【文章标题】：How to turn your AI into a world-class designer
如何将你的AI培养成世界级设计师
【文章正文】：
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I’d always thought AI was bad at design. But after reading this mind-blowing post by Anshu Chimala, I realize I was just doing it wrong.
我曾认为AI不擅长设计。但读完Anshu Chimala这篇令人震撼的文章后，我才意识到是自己方法不对。
Anshu led software engineering and design teams at Apple for 12 years, focusing on research and prototyping for future AI products. He regularly shares design tutorials and demos on X (he’s one of my favorite follows). For deeper dives into crafting distinctive experiences with AI, check out his Substack and connect with him on LinkedIn.
Anshu曾在苹果领导软件工程与设计团队12年，专注于未来AI产品的研究与原型开发。他常在X平台分享设计教程和演示（是我最爱的关注者之一）。想深入了解如何用AI打造独特体验，可订阅他的Substack或在LinkedIn联系他。
Let’s get into it.
进入正题。
A conversational calorie tracker, built in three prompts with Claude Fable 5:
用Claude Fable 5通过三次提示构建的对话式卡路里追踪器：
A space exploration game, built in two prompts with Claude Opus 5:
用Claude Opus 5通过两次提示构建的太空探索游戏：
A dynamic landing page, built in three prompts with Claude Opus 5 + GPT-5.6 Sol:
用Claude Opus 5+GPT-5.6 Sol通过三次提示构建的动态落地页：
I often post AI design demos like these on X. Every time I do, someone inevitably asks, “Why does the model create all this incredible stuff for you, but when I try, I only get generic slop? It’s like you’re using a completely different model.”
我常在X平台发布这类AI设计演示。每次总有人问：“为什么模型能为你创造这些惊人作品，而我只能得到平庸结果？好像你用的完全是另一个模型。”
I’m not using a different model, but I am getting more out of the models I work with. Most people only see 1% of AI’s creative potential. I want to show you how to tap into the other 99%.
我用的模型相同，但挖掘得更深。大多数人只看到AI 1%的创意潜力。我将展示如何解锁剩下的99%。
AI models are capable of amazing creativity, but that creativity gets stifled by how they’re trained.
AI模型本具备惊人创造力，但其训练方式抑制了这种能力。
Large language models are next-token predictors: at each step, they look at a sequence of text and predict what comes next based on millions of examples. The results may be rated by humans, and those ratings fed back into the model. This teaches the model to make consistent, safe choices that fit everyone’s preferences.
大语言模型是”下一词预测器”：它们根据数百万案例预测文本序列的下一个词。人类对结果的评分反馈给模型，使其倾向于做出符合大众偏见的稳妥选择。
This makes typical LLMs great at most tasks but poor designers. To create a design, an LLM has to build it out token by token. Whenever it needs to make a design decision—what colors to use, or how to arrange elements—the model fills in the tokens it thinks are most likely to please everyone. As a result, the design usually ends up being repetitive and bland. It’s like the ultimate case of design-by-committee.
这使得通用大模型虽擅长多数任务，却是糟糕的设计师。当需要逐词构建设计时，模型总会选择最讨好大众的方案——最终产出重复乏味的作品，就像委员会设计的终极案例。
Great design, on the other hand, starts with feeling and aims to create an emotional response. It bends the rules and delights users with memorable, unexpected choices. Great design is exactly the opposite of what an LLM does naturally, which is to make the most predictable choice at every step.
伟大设计始于情感共鸣，通过打破常规带来惊喜。这与大模型的本能完全相悖——后者每一步都选择最可预测的方案。
However, if we can get the model to reach beyond the most predictable choices, we can access a vast landscape of creative ideas that most people miss out on.
但若能引导模型突破惯性思维，就能解锁被多数人忽视的创意疆域。
This is a lesson I learned from managing human designers, before I was managing AI ones. For most of my career at Apple, I led an R&D team designing exploratory future AI products. Early on, our preconceived notions about how user interfaces should work limited our creativity and kept us returning to the same old ideas. Through rigor and new processes, we learned to stop re-creating what’s comfortable and instead look to the fringes of what’s possible, to generate something new. We became experts at polishing the little details to an Apple level of quality.
这是我在管理人类设计师时就领悟的道理。在苹果领导AI产品研发团队时，我们曾因固有认知陷入创意窠臼。后来通过严格流程，我们学会突破舒适区，在可能性边缘探索，最终打磨出苹果级品质的细节。
Since my time at Apple, I’ve been working on applying that same process to my work with AI. In the past couple years, AI agents have become extremely capable. They can do in hours what used to take my team weeks. And with the right guidance, they can create designs that look completely unlike anything else.
离开苹果后，我将这套方法应用于AI。如今AI智能体能在数小时完成团队过去数周的工作，在正确引导下更能创造出独一无二的设计。
Loosely inspired by the Double Diamond design process, I’ve reimagined the design process for a team of AI agents instead of human designers:
受双钻设计流程启发，我为AI团队重构了设计流程：
Discover new ideas beyond the average slop by exploring a variety of directions and creating bold, ambitious design briefs.
探索阶段：通过多方向探索和大胆的设计概要，突破平庸创意。
Define an individual design identity by pushing AI beyond its familiar patterns and chaining models together to fully realize the design’s potential.
定义阶段：突破AI惯用模式，串联多模型充分释放设计潜力。
Deliver a stunning final result by polishing away the sloppy rough edges and focusing on the key elements.
交付阶段：打磨粗糙细节，聚焦关键元素呈现惊艳成品。
By following these stages and applying the techniques within each one, you can create an incredible design remarkably quickly—and make people ask, “Why does AI create magic for you (and not me)?”
遵循这三阶段并运用对应技巧，你就能快速产出惊人设计——让人不禁发问：“为什么AI独为你创造奇迹？”
Discover: Explore the space of possibilities
探索阶段：可能性空间的开拓
The hardest part of the design process is looking at a blank screen with infinite possibilities. The best way to tackle that moment is to start by going broad before going deep. AI is an excellent tool to explore a wide variety of potential directions.
设计最难的莫过于面对充满无限可能的空白画布。最佳策略是先广度后深度，而AI正是探索多元方向的利器。
As we know, though, models tend to overrely on familiar patterns and make conser
但众所周知，模型往往过度依赖熟悉模式并做出保…（翻译中断）