Eventually you are faced with company culture that sees review as a bottleneck stopping you from going 100x faster rather than a process of quality assurance and knowledge sharing, and I worry we'll just be mandated to stop doing them.

This is a huge overstatement that isn't supported by your own links.

- Donald Knuth: the link is him acknowledging someone else solved one of his open problems with Claude. Quote: "It seems that I’ll have to revise my opinions about “generative AI” one of these days."

- Linus Torvalds: used it to write a tool in Python because "I know more about analog filters—and that’s not saying much—than I do about python" and he doesn't care to learn. He's using it as a copy-paste replacement, not to write the kernel.

- John Carmack: he's literally just opining on what he thinks will happen in the future.

Honestly I don't think so. An essay like this is more than just content, it's an experience for the reader. I value the time I got to spend with it and feel I came way with value that a summary or condensed version would just not have had.

I hear this and FWIW, if there aren't very specific things being asked of you, using AI as a stack overflow replacement as the OP admits to doing is as "AI fluent" as anything else in my book.

>Stop me if you’ve heard this one before: “After [however long] using AI coding assistants, there’s no way I’m going back!” You know, I don’t doubt that this is true. Because I’m not sure some of the people who say this could go back. It reads like praise on the surface, but those same words betray a chilling sense of dependence.

Perhaps, very ironically, they did "have to."

This just isn't true at all in my experience. Do I remember every detail of code I haven't looked at for six months? No, but I can go back and recall pretty quickly how it's structured and find my way around. I'm much more able to do that with code I wrote and thought deeply about. It's like riding a bicycle - if you invested in building up your knowledge once, you can bring it back more easily.

LLMs can sometimes help you to understand someone else's code but they can also hallucinate and I think people gloss over how frequently this happens. If no one actually understands or can verify what it's saying, all I can say is good luck.

I believe and hope eventually we'll come around to valuing people who have put in the work - not just to understand and review output but to make choices themselves and keep their knowledge and judgement sharp - when we fully realize the cost of not doing so.

Honestly, without judgment, I think this is just a fundamental difference in how people approach their craft. You either want to be capable yourself or you just want the results.

People often say this when giving examples, but what specifically made the problem intractable?

Sometimes before beginning work on a problem, I dramatically overestimate how hard it will be (or underestimate how capable I am of solving it.)

Ultimately the author had some simple ideas that are worth sharing and discussing, but they're hidden behind so much non-additive slop.

(Please don't just respond to the quote - lots of context in the full article.)

https://www.npr.org/2025/04/14/nx-s1-5349473/trump-free-spee...

This language-based filtering began in the first term and has been widely reported.

https://www.theguardian.com/us-news/2017/dec/16/cdc-banned-w...

Conservatives in the past have also tried to belittle research grants to justify eliminating them, such as "studying X about fruit flies." It might sound silly to a lay person but drosophila is an incredibly important model organism from which many discoveries have come.

The problem is a highly political, often careless or incompetent, and sometimes blatantly corrupt administration taking a sledgehammer instead of a scalpel to so-called "waste."

[1] https://www.biologicaldiversity.org/news/press_releases/2019...