I don't see how this rebutts the implication.

> This again assumes that people working on high stakes projects only work on one single project.

No it doesn't. It's a very straightforward yes or no question.

> This again assumes that people finding issues with LLM-generated code have not tried every magic recipe under the sun from people claiming their hair growth elixir is 100% a working solution.

He's just describing very common failure modes that come from a lack of structure/linting.

You're framing things like this is some grand conspiracy. OP is literally describing flat tires and your rebuttal is "these magical round tires i keep hearing about." It's very strange.

LLMs will dedupe code if you give them structures to find the duplication. It's not magic. I do it every day.

Do you think it's better to experiment with high stakes projects? Do you think it'll be easier to avoid defaulting to line by line auditing of a project that is high stakes?

There is a sample bias there where the people who are recorded are the kinds of people who feel that way, and the people who don't feel that way are lost to time.

> I think you gravely underestimate how important this is, and how bored and dismal life would be if you didn't have some kind of purpose in your community.

I'm speaking from experience. I have a large family of low achievers I grew up with, and not one of them has ever voiced a concern about purpose, only annoyance with effort. I think this worrying about our place in the universe and where we fit in and "what am I living my life for" is only a concern for a narrow piece of the population, and it happens to be the same slice that talks a lot online.

Most people only worry about their skills and place in the world relative to their ability to survive comfortably. They will happily spend their days idle, going to church, playing games, exercising, whatever, and really only experience any degree of existential dread as it relates to their own impending mortality.

I cannot trust current models to find all the necessary context, or to make what I consider to be good trade offs. A much more capable model would be able to see my existing patterns (or at least not have context rot make them blind to my convention docs) and make trade offs I agree with much more consistently, and I'd be able to do more with my time.

I've actually found models to be pretty poor at driving things I don't know well, so I generally don't do that unless its general design/product exploration and the end product code is throw-away.

If you had a model 10x as capable as the best model out today, but it cost 100x more, would there be a market, and, if so, how big?

I think there would be a market and I think it would be large.

So, I agree.

Everything I said applies to that question as well. The only difference is that'd I'd probably also ask "why are you phrasing that question so strangely?"

If you were home and a family member asked you that question, you'd probably criticise the question rather than answering. LLM are RLHF'd into being milk-toast helpers that just try to answer questions like that with no criticism.

This is all beside the fact that the world of AI has changed pretty dramatically in the last few months.