AI has a multiplying effect on existing technical skills
AI has a multiplying effect on existing technical skills
AI 对现有技术能力具有乘数效应
Hi there! I want to talk a bit about AI and the related shifts in the tech industry. I know this is top-of-mind for lots of y’all, and you might be wondering if it even makes sense to learn new programming skills in this environment. 大家好！我想聊聊人工智能以及它给科技行业带来的相关变革。我知道这是许多人目前最关心的问题，你可能也在怀疑，在这种环境下学习新的编程技能是否还有意义。
Let’s start with an uncomfortable truth: AI models have become shockingly good at completing a wide variety of programming tasks. They’re certainly not perfect, but in many cases, they’re good enough. I’m not happy about this, for a wide variety of ethical/environmental/safety reasons, but it is what it is. 让我们先从一个令人不安的事实说起：AI 模型在完成各种编程任务方面已经变得极其出色。它们当然还不完美，但在许多情况下，它们已经足够好用了。出于各种伦理、环境和安全方面的考虑，我对此并不感到高兴，但事实就是如此。
In this email, I want to zoom into one specific thing: I think people are jumping to the wrong conclusion about what AI means for their careers. Alright, so the biggest concern I’ve seen from my fellow developers is that human developers won’t be necessary in the near future, since LLMs (Large Language Models) will be able to fully design and build projects of all sizes and scales. And, well, I just haven’t seen any evidence of that. 😅 在这封邮件中，我想重点探讨一件事：我认为人们对 AI 对职业生涯的影响得出了错误的结论。我从同行开发者那里看到的最大担忧是，在不久的将来，人类开发者将不再被需要，因为大语言模型（LLM）将能够完全设计和构建各种规模的项目。然而，我并没有看到任何证据支持这一点。😅
In fact, it’s kind of the opposite. The biggest AI success stories I’ve seen have been from people who are highly technical, folks with deep subject matter expertise. For example, Matt Perry recently shared in his newsletter that he was leaning into AI in 2026. Matt is the author of several animation libraries including Popmotion, Motion One, and Motion (formerly Framer Motion). There aren’t many people on this planet who know as much about animations on a technical level. 事实上，情况恰恰相反。我所见过的最成功的 AI 应用案例，都来自那些技术能力极强、在特定领域拥有深厚专业知识的人。例如，Matt Perry 最近在他的通讯中分享了他如何在 2026 年全面拥抱 AI。Matt 是多个动画库的作者，包括 Popmotion、Motion One 和 Motion（前身为 Framer Motion）。在这个星球上，在技术层面了解动画的人寥寥无几。
The layout projection engine he created for Motion is one of the most sophisticated pieces of engineering I’ve ever seen. In his email, Matt explains that he set a goal of closing 60 issues in Q1, and wound up closing 160. He wanted to do a major refactor of Motion in Q2, and got it done in a single January afternoon! AI has significantly boosted his productivity. 他为 Motion 创建的布局投影引擎是我见过最复杂的工程杰作之一。Matt 在邮件中解释说，他原本设定了第一季度解决 60 个问题的目标，结果最终解决了 160 个。他原本计划在第二季度对 Motion 进行重大重构，结果在 1 月份的一个下午就完成了！AI 显著提升了他的生产力。
This is remarkable, and you might think that this is evidence that LLMs are even better than the best human developers… but that implies that everyone is having the same success with AI tooling as Matt. And that’s just not true. Every now and then, I pop into the /r/vibecoding subreddit, a place where people (mostly with little to no dev experience) share their experiences with vibe-coding, and there are countless stories like this: Without guidance, LLMs tend to paint themselves into a corner, because they’re generating code to solve individual prompts, not thinking holistically about an application’s architecture. 这非常了不起，你可能会认为这是 LLM 比最优秀的人类开发者更强的证据……但这暗示了每个人都能像 Matt 一样成功地使用 AI 工具。事实并非如此。我偶尔会逛逛 /r/vibecoding 子版块，那里的人（大多几乎没有开发经验）分享他们“凭感觉编程”（vibe-coding）的经历，有无数这样的故事：如果没有引导，LLM 往往会陷入死胡同，因为它们是在生成代码来解决单个提示，而不是从整体上思考应用程序的架构。
So, on the one hand, I’m seeing the most talented developers I know amplify what they can do with AI, and on the other, I’m seeing people with less domain knowledge struggle to get past the “MVP” stage. AI is a tool, and tools need to be wielded proficiently. You could give me Jimi Hendrix’s exact guitar but it would sound very different if I tried to play it! I also wouldn’t be able to cook like Gordon Ramsey if I had access to his kitchen, or serve like Serena Williams if you handed me her tennis racket. 所以，一方面，我看到我认识的最有才华的开发者利用 AI 放大他们的能力；另一方面，我也看到那些领域知识较少的人在跨越“MVP”（最小可行性产品）阶段时举步维艰。AI 是一种工具，而工具需要熟练掌握。你可以把吉米·亨德里克斯（Jimi Hendrix）的吉他给我，但如果由我来弹，声音会完全不同！如果我能使用戈登·拉姆齐（Gordon Ramsey）的厨房，我也做不出他那样的菜；如果把小威廉姆斯（Serena Williams）的网球拍给我，我也打不出她那样的发球。
We tend to overweight the importance of tools, and I think this is a nearly-universal human bias. Marketing teams routinely take advantage of this, selling us Michael Jordan’s sneakers with “air technology” as if that’ll suddenly grant us the ability to dunk. 😅 I think it’s harder for us to see AI agents as tools because we’ve anthropomorphized them. If my basketball started telling me what a great basketball player I am, I might be less inclined to see it as a tool as well! 我们往往过分看重工具的重要性，我认为这是一种几乎普遍存在的人类偏见。营销团队经常利用这一点，向我们兜售迈克尔·乔丹（Michael Jordan）的“气垫技术”运动鞋，仿佛穿上它我们就能突然学会扣篮一样。😅 我认为我们很难将 AI 代理视为工具，因为我们已经将它们拟人化了。如果我的篮球开始夸我是个伟大的球员，我可能也会不太愿意把它仅仅看作一个工具！
When we treat LLMs like little autonomous robots, we start to give them more credit than they deserve, and it starts to feel plausible that they could one day replace us. But that’s not the right mental model. I think AI tools are more like Iron Man’s suit. It can do incredible things, but not on its own. Similarly, if Matt Perry handed me the keys to the Motion repository and told me to take over, I wouldn’t have the same results even though I have access to the same set of LLM tools. If I tried to move at the same cadence, I’d wind up making a huge mess of things. 😂 当我们把 LLM 当作小型自主机器人时，我们开始给予它们过高的评价，并觉得它们有朝一日取代我们似乎变得“合理”了。但这不是正确的思维模型。我认为 AI 工具更像是钢铁侠的战甲。它能做不可思议的事情，但不能独立运作。同样地，如果 Matt Perry 把 Motion 仓库的钥匙交给我让我接手，即使我拥有同样的 LLM 工具，我也无法取得同样的成果。如果我试图以同样的节奏推进，最终只会把事情搞得一团糟。😂
So, this is the big mistake I think people are making. We look at what a skilled developer can do with an LLM and credit the LLM rather than the skilled developer. My experience suggests that AI has a multiplying effect on our existing technical skills, so the more we understand web development, the more effective we’ll be with AI. 所以，我认为人们犯了一个巨大的错误。我们看到熟练的开发者利用 LLM 取得的成就，却把功劳归于 LLM 而非开发者本人。我的经验表明，AI 对我们现有的技术能力具有乘数效应，因此我们对 Web 开发了解得越深，使用 AI 的效率就越高。
Whimsical Animations
奇思妙想的动画
On Monday, I launched my brand-new course, Whimsical Animations. ✨ I’ve been building websites and web applications for nearly 20 years now, and in that time, I’ve learned a lot about how to craft memorable, impactful animations and interactions. It’s my favourite part of web development, and I’ve spent a lot of time experimenting and discovering what works and what doesn’t. 周一，我发布了我的全新课程《Whimsical Animations》（奇思妙想的动画）。✨ 我从事网站和 Web 应用程序开发已经近 20 年了，在此期间，我学到了很多关于如何制作令人难忘且具有影响力的动画和交互的知识。这是我最喜欢的 Web 开发部分，我花了很多时间进行实验，探索什么有效，什么无效。
It’s been a very interesting road, learning about animation. There’s a vast sea of information out there, but very little of it is targeted towards web developers. I’ve had to adapt a bunch of concepts from the world of game development, things like linear interpolation, simplex noise, and delta time. This stuff isn’t part of the typical “web developer” skillset, and as a result, it can make our projects really stand out! 学习动画的过程非常有趣。市面上有海量的信息，但针对 Web 开发者的却寥寥无几。我不得不从游戏开发领域借鉴了一系列概念，比如线性插值（linear interpolation）、单纯形噪声（simplex noise）和增量时间（delta time）。这些东西不属于典型的“Web 开发者”技能集，因此，它们能让我们的项目真正脱颖而出！
It’s never been easier to learn about new topics, with tools like ChatGPT that can answer any questions you have. But that only works when you know what questions to ask. My course offers a curated curriculum that will introduce you to all sorts of new techniques. I think you’ll be amazed at what you can build after taking the course. 😄 Registration is now open, but there’s not too much time left in the launch sale. 有了像 ChatGPT 这样可以回答你任何问题的工具，学习新主题从未如此简单。但前提是你得知道该问什么问题。我的课程提供了一套精心策划的教学大纲，将向你介绍各种新技术。我相信在学习完这门课程后，你会对自己能构建出的作品感到惊讶。😄 注册现已开放，但发布促销活动的时间所剩不多了。