> 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've caught Claude Code generating some pretty egregious security vulnerabilities. I'm using it to build an AI RPG site and the goal is to use web assembly as a bridge between author submitted code and LLMs in order to help shore up state management at the game level.
The language that I picked for the game runtime is Python. Claude really thought that the best way to validate user submitted Python was to bypass the WASM sandbox and execute it within the application container using shell exec - essentially opening up an RCE vulnerability.
I also find that the quality of Claude Code degrades substantially. Claude really wants to implement every feature in as bespoke way as possible. This is fine when you first generate the project but over time you'll find that every web modal is implemented differently. Every button is different. Business logic is disconnected. It's why agentically produced codebases are MUCH larger than they should be; every feature is developed in a vacuum.
Then I'm trying to shove stuff in my AGENTS.md or CLAUDE.md files like "ALWAYS look for existing patterns within the codebase to keep it consistent." But the harness doesn't always work and it'll generate useless, verbose code anyways.
In some cases it's useful - like if I am shaky on the DSA knowledge needed for a specific operation or optimization then Claude can replace Stackoverflow. But, man, I'm so frustrated with it.
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).
Eric S. Raymond has basically stopped writing code by hand altogether. He consistently delivers high quality code without intervening to fix the LLM's output himself, much faster than he would have been able to alone. This is very bad news for camp 2 because it means one of three things:
1) he is extraordinarily lucky
2) he is extraordinary brilliant at manipulating LLMs
3) you really are "holding it wrong" and you are hobbling yourself with your failure to properly learn the tools
I used LLM to teach me how to code and get through obstacles that would have me spending a lot of time doing ???. Typically, I just write code that I know a lot of time is absolutely wrong but the LLM helpfully point out mistakes.
I am slowly doing more of my own code and cutting out the LLM out of the loop in the unfamiliar territory I am working in.
My main concern is not so much productivity but understanding the code I have written and feeling agency over it.
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 haven't used these things for writing recreationally for a while (since the Claude 3.X days), so my opinions might be outdated - but they definitely weren't bad - after all they had a huge library of witticisms to pull from, and like Stable Diffusion that pulls from master artists, so do LLMs from skilled writers. Pro writers did come up with an absolute dearth of interesting ideas, and there are mountains of skillfully written prose out there - and its all in the training data, and AI is quite good at pulling from it.
The advantage of the writing vs images, is that it takes longer to absorb the whole with text, so its less apparent that the whole thing doesn't quite come together.
My problems was with Claude's prose and ideas is that it kept recycling the tropes and phrases after a while - something that has been observed that these models have very strong statistical biases - when asking for a random number for example, LLMs are far more predictable than even humans, this shows up in unguided writing exercises.
But as for actually crafting text that is both terse and to the point - such as oneliner explanations, or writing summaries - these models are quite bad. The best I have seen is they could turn a given length of prose into an even longer version - with generally some loss in the tonal accuracy or the points made in there.
As such they are a terrible tool for professional communication, but unfortunately, lots of people have started using them for exactly that.
> 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".
Isn’t “Writing is a Technology that Restructures Human Thought” another way of saying that “feedback has an effect”?
If so, this seems to be a trivial (still worthy) assertion.
For example, I intend to, say, construct a shed. I make mistakes that I only see because I actually constructed. I revise future endeavours involving sheds.
I admit to not having read this piece, and am merely reacting to the title.
—-
Okay, I got through the first paragraph of Walter’s writings. While I nod to the bitterness (I assent to the existence of it), I do not bow.
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.
Imo, this is like saying "I judge a carpenter based on how straight they can cut a piece of plywood." Or like saying "I judge an artist on how accurately they can draw a circle by hand."
I mean that's certainly one way of looking at it, and both can be impressive technical feats. But most people judge carpenters and artists on their end products, their overall vision, their motifs, their philosophy, and so on. On the other hand, as a trained logician, I definitely see proofs (which, by the Curry–Howard isomorphism, are computer programs) have some degree of beauty-within-themselves, but that's quite hard to achieve. Not everyone is a Gödel, after all.
I also think programming languages, despite being Turing complete (which is frankly not saying much), are far too limiting to truly construct magnificent things with.
No, it's more like saying "I judge an artist on my terms regardless of how well they sell on the market".
> artists on their end products, their overall vision, their motifs, their philosophy, and so on
The main output of programmer's work is their understanding of the system they work with. Behind the code there's its author's intention, vision, their tastes, philosophy and experience that makes them tackle problems in specific ways. Code review is, aside of quality assurance, mostly about communication between people, convincing to your ways of doing things and communicating needs. It's what keeps projects running and what makes people improve their skills.
You don't need to see magnificence in code to realize that there's more to it than just the syntax tree to compile.
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.
Hasn't this always been an intelligence thing? I think across all societies and eras we find that generally a a rather alarmingly large section of population is unable to grasp basic written instructions - and that section usually increases to the majority of people, when we start getting into things like an employment contract, or mortgage document.
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 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 know, and we've all been there. It's comfortable to criticize, only when I had a very divisive publication hit front page that I've seen how hurtful dismissive or sarcastic comments can be (https://news.ycombinator.com/item?id=45277346)
And sorry about your blog :/ didn't know it was hacked. Looking at the comment section of the hello world though it gets pretty obvious LOL. You should consider removing it from your HN about though.
I dabble in drawing and I find LLM images (and maybe some non LLM one) abhorrent. As for why, the reason I can think of 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 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.
See, I disagree. Having seen plenty of Claude generated websites and slide decks, to me it just screams "no effort whatsoever". AI sloppypasta for content, if you will.
If I can see within a few seconds that your website or slide was obviously AI generated, I will doubt its content, how much effort (if any) you've put into it, if it won't have hallucinations, and (especially for websites) if it's even real or a scam farm.
I'm not saying every website has to be unique, but at least tell your prompt to use a font or colour scheme or something specific to you that will make it seem like you've put in some effort and make the result stand out from the slop.
I'm going to play devil's advocate, who cares if it all looks generally the same? I grew up before everyone had dial-up, and I remember back then, when Web surfing on Netscape Navigator, all the websites also had a similar structure. Homogeneity in this context, to me, signals a design system that works best in the moment.
This has been a bugbear of mine (and many other people) since long before the advent of LLMs. It is not an intrinsically virtuous thing for a web design to be "effortful". Some of the most well-regarded UX systems in the industry are defined by rigorous sameness. If the baseline is good, departing from it is as likely to reduce legibility as increase it.
- “(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.
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.
> 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.
Everything is an escape hatch, try catch is an escape hatch, a cli flag is an escape hatch. It makes no sense, and quickly ended up in my “banned words and phrases” md file
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.
> Contrastive negation is a rhetorical structure that denies a specific idea in the first half of a sentence and asserts an alternative in the second half.
> It typically follows an "It’s not X, it’s Y" or "not just X, but Y" formula.
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.
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"
I wonder if the tendency to write short punchy sentences stems from deliberate RL efforts to avoid repetitive, consistent writing? I seem to remember that a critique of early LLMs was that they would produce sentences whose construction was too homogeneous. Would be interesting to know the answer to this.
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
"A is not B instead A is blah blah" instead of just saying "A" is a very common pattern have seen in Claude.
It is strange to read as the topic A has often not been introduced and introducing it by saying what it is not makes very little sense to a new reader.
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
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.
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.
The second way produces more billable output tokens. Worse, when you feed that code back into the LLM service, the extra whitespace counts as input tokens.
If you have to add arguments, when they're on one line like that, the diff is cleaner, so the reviewer has an easier time kf understanding what's going on. That is, if you still have a human reviewing code, that is.
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"!?
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...
The language that I picked for the game runtime is Python. Claude really thought that the best way to validate user submitted Python was to bypass the WASM sandbox and execute it within the application container using shell exec - essentially opening up an RCE vulnerability.
I also find that the quality of Claude Code degrades substantially. Claude really wants to implement every feature in as bespoke way as possible. This is fine when you first generate the project but over time you'll find that every web modal is implemented differently. Every button is different. Business logic is disconnected. It's why agentically produced codebases are MUCH larger than they should be; every feature is developed in a vacuum.
Then I'm trying to shove stuff in my AGENTS.md or CLAUDE.md files like "ALWAYS look for existing patterns within the codebase to keep it consistent." But the harness doesn't always work and it'll generate useless, verbose code anyways.
In some cases it's useful - like if I am shaky on the DSA knowledge needed for a specific operation or optimization then Claude can replace Stackoverflow. But, man, I'm so frustrated with it.
1) he is extraordinarily lucky
2) he is extraordinary brilliant at manipulating LLMs
3) you really are "holding it wrong" and you are hobbling yourself with your failure to properly learn the tools
The first two seem rather unlikely.
I am slowly doing more of my own code and cutting out the LLM out of the loop in the unfamiliar territory I am working in.
My main concern is not so much productivity but understanding the code I have written and feeling agency over it.
The LLM is a very good teacher.
It's bad if they work in a part of the industry where code quality or efficiency matters. That's maybe 10% of the total though.
The industry largely has selected for camp 1 long ago.
If you don't get immediate negative feedback camp 1 can go quite a ways before problems surface.
The advantage of the writing vs images, is that it takes longer to absorb the whole with text, so its less apparent that the whole thing doesn't quite come together.
My problems was with Claude's prose and ideas is that it kept recycling the tropes and phrases after a while - something that has been observed that these models have very strong statistical biases - when asking for a random number for example, LLMs are far more predictable than even humans, this shows up in unguided writing exercises.
But as for actually crafting text that is both terse and to the point - such as oneliner explanations, or writing summaries - these models are quite bad. The best I have seen is they could turn a given length of prose into an even longer version - with generally some loss in the tonal accuracy or the points made in there.
As such they are a terrible tool for professional communication, but unfortunately, lots of people have started using them for exactly that.
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".
If so, this seems to be a trivial (still worthy) assertion.
For example, I intend to, say, construct a shed. I make mistakes that I only see because I actually constructed. I revise future endeavours involving sheds.
I admit to not having read this piece, and am merely reacting to the title.
—-
Okay, I got through the first paragraph of Walter’s writings. While I nod to the bitterness (I assent to the existence of it), I do not bow.
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 mean that's certainly one way of looking at it, and both can be impressive technical feats. But most people judge carpenters and artists on their end products, their overall vision, their motifs, their philosophy, and so on. On the other hand, as a trained logician, I definitely see proofs (which, by the Curry–Howard isomorphism, are computer programs) have some degree of beauty-within-themselves, but that's quite hard to achieve. Not everyone is a Gödel, after all.
I also think programming languages, despite being Turing complete (which is frankly not saying much), are far too limiting to truly construct magnificent things with.
> artists on their end products, their overall vision, their motifs, their philosophy, and so on
The main output of programmer's work is their understanding of the system they work with. Behind the code there's its author's intention, vision, their tastes, philosophy and experience that makes them tackle problems in specific ways. Code review is, aside of quality assurance, mostly about communication between people, convincing to your ways of doing things and communicating needs. It's what keeps projects running and what makes people improve their skills.
You don't need to see magnificence in code to realize that there's more to it than just the syntax tree to compile.
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.
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...
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.
And sorry about your blog :/ didn't know it was hacked. Looking at the comment section of the hello world though it gets pretty obvious LOL. You should consider removing it from your HN about though.
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.
See, I disagree. Having seen plenty of Claude generated websites and slide decks, to me it just screams "no effort whatsoever". AI sloppypasta for content, if you will.
If I can see within a few seconds that your website or slide was obviously AI generated, I will doubt its content, how much effort (if any) you've put into it, if it won't have hallucinations, and (especially for websites) if it's even real or a scam farm.
I'm not saying every website has to be unique, but at least tell your prompt to use a font or colour scheme or something specific to you that will make it seem like you've put in some effort and make the result stand out from the slop.
- “(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.
If a repo is bare of CLAUDE.md but mentions a smoke test in a commit in the last year I assume it to be LLM written.
Everything is an escape hatch, try catch is an escape hatch, a cli flag is an escape hatch. It makes no sense, and quickly ended up in my “banned words and phrases” md file
- And a variant of the above is omitting the subject, "happy to" instead of "I am happy to"
- Codex refers to "the spine" of something
- Claude often says some decision is "locked" (i.e. decided on)
Will be interesting if that holds in other areas when chasing super intelligence.
> Contrastive negation is a rhetorical structure that denies a specific idea in the first half of a sentence and asserts an alternative in the second half.
> It typically follows an "It’s not X, it’s Y" or "not just X, but Y" formula.
Wikipedia also has a great resource which covers many of the common LLM patterns: https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing
"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"
My favourite one today from today:
“The tax isn't the problem. The mindset is.”
For those curious https://github.com/ryanthedev/oberskills/blob/main/commands/...
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.
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.
It is strange to read as the topic A has often not been introduced and introducing it by saying what it is not makes very little sense to a new reader.
> "belt and suspenders"
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.
Instead of this:
it will write: 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.If you have to add arguments, when they're on one line like that, the diff is cleaner, so the reviewer has an easier time kf understanding what's going on. That is, if you still have a human reviewing code, that is.