I'm undecided about my stance for gen AI in code. We can't just look at the first order and immediate effects, but also at the social, architectural, power and responsibility aspects.

For another area, prose, literature, emails, I am firm in my rejection of gen AI. I read to connect with other humans, the price of admission is spending the time.

For code, I am not as certain, nowadays I don't regularly see it as an artwork or human expression, it is a technical artifact where craftsmanship can be visible.

Will gen AI be the equivalent of a compiler and in 20 years everyone depends on their proprietary compiler/IDE company?

Can it even advance beyond patterns/approaches that we have built until then?

I have many more questions and few answers and both embracing and rejecting feels foolish.

For the record, I'll use it as a better web search or intro to a set of ideas or topic. But i no longer use it to generate code or solutions.

1. https://nikomatsakis.github.io/rust-project-perspectives-on-...

In other words, one has to lean into the exact opposite tendencies of those which generally make people reach for AI ;)

Sure, people are not perfect, but there are established common values that we don't need to convey in a prompt.

With AI, despite its usefulness, you are never sure if it understands these values. That might be somewhat embedded in the training data, but we all know these properties are much more swayable and unpredictable than those of a human.

It was never about the LLM to begin with.

If Linus Torvalds makes a contribution to the Linux kernel without actually writing the code himself but assigns it to a coding assistant, for better or worse I will 100% accept it on face value. This is because I trust his judgment (I accept that he is fallible as any other human). But if an unknown contributor does the same, even though the code produced is ultimately high quality, you would think twice before merging.

I mean, we already see this in various GitHub projects. There are open-source solutions that whitelist known contributors and it appears that GitHub might be allowing you to control this too.

https://github.com/orgs/community/discussions/185387

I don't know what most people are doing in their day to day with AI but this is the closest to reality I have seen thus far. I have seen posts on here about how they have 4 agents making 50kloc a day or something and I can't reliably get a complete spec to output 50 lines of commit worthy code. Emphasis on reliable and commit worthy. I won't go into pros and cons, but I just don't see how everyone is even operating like this, especially with a team of people and any semblance of legacy code. Note, by legacy I do not mean old bad code, I mean pre existing code from various contributors.

For research on crates/integrations, I see some benefits, but sometimes I think it is because search engines have been enshittified and inundated with the top 100 results of nearly all queries being AI slop. 10 out of 10 times I would rather ping a person. Lately I have been assuming most pro-ai articles are written by LLMs or advertising campaigns and ignore it. It's working well so far. Still a top performer on my team...

> The comments within do not represent “the Rust project’s view” but rather the views of the individuals who made them. The Rust project does not, at present, have a coherent view or position around the usage of AI tools; this document is one step towards hopefully forming one.

So calling this "Rust Project Perspectives on AI" is not quite right.