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> fixing locally triggers a need for refactor elsewhere. Yes, but such refactors are most of the time very mechanical, and there's no reason to believe the age

> fixing locally triggers a need for refactor elsewhere. Yes, but such refactors are most of the time very mechanical, and there's no reason to believe the agent won't be able to do it. > the LLM cannot reason so types are not as big a help as one might think. You are missing the point: the person you are responding expects it to be superior in an agentic scenario, where the LLM can try its code and see the compiler output, rather than in a pure text-generation situation where the LLM can only assess the code from bird eye view.

inciampati 2y ago
Mechanical repairs, and often indicative of mistakes about lifetimes. So it's just part of the game.
Capricorn2481 2y ago
No, I think others are missing the point. An "Agentic scenario" is not dissimilar from passing code manually to an AI, it just does it by itself. And if you've tried to use AI for Rust, you would understand why this is not reliable. An LLM can read compiler output, but how it corrects the code is, ultimately, a semantic guess. It can look at the names of types, it can use its training to guess where new code should go based on types, but it's not able to actually use those types while making changes. It would use them in the same way it would use comments, to inform what code it should output. It makes a guess, checks the compiler output, makes another guess, etc. This may lead to code that compiles, but not code that should be committed by any means. And Rust is not what I'd call a "flexible language," where lots of different coding styles are acceptable in a codebase. You can easily end up with brittle code. So you don't get much benefits from types, but you do have the overhead of semantic complexity. This is a huge problem for a language like Rust, which is one of the most semantically complicated languages. The best languages are going to be ones that are semantically simple but popular, like Golang. Although I do think Clojure's support is impressive given how little code there is compared to other languages.

inciampati 2y ago

Mechanical repairs, and often indicative of mistakes about lifetimes. So it's just part of the game.

Capricorn2481 2y ago

No, I think others are missing the point. An "Agentic scenario" is not dissimilar from passing code manually to an AI, it just does it by itself. And if you've tried to use AI for Rust, you would understand why this is not reliable. An LLM can read compiler output, but how it corrects the code is, ultimately, a semantic guess. It can look at the names of types, it can use its training to guess where new code should go based on types, but it's not able to actually use those types while making changes. It would use them in the same way it would use comments, to inform what code it should output. It makes a guess, checks the compiler output, makes another guess, etc. This may lead to code that compiles, but not code that should be committed by any means. And Rust is not what I'd call a "flexible language," where lots of different coding styles are acceptable in a codebase. You can easily end up with brittle code. So you don't get much benefits from types, but you do have the overhead of semantic complexity. This is a huge problem for a language like Rust, which is one of the most semantically complicated languages. The best languages are going to be ones that are semantically simple but popular, like Golang. Although I do think Clojure's support is impressive given how little code there is compared to other languages.