Is your LLM detector on a hairtrigger? At best the headings seem like LLM, but the rest don't look LLM generated.
- "This isn't just a "status" bug. It's a behavioral tracker."
- "It essentially xxxxx, making yyyyyy."
- As you mentioned, the headings
- A lack of compound sentences that don't use "x, but y" format.
This is clearly LLM generated text, maybe just lightly edited to remove some em dashes and stuff like that.
After you read code for a while, you start to figure out the "smell" of who wrote what code. It's the same for any other writing. I was literally reading a New Yorker article before this, and this is the first HN article I just opened today; the writing difference is jarring. It's very easy to smell LLM generated text after reading a few non-LLM articles.
LLMs didn’t randomly invent their own unique style, they learned it from books. This is just how people write when they get slightly more literate than nowadays texting-era kids.
And these suspicions are in vain even if happen to be right this one time. LLMs are champions of copying styles, there is no problem asking one to slap Gen Z slang all over and finish the post with the phrase “I literally can’t! <sad-smiley>”. “Detecting LLMs” doesn’t get you ahead of LLMs, it only gets you ahead of the person using them. Why not appreciate example of concise and on-point self-expression and focus on usefulness of content?
Again, clearly? I can see how people might be tipped off at the blog post because of the headings (and apparently the it's not x, it's y pattern), but I can't see anything in the comments that would make me think it was "clearly" LLM-generated.
One way of describing it is that I've heard the exact same argument/paragraph structure and sentence structure many times with different words swapped in. When you see this in almost every sentence, it becomes a lot more obvious. Similar to how if you read a huge amount of one author, you will likely be able to pick their work out of a lineup. Having read hundreds of thousands of words of LLM generated text, I have a strong understanding of the ChatGPT style of writing.
That can said, I do think it would be better to be up front about this sort of thing, and that means that it's not really suitable for use on a site like HN where it's against the rules.
Your point about being able to prompt LLMs to sound different is valid, but I'd argue that it somewhat misses the point (although largely because the point isn't being made precisely). If an LLM-generated blog post was actually crafted with care and intent, it would certainly be possible to make less obvious, but what people are likely actually criticizing is content that's produced in I'll call "default ChatGPT" style that overuses the stylistic elements that get brought up. The extreme density of certain patterns is a signal that the content might have been generated and published without much attention to detail. There's was already a huge amount of content out there even before generating it with LLMs became mainstream, so people will necessarily use heuristics to figure out if something is worth their time. The heuristic "heavy use of default ChatGPT style" is useful if it correlates with the more fundamental issues that the top-level comment of this thread points out, and it's clear that there's a sizable contingent of people who have experienced that this is the case.
But to add a personal comment or criticism, I don't like this style of writing. If you like prompt your AI to write in a better style which is easier on the eyes (and it works) then please, go ahead.
I agree. I wasn't really trying to make a point. But yes, what I am implying is that posts that you can immediately recognize as AI are low effort posts, which are not worth my time.
But agreed, to me the primary concern is that there's no disclosure, so it's impossible to know if you're talking to a human using an LLM translator, or just wasting your time talking to an LLM.