Fast and Hard Code
The author argues that LLMs are reducing the friction of learning new programming languages, allowing developers to prioritize performance-oriented languages like Rust and Zig. This shift is enabling more projects to adopt 'hard' languages, as AI agents can handle the complexity of optimization and syntax.
Why it matters
The democratization of complex programming languages through AI could lead to a significant increase in software performance and efficiency across the industry.
One of the memes on Twitter is that “programming is solved now.” I’m not sure to what degree it is, but one thing is pretty clear: the act of familiarizing yourself with a language no longer matters and some of the friction that mattered for humans does not matter for agents.
As a result, LLMs make language choice much less consequential than it used to be. If you don’t like the choice, you can seemingly rewrite it in another language and you can make it pick a language that you, as a programmer, are entirely unfamiliar with.
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