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AI时代的软件正在转向“积木式经济”

这篇文章抓住了一个真实转向:AI 确实在放大“拼装成熟开源组件”的优势,但作者把“底层构件扩散更快”直接上升为“做软件最有效的方法已变”,这个结论有洞察也有明显外推过度。
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2026-04-08 原文链接 ↗
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核心观点

  • 增长入口变了 作者认为,今天更高效的不是先做完整主线应用,而是做可被他人和 AI 快速拼装的“积木”;这个判断在开发工具、开源基础设施里很成立,但在高责任、强交付行业并不天然成立。
  • AI 强化“拿现成的” 作者最站得住脚的一点是:AI 特别擅长把高质量、文档完善、已验证的组件胶合起来,这使“可调用、可组合、可验证”的软件比“功能大而全”的软件更容易扩散。
  • 外围生态替主线试错 作者主张把低频、垂直、争议需求交给 fork、插件和封装层,让外围先跑实验,再把验证过的能力回收主线;这套逻辑对控制 roadmap 膨胀很有效,但也会把维护成本和体验碎片化转嫁给下游。
  • 开源免费在 agent 时代占优 作者判断,当前模型更偏好开放、免费、接口清晰的方案,因此闭源商业软件处在结构性劣势;这个趋势大概率存在,但文中证据不足,离“已经被证明”还有距离。
  • 数据支持弱于观点力度 Ghostty 与 libghostty 的增长对比很抓人,但统计口径并不一致、追踪也不完整,所以它最多说明“组件传播可能更快”,远远不能证明“最有效的方法已经全面改变”。

跟我们的关联

  • 对 ATou 意味着什么、下一步怎么用 ATou 做产品时不该默认“主应用越完整越好”,而该优先检查自己是否能成为别人工作流里的标准件;下一步可以用“可调用性/可组合性/可验证性”三项来重排产品优先级。
  • 对 Neta 意味着什么、下一步怎么用 Neta 如果做内容、工具或系统设计,重点不该只是表达完整观点,而该考虑怎样把能力拆成可复用模块;下一步可以把方法论产品化成模板、接口、组件,而不是只做一次性交付。
  • 对 Uota 意味着什么、下一步怎么用 Uota 若在生态里找位置,更适合押注“被集成能力”而不是单点应用体验;下一步应评估哪些能力可以成为默认依赖,哪些只是好看但难以嵌入的成品。
  • 对三者共同意味着什么、下一步怎么用 这篇文章最值得吸收的不是“全盘拥抱 AI 工厂”,而是“主线收敛、边缘发散”的组织方式;下一步可以在任何项目里明确内核边界,把实验性交给外围生态验证。

讨论引子

1. “被大量集成”到底等不等于“更成功”,还是只是分发更广、价值更薄? 2. 哪些领域适合“积木优先”,哪些领域仍然必须坚持“完整产品优先”? 3. 如果 AI 和开发者都偏好开源免费组件,闭源商业软件未来靠什么建立不可替代性?

如今,要做出软件并获得海量采用,最有效的方法不再是打造高质量的主线应用,而是提供“积木”式的构件,让并鼓励他人以数量优先于质量的方式去搭建。

Ghostty 用了 18 个月:macOS 每日更新检查一百万次。
libghostty 用了 2 个月:每日用户数达数百万。1

在其他“积木”型技术上也能看到类似的增长轨迹:Pi Mono、Next.js、Tailwind 等等。

亲身经历这些,并在其他生态里看到同样的现象后,无论目标是商业还是非商业,这都从根本上改变了我对当下产品与软件开发实践的看法。

导入在上升

我用“building block”这个词来描述它们被使用的方式,因为今天它们被组装起来的方式,和过去几十年非常不同。

我不用“library”或“framework”,因为这种用法甚至延伸到了“applications”(例如 Ghostty 的 GUI 应用被 fork 的数量比以往更多,上面叠了各种自定义补丁,这很棒)。

今天的工厂是由智能体驱动的。我把这当作客观事实,不管你对此有什么感受。你可以说这些工厂产出的东西里有 99% 都是彻头彻尾的垃圾,但你无法否认它们产出的数量之巨大。数据随处可见,横跨技术栈与行业,无法辩驳。

AI 当然也能从零搭建一切,但它在把高质量、文档完善、且已经被验证的组件“粘”在一起这件事上,真的很擅长。而且只要条件允许,除非你明确提示它不要这样做,AI 会偏好这么做。这就是今天软件的“积木”属性:比以往任何时候都更频繁地从货架上拿现成组件,然后把它们粘合起来。

当然,人类一直也在做这件事。我的整个职业生涯里,人类软件开发者都更愿意在被验证过的基础原语之上继续构建。但过去要把组件理解到足以“先拼起来再说”的门槛高到足以限制生态规模。这个门槛现在消失了。

导出在上升

从这些工厂里出来的当然是软件。大量的软件。

这有负面影响。我认为负面已经足够明显,不打算花太多篇幅展开,但需要承认它们确实存在:安全漏洞、不稳定,以及对承载关键负载的系统如何运作的普遍缺乏理解。

但正面也非常多:

  • 质量门槛更低。 一个被大量不同用户使用的主线应用,必须把每个功能与其他功能一起权衡:它们如何交互?是否符合长期愿景?能否为数百万用户维护它?而一个面向一到几百名用户的工厂产物不需要在乎这些。于是可以更快、更松弛地交付。

  • 认知更广。 主线应用不可能做所有事。它通常会针对最多用户最常用的场景做优化。工厂产物可以为极小的一部分用户做优化,而这些用户因此会对这个积木式构件产生认知。我在 Ghostty 上强烈地看到这一点:非常小众的社区也开始拥有适合他们的终端。

  • 维护负担更低。 现在,维护者对功能请求说“不了,谢谢”比以往任何时候都容易,因为你提供的是生产资料中的关键一环。关于我对“糊弄式”请求的困扰,已经很公开了,公开到我做了个“no machine”,但每天对说“不”这件事的内疚感也在持续下降。

  • 研发被外包。 作为维护者,现在更容易去观察别人做了什么,看到能跑的概念验证,再决定哪些要带回主线。嘴上讨论少了,动手做事多了。别人走在前面时,你可以挑拣最好的点子带走(这很公平:你免费给出一个积木式构件,他们也免费给出他们的想法)。

影响

这正在改变我看待软件与产品开发的方式。

我更有意识地去创造积木式构件,并鼓励大家在其之上做应用或 fork。我认为这带来了更开心的社区、更大的社区,并最终带来更好的主线软件。

高质量应用不会消失。由积木式构件的开发者自己做出来的高质量应用也不会消失。就我而言,Ghostty 这个应用不会因为 libghostty 这个积木式构件存在而消失。

相反,我认为主线应用会变得更稳定,在功能集合上也更有目的性。稳定性来自更庞大且更多样的用户群。功能集合来自规模巨大的外包式研发生态。

房间里的大象:商业化

接下来最显而易见的问题是,这对商业化意味着什么。闭源的商业软件看起来处于巨大的劣势。确实如此。

智能体会更倾向选择开放且免费的软件,而不是闭源的商业软件。在写下这篇文章的时刻,这是一条客观事实。独立研究实验室在流行模型上反复做过实验,发现即使在多样化的情境下,模型也会选择开放且免费的替代方案,而不是商业方案。至少目前如此。

但我在这里没有一个明确答案,因为不同于产品与软件开发,我现在并没有在直接构建一个可商业化的产品。我有一些想法,和所有难题一样,我认为答案很微妙。但我不想制造一种自己在权威发言的错觉,所以会避免展开。等真正走到那一步、学到更多之后,再分享更多。

这里只是再次承认,这个挑战显然存在。

转变已经发生

必须接受积木式构件与软件工厂正在支配我们周遭的一切,并接受、内化由此带来的后果。

可以选择往相反方向跑,建立一些与之对抗的飞地。也可以选择完全把自己交给混沌。了解我的人知道,我的行动远没有这么极端,我会因情境不同而持有不同观点。

重点在于,转变已经发生。我们正活在其中。


  1. 要拿到精确数字显然很难,因为 Ghostty 没有真正的追踪。我们能看到 macOS 的更新文件检查总量。对 Linux 则完全不可见。libghostty 也没有追踪,但集成 libghostty 的工具可能有,并且曾与我们分享过汇总数据。 

  2. 这篇文章是手写完成的,没有借助 AI。我非常喜欢也大量使用 AI,但在内容上,我个人划了一条线。我希望文章能直接反映我是谁。 

The most effective way to build software and get massive adoption is no longer high quality mainline apps but via building blocks that enable and encourage others to build quantity over quality.

如今,要做出软件并获得海量采用,最有效的方法不再是打造高质量的主线应用,而是提供“积木”式的构件,让并鼓励他人以数量优先于质量的方式去搭建。

Ghostty in 18 months: one million daily macOS update checks. libghostty in 2 months: multiple millions of daily users. [^1]

Ghostty 用了 18 个月:macOS 每日更新检查一百万次。
libghostty 用了 2 个月:每日用户数达数百万。[^1]

Similar growth trajectories can be seen in other "building block" technologies: Pi Mono, Next.js, Tailwind, etc.

在其他“积木”型技术上也能看到类似的增长轨迹:Pi Mono、Next.js、Tailwind 等等。

Experiencing this firsthand as well as witnessing it in other ecosystems has fundamentally shifted how I view the practice of product and software development today, regardless of commercial vs non-commercial goals.

亲身经历这些,并在其他生态里看到同样的现象后,无论目标是商业还是非商业,这都从根本上改变了我对当下产品与软件开发实践的看法。

Imports Are Up

导入在上升

I use the term "building block" to describe how they're being used because they're being assembled today in a very different way than former decades.

我用“building block”这个词来描述它们被使用的方式,因为今天它们被组装起来的方式,和过去几十年非常不同。

I don't use the term "library" or "framework" because it extends even up to "applications" (e.g. the Ghostty GUI app has more forks than ever before with customized patches on top, which is awesome).

我不用“library”或“framework”,因为这种用法甚至延伸到了“applications”(例如 Ghostty 的 GUI 应用被 fork 的数量比以往更多,上面叠了各种自定义补丁,这很棒)。

The factory of today is agentic. I say that as objective truth, regardless of what your feelings about it are. You can argue that 99% of the stuff coming out of these factories is total crap, but you can't argue the sheer quantity of stuff coming out. The numbers are everywhere spanning tech stacks and industries and they're undeniable.

今天的工厂是由智能体驱动的。我把这当作客观事实,不管你对此有什么感受。你可以说这些工厂产出的东西里有 99% 都是彻头彻尾的垃圾,但你无法否认它们产出的数量之巨大。数据随处可见,横跨技术栈与行业,无法辩驳。

AI is okay at building everything from scratch, but it is really good at gluing together high quality, well documented, and proven components. And, AI prefers to do this when it can unless explicitly prompted otherwise. This is the "building block" nature of software today: we're more than ever before grabbing off the shelf components and gluing them together.

AI 当然也能从零搭建一切,但它在把高质量、文档完善、且已经被验证的组件“粘”在一起这件事上,真的很擅长。而且只要条件允许,除非你明确提示它不要这样做,AI 会偏好这么做。这就是今天软件的“积木”属性:比以往任何时候都更频繁地从货架上拿现成组件,然后把它们粘合起来。

Humans, of course, always have done this as well. For my entire career, human software developers have preferred to build on top of proven primitives. But the natural barrier to entry of understanding the component pieces well enough to even slap them together was high enough to limit the ecosystem. This barrier is now gone.

当然,人类一直也在做这件事。我的整个职业生涯里,人类软件开发者都更愿意在被验证过的基础原语之上继续构建。但过去要把组件理解到足以“先拼起来再说”的门槛高到足以限制生态规模。这个门槛现在消失了。

Exports Are Up

导出在上升

Coming out of these factories is of course software. So much software.

从这些工厂里出来的当然是软件。大量的软件。

There are negatives to this. I think the negatives are obvious enough that I'm not going to dedicate much time to them, but I want to recognize they exist: security vulnerabilities, instability, a general lack of understanding about how load-bearing systems might work.

这有负面影响。我认为负面已经足够明显,不打算花太多篇幅展开,但需要承认它们确实存在:安全漏洞、不稳定,以及对承载关键负载的系统如何运作的普遍缺乏理解。

But there are a huge amount of positives:

但正面也非常多:

  • The quality bar is lower. A mainline application used by a large cross-section of users has to weigh every feature against every other feature: how do they interact? does it make sense for the long term vision? can I maintain this for millions of users? A factory artifact targeting one to hundreds of users doesn't need to care about this. You can ship faster and looser, as a result.
  • 质量门槛更低。 一个被大量不同用户使用的主线应用,必须把每个功能与其他功能一起权衡:它们如何交互?是否符合长期愿景?能否为数百万用户维护它?而一个面向一到几百名用户的工厂产物不需要在乎这些。于是可以更快、更松弛地交付。
  • The awareness is greater. A mainline application can't do everything. It usually optimizes for the use cases that the most users need and use. A factory artifact can optimize for a tiny cross-section of users, and these users gain awareness of the building block as a result. I'm seeing this hugely in Ghostty, as very niche communities are getting terminals.
  • 认知更广。 主线应用不可能做所有事。它通常会针对最多用户最常用的场景做优化。工厂产物可以为极小的一部分用户做优化,而这些用户因此会对这个积木式构件产生认知。我在 Ghostty 上强烈地看到这一点:非常小众的社区也开始拥有适合他们的终端。
  • The maintenance burden is lower. It is easier than ever to say "no thank you" to feature requests, because you're offering a key part of the means to production. My challenges with slop requests is very public, to the point I made a "no machine", but I'm also feeling less and less bad every day about saying "no."
  • 维护负担更低。 现在,维护者对功能请求说“不了,谢谢”比以往任何时候都容易,因为你提供的是生产资料中的关键一环。关于我对“糊弄式”请求的困扰,已经很公开了,公开到我做了个“no machine”,但每天对说“不”这件事的内疚感也在持续下降。
  • R&D is outsourced. It is so much easier now as a maintainer to look at what others are doing, see working proof of concepts, and decide what you want to bring back to mainline. There's way less talk and way more walk. And while others walk you can cherry pick the best ideas (this is fair: you're giving away a building block and they're giving away their ideas).
  • 研发被外包。 作为维护者,现在更容易去观察别人做了什么,看到能跑的概念验证,再决定哪些要带回主线。嘴上讨论少了,动手做事多了。别人走在前面时,你可以挑拣最好的点子带走(这很公平:你免费给出一个积木式构件,他们也免费给出他们的想法)。

The Impact

影响

This is changing how I view software and product development.

这正在改变我看待软件与产品开发的方式。

I'm much more purposeful about creating building blocks and encouraging applications or forks on top of that. I think this is resulting in a happier community, a larger community, and ultimately better mainline software.

我更有意识地去创造积木式构件,并鼓励大家在其之上做应用或 fork。我认为这带来了更开心的社区、更大的社区,并最终带来更好的主线软件。

High-quality applications aren't disappearing. And high-quality applications produced by the developers of the building block aren't disappearing. In my case, Ghostty the application isn't disappearing because libghostty the building block exists.

高质量应用不会消失。由积木式构件的开发者自己做出来的高质量应用也不会消失。就我而言,Ghostty 这个应用不会因为 libghostty 这个积木式构件存在而消失。

Instead, I think the mainline application is becoming more stable and more purposeful in its feature set. The stability comes from a much larger and diverse user group. The feature set comes from the massive ecosystem of outsourced R&D.

相反,我认为主线应用会变得更稳定,在功能集合上也更有目的性。稳定性来自更庞大且更多样的用户群。功能集合来自规模巨大的外包式研发生态。

The Elephant in the Room: Commercialization

房间里的大象:商业化

The obvious question that follows is what this can mean for commercialization. Closed source, commercial software appears to be at a massive disadvantage. And it is.

接下来最显而易见的问题是,这对商业化意味着什么。闭源的商业软件看起来处于巨大的劣势。确实如此。

Agents will more readily pick open and free software over closed and commercial. At the time of writing this article, this is an objective truth. Independent research labs running experiments on popular models have found repeatedly that under diverse circumstances, models pick open and free alternatives over commercial. So far.

智能体会更倾向选择开放且免费的软件,而不是闭源的商业软件。在写下这篇文章的时刻,这是一条客观事实。独立研究实验室在流行模型上反复做过实验,发现即使在多样化的情境下,模型也会选择开放且免费的替代方案,而不是商业方案。至少目前如此。

But, I don't have a concrete answer here, because unlike product and software development, I'm not directly building a commercializable product right now. I have thoughts, and as with all hard things, I think the answer is nuanced. But, I don't want to give the illusion of talking authoritatively about this so I'm going to avoid it. When I walk the walk and learn more, I'll share more.

但我在这里没有一个明确答案,因为不同于产品与软件开发,我现在并没有在直接构建一个可商业化的产品。我有一些想法,和所有难题一样,我认为答案很微妙。但我不想制造一种自己在权威发言的错觉,所以会避免展开。等真正走到那一步、学到更多之后,再分享更多。

I'm once again simply acknowledging that this challenge obviously exists.

这里只是再次承认,这个挑战显然存在。

The Shift Has Happened

转变已经发生

We have to accept that building blocks and software factories rule everything around us and accept and internalize the consequences of that.

必须接受积木式构件与软件工厂正在支配我们周遭的一切,并接受、内化由此带来的后果。

We can choose to run the other direction and create enclaves where we fight against it. Or we can choose to submit ourselves completely to the chaos. People who know me know I'm far less extreme in my actions and carry different opinions depending on context.

可以选择往相反方向跑,建立一些与之对抗的飞地。也可以选择完全把自己交给混沌。了解我的人知道,我的行动远没有这么极端,我会因情境不同而持有不同观点。

The point is the shift has already happened. We're living in it.

重点在于,转变已经发生。我们正活在其中。


  1. Getting exact numbers is obviously hard since Ghostty has no real tracking. We can see aggregate update file checks for macOS. We have no visibility at all into Linux. libghostty has no tracking but tools integrating libghostty might and have shared aggregates with us. 


  1. 要拿到精确数字显然很难,因为 Ghostty 没有真正的追踪。我们能看到 macOS 的更新文件检查总量。对 Linux 则完全不可见。libghostty 也没有追踪,但集成 libghostty 的工具可能有,并且曾与我们分享过汇总数据。 


  1. This article was written by hand, without the assistance of AI. I love and use AI abundantly, but I draw the line personally at content. I want posts to reflect who I am directly. 


  1. 这篇文章是手写完成的,没有借助 AI。我非常喜欢也大量使用 AI,但在内容上,我个人划了一条线。我希望文章能直接反映我是谁。 

The most effective way to build software and get massive adoption is no longer high quality mainline apps but via building blocks that enable and encourage others to build quantity over quality.

Ghostty in 18 months: one million daily macOS update checks. libghostty in 2 months: multiple millions of daily users. 1

Similar growth trajectories can be seen in other "building block" technologies: Pi Mono, Next.js, Tailwind, etc.

Experiencing this firsthand as well as witnessing it in other ecosystems has fundamentally shifted how I view the practice of product and software development today, regardless of commercial vs non-commercial goals.

Imports Are Up

I use the term "building block" to describe how they're being used because they're being assembled today in a very different way than former decades.

I don't use the term "library" or "framework" because it extends even up to "applications" (e.g. the Ghostty GUI app has more forks than ever before with customized patches on top, which is awesome).

The factory of today is agentic. I say that as objective truth, regardless of what your feelings about it are. You can argue that 99% of the stuff coming out of these factories is total crap, but you can't argue the sheer quantity of stuff coming out. The numbers are everywhere spanning tech stacks and industries and they're undeniable.

AI is okay at building everything from scratch, but it is really good at gluing together high quality, well documented, and proven components. And, AI prefers to do this when it can unless explicitly prompted otherwise. This is the "building block" nature of software today: we're more than ever before grabbing off the shelf components and gluing them together.

Humans, of course, always have done this as well. For my entire career, human software developers have preferred to build on top of proven primitives. But the natural barrier to entry of understanding the component pieces well enough to even slap them together was high enough to limit the ecosystem. This barrier is now gone.

Exports Are Up

Coming out of these factories is of course software. So much software.

There are negatives to this. I think the negatives are obvious enough that I'm not going to dedicate much time to them, but I want to recognize they exist: security vulnerabilities, instability, a general lack of understanding about how load-bearing systems might work.

But there are a huge amount of positives:

  • The quality bar is lower. A mainline application used by a large cross-section of users has to weigh every feature against every other feature: how do they interact? does it make sense for the long term vision? can I maintain this for millions of users? A factory artifact targeting one to hundreds of users doesn't need to care about this. You can ship faster and looser, as a result.

  • The awareness is greater. A mainline application can't do everything. It usually optimizes for the use cases that the most users need and use. A factory artifact can optimize for a tiny cross-section of users, and these users gain awareness of the building block as a result. I'm seeing this hugely in Ghostty, as very niche communities are getting terminals.

  • The maintenance burden is lower. It is easier than ever to say "no thank you" to feature requests, because you're offering a key part of the means to production. My challenges with slop requests is very public, to the point I made a "no machine", but I'm also feeling less and less bad every day about saying "no."

  • R&D is outsourced. It is so much easier now as a maintainer to look at what others are doing, see working proof of concepts, and decide what you want to bring back to mainline. There's way less talk and way more walk. And while others walk you can cherry pick the best ideas (this is fair: you're giving away a building block and they're giving away their ideas).

The Impact

This is changing how I view software and product development.

I'm much more purposeful about creating building blocks and encouraging applications or forks on top of that. I think this is resulting in a happier community, a larger community, and ultimately better mainline software.

High-quality applications aren't disappearing. And high-quality applications produced by the developers of the building block aren't disappearing. In my case, Ghostty the application isn't disappearing because libghostty the building block exists.

Instead, I think the mainline application is becoming more stable and more purposeful in its feature set. The stability comes from a much larger and diverse user group. The feature set comes from the massive ecosystem of outsourced R&D.

The Elephant in the Room: Commercialization

The obvious question that follows is what this can mean for commercialization. Closed source, commercial software appears to be at a massive disadvantage. And it is.

Agents will more readily pick open and free software over closed and commercial. At the time of writing this article, this is an objective truth. Independent research labs running experiments on popular models have found repeatedly that under diverse circumstances, models pick open and free alternatives over commercial. So far.

But, I don't have a concrete answer here, because unlike product and software development, I'm not directly building a commercializable product right now. I have thoughts, and as with all hard things, I think the answer is nuanced. But, I don't want to give the illusion of talking authoritatively about this so I'm going to avoid it. When I walk the walk and learn more, I'll share more.

I'm once again simply acknowledging that this challenge obviously exists.

The Shift Has Happened

We have to accept that building blocks and software factories rule everything around us and accept and internalize the consequences of that.

We can choose to run the other direction and create enclaves where we fight against it. Or we can choose to submit ourselves completely to the chaos. People who know me know I'm far less extreme in my actions and carry different opinions depending on context.

The point is the shift has already happened. We're living in it.


  1. Getting exact numbers is obviously hard since Ghostty has no real tracking. We can see aggregate update file checks for macOS. We have no visibility at all into Linux. libghostty has no tracking but tools integrating libghostty might and have shared aggregates with us. 

  2. This article was written by hand, without the assistance of AI. I love and use AI abundantly, but I draw the line personally at content. I want posts to reflect who I am directly. 

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