Wikipedia has an excellent article about exactly this [1], in their editor information section. There's a section called "Undue emphasis on significance, legacy, and broader trends" that provides some examples:

>Words to watch: stands/serves as, is a testament/reminder, a vital/significant/crucial/pivotal/key role/moment, underscores/highlights its importance/significance, reflects broader, symbolizing its ongoing/enduring/lasting, contributing to the, setting the stage for, marking/shaping the, represents/marks a shift, key turning point, evolving landscape, focal point, indelible mark, deeply rooted, ...

Once I read this, it started sticking out to me all the time.

[1] https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing

I like the take on "undue emphasis on significance." To me, that's such an obvious tell. That's actually an old pre-LLM tell, we just used to call it "pretension." Once we get into long lists of specific words, it feels like we're getting into rules. You can't use this or that word cuz LLMs do. That's crazy problematic. It has to be about the way the emphasis and the overuse of certain words in a single piece reflects inauthenticity. But, eff if I'm gonna stop using "significance" cuz some LLM does.

I'm having fun with this.

Input: I want to stab you with a knife until the light drains out of your eyes.

Output: I’m looking to deeply engage with your core perspective until we’ve fully extracted every last drop of insight from your vision.

I ended up doing something similar to this project a year or so ago: for nearly an entire year, I tracked every single thing I ate or drank.

Who knows how many hours I spent scanning nutritional facts on the backs of boxes, estimating amounts of liquids, and even tracking sips of water. And weighing myself! Thank goodness I used a "smart" scale at least, and I didn't have to worry about carefully inputting my weight to an app each time.

But the whole project was an exercise in perfectionism. "I have to remember this sandwich and log it the next time I'm alone" made me anxious, but once I logged it, I felt a sense of completion. The database and my personal history are now at nirvana. Everything is complete.

All for me to learn things every human alive knows today: eat more food and you'll gain weight; eat less food and you'll lose weight. Yes, I can now tell you the exact average difference in calories I'll eat, statistically speaking, on a day that I have adderall in the morning vs a day that I don't. Yes, there's a similar (but much smaller) difference in average calories per day if I have caffeine in the morning as well. And I can tell you that I generally eat an additional 200-400 calories per day on a Fri-Sun than on a Mon-Thu. Wow, groundbreaking.

I've always had a lot of water, but matching foodanddrink.csv to my HealthKit data showed that I have more water on days that I walk more steps. Mildly interesting to see it written out for me? I guess. But was it worth cataloguing every cup of water? Absolutely not.

Was any of [gestures broadly at me pulling out my phone and cataloguing each item I ate] necessary to learn that? Of course not. It gave me a chance to look back at the database and say "Wowee! I did that! Every day for a year, wow, I'm so cool!" and not much else.