快节奏与硬核代码

文章背景与核心概要

大语言模型（LLM）的兴起显著降低了学习新编程语言的门槛，使得语言选择本身变得不再那么至关重要。开发者现在可以利用AI代理来编写和优化诸如Rust和Zig等不熟悉的高性能语言代码。这种转变正赋能开发者去攻克以往难以触及的复杂技术——例如eBPF、DWARF文件和自定义加密等，从而引领一个追求快速、轻量且高性能软件的新时代。

语言摩擦的消亡

The rise of Large Language Models (LLMs) has reduced the friction of learning new programming languages, making language choice far less consequential. Developers can now leverage AI agents to write and optimize code in unfamiliar, high-performance languages like Rust and Zig. This shift is empowering builders to tackle previously inaccessible, complex technologies—such as eBPF, DWARF files, and custom crypto—ushering in a new era of fast, small, and high-performance software.

大语言模型（LLM）的崛起降低了学习新编程语言的摩擦力，使得语言的选择变得远不如从前那样重要。开发者现在可以利用AI代理，在诸如Rust和Zig这样不熟悉的高性能语言中编写和优化代码。这种转变正赋能构建者去攻克以往无法企及的复杂技术——例如eBPF、DWARF文件以及自定义加密，从而引领一个快速、轻量且高性能软件的新时代。

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上流传着这样一个梗：“编程现在已经被彻底解决了。”我并不确定它在多大程度上实现了这一点，但有一点相当明确：熟悉一门语言的动作已经不再重要，对于人类而言曾经至关重要的一些摩擦力，对AI代理来说根本不算什么。

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.

因此，LLM使得语言的选择远没有过去那么重要了。如果你不喜欢当前的语言选择，你似乎可以用另一种语言重写它，并且你可以让它选择一门身为程序员的你完全不熟悉的语言。

氛围转变：营销、速度与LLM

The Vibe Shift: Marketing, Speed, and LLMs

氛围转变：营销、速度与LLM

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

这反过来意味着，人们能够并且确实更多地根据语言的营销宣传来进行选择。作为一名长期的Rust程序员，我发现看到那些以前可能不会选择Rust的人现在却在交付Rust代码，是一件非常有趣的事。我将这一点至少归因于最近的两大氛围转变：一是关于渴望快速软件的讨论变多，二是关于LLM在不发生行为回退的前提下优化代码表现得极为出色。

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以及其他不少人，对快速和高性能软件始终有一种程度的执念，而且他们恰好也都乐于接受由代理编写代码。也许是由于这个原因，或者与之无关，其他人现在也纷纷加入进来。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：你只需要把一个代理投入进去——尽管专业知识仍然大有裨益！

“硬核语言”的崛起

The Rise of "Hard Languages"

“硬核语言”的崛起

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.

环顾四周，有大量项目既想要速度快又想要体积小，它们正越来越多地选择“硬核语言”。而且受益的不仅仅是Rust。甚至连Zig——尽管其创始人和部分核心社区成员对整个人工智能技术持相当消极的态度——也同样在受益。

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.

例如，Cloudflare的新服务 Artifacts 使用了纯Zig编写的Git协议引擎，并被编译为一个约100 KB的WebAssembly模块；Vercel则发布了 fx，这是一个号称小巧且快速的Zig编码代理。据我所知，所有这些项目在很大程度上都得到了LLM的协助。

解锁复杂技术

Unlocking Complex Technologies

解锁复杂技术

But it’s not just people picking less common languages; they are also 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.

但不仅仅是人们开始选择冷门语言；他们也越来越多地涉足“难度大得多”的技术。突然之间，我看到人们在使用DWARF文件、eBPF、自定义网络驱动程序、自定义加密以及非常古老的计算硬件时，做出了一些令人印象深刻的成果。

Many of these things were previously off-limits for lots of developers. In some cases (e.g., crypto), you were even pushed away because those things were intentionally gatekept by the people in the know.

其中许多技术在过去对许多开发者来说是禁区。在某些情况下（例如密码学），你甚至会被排挤在外，因为这些领域被业内知情人士刻意筑起高墙进行把控。

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

所以，也许这个世界会出现更多平庸的垃圾代码，但它也可能孕育出更多渴望让软件变得快速、小巧的开发者。