Fast and Hard Code / 快速与硬核代码

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.

Twitter 上流传着一个梗，说“编程问题现在已经解决了”。我不确定这在多大程度上是真的，但有一点很明确：熟悉一门语言的过程不再重要，而且过去对人类而言的一些阻碍，对 AI 智能体（agents）来说已不再是问题。

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. Which in turn means that people can, and do, choose based on the marketing of languages much more.

因此，大语言模型（LLMs）使得编程语言的选择变得不再像过去那样举足轻重。如果你不喜欢当前的语言选择，似乎可以随时将其重写为另一种语言，甚至可以让它选择一门你作为程序员完全不熟悉的语言。这意味着人们现在更多地根据语言的营销热度来进行选择，事实也确实如此。

As a long-term Rust programmer I found it quite fascinating to see people now ship Rust code who previously might not have chosen it. I attribute at least one part of this to two recent vibe shifts: there is a lot more talk about wanting fast software, and about LLMs being exceptional at optimizing code without regressing behavior.

作为一名资深的 Rust 程序员，我发现一个有趣的现象：现在很多人开始发布 Rust 代码，而他们以前可能根本不会选择这门语言。我认为这至少归功于最近两种氛围的转变：人们对“追求高性能软件”的讨论越来越多，同时大家也意识到 LLMs 在优化代码且不破坏原有功能方面表现得非常出色。

Folks like Mitchell Hashimoto, Charlie Marsh, Jarred Sumner, Daniel Lemire and quite a few others always carried a certain level of obsession with fast and performant software and they also all happen to be receptive to agents writing code. Maybe as a result, or unrelated others are now joining in. That’s because with things like autoresearch you don’t even necessarily need to know all the tricks: you just need to put an agent on it — though knowledge greatly helps!

像 Mitchell Hashimoto、Charlie Marsh、Jarred Sumner、Daniel Lemire 等人一直对快速且高性能的软件有着某种执着，而且他们恰好都乐于接受由智能体编写代码。也许是受此影响，又或是其他原因，现在越来越多的人加入了这一行列。这是因为有了像 autoresearch 这样的工具，你甚至不需要掌握所有的技巧：你只需要让智能体去处理它——当然，拥有相关知识依然大有裨益！

If you look around, there are plenty of projects that want to be fast and small, and they increasingly pick “hard languages”. And it’s not just Rust that is benefiting. Even Zig — despite the fact that the creators and parts of the core community are pretty negative on the whole AI thing — is too. For instance Cloudflare’s new Artifacts service uses a pure-Zig Git-protocol engine, compiled to a roughly 100 KB WebAssembly module and Vercel released fx, a Zig coding agent advertised to be small and fast. From what I can tell, all these projects are largely LLM-assisted.

环顾四周，你会发现许多项目追求快速与轻量，并且越来越多地选择“硬核语言”。受益的不仅仅是 Rust。即使是 Zig——尽管其创始人和部分核心社区成员对 AI 持相当负面的态度——也同样从中受益。例如，Cloudflare 新推出的 Artifacts 服务使用了一个纯 Zig 编写的 Git 协议引擎，编译后仅约 100 KB 的 WebAssembly 模块；Vercel 也发布了 fx，这是一个主打小巧快速的 Zig 编码智能体。据我所知，所有这些项目在很大程度上都是由 LLM 辅助完成的。

But it’s not just people picking less common languages but also that they are increasingly working with “much harder” technologies. All of a sudden I have seen people do some really impressive stuff with DWARF files, eBPF, custom network drivers, custom crypto and really old computing hardware. Many of these things were previously off-limits for lots of developers. In some cases (eg: crypto) you were even pushed away because those things were intentionally gatekept by the people in the know.

不仅是人们开始选择冷门语言，他们也越来越多地接触“更硬核”的技术。我突然看到人们利用 DWARF 文件、eBPF、自定义网络驱动、自定义加密算法以及非常古老的计算硬件做出了令人印象深刻的成果。其中许多领域在过去对许多开发者来说是禁区。在某些情况下（例如加密技术），你甚至会被拒之门外，因为这些领域被业内人士刻意把持。

So maybe the world will have more slop, but it might also have more developers in it, that want things to be fast and small.

所以，也许未来世界会充斥着更多垃圾代码，但同时也可能会涌现出更多追求软件快速与轻量的开发者。