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Learnings from 100K lines of Rust with AI (2025)

zfhuang99.github.io

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Re: Learnings from 100K lines of Rust with AI (2025)

#221

Post by pramodbiligiri »

andai wrote: post #38
pramodbiligiri wrote: post #8

Earlier quoted context omitted.

It is described in the "Code Contracts" section of the article: "Code contracts specify preconditions, postconditions, and invariants for critical functions. These contracts are converted into runtime asserts during testing but can be disabled in production builds for performance". The .NET framework article that he links to: https://learn.microsoft.com/en-us/dotnet/framework/debug-tra...

Is this basically what Dijkstra was saying? I've been thinking how his approach was considered impractical, but may eventually become necessary for security/stability reasons the way things are going. (Seems like new zeroday on HN front page every day now.)

There was a good blog post recently along these lines: https://aybabt.me/blog/correctness-agentic-world

Re: Learnings from 100K lines of Rust with AI (2025)

#222

Post by tensegrist »

andai wrote: post #205
raincole wrote: post #188

Earlier quoted context omitted.

People though asking LLM to output the reasoning steps was astrology until it's standardized and made ubiquitous.

Didn't multiple studies find the reasoning traces didn't have much to do with the final output? And even that outputting placeholder tokens during reasoning has a similar beneficial effect on benchmark scores? (I don't think that's the full picture but, there's definitely something fishy going on there.)

reasoning itself just affords the model a ton of extra forward passes / "time to think"

the, como se dice, "misalignment" between the content of reasoning tokens and the actual output following the end of the reasoning is a separate problem, extensively studied by e.g. Anthropic

Re: Learnings from 100K lines of Rust with AI (2025)

#223

Post by rirze »

pjmlp wrote: post #151
rirze wrote: post #56

Earlier quoted context omitted.

Then your domain problem you’re trying to solve doesn’t benefit from Rust. Sounds like your work doesn’t need Rust and that’s ok. But don’t generalize.

Unless you're writing kernels, or high integrity systems with memory allocation constrains there is very little reason to use a language like Rust. Everything that people find great on Rust with exception of the borrow checker, can be found in any compiled language from ML linage. And even that is fading away as they introduce a mix of linear types, dependent types, effects and formal logic.

> high integrity systems with memory allocation constrains

I agree. I also find that a lot of software should have this mindset anyways so Rust is a great fit for that domain. Anything that others depend on should be high integrity and memory efficient.

Not to mention the ecosystem is very wide in Rust. Other ML languages may not have what one needs.

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