The revolt of the reader

I was so optimistic about using LLMs for "write once, read many" English language documents, but the more I've used the tools, the more pessimistic I get.

More and more, I try to ask it for low prose responses because its writing just seems like such a low signal to noise ratio

I'm curious about why LLM writing fails. Particularly whether LLM writing is fundamentally flawed, or if it's just distinctive and since it often reflects low effort, that distinctive voice is associated with low quality.

I find its reliance on extremely consistent rhetorical patterns concerning. The fact that it always finds a way to talk about how "It's not the X, it's the Y Z" no matter what topic you feed it, makes me concerned that the tail is wagging the dog

My revolt is against the cognitive stress of reading generated text. A trope typically indicates I’m in for an uphill read.

I recently read this William Zinsser quote that inspired a nickname for this: Clotted Claude [1].

> Nobody has made the point better than George Orwell in his translation into modern bureaucratic fuzz of this famous verse from Ecclesiastes:

> > I returned and saw under the sun, that the race is not to the swift, nor the battle to the strong, neither yet bread to the wise, nor yet riches to men of understanding, nor yet favor to men of skill; but time and chance happeneth to them all.

> Orwell's version goes:

> > Objective consideration of contemporary phenomena compels the conclusion that success or failure in competitive activities exhibits no tendency to be commensurate with innate capacity, but that a considerable element of the unpredictable must invariably be taken into account.

> First notice how the two passages look. The first one at the top invites us to read it. The words are short and have air around them; they convey the rhythms of human speech. The second one is clotted with long words. It tells us instantly that a ponderous mind is at work. We don't want to go anywhere with a mind that expresses itself in such suffocating language. We don't even start to read.

[1] https://blog.kierangill.xyz/clotted-claude

I would love to use Pangram but they simply don’t allow signing up with my custom email domain. The error was “This email address can't be used for signup. Please use a different email.” I’m not about to create a Gmail is to use your service. To me the attack on the decentralized nature on Internet infrastructure is no less serious than the attack on the human provenance of writing itself.

Disclaimer: I do not like to read LLM-generated text any more than anyone else.

IMHO a big problem with Pangram in particular is that they market it as a reliable tool that can be used to catch students cheating. This can obviously have disastrous effects on young lives, because it is not as reliable as they suggest.

Per their own benchmarks, they do not achieve 100% accuracy even on text that is published on the Internet, and which is likely encoded into the models themselves.

There is validity to their goals, but that is overshadowed by the irresponsible way in which it is marketed.

(All of this, swirling in a context where students are being told that they absolutely must become proficient at using LLMs to do exactly this kind of work by the highest levels of state and federal governments, faculty leadership, as well as the leaders of the workforce into which they hope to graduate. The message to youth is extremely muddled at best.)

Someone should make a browser extension to label HN posts with Pangram results of the top 100 posts, so I don't waste my time reading crap.

Always a pleasure reading Bryan's writing; it's like Bryan is sitting there with you and saying the words (hard to convey the feeling).

Nowadays we use LLMs mostly for doing agentic-based work. LLMs new Pareto frontier only make the headlines if they push the boundaries on benchmarks that are deterministic tasks. So models are encouraged to focus on these deterministic tasks that are, in nature, structured texts. I think that this makes models more “plastic” or “polished”, as opposed to natural and pleasant to read. User-based benchmarks, like LLM Arena, are for me the best we can do in order to rank models in this way, but come with its own drawback (subjective evaluation, prone to spam or techniques to promote a giving model).

So you believe that writers are not making the necessary effort and write using LLMs, so you then use an automatic LLM to filter it as a reader(because you don't care as a reader and don't want to make the effort manually).

So this way there will be a lot of false positives like with school assignments.

I think a better solution would be to have a network of people that you trust manually read and label texts instead, so this way no machines are used and you don't need to read a text that 100 of your trusted friend/trusted readers flagged as artifitial.

By the way, this man does not care about AI slop. He cares about AI usage. In the same way there is very good code created with the help of LLMs, albeit a minority like Linus Towards says, there will be very good writing created with the help of LLMs.

For me it’s AI videos or music / narration that is beyond off putting. What’s worse now it seems people are writing their YouTube scripts with Claude et al. so at times even if it is a human creator you can clearly and immediately tell the words are not their own. To those creators I have but one message: IT SUCKS. I’d rather have you ramble incoherently in your mic then reading an LLM script and I will remove you from my feed immediately. I concur with the author on all accounts. We all can tell the BS people are selling us, unoriginal ideas, shallow concepts, open ended questions that hint at exactly nothing. Don’t be an LLM echo

> do you think readers can’t tell?

No. I have good anecdata: readers cannot reliably distinguish my own prose from LLM-written one apart from cases where LLMs use odd metaphors or one of their specific patterns. I've been specifically experimenting with that.

> we readers shouldn’t be expected to labor to understand a sentence that the writer themselves didn’t work to create.

What about answers that an LLM gave to a question that we ourselves asked? Should we “labor” to understand that answer?

I think the argument, as presented in this and other similar pieces of critique, is too simplistic.

I do understand the criticism, but I think it should be framed in a different manner. The problem, when we read a long form piece by an author, is that we imagine that there’s another “mind” at the other side. We imagine that we are following the reasoning within the mind of a fellow human being, the writer. There’s an implied sort of “intimacy” to it. And the breach is when we are fooled into thinking that we are engaged in human communication, only to discover that there is a machine on the other side.

When we ask questions to an AI, this problem does not exist, because we are fully aware that the entity on the other side is not a human being.

Yet there is no doubt that the reply from an AI can contain information that is very much worthy of our time, and of our “labor” and effort to understand it.

So I think this ultimately will be about disclosure. As long as we are being made aware of the percentage of AI use in a text, explicitly or implicitly, I think we will actually grow to accept it.

I see this at work. People are "writing" specs and design proposals with bots. This is noticeable and is a huge turn off. I don't have issues with using bots to aid research, but I'm not reading the doc you slopped together.

How can you tell if people can accurately identify AI generated text?

If a person reads AI generated text and does not notice, they by definition will not know about it.

There have been numerous cases of people accessing human created content as being AI.

There are instances where it seems relatively uncontroversial that it is AI generated, but without knowing both the amount of AI content people are exposed toand the amount that they register I don't think you can draw a conclusion of the overall state.

Great piece and interesting data. The rate of LLM-based writing rejection among developers is even higher than I thought it would be.

To me, the glaring question is: What are we doing? The act of writing exists to 1) externalize and organize one's own thoughts for the purpose of considering and revising those thoughts; and 2) share one's own thoughts with other minds.

When we hand writing to a machine, we hand thinking to a machine, denying both our humanity and our role in the conversation.

I am bad at recognizing LLM writing off the bat, though I am getting better. It's pretty common that the writing is good enough to get me reading on a topic I am interested in; then, once I am invested in the piece, it turns out to be shallow, wildly incomplete, or simply wrong.

It's common enough that it's training me to recognize and recoil from AI tics through sheer classical conditioning.

For me, writing is an activity of expressing my feelings and conveying my thoughts. I rarely left that to LLM simply because one does not contract out activities one cherishes.

I (am kinda forced to) use LLM to generate maybe 40% of the code at work, that is after my review and modifications. But I pretty much wrote all of the comments by myself. I can get into the flow by writing comments.

Hi Bryan,

I liked your piece, and agree with almost all of it, but I'm surprised by your faith in the accuracy of Pangram at detecting AI writing. Is your faith based on testing it with lots of writing of known origins, or are you just saying that it reaches the same conclusion that you do as a talented human?

In particular, I wondered if you have tried running all of your own writings through it to verify that it thinks you are human. I was struck by Freddie deBoer's recent piece where he did this and said it often failed: https://freddiedeboer.substack.com/p/i-wouldnt-say-pangram-i...

What percentage of false positive rejections would you find acceptable? Would you accept this even if it forced you to change the way you write?

I did some experiments with very simple AI detection. You can get a very long way with simple ngram probabilities.

https://meatbag.atomic14.com/

https://www.atomic14.com/2026/08/18/detecting-claude-with-le...

It’s very hard to make reliable though. Different models have different characteristics and you can prompt your way out of being detected.

In a way, The ubiquity of AI-generated material will force the world to acknowledge the superiority of the human mind. Already on Youtube there are channels proudly claiming their music was not generated by AI. Will the software industry have similar disclaimers? (some already have).

"you probably shouldn’t let it write it for you if you actually expect the rest of us to read it." definitely resonates with me.

Where I kind of disagree is that I don't think most readers will revolt. I think the mountain of LLM slop has actually changed people's behavior in more ways than one. Some are already relying on LLMs to summarize articles: then it doesn't matter to them who wrote it, they're just consuming machine-condensed content with no way to tell if a human or an LLM wrote the original piece. Or if their summarizer hallucinated.

It is not clear to me what the author is SPECIFICALLY against.

Only saying "LLM writing" is honestly lazy writing. Specifically what?

I get the glaring cases, I get the idea that if the prose is generated then maybe also the idea, I get the feeling when reading a complete LLM authored piece.

But that doesn't help the piece, because - beside those glaring cases - most writing today is a mix between authors ideas and LLM prose.

A lot of similar pieces have not considered a post is both the first and final work of a thing: opinions, and experience, and less of much in cited facts; with AI, that there even was a revision pass at all.

I guess there is a kind of participatory element to the discourse where, if you want an audience, there is an editing process. Whereas in other cases, we wrote these as progress notes on an unknown journey, breadcrumbs or upturned stones to mark a path to the horizon.

Maybe it's the difference between writing as a mode of discovery, retreading the mental arc of a solution, and writing something honed to leave a mark.

"I have fantasized about sentencing the author to read them aloud, certain that they themselves will be unable to endure the slop that they are foisting upon the rest of us.)"

I wish that were true, but I fear it may not be.

https://arstechnica.com/ai/2026/07/canadian-legislator-reads...

Blocked EVERY single LLM generated blog and content farm with uBlacklist.

Another great day where Google only gives me 2 results on the first page.

>to use an LLM to write is to void the social contract between writer and reader: we readers shouldn’t be expected to labor to understand a sentence that the writer themselves didn’t work to create.

Pretty much sums up the issue re: workplace lazy AI dumping on folks as well.

In a way, I think they're doing us a favor with LLM slop: It's rare to have a signal that's 100% accurate at telling me it's safe to stop reading.

I'm confused and disturbed by the need to invoke Pangram (a model) as the arbiter of slop here. Slop, like smut, is self evident. You know it when you see it. Yes, some effort may be required before realizing that something is slop, which, yeah, is annoying, but that's nothing in comparison to outsourcing your shiite detection to a model! What do you get, except the loss of self worth, by needing a model to have the confidence to call something slop?

> Why do people have this reaction? Beyond having to endure aggravating stylistic tics, when reading a piece that has had substantial LLM assistance, we — the readers — don’t know what is real and what isn’t.

This is well said. But, here too, I would pause and reflect on what it means to (think you) know what is real and what isn't in a pre-LLM setting. For example, authority bias predates LLMs, and can have disastrous consequences.

When I write technical documentation, here's how I use LLMs:

* If I need to learn something before I write about it, I rely on LLMs heavily to answer questions that I have about other source materials, e.g. to clear up ambiguities.

* I've recently started prompting it to find grammatical and spelling errors.

* And I've prompted it to find technical errors, places where I'm just wrong.

For all the prompting, I additionally tell it to not rewrite anything or offer any prose suggestions. It can keep all that to itself, thank you.

And I verify what it gives back for correctness.

(I'd encourage non-native speakers to use LLMs in much the same way. Don't sacrifice your human voice by letting the AI rewrite your words. Personally, I'd very much rather hear it from you, blemishes and all, than hear it from an AI.)

But if I could step back for a minute:

Why write anything?

If your writing goal is to flood the zone and make as much money as humanly possible from ads, then hell yeah, paperclip the everliving shit out of that.

But if your writing goal is to learn material or share material, then put that LLM on the back burner and don't use it to directly generate your text. It's bad for you, and the results are subpar.

When I'm learning something, I can go through reams of tokens and then, once I understand it, I digest that to single a paragraph about the topic. The paragraph is as concise and as helpful as I can make it. Now, I could just share the prompts that I went through with those pages of back-and-forth with the LLM... but wouldn't you rather just read the concise paragraph that gets the point across?

It's not hard to be better than an AI at writing for humans, so the minimum low bar to aim for is "better than an AI". And we can all get there with a small amount of practice. The real goal is to greatly exceed the LLMs' capabilities for sharing information.

Finally, I think everyone should write a lot. Blogs, morning pages, fiction, technical books, letters, whatever. Especially when it comes to technical content, nothing makes you do your research like putting your ass out in the ether to get flamed by 5 billion people. And teachers the world over know the best way to learn something is to teach it. Pick a topic, research, and write it up more clearly and concisely than anyone else ever has. You'll learn so much, and your readers will, as well. Writing fires up your brain. Don't give that up to an LLM.

if its not worth your time to write, its not worth my time to read

this goes 10x for all the slide decks and google docs and wikislop everyone's trying to pass off as an accomplishment lately

AI detection should NEVER be used in an educational setting where the only acceptable false positive rate is 0%. That being a rate that which will never be achieved.

Look, in the future we may get to a point where LLMs are indistinguishable from humans in writing style.

Even then, I would say that using an LLM is robbing you of the process of writing, a process that is crucial to developing and understanding your own ideas.

Think about the last time you wrote something for consumption and the sentence to sentence thought processes you’re going through. I bet a lot of that was “is that right?” Or “does that make sense?” Or “am I communicating this at the level of my reader?”.

All of that is fundamental to your readers understanding, but more importantly, its fundamental to YOUR understanding.

This meme of trying to make it sound like LLM text is so obvious is a joke. It’s literally not, you can tell it to write in literally any style and given just a bit of an example of a person’s writing style, frontier models copy it completely and effectively. This argument can probably be leveled at vanilla raw output from an LLM, but even the slightest attempt at obfuscation bears solid fruit.

so, yet another post encouraging the use of AI tools lol... great. that's the literal meaning of the post.

> To those who read broadly, the hand of the LLM is so clear it’s as if the writer’s intellectual fly is open

I dunno, man, according to Hardcover, I've read 76 fiction books this year, and I can't tell. All the "AI tells" fail the vibe check. I'm a writer and I get flagged by many of them.

And according to PhD linguists with expertise in the field, most AI tells are just the equivalent of old wives' tales. https://www.youtube.com/watch?v=ORgKY9AlybA

I vaguely recall that researchers were able to train people to tell, but only for a minority language that AIs likely aren't particularly good at mimicking, and after training.

This whole thing reminds me of how "you can recognize a vegan because they'll tell you." There, you have a ton of false negatives (i.e., since you aren't polling people to find out if they're vegan, you're only flagging the obvious vegans and missing all the regular people who happen to be vegan).

Except here, it's a bunch of false positives and negatives I bet. You don't really have a way of knowing, so you're accusing some people (without complete accuracy) and missing some people (without complete accuracy). But you have no way of knowing, so you're just like "hell yeah, my vibes tell me I'm right."

Research and experts disagree.

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is this... an ad

> Indeed, Pangram has become important to so many of us that I was thrilled when Pangram Labs co-founder and CEO Max Spero joined us recently on Oxide and Friends.

Is obvious AI-assisted writing better or worse than an obvious PR quid pro quo and/or cross-promotion?

The idea that readers "can tell" remains laughable. Readers routinely claim they "can tell" on things that turn out to be entirely hand authored.

If you want to read something good, read a good book.

Ending with a spin on "if you didn't bother to write it why should people bother to read it." Way to rail on cliche repetitive slop, with more cliched slop. Will the irony never cease.

This reader revolted after the second unnecessary (and exclaimed!) parenthetical. You can't please some people.

> Today, legitimate businesses are very careful about how they use bulk e-mail

I don’t think this is remotely true. Sure, they’re legally obliged to let you unsubscribe, and sure, it’s not dick pills, but every US company will immediately send you a newsletter when you purchase something, review requests and, if they/you use Shop for checkout, expect an abandoned cart reminder.

PR pieces and software companies don’t write tutorials to be helpful, they are advertising to you. If the LLM can do it for cheap, they really don’t care.

This entire article is the bad toupee fallacy.

Readers think they don't like LLM-authored text because they only recognize bad LLM-authored text as LLM-authored.

Blind trials have actually shown that readers generally prefer LLM authored books to human-authored ones on the same subject.