I've worked with 10x developers who committed a lot of features and a lot of bugs, and who got lots of accolades for all their green squares. They did not use LLM dev tools because those didn't exist then.

If they had used AI, their PRs might have been more understandable / less buggy, and ultimately I would have preferred that.

  If they had used AI, their PRs might have been more understandable / less buggy, and ultimately I would have preferred that.

Sure, and if they had used AI pigs could depart my rectum on a Part 121 flight. One has absolutely nothing to do with the other. Submitting AI slop does not demonstrate any knowledge of the code in question even if you do understand the code.

To address your claim about AI slop improving the output of these mythical 10x coders: doubtful. LLMs can only approximate meaningful output if they've already indexed the solution. If your vaunted 10x coders are working on already solved problems you're likely wasting their time. If they're working on something novel LLMs are of little use. For instance: I've had the pleasure of working with a notoriously poorly documented crate that's also got a reputation for frequently making breaking changes. I used DDG and Google to see if I could track down someone with a similar use case. If I forgot to append "-ai" to the query I'd get back absolutely asinine results typically along the line of "here's an answer with rust and one of the words in your query". At best first sentence would explain something entirely unrelated about the crate.

Potentially LLMs could be improved by ingesting more and more data, but that's an arms race they're destined to lose. People are already turning to Cloudflare and Anubis en masse to avoid being billed for training LLMs. If Altman and co. had to pay market rate for their training data nobody could afford to use these AI doodads.