Posted by adius 19 hours ago
That's a lot of people contributing.
How many of them will be less willing to contribute in the future, and less productive when they do if a sizable portion is in Rust? Maybe there'll be more contributions and maybe there'll be less. I don't know. If you've managed to develop a community of 1200 developers who are willing to advance the project why upset the applecart?
I guess it's a long way off, since the LLM translation would need to be refactored into natural Rust first. But the value of it would be in that it's a real world project, and not a hypothetical "well, you could probably just...".
There is no evidence of that coming from this post. The work was highly directly by an extremely skilled engineer. As he points out, it was small chunks. What chunks and in what order were his decision.
Is AI re-writing those chunks much faster than he could. Yes. Very much so. Is it doing it better? Probably not. So, it is mostly just faster when you are very specific about what it should do. In other words, it is not a competitor. It is a tool.
And the entire thing was constrained by a massive test suite. AI did not write that. It does not even understand why those tests are the way they are.
This is a long way from "AI, write me a JavaScript engine".
Both will get a skilled craftsman to the point where thie output is a quality piece of work. Using the autotoools to prepare the inputs allows velocity and consistency.
Main issue is the hype and skiddies who would say - feed this tree into a machine and get a cabinet.Producing non-detrministic outputs with the operator being unable to adjust requirements on the fly or even stray from patterns/designs that havent been trained yet.
The tools have limitiations and the operators as well , and the hype does adisservice to what would be establishing reasonable patterns of usage and best practices.
Personally my sweet spot for LLM usage is for such tasks, and they can do a much better job unpacking the prompt and getting it done quickly.
In fact, there's a few codebases at my workplace that are quite shit, and I'm looking forward to make my proposal to refactor these. Prior to LLMs, I'm sure I'd have been laughed off, but now it's much more practical to achieve this.
In ~5 hours of prompting, coding, testing, tweaking, the STL outputs are 1:1 (having the original is essential for this) and it runs entirely locally once the browser has loaded.
I don’t pretend that I’m a frontend developer now but it’s the sort of thing that would have taken me at least days, probably longer if I took the time to learn how each piece worked/fitted together.
I imagine LLMs do help quite a bit for these language translation tasks though. Language translation (both human and programming) is one of the things they seem to be best at.
Helps me.
In the hands of experienced devs, AI increases coding speed with minimal impact to quality. That's your differentiator.