编译自 Lex Fridman Podcast 出品 | CSDN（ID：CSDNnews） 原文 | https://lexfridman.com/dhh-david-heinemeier-hansson-transcript 投稿或寻求报道 | zhanghy@csdn.net 以下是对这次长达六小时访谈的部分翻译，我们节选了其中最精华、最与我们行业息息相 关的部 分。 · · · 「我不理解变量有什么用」 传 奇 程 序 员 、 Ruby on Rails 框 架 创 始 人 David Heinemeier Hansson (DHH) 最 近 做 客 Lex Fridman 播客，来了一次深度对话。 David Heinemeier Hansson ，通常被称为 DHH，是软件开发领域一位标志性的人物。作为热门 Web 开发框架 Ruby on Rails 的创造者，他不仅改变了无数程序员构建网络应用的方式，更以 37signals（现 Basecamp & HEY）联合创始人的身份，倡导着一种"拒绝风险投资、远程优先、可 持续发展"的商业哲学。 DHH 以其直言不讳和鲜明的观点而闻名。他从不回避争议 ...

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：本文作者现身说法，戳破"万能AI提示词"的营销泡沫，分享其基于任务类型（日常编码/宏观设计/并行开发）精准选用AI工作流的实战经验。通过 三种分层协作模式，作者将编程效率提升至新维度，为开发者提供了极具参考价值的LLM应用范式。文章来自编译。 过去需要我花一周时间编程的工作，如今几小时就能完成。诀窍在于弄清楚哪种AI工作流最适合你的问题。 我上周在X平台上花了三个小时，看着那些提示词大师推销他们最新的"万能灵药"： "用这个ChatGPT提示词，就能取代你整个工程团队。" "搭配这个秘密系统提示词来使用Claude，就能超越所有开发者。" "我这份497美元的提示词库，能让你成为效率10倍的码农。" 与此同时，我给Cora（我们的AI邮件助手）推出了五个新功能，里面用到了Anthropic、Google以及OpenAI这三家提供的模型，但上述"神奇提示词"一个都 没有用。我没找到一个完美的提示词或工具来包揽我所有工作。事实上，我已经不再寻找这种"万能钥匙"了。相反，我根据手头要解决的具体问题来选择不 ...

作者｜冬梅 最近有个金额不算特别巨大的收购案在技术圈内引发持续关注：海外互联网巨头 Wix 斥资 8000 万美元（约 5.7 亿人民币）现金，买下一家成立仅 6 个月的 AI 小公司 Base44。 这家公司到底有多神奇？它的创始人身上有着这样几个标签：90 后、独立开发者、白手起家 的"富一代"。 据报道，Base44 作为一家独立公司成立六个月后，用户数量增长至 25 万，并在成立后的三周内 就达到了 1 万。根据 Shlomo 在 X 和 LinkedIn 上的帖子，该公司已实现盈利，即使在支付了高 昂的大语言模型 token 成本（他也公开记录了这一点）后，5 月份仍实现了 18.9 万美元的利 润。 这个时代最大的红利是，AI 降低了创业门槛，普通人也能借助 AI 工具快速变现。 其实在创建 Base44 项目之前，Shlomo 在 AI 创业圈已经小有名气。 Shlomo 今年 31 岁，是一位前端开发者。早在 2017 年，他就与朋友共同创办数据分析公司 Explorium，经过 8 年的发展，Explorium 目前拥有 100 多名员工，并获得全球知名投资机构 Insight Partne ...

Meanwhile, tech giants like Meta and Google now say they're planning to have AI do as much as half of all of their coding. But some new research suggests the productivity gains from that might not be as impressive as early reports suggest. Dearra Bosa has more in Tech Check.Dearra, so Kelly, this study has touched off a nerve. We're not saying here that AI isn't leading to be productive. We're just saying that AI tools, yes, they're here and they're being used.The payoff may be more uneven than the hype sug ...

Group 1 - The A-share software development sector experienced a midday surge, with Zhongrun Optical rising over 10% [1] - Jiuqi Software quickly reached its daily limit, indicating strong investor interest [1] - Other stocks such as Fanwei Network, Yongyou Network, and Zhiyuan Interconnection also saw gains, reflecting a broader positive trend in the industry [1]

Core Insights - The article highlights the success story of Maor Shlomo and his product Base44, which is an AI-powered no-code platform that allows users to generate full-stack applications using natural language, achieving significant user growth and a successful exit in just six months [2][6][7]. Group 1: Product Development and Unique Approach - Base44 was developed to address real user needs, with 90% of its code generated by AI, showcasing a unique approach in the competitive AI startup landscape [2][6]. - The platform allows users to create applications without needing to integrate third-party services, providing a "self-contained" experience [6][7]. - The initial motivation for creating Base44 stemmed from personal experiences, including the challenges faced while building a website for a girlfriend's art studio and the software needs of a large volunteer organization [10][11][12]. Group 2: User Acquisition and Growth Strategies - The initial user base was built through personal connections, with early adopters providing feedback and sharing the product with others, leading to organic growth [15][16]. - The concept of "Build in Public" was effectively utilized, where sharing progress and updates on platforms like LinkedIn helped in gaining community support and user engagement [19][23]. - The product saw rapid user growth, reaching 4000 new users per day after implementing community-driven initiatives and incentives for sharing [20][19]. Group 3: Insights on Entrepreneurship and Market Dynamics - The article emphasizes that independent entrepreneurship can be advantageous in certain markets, especially when products have viral potential and can achieve product-market fit [38][42]. - It discusses the importance of focusing on tasks that align with personal strengths and interests, suggesting that at least 50% of time should be spent on enjoyable and proficient activities to maintain motivation [48][49]. - The narrative also reflects on the changing landscape of entrepreneurship, where smaller teams can leverage AI to compete effectively against larger companies, diminishing the absolute advantage of team size and funding [42][39].

Group 1 - Trifork Switzerland has been selected as a subcontractor to Deloitte Switzerland for the DigiSanté framework agreement, focusing on healthcare standards [1][3] - The DigiSanté program aims to enhance the Swiss digital health infrastructure through standards-based development and secure data architecture [2][4] - The agreement allows for up to 144,000 hours of work over nine years, with a total value ranging from CHF 27.7 million to CHF 38.8 million [3] Group 2 - Deloitte and Trifork will leverage their combined expertise in standards and healthcare system architecture to support the Swiss Federal Office of Public Health [4][5] - Trifork has significant experience in regulated health software development and is involved in national initiatives like the electronic patient dossier [4][9] - The collaboration is seen as a strategic move to support the long-term goals of the Swiss Federal Office of Public Health [5]

作者 | Indragie Karunaratne 转自| CSDN（ID：CSDNnews） "开发工作即将迎来一次彻底重置，而大多数人还毫无准备。" 这是 Reddit 上一篇爆火帖子的标题，也是一位资深程序员在深入使用 Claude Code（搭载 Opus 4、Max 模式）之后，得出的明确判断。他写道： 这番言论一出，在开发圈激起了广泛讨论，有人附议，有人质疑。但与此同时，另一位开发者 Indragie Karunaratne 选择不谈趋势、不谈理论，而是直 接投入实战。 他亲手用 Claude 构建出一款完整的 macOS 原生应用—— Context 。这不是小打小闹的 Demo，而是一个真正上线的软件，项目总计约 2 万行代码， 其中他本人手写的不到 1000 行， Claude 生成代码的比例高达 95%。 从功能实现、UI 构建、Bug 修复，到测试、打包、上线，Claude 几乎贯穿了整个开发流程。与此同时，他也用这次完整实践，亲身验证了另一个问 题： 每月 200 美元的 Claude Max，真的值吗？ 接下来，我们就一同走进他的开发旅程。这不是一场炫技展示，而是一份详实记录：关于工 ...

在前端技术快速迭代的当下，掌握Vue3已成为开发者立足未来的关键。若想通过2022版Vue3系统入门实战课程快速上手，需聚焦以下核心模块。 虚拟DOM与Diff算法优化是性能提升的关键。Vue3的双端比较和LIS算法能精准定位节点变化，减少不必要的DOM操作。例如，在列表渲染场景 中，Vue3的Diff算法能高效处理节点顺序变化，渲染速度比Vue2更快。理解这些原理，能帮助开发者写出更高效的代码。 生态工具链是开发效率的保障。课程结合Vite构建工具，利用其冷启动和HMR特性，大幅提升开发体验。同时，掌握Vue Router实现路由管理、 Pinia进行状态管理，能构建出结构清晰、可维护性强的应用。 聚焦这些核心模块，结合实战项目不断练习，开发者能快速掌握Vue3，在前端开发浪潮中占据先机 响应式系统与组合式API是Vue3的灵魂。与Vue2基于Object.defineProperty的实现不同，Vue3采用Proxy实现响应式，不仅能监听对象属性的增删， 还能追踪数组索引变化。组合式API通过setup函数将逻辑聚合，配合ref、reactive等函数管理状态，让代码更易维护与复用。例如，使用ref定义计 ...

Core Insights - The article emphasizes the importance of treating AI as a junior developer that requires clear guidance rather than a magical tool, highlighting the need for engineers to adapt their management style to effectively utilize programming agents [1][3][9] - Senior engineers are found to be the quickest adopters of these tools, which can save approximately 80% of time on medium to large tasks [1][8][24] Introduction - The article introduces a practical guide based on two years of experience building Devin, an autonomous programming agent, and aims to share valuable insights from customer feedback and internal practices [1][3] Getting Started: Basics and Daily Applications - Key principles for effective communication with agents include providing specific instructions, indicating starting points, anticipating potential errors, and establishing a feedback loop [10][11][13][15] - The guide suggests integrating agents into daily workflows to enhance personal efficiency, such as handling new requests without interrupting deep work and managing urgent issues on the go [17][19][20] Intermediate: Managing Complex Tasks - For complex tasks, the article recommends having agents draft initial versions and collaborating on implementation plans, while also setting checkpoints to ensure alignment with expectations [23][25][26] - It emphasizes the importance of teaching agents how to validate their work and increasing testing coverage in areas frequently modified by AI [28][29] Advanced: Automation and Customization - The article discusses creating automation templates for repetitive tasks and implementing intelligent code reviews using agents [30][33] - It highlights the need for a unified development environment to enhance agent performance and suggests building custom tools to empower agents [35][36] Practical Considerations: Embracing Change - The article outlines the limitations of autonomous agents, such as their debugging capabilities and knowledge cut-off dates, advising users to manage expectations and time effectively [39][42][43] - It concludes by asserting that the value of software engineers will not diminish, as deep technical knowledge and understanding of business codebases remain essential in the evolving landscape of software development [50]