A lot of people criticizing because it's heavily written with LLM, but I mean, if someone produced this piece pre-LLM, would they criticize it? is the critique due to use of LLM or due to the content being truly hard to follow? I read it and I would say, there are some problems with the writing, but its not a bad piece.

Of course this is a bigger problem, as its now harder to distinguish content that is "AI slop" with "content co-authored with AI that is carefully reviewed" with a quick glimpse, and the "AI smell" is quite off-putting. My initial reaction was also negative, but after glimpsing it through and reading the summaries, I found it decent summary, which also... speaks of this thread, of the content of the blog post and everything about the discussion and the strong feelings people have developed around the use of LLMs.

Anyhow, it would be good to disclose the repo with the code for the statistics & use of LLM in the writing right up front. Which model, and why it was used to do the writing, etc. Its enough to say "I think it writes better than I do" or "I was in a hurry, sorry" or what ever, but it really should be disclosed. It reads more honest.

ps. really... that sideways scroll? plz fix it.

> content co-authored with AI that is carefully reviewed

The problem I see is that this is indistinguishable to a reader at a glance.

Distancing the writing from the "AI smell" not only improves the quality by dropping the unnecessary ocean of rhetorical devices, it forces the human to have real weight and agency on what's being said.

I think that act of distancing from raw LLM output through refinement is a huge quality leap. Even if you're only doing the refinement with an LLM, it forces the writing to have more voice and ideas from the author.

I can see the work that went into the analysis here but again, as a casual reader, it's impossible to tell that there were any original ideas here expressed by the author.

Thank you for your constructive input, you're one of only a few others here who had any. I'll definitely do that. I didn't think, since the output was templated directly from the numbers generated by a reproducible python script, that people would get so up in arms about the aesthetics, but I guess I forgot to say that.

The most quoted line here is "A simple distributional analysis of every rsync release with bug data. No model. No assumptions. Just placement." Not only is it cringe to read, it's also nonsensical ("placement" means what?)

If OP had said "here's an AI summary of the data" and generated a conscise summary, I think I would fine with it. But default AI writing is really verbose -- the opposite of a compression algorithm, spewing out cliched phrases that don't add information. It's exhausting to read, and it lacks the interesting noise of a human response.