神译局是36氪旗下编译团队，关注科技、商业、职场、生活等领域，重点介绍国外的新技 术、新观点、新风向。 编者按：痴迷于用AI提效，可能正以惊人的速度，解决着错误的问题。文章来自编译。 大家的共同执念显而易见：学会用人工智能更快地执行，你就能保持竞争力。每天我都能在领英上看到 关于"提示工程"的新帖子，又一门关于"AI生产力技巧"的课程，又一个让ChatGPT写出更好的代码、创 建更棒的演示文稿或自动化工作流程的框架。 但有个没人谈论的事实是：人工智能只会让糟糕的决策变得更快，而不是让决策变得更好。而且，当下 最危险的处境并非在人工智能工具上落后，而是以超凡的效率去解决错误的问题。 在一个由人工智能驱动的世界里，真正的竞争优势并非执行速度，而是从一开始就知道哪些问题值得解 决。这也正是让"设计思维"成为你秘密武器的用武之地。 对执行力的痴迷正在将我们引入歧途 大多数人认为，人工智能的成功等于更好的提示词加上更快的执行速度。 我曾亲眼目睹我所在组织的团队沉醉于人工智能带来的生产力提升。他们能在几小时内完成过去需要数 天才能完成的分析，以闪电般的速度制作演示文稿，自动化那些他们一直想简化的流程。 可是，他们却比以往 ...

"我的使命就是让今天的政府服务像 Apple Store 一样令人满意：设计美感、用户体验优秀， 并运行于现代化软件之上。"Business Insider Africa 落实改革进度：瞄准美国建国 250 周年 全球企业观察 美国总统特朗普于 2025 年 8 月正式签署行政命令，设立国家设计工作室（National Design Studio， NDS），并任命 Airbnb 联合创始人乔·杰比亚（Joe Gebbia）为美国历史上首位"首席设计官"（Chief Design Officer, CDO）。这一角色将直属白宫幕僚长，负责推动联邦政府从视觉与交互体验层面展开深 度改革，以实现"美观、现代、易用" 的数字政务服务。The Washington PostAxiosThe Times of India 乔·杰比亚的设计愿景：打造"Apple Store 式体验" 在接受 Axios 的采访中，杰比亚直言，美国政府的网站与移动 App 是"民众与政府接触的前门"，目前 却"过时且令人沮丧"，堪称数字化"盲点"与"坑洼路面"。他强调，"没有理由让我们的政府不能成为优 秀设计的标准"，目标是打造"像 Ap ...

Core Insights - AI tools are accelerating the software development process while exposing significant capability gaps among different teams, leading to output differences of up to tenfold or more [1] - The concept of "AI-native development" requires a complete redesign of the development system, integrating AI at every stage from prototyping to deployment [1] - The conversation with Cedric Ith, founder of Perceptron AI, highlights the need for developers to collaborate effectively with AI, focusing on what successful teams do right [1][2] Group 1: Key Experiences from Cedric - Taste is the new competitive advantage, shifting focus from technical skills to design thinking and product intuition in an era where AI can generate code rapidly [3] - The ability to ask precise questions and create delightful user experiences is becoming the new barrier to entry in software development [3] - AI is redefining the design process, allowing designers to explore numerous concepts quickly and generate user-centric solutions [3] Group 2: New Design Paradigms - Natural language is emerging as a primary design interface, shifting the designer's role from creating visuals to articulating product structure through language [4][5] - Designers are developing a "design vocabulary" to communicate effectively with AI, enabling rapid prototyping that previously took engineers days to complete [5][6] - The ability to break down complex requests into clear, executable language is becoming essential for effective collaboration with AI [6] Group 3: The Rise of Design Engineers - The traditional boundary between design and engineering is dissolving, with designers now able to contribute directly to code and manage the entire tech stack [7][8] - This shift enhances efficiency and redefines product manufacturing, as designers gain control over the entire delivery process [8][9] - The iterative speed of design and development has significantly increased, compressing the time between design reviews and implementation from days to hours [10] Group 4: AI-Native Design Principles - Key principles for AI product design include reducing cognitive load, accepting non-determinism, and ensuring transparency in AI reasoning processes [11][12][13] - The design focus is shifting from user execution to user orchestration, requiring designs that facilitate coordination among multiple intelligent agents [14] - Teams adopting these principles early will create more intuitive and trustworthy AI experiences [14] Group 5: Organizational Adaptation in the AI Era - Organizations must transition from building perfect products to creating rapid learning organizations to keep pace with the fast-evolving AI landscape [15][16] - Cedric emphasizes the importance of quickly producing high-fidelity prototypes to gain internal buy-in, making design a catalyst for organizational change [16] - The entire product development cycle is being compressed, leading to unprecedented innovation density [16] Group 6: Cedric's AI Design Stack - The design stack includes tools like Figma for visual design, v0 for dynamic behavior definition, and Cursor for code-level adjustments, facilitating seamless transitions between design and engineering [17] - Component libraries like Shadcn and Tailwind provide standard semantics for AI, reducing risks associated with hallucinations in code generation [17]