Comment by shmerl
3 months ago
Using poor quality AI suggestions as a reason not to use Rust is a super weird argument. Something is very wrong with such idea. What's going to be next, avoiding everything where AI performs poorly?
Scripting being flexible is a proper idea, but that's not an argument against Rust either. Rather it's an argument for more separation between scripting machinery and the core engine.
For example Godot allows using Rust for game logic if you don't want to use GDScript, and it's not really messing up the design of their core engine. It's just more work to allow such flexibility of course.
The rest of the arguments are more in the familiarity / learning curve group, so nothing new in that sense (Rust is not the easiest language).
Yes, a lot of people are reasonably going to decide to work in environments that are more legible to LLMs. Why would that surprise you?
The rest of your comment boils down to "skills issue". I mean, OK. But you can say that about any programming environment, including writing in raw assembly.
First argument sounds like a major fallacy to me. It doesn't surprise me, but it find it extremely wrong.
Why?
9 replies →
it could be a weird argument, but as a rust newcomer, i have to say it's really something that jumps to your face. LLMs are practically useless for anything non-basic, and rust contains a lot non-basic things.
So, what are the chances that the pendulum swings to lower-level programming via LLM-generated C/C++ if LLM-generated Rust doesn't emerge? Note that this question is a context switch from gaming to something larger. For gaming, it could easily be that the engine and culture around it (frequent regressions, etc) are the bigger problems than the language.
I haven't coded in C/C++ in years but friends who do and worked on non-trivial codebase in those languages had a really crappy experience with LLMs too.
A friend of mine only understood why i was so impressed by LLMs once he had to start coding a website for his new project.
My feeling is that low-level / system programming is currently at the edge of what LLMs can do. So i'd say that languages that manage to provide nice abstractions around those types of problems will thrive. The others will have a hard time gaining support among young developers.
Developers often pick languages and libraries based on the strength of their developer tools. Having great dev tools was a major reason Ruby on Rails took off, for example.
Why exclude AI dev tools from this decision making? If you don’t find such tools useful, then great, don’t use them. But not everybody feels the same way.
It's a weird idea now, but it won't be weird soon. As devs and organizations further buy into AI-first coding, anything not well-served by AI will be treated as second-class. Another thread here brought up the risk that AI will limit innovation by not being well-trained on new things.
I agree that such trend exists, but it's extremely unhealthy and if anyone, developers should have more clue how bad it is.