> The LLM generated writing obviously felt significantly better than my own writing.
A general pattern for LLMs is that they look really good at things you are bad at. What that means is that if you find yourself thinking of its output as significantly better than yours in a particular domain, there's a high chance that you are not equipped to judge that quality effectively.
> A general pattern for LLMs is that they look really good at things you are bad at.
This is true for coding, too, which I think, to a large degree, might explain the polarized differences in opinions on HN about the quality of LLM-produced code. You have the 1. "AI produces code better than I could possibly write, one shots things it would take me days to do, and has made me 10X more productive!" camp, and you have the 2. "AI constantly hallucinates, makes mistakes, has to be babysat, and ultimately costs me time!" camp, with a spectrum in between those. How could the output of the same product be seen so differently? Well, I have bad news for camp 1...
I think there are some factors beyond just skill too - the kinds of tasks you're giving the AI, and how involved you are in ensuring the output is good (via either extensive planning guidance, extensive review/testing, or a combination).
I don't disagree about the probability, but the current frontier models are not completely useless for writing even in areas where I have significant knowledge. I would not have said that a year ago. You have to watch them like a hawk -- they are good at spitting out plausible sounding nonsense that is hard even for an expert to discern. But the dice roll going on behind the scenes is continually more biased towards being correct/useful than not.
On factual things, potentially. But if I want to read your writing, wouldn't I be trying to pick your brain? Otherwise why don't I read wikipedia or usage documentation?
Honestly, I can't fathom thinking that LLM writing is even remotely passable. People that think this should honestly read more. One book a month is hardly an aspirational goal. You don't even have to read Melville or Hemingway or Chaucer or Shakespeare, just pick up any popular NYT best seller, and it'll be significantly better than anything an LLM can generate.
> I can't fathom thinking that LLM writing is even remotely passable. People that think this should honestly read more.
This makes me think you're only exposing yourself to high quality writing online and from an intelligent circle of friends and coworkers. The average person's reading and writing abilities are _atrocious_ and only getting worse. We're almost at the point where kids are communicating through abbreviations and emojis exclusively. LLM prose is significantly better than what the average person can produce.
Someone way more eloquent than me should write a column titled "Why do we read?"
Way back in the past (around 30 years ago) I remember reading an article on "how to read a book" or a similar subject. They argued that, you should not skip the acknowledgments, preface and other "personal" related sections of a book, because it was there where you got a glimpse of the person that was writing the book. The idea being that, you should had in mind that the person writing was explaining something through you.
Carl Sagan even has a video where he argues Books/Writing is some sort of communication through time.
Now, this has been the case historically: A person writes some text (even in botched language like my writing, as English is not my first language) with thinking that someone else in the future will read the ideas and reason about them.
But what about text written by an LLM? Does it have inherent intention? When reading LLM text, it feels like looking at those "this is not a person" photos. Yeah, they are words, yeah they form sentences and paragraphs but... they lack "soul".
It's not "Why do we read?" but something related that is coming up a lot in my thinking lately is Walter J. Ong's "Writing is a Technology that Restructures Human Thought".
I think it's both true that most LLM writing ("writing") sucks and that it's better than what a lot of people can produce unassisted. Which to me doesn't mean that we should roll over and accept LLM output as a lesser evil... it just means that the bar is so low it might as well be in hell, and rapidly getting lower :')
They weren't saying it is aceptable, or making excuses, just stating how things are. Average reading and writing abilities seem to be dropping noticeably in many circles. Probably as a consequence of falling attention spans rather than an issue in is own right.
It’s acceptable for someone to buy a ready meal or takeout if it’s better than what they can cook. Why wouldn’t it be? Is that the greatest choice for their personal development? Probably not, but life is complex and folk have limited capability and bandwidth for acquiring skills.
Tell me your thoughts on the quality of LLM-generated code. I've never understood this attitude where people are absolutely disgusted by the slightest whiff of AI prose but will happily slurp up AI-generated code by the bucketful and proudly proclaim that it's OK because it's better than the average developer can produce.
The key difference is that code is not the end product, but writing is itself the product. (No one's doing "vibe-product-management" for example.) Tbh, I still think code can have a beauty and elegance to it (like a logical proof can, or like a mathematical theorem can), but there's a difference between the two and I'm way less forgiving of AI writing than I am of AI code, especially considering most code (by line count) is just boilerplate anyway.
> The key difference is that code is not the end product
I think this is open to debate. To me, the code has always been the goal, and the fact that writing it sometimes serves to produce a product is important to others (and what brings the paychecks in), but ultimately not something I've ever been excited about or interested in throughout my career. So I judge a developer based on the beauty and quality of the code he produces, just as I judge an LLM by the same sorts of things.
The fact that AI can one-shot a working CRUD app is not really that interesting to me. If it could make the code beautiful, concise, maintainable, extensible, minimal, performant, readable, and bug-free: a work of art and love that a craftsman would be proud of... that would impress me.
I'm not sure if your question is serious, but I've been a developer for over a decade now.
I write code for a living mostly by hand. In the odd case where I need help I still use google like I always have. I spend more of my time in meetings or staring at the ceiling than writing code. This was also true a decade ago before LLMs. It was also true several decades ago when someone else's ass was in my seat.
Really hard to take your comment serious when the only post on dvt.name is a hello world page, because at least OP is trying to publish and you are lacking moral high ground to judge him thinking LLM writing is good.
Oh if I had a nickle for every web domain I bought and put a hello-world.html into s3 and never checked again ...
FWIW, I'm with GP. It's quite easy to get just mind-numbingly tired reading beyond the first two sentences of a typical LLM output, let alone on something I'm familiar with.
It's on dvt about page in HN, so hardly something hidden. People are different, and the in the blog post itself the author writes that in time he became tired of the way LLM wtites
I'm trying to playfully divert away from the captious and unhelpful comment, but if you want to double down, that's ok too. Cheers, my dude, have a good Thursday.
Sure whatever, why even bother commenting if you didn't want to engage then. I don't owe you anything just because you were trying to cheerfully diverge.
Lol my blog was hacked recently and I've been lazy about moving my backed-up mySQL DB to the new WP installation. Not sure where moral high ground enters the picture. If I really wanted to be an asshole, I'd cite a book I co-wrote and another I edited.
> Honestly, I can't fathom thinking that LLM writing is even remotely passable. People that think this should honestly read more.
How do you think the author of the page would read this? That sounded pretty asshole-like for me. If it's not for you I'm really sorry for you, you must have to endure really screwed up people.
Maybe you're right and I was a bit too snarky, apologies to the author if he/she was offended. Writing anything implies some vulnerability, and criticism should be constructive.
I dabble in drawing and I find LLM images (and maybe some non LLM one) abhorrent. As for why, I can think are no consistency (perspective, small details, and color theory) and too much details making it a visual noise. In most painting, the artist will have a subject that is most detailed (to draw the eyes) and from there, the lost of details will follow some kind of logic. This is how you pinpoint what the artist is most interested in. LLM looks like a filter applied to a montage of pictures.
It's like a gross looking slice of pizza, it's mindbending because at first it looks good, after all it's pizza, but something in it makes it really disgusting
The LLM writing sameness is bad. Use LLMs to help your writing! But don't include a word they generate, even just a vocabulary adjustment, in your own output. Have them critique structure and flow, spot overused words and passive constructions and dumb picks for topic sentences. It's great for that, and those are all objective improvements in your writing that won't mess up your style.
The LLM sameness in web design is good. Most sites shouldn't try to be idiosyncratic. The best design for a site with real utility is legibility, and LLMs are better at that than the median developer. Always laying out the same buttons? Always using the same type scales? Good! If it looks good to you, you weren't going to do better on your own, and you were very likely to do worse.
Absolutely agree. I recently wrote a speech and can't imagine how terribly hack it would have been had I taken the LLM's words as my own. I have second hand embarrassment just thinking about someone writing something important for or about a loved one and using the saccharine crap that was suggested at various points to me. Absolute drivel and a giant flag that you don't actually care enough about the audience to bring your own words.
- “(The) honest caveat:” (or “genuine caveat:”, both with the colon)
- “(The) honest answer:” (again, with colon)
- “The thing to internalize:”
- “The smoking gun:”
(really, sentences that start with “The <tag suggesting the next clause is the key point>:” are a strong tell, but those four are the most prolific)
- “load bearing” (when not talking about architecture)
- “blast radius” (when not talking about actual explosives, but rather the effect of an event/action)
- “smoke test” (esp. when “sanity check” is more apropos)
- Lists of three clauses/adjectives where the third is really just a combination of the first two
- Referring to the “shape” of things figuratively
- Social media posts that end with “Curious if anyone…”
- Stories or anecdotes using. “Oh. Oh.” (where the second “oh” is italicized)
Edit: Yes, some of those last ones are terms that we often use as devs...but I would argue about the actual frequency of their use. Plus, these tells live on in prose generated by the latest models.
> I would argue about the actual frequency of their use
Assuming you mean load bearing & blast radius, I'd see those used and use them myself very frequently pre LLM, mostly in online discussions though so its telling where they got their training data. Load bearing itself is/was a pretty normal phrase in the ops world in daily discussion.
Smoke test though, I can't say I've ever see irl usage.
These LLM idioms are constantly being consumed every day and are bound to make it into the next, if not current, generation's vernacular. It's going to be unbearable.
One Python one I hate is that it adds crazy amounts of newlines for no real readability gains.
Instead of this:
def add_three_ints(x: int, y: int, z: int) -> int:
return x + y + z
it will write:
def add_three_ints(
x: int,
y: int,
x: int,
):
return x + y + z
While it's always preferable to do this when you get either long or complex function signatures, Opus 4.7 and GPT 5.5 do this everywhere. When you combine it with their penchant for writing helper functions for everything, you get a ton of vertical padding that messes up the readability imo because Python really relies on your eye seeing indents for scope. Lots of vertical spacing makes scopes less obvious sometimes.
At this point, I want somebody's raw(ish) writing, with spelling errors and grammar mistakes and whatever, at least when it comes to most writing: blog posts, Slack messages, etc. LLMs are great for helping generate ideas, writing code, and maybe even cleaning up some writing, but doing the writing overall? Please don't. I want to hear what you have to say, not what the AI says, if it's something along those lines.
The interesting thing for me is that I do not feel like the writing of LLMs has improved very much lately stylistically.
They have reached a "good" level some time ago but the newer models havn't brought such improvements that you would prefer them to an expert human writer.
Will be interesting if that holds in other areas when chasing super intelligence.
Honest, straight, genuine, actual, real are all words that paper over a weak claim to me. Im thinking about a hook that injects a subagent fact checking in an "are you sure" style here because it's so bad.
Also the false not X it's Y is used in a similar way for faux distinctions like a sov cit claiming "it's not driving, it's traveling in a car"
The LLM doesn't smell like authentic writing but it does a great job for fast and cheap words. We've gained something similar to fast food. Words made very cheap, very fast, easily digestible, but they have no emotion. In short stints it does have a place in the world.
Like corporate manager-type emails, of which I get AI generated ones frequently from company ownership. They think LLMs are the best thing since sliced bread.
It's taken corpo-speak to an entirely new level. On the plus side I no longer have to read them, and can just have AI reply on my behalf with more fast food.
It's kind of interesting how genuinely hard it is to get models to deviate from basically all of these tropes. You can straight up tell it "I hate that card design, do something different, get creative!" and it'll do something either (a) ugly as sin (clearly just essentially a random walk through parameters) or (b) some same-y derivation of that card.
In coding, I've noticed a few tropes as well: everything is a "contract" or an "artifact" (clearly trained on like three decades of Java lol), everything is constantly "backwards-compatible" or "versioned" (even if working on a brand new greenfield project), and a few others.
That's a funny one. I don't use LLMs at all but "load bearing" is such a common/over-used internet joke for DIY building projects and stuff like "load bearing caulk". Have never heard it in a software sense really so am slightly perplexed
All of those are included in the bulk of the documents passing my work input these days. It is infuriating. Out of principle I maintain 100% me in all my writing but I don't know if it matters. Well maybe it does... an interviewee recently complimented me on the "nicest and most human resume" they saw recently. That felt good
So the year is 2026 and we cannot point a LLM at, say, this HN thread, and give it the instructions: "I don't want to look like a dumbass, so don't make these obvious mistakes / don't use these obvious tells"!?
Those cards, so familiar! Exactly what Opus produced for me.
Did Anthropic and/or OpenAI deliberately train their models to produce websites with a specific design language, or did these stylistic preferences emerge naturally as some kind of LLM-selected optimum?
It's not the base model, it's the system prompt in dev tools.
To give an example I'm personally frequently annoyed by, Google's Antigravity will consistently use the word "anthropomorphic" while "thinking" and the end result will consistently have obnoxiously large border radius (kind of like Android's design language).
Codex on the other hand likes to make websites with blue elements on a black background and likes to use emojis for icons for some reason, which is a terrible idea accessibility-wise.
What I find amazing is how HARD it is to make the LLM produce a piece of text that does not sound like slop. I have had dozens of sessions where I tried to make it write like a human would, and yet it still uses those tired writing phrases. I don't understand why neither openai, nor anthropic are able to do anything to make it better, and in some cases it feels like we are actually going backwards.
A general pattern for LLMs is that they look really good at things you are bad at. What that means is that if you find yourself thinking of its output as significantly better than yours in a particular domain, there's a high chance that you are not equipped to judge that quality effectively.
This is true for coding, too, which I think, to a large degree, might explain the polarized differences in opinions on HN about the quality of LLM-produced code. You have the 1. "AI produces code better than I could possibly write, one shots things it would take me days to do, and has made me 10X more productive!" camp, and you have the 2. "AI constantly hallucinates, makes mistakes, has to be babysat, and ultimately costs me time!" camp, with a spectrum in between those. How could the output of the same product be seen so differently? Well, I have bad news for camp 1...
This makes me think you're only exposing yourself to high quality writing online and from an intelligent circle of friends and coworkers. The average person's reading and writing abilities are _atrocious_ and only getting worse. We're almost at the point where kids are communicating through abbreviations and emojis exclusively. LLM prose is significantly better than what the average person can produce.
Way back in the past (around 30 years ago) I remember reading an article on "how to read a book" or a similar subject. They argued that, you should not skip the acknowledgments, preface and other "personal" related sections of a book, because it was there where you got a glimpse of the person that was writing the book. The idea being that, you should had in mind that the person writing was explaining something through you.
Carl Sagan even has a video where he argues Books/Writing is some sort of communication through time.
Now, this has been the case historically: A person writes some text (even in botched language like my writing, as English is not my first language) with thinking that someone else in the future will read the ideas and reason about them.
But what about text written by an LLM? Does it have inherent intention? When reading LLM text, it feels like looking at those "this is not a person" photos. Yeah, they are words, yeah they form sentences and paragraphs but... they lack "soul".
At least in the USA: 21% of adults in the US are illiterate in 2024. 54% of adults have a literacy below a 6th-grade level [1].
1: https://www.thenationalliteracyinstitute.com/2024-2025-liter...
At some point you're just making bad excuses for false scarcity.
I think this is open to debate. To me, the code has always been the goal, and the fact that writing it sometimes serves to produce a product is important to others (and what brings the paychecks in), but ultimately not something I've ever been excited about or interested in throughout my career. So I judge a developer based on the beauty and quality of the code he produces, just as I judge an LLM by the same sorts of things.
The fact that AI can one-shot a working CRUD app is not really that interesting to me. If it could make the code beautiful, concise, maintainable, extensible, minimal, performant, readable, and bug-free: a work of art and love that a craftsman would be proud of... that would impress me.
I write code for a living mostly by hand. In the odd case where I need help I still use google like I always have. I spend more of my time in meetings or staring at the ceiling than writing code. This was also true a decade ago before LLMs. It was also true several decades ago when someone else's ass was in my seat.
FWIW, I'm with GP. It's quite easy to get just mind-numbingly tired reading beyond the first two sentences of a typical LLM output, let alone on something I'm familiar with.
Same to you though, have a nice day
How do you think the author of the page would read this? That sounded pretty asshole-like for me. If it's not for you I'm really sorry for you, you must have to endure really screwed up people.
The LLM sameness in web design is good. Most sites shouldn't try to be idiosyncratic. The best design for a site with real utility is legibility, and LLMs are better at that than the median developer. Always laying out the same buttons? Always using the same type scales? Good! If it looks good to you, you weren't going to do better on your own, and you were very likely to do worse.
- “(The) honest answer:” (again, with colon)
- “The thing to internalize:”
- “The smoking gun:”
(really, sentences that start with “The <tag suggesting the next clause is the key point>:” are a strong tell, but those four are the most prolific)
- “load bearing” (when not talking about architecture)
- “blast radius” (when not talking about actual explosives, but rather the effect of an event/action)
- “smoke test” (esp. when “sanity check” is more apropos)
- Lists of three clauses/adjectives where the third is really just a combination of the first two
- Referring to the “shape” of things figuratively
- Social media posts that end with “Curious if anyone…”
- Stories or anecdotes using. “Oh. Oh.” (where the second “oh” is italicized)
Edit: Yes, some of those last ones are terms that we often use as devs...but I would argue about the actual frequency of their use. Plus, these tells live on in prose generated by the latest models.
Assuming you mean load bearing & blast radius, I'd see those used and use them myself very frequently pre LLM, mostly in online discussions though so its telling where they got their training data. Load bearing itself is/was a pretty normal phrase in the ops world in daily discussion.
Smoke test though, I can't say I've ever see irl usage.
My favourite one today from today:
“The tax isn't the problem. The mindset is.”
Instead of this:
def add_three_ints(x: int, y: int, z: int) -> int: return x + y + z
it will write:
def add_three_ints( x: int, y: int, x: int, ): return x + y + z
While it's always preferable to do this when you get either long or complex function signatures, Opus 4.7 and GPT 5.5 do this everywhere. When you combine it with their penchant for writing helper functions for everything, you get a ton of vertical padding that messes up the readability imo because Python really relies on your eye seeing indents for scope. Lots of vertical spacing makes scopes less obvious sometimes.
Will be interesting if that holds in other areas when chasing super intelligence.
"Smooth. Effortless. A perfect fit for your needs".
In any style of informal or persuasive writing this shows up , as if it has to drive the point in.
I kind of wish we'd stop talking openly about what the tells are. It's nice to be able to determine with fair accuracy - but it couldn't last forever.
Least this way it’s out in the open perhaps, since enough users have training enabled labs will naturally learn what annoys us.
Had the same thought though
Also the false not X it's Y is used in a similar way for faux distinctions like a sov cit claiming "it's not driving, it's traveling in a car"
Thought for sure we'd get a critique of Inter overuse. JetBrains Mono is a lovely font, though.
Like corporate manager-type emails, of which I get AI generated ones frequently from company ownership. They think LLMs are the best thing since sliced bread.
It's taken corpo-speak to an entirely new level. On the plus side I no longer have to read them, and can just have AI reply on my behalf with more fast food.
> "belt and suspenders"
In coding, I've noticed a few tropes as well: everything is a "contract" or an "artifact" (clearly trained on like three decades of Java lol), everything is constantly "backwards-compatible" or "versioned" (even if working on a brand new greenfield project), and a few others.
It's been used in an ops context for a long time, pre LLM even. Same with "blast radius" has been a cybersecurity term for as long as I can remember.
Did Anthropic and/or OpenAI deliberately train their models to produce websites with a specific design language, or did these stylistic preferences emerge naturally as some kind of LLM-selected optimum?
To give an example I'm personally frequently annoyed by, Google's Antigravity will consistently use the word "anthropomorphic" while "thinking" and the end result will consistently have obnoxiously large border radius (kind of like Android's design language).
Codex on the other hand likes to make websites with blue elements on a black background and likes to use emojis for icons for some reason, which is a terrible idea accessibility-wise.
When you bring your own ideas you can get AI to dev pretty nice looking non-generic stuff.