Out of curiosity, what are you basing this on?

The text has few of the obvious AI tells. The only thing that, to me, looks characteristic of LLM-generated text is the short and terse sentence structure, but this has been a "prestigious" way to write in English since Hemingway.

Sort of a taste receptor I’m sure many have developed now.

The most obvious patterns here are: antithesis constructions, words choices and distribution, attempt at profundity in every paragraph but instead are runs of text that doing say anything, and even the perfect use of compound hyphenation. I think and can appreciate that there is definitely an attempt at personalization and guidance to make it less LLM-y and not just a default prompt, but it’s still kind of obvious. You could use a detector tool too of course.

What are the obvious tells? List them, because I think our sense of the tells may not overlap.

This article is clearly LLM-generated, even the title. A key indicator is that it almost makes sense: we forgot how to manufacture because that got sent to a different nation. The coding thing isn’t getting sent anywhere, so humanity is forgetting how to code. The distinction undermines a lot of the emotional baggage about offshoring that the article wants you to bring along.

The blog post reads nothing like Hemingway. Here's a classic example: https://anthology.lib.virginia.edu/work/Hemingway/hemingway-...

Hemingway writes simple sentences with a kind of detachment to make the emotional flow of his stories as transparent as possible.

LLM slop reads more like slide bullet points extrapolated to prose-length text

Blog posts aren't typically written like Hemingway.

Find some pre 2020 that are, and you'd have a point.