There are probably less code samples and let’s be honest this is 2025, how well do LLMs generate code for obscure languages where the training data is more sparse?
There are probably less code samples and let’s be honest this is 2025, how well do LLMs generate code for obscure languages where the training data is more sparse?
I've had 3 Elixir jobs and 2 Rust jobs in the last 10 years. All were on real products, not vaporware. I learned a ton, worked with great people, and made real friends doing it.
Luck? Skill? Who knows. It's not impossible to work with the technology of your choice on problems you find interesting if you're a little intentional.
Nothing ever gets better if everybody just does what's already popular.
He spent time running benchmarks for 0-1 apps and all kinds of other metrics and found basically no appreciable difference in the speed or accuracy of AI at generating Elixir vs. Python. Maybe some difference, but honestly it just doesn't exist enough to matter.
Most code is boilerplate and that's where LLMs shine, I don't think this specific issue is very important.
You'd be surprised: https://github.com/Tencent-Hunyuan/AutoCodeBenchmark/blob/b1...
A: why in gods name B: Every language, every framework and every tech stack is 1 month to 5 years away from being legacy crap. Unless you're learning something like KOBOL it's better to be able to use a variety of languages and show that you can adapt.
LOL. Speaking about absolutely horrible ideas ...
As an acceptor of reality, you can begin to accept that as well.