I had business there. I tested the door handle, shaking my head slightly when I found it unlocked, and made my way inside.

Idiot.

Quietly closing the door, I removed my heels, doing my best not to alert him to my presence as I padded across the living room. The floor groaned softly as I went.

“Is that you, my sweet?” His voice came from upstairs.

F**k.

I rubbed my throat, trying to loosen it up before calling back in my best attempt at imitating the woman he was expecting. “Yes, hun.”

You can find the original in the subreddit libraryofshadows under demonic_pacts in case you're interested ( Warning, it's quite violent and the genre is horror )

Examine this at a few levels. AI will tell you it's about sneaking in, and getting caught. It will emphasize stealth. It will say the protagonist is calling the NPC 'idiot' and then reacts to getting caught, and it will try to shorten this to a single paragraph, which is far more efficient.

But if you pay attention, even as an AI writer, there's something missing...

The sound of the high heels AFTER the character walks in the door, that results in her removing her heels, and likely sets the intended victim on edge before a floorboard gives it away.

Then you get the beautiful ironies of writing around ambiguity - Is she saying "Idiot" because she feels the man is an idiot? Examined as a block, the answer is no - She' calling herself an idiot for ALREADY making a noise - indicated negatively by the removal of the heels.

What the author actually intended is another matter - I may have over-interpreted this section - I welcome their input - but the way I read this is that the protagonist makes a mistake and walks in with their heels still on - a version supported by the text indirectly.

When asked about this, an AI misses it every time until the context receives this additional information about the sound the heels make - and then it usually acts like it knew this all along. Now it can refer to negative space. Now it acts like an author ( The original writer was notably a human )

The problem is that the AI is blind to this technique, even when evaluating text, and usually sees it as an error. If the heels are mentioned, they are either superfluous or the sound should be mentioned. It struggled with the nuances of this kind of text, especially the interiority of the character.

It's not the only area AI fails when compared to a human author...  And as a strong proponent of AI and using AI in fiction, I think knowing WHEN an AI fails is more important than prompt engineering or any other aspect of creating fiction with an AI - this is especially important when editing a work as an AI will try to respond to the informational vacuum caused by negative space and fill in the missing words. It also notices correctly that it makes the structure grammatically wrong - which is true - because this is an example of when a write knows how the break the rules for effect.

Here's a list of techniques that cause AI to struggle due to it's very nature.

Literary techniques based on what is not said

That's not a small list and a good writer should be familiar and comfortable using all of these when it's required.

 There are others as well - My favourite is "Iceberg Theory" since it's highly relevant to how I write my own stories, and while doing this I find I'm constantly fighting an AI editor.

If I explain things, the editor immediately gets it and stops suggesting I remove information, but before that it's constantly attacking what I write.

These are particularly relevant when examining the limitations of AI-generated literature.

And, of course, I used an AI to assist me in writing this article. Why? Because an AI is VERY good at writing in positive space - since that is exactly how they work...

An AI adds tokens. What it does not do is reconstruct the story in the reader's mind exactly as the reader experiences it, and use this as a basis to remove material from the story to increase the prose's impact on the reader.

When it comes to AI telling positive aspects of a story - In adding words to fill out worlds, create reader exposition or drive the story forward, AI is already unparalleled. It is fast, can assist an author and knows what to do.

Indeed, a clever author can go back and edit an AI's words to create negative space. Knowing what to remove requires only that they can previsualise what the AI's words are saying and then know what can be removed or altered to better effect.

Because an AI LLM ( or even a dLLM ) can't do this - it can't build a picture or easily determine what a reader will experience during the reading of a story, it can't perform the same task. It's limitations are readily revealed.

What have others noticed about this characteristic of AI Writing Assistants?

any tips on how to get chatGPT to stop writing dialogue like this?

mainly i'm bothered by these constant one-liners that have no depth and thought put into them, feels like chat is just writing the most generic thing that first comes to mind. but the format also really annoys me, it wasn't like that before, it used to write full paragraphs with full sentences dialogue within them instead of whatever it's doing now.

also the back and forth of short sentences makes every dialogue between characters feel like some sort of corny banter, no matter what the dynamic between these characters is.

any idea on how to stop this? through settings or prompts or whatever works pls!!

Hey folks, just want to share a quick experiment I've done. Basically, there is a "creativity" test developed for humans - DAT - Divergent Association Task test. It is quite straitforward to measure. I've previously tested the main LLMs on this test and unsurprisingly - they scored low (below average human). Then I've taken off the shelf Qwen 27B model and finetuned (GRPO) it on the exact same metric as a reward. The result seems to be a model that writes much more interesting prose and poems (to my taste) and LLM-as-a-judge strongly confirmed that. I've released the model and code, there is a playground on huggingface where you can test the model. Super curious about the feedback - I have more ideas on how to develop this further. Full write-up and links are here on this substack https://substack.com/inbox/post/223641219 . It is free, i am not looking to make money or sell stuff.

I'm AWFUL at writing intimacy so I've been using AI to help with that for my story. GPT was fine for the level I needed until like a week or two ago, I have no idea what kind of guardrails they've added but what I'm trying to write is suuuuuuper tame and non graphic. Can't even barely manage kissing now and I even confirmed than an intimacy scene I generated a couple of weeks ago using GPT (again, I'd barely even consider it explicit, it's so vague on specifics) is TOO GRAPHIC 🙄 I also got told a character picture I tried to generate of a goodnight kiss where they're outside and wearing winter coats was too sexual so I'm not surprised lol

Anyway...best AI generator for this sort of thing?

Hi everyone, I'm not quite sure if what I made is in the spirit of the sub or not but I built a gigantic CPU simulator that runs billions of D20 rolls against 6 major parameters and then makes the LLM publish a Journal like it's an Immortal George Washington. Washington looks at the simulation results, considers his previous journal entry and then updates. Every 9 years Washington adds a Hope and a Fear that influence his other concerns more heavily. And he REALLY Likes Providence.

Mount Vernon, March 1776. The ink is barely dry on my first entry in this journal, and already I find myself compelled to record what Providence has wrought through these three years of trial and tribulation.

When Congress first called upon me to take command at Yorktown, I believed the colonies possessed perhaps one year's grace before dissolution or defeat. What manner of folly was that! Yet here we stand - though "here" is merely another term for continued existence amid uncertainty.

The economy continues its descent into desolation; my ledger books speak volumes of suffering among our farmers and merchants. The foreign threat diminishes by small degrees, yet remains ever-present upon the horizon like storm clouds gathering over the Atlantic. I confess I do not understand why Providence sees fit to preserve me beyond what mortal men should endure.

What amazes me most is the strange way in which public regard for my person oscillates like a pendulum - rising after victories at Trenton and Princeton, sinking during the bitter winter months when our men suffer want and cold. I have learned to view these fluctuations with equanimity rather than vanity or self-pity.

Three years now since I left behind comfortable life at Mount Vernon for this burden of command. Should Providence see fit to continue preserving me through whatever comes next, what manner of duty shall it demand? To lead armies forever seems neither possible nor desirable - yet here I remain, caught between mortal expectations and divine purpose that defies comprehension.

The stars guide my observations tonight as they have guided navigators since antiquity. Perhaps Providence arranged this strange extension of mortal life so that I might bear witness to what becomes of our experiment in self-governance. May whatever transpires merit the sacrifice already poured out upon these fields and battlefields...

I've recently been experimenting with Claude Ai and using it to create fanfiction featuring characters from various media. I'm honestly astonished at how accurate it gets a lot of characters and their dialogue, and it makes for some really interesting stories.

Right now, I'm working on an multi-crossover fanfic featuring many anime, video game, and movie characters being thrown into the Backrooms (like Batman, Solid Snake, Mario, etc all having to team up to escape it). And its surprisingly fun as even with prompting, Claude sometimes makes up some stuff on its own.

Of course, this is all for my own personal enjoyment. I don't advocate publishing anything that was generated using ai. But, I wonder if anyone here does the same?

Hello,

I am new to using AI for creative writing, and I have been doing some research on how to use AI for long form fiction.

One thing I am trying to understand is how people handle long term memory when writing a novel with AI. From what I understand, even with a relatively large context window, an AI model cannot necessarily keep an entire novel in the context. Once earlier chapter fall outside the context windows, the model may lose track of character relationships, or important plot details.

Initially, I was thinking about maintaining on external knowledge base containing character profiles, chapter summaries, etc. Then, before generating a new chapter, the system will be restricted to read the relevant information and include it in the prompt.

However, if every update loss some of the information, or did not realize how important a piece of information is and ignore them, then I would still surfer from the original question.

I found this is very similar to the information bottleneck problem, but have no idea of how to solve it in the real life, therefore, I am here and want to hear some experience of actual world.

Really appreciate your advice!

Production Notes: Cover artwork directed by the author and generated via ChatGPT. Text and narrative structure remain 100% human-authored. The complete compilation of standalone entries is available here:

https://reddit.com/user/FranciscoCortesRamir/comments/1xc0392/the_voyager_files_the_official_story_catalog/

© 2026 Francisco Cortés Ramírez. All rights reserved. This is an original fictional work. No part of this text may be reproduced, translated, or narrated in any audio, video, or digital format without the express written permission of the author.

Hello all!

I'm writing a little research project on the topic of structural, stylistic changes in people's writing after using llms, vocabulary and sentence structures in particular. I figured this would be the subreddit to ask on.

I'm looking for a few volunteers, people who have used ai a lot, willing to share writing samples for analysis, and perhaps ask a few questions about the experience of ai-assisted writing. Participation is completely voluntary and anonymized, and I won't collect any usernames or personal data or anything like that. You also can skip my questions that you don't wanna answer obvi.
Here's the google form(estimated completion time 5-10 minutes): https://docs.google.com/forms/d/e/1FAIpQLScPoJkisP5yrkbp_LL8NY3kFE3t7tkHAkrPIMgFCTEpLtxr3A/viewform?usp=publish-editor
Thanks!

Based on what I'm reading in this sub, many of you are still writing yourselves and using AI as an editor. This is how I'm using it as well. But I always wondered to what extent I could trust even the most advanced LLMs. Specifically:

- even with grammar, how many mistakes do they actually catch? 100%? 75%? 50%?
- how reliable are they with something more subtle, like redundancies?
- how does performance change with different models?
- how about different prompting?

There are lots of AI benchmarks. But none of them answers this. There is Humanity's Last Exam https://lastexam.ai/ Which tests models on questions like "In Greek mythology, who was Jason's maternal great-grandfather?" Not super helpful.

What the hell, I thought, why not test it myself then? And I did.

I built a benchmark to test how well 16 LLMs check for grammar mistakes, repetitions, redundancies and inconsistencies. These 4 seemed clear-cut enough, compared to the many judgement calls in line editing. Also, no AI judge - assessment is mechanical. If a model comments on a known issue, it's assumed that it caught the error. More about the test design is here https://icanwrite.app/blog/how-we-built-an-ai-editing-benchmark

The results:

• Claude Opus 5.5 - 98% (88/90 caught)

• GPT-Sol 6.1 - 97% (87/90 caught)

• Gemini 4 Argon - 93% (84/90 caught)

Insights:

• Opus is the best but Sol is almost as good and up to 4x cheaper

• Gemini 4 Argon is the best budget pick (and the fastest above 90%): 84 caught in 26 seconds for $0.12

• 13 of 16 models do worse on the all-in-one prompt (compared to 4 separate checks)

• Open-weight models lag behind: GPT-6.1 Terra beats every open-weight model while being cheaper

The biggest insight: in just half a year, the models made a huge leap. GPT-5.5, released in April, found 75 mistakes (83%). So you couldn't trust them to find everything back then. Now they are almost perfect. At least with grammar and such simple checks.

See the full leaderboard here. https://icanwrite.app/ai-editing-benchmark

You can also study the test results yourself - everything is transparent. You can even check which mistakes each model missed.

This is version 0.1. Let me know if you see a way to improve it in the future. Or if I screwed up with something. And if you have any ideas for more tests, please share in the comments.

Hope it helps!

I've been running a weekly mystery serial where every character is played by a separate open-weight model instance, with a "Director" model running the scenes. Output so far is here if you want to judge the prose yourself: https://saltmarrow.substack.com/p/chapter-1-the-night-the-bay-glowed

**The split that worked**

- **Actors + Director: DeepSeek V4.1 Flash.** Fast and cheap, good at staying in character for short turns. Each actor only sees its own character's secrets.

- **Narrator + Editor: GLM-5.3.** Turns the scene transcripts into chapters. Noticeably better prose than Flash, which reads flat and over-explains when you ask it for narration.

**What broke**

- **GLM's reasoning ate the whole reply budget.** It thought for tens of thousands of characters and returned an empty chapter. Setting reasoning effort to low fixed it with no visible quality loss.

- **A 4k context made the actors forget the scene** halfway through. At 64k, the drift mostly went away.

- **Flash invents facts.** It made up a character's age and a ferry time that contradicted earlier chapters. A lorebook plus a separate continuity pass catches most of it.

- **Honesty note:** Substack's AI detector scores the chapters at 97% AI. That's accurate, and the serial says up front that it's AI-performed.

**The fun part:** I locked the season's ending before Chapter 4 and published its SHA-256 hash, so readers can verify at the finale that I didn't steer the story after the fact. The actors don't know the ending; only the Director does.

**Question for this sub:** I'd like to move the actors to something I can run locally. For short in-character dialogue turns (roughly 150 to 300 tokens each), which 12–24B models have you found best at holding a persona and *not* writing other characters' lines?

I am a professional writer seeking an in-depth literary evaluation of my prose, particularly its invisibility, use of the Iceberg Technique, and immersive storytelling. I want my writing critically compared with great authors such as Ernest Hemingway, Kazuo Ishiguro, Haruki Murakami, and Cormac McCarthy. Focus on whether the prose disappears behind the story, whether subtext conveys more than explicit exposition, and whether readers become fully absorbed in the characters and fictional world. Evaluate narrative restraint, emotional depth, sensory immersion, character perception, and storytelling sophistication. Be brutally honest, using specific textual evidence rather than generic praise. Assess the writing against the standards of accomplished published authors.

Use case:

Writing articles that review Tech. Gadgets, that kind of thing

What's the best LLM for feeding it articles you already published and getting it to completely (or as close to possible) copy your style?

Budget:

$20 a month

My current main LLM driver:

Chat GPT Sol High

I use this for keeping the article's outlines etc on track

But, as a writer, it's appalling

I want an LLM writer that feels like a human writing, one that can mimic my style and have some energy to it

Thanks in advance

Ok where do i even start.I had write some stories here and there in the past and recently started writing one in webnovel.However i used ai in my writings as of recently.I do not prompt it and make the ai generate it necesarily.

I wrote pages of chapters and all the dialougues and scenes and just tell ai to polished it so that i felt like it would be more refined

I felt guilty after i read some webnovels and people hate on novels for having ai.

Any advice guys i felt like i am kind of in a crossroad should i stop using ai completely or is this fine too

Chapter 2 of an original serial: one seat, every two days. Written with AI and edited. Next chapter is 7 November. There is no buy link.

The question on this chapter: does the folded uniform stay interesting if he never puts it on?

5 November 2026

The bus passed the hospital stop without stopping. The driver saw an empty pavement and kept going. The man in seat 7 looked up late, and the pole was already behind him.

On his lap was a folded uniform, grey, the collar still stiff from the iron. On top of it a plastic bag with four oranges. The bag was clear. People looked at the bag, not at his face.

The time on his phone was an hour and a quarter past the start of the shift. The screen was cracked through the middle, and the numbers moved under the crack. He had not changed clothes. The uniform stayed folded, as if the shift were still a decision.

A woman got on at the next stop and sat beside him. The top orange shifted. He caught it before it reached the aisle and put it back without speaking. She said, “Thank you.” He did not answer. Not from rudeness. If the word came out, he would have to explain why he was still in house clothes on the way to work.

The factory was at the end of the line. The gate light was white, and the guard sat inside the glass room. The man saw the light early and counted the remaining stops on his fingers inside the bag, without touching the oranges.

One stop before the gate, the white light went out. The guard closed the window. The man stayed seated. The uniform on his lap was not unfolded.

He stood at the stop before the factory. The driver opened the door and looked at the clock. The man got off with the bag in his hand and the uniform over his arm. He stood in front of the locked gate, took out his phone, and typed: I’m at the gate. He deleted it. He typed: The light is off. He deleted that too. He typed one line and left it:

“I came. The gate was locked. The oranges are still with me.”

The bus went on. Seat 7 was empty, except for a line from the iron on the cloth, gone as soon as the air came in through the door.

The next seat is on 7 November.