当"AI 10 倍工程师"的论断在社交平台上泛滥，当"不用 AI 就会被淘汰"的焦虑如潮水般袭来，也许我们 更该停下脚步，冷静地追问一句：AI 真能带来编程效率的指数级提升吗？ 如果我错了呢？如果不立即学会使用 AI，会不会错过机会，再也找不到工作？毕竟，现在 很多流传的花哨词汇，让他们口中的"AI"与我所熟悉的"AI"不同。 他们所说的是 Agentic AI，一种能够浏览网页、运行测试、纠正自身错误的思考（thinking）模型。当 然，我也会在聊天窗口中让它写一些代码，但通常会在获取想法后，把大部分丢掉。然而，这些工程师 却把工作完全交给 Claude，在他们喝早咖啡时，让 Agent 替他们提交 5 个PR。难道，我真成了那个跟 不上时代的"恐龙"？ 让我感到焦虑的部分原因是，也许 AI 已经在我不经意间发生了巨变，因为我很少使用 AI，也并不喜欢 使用 AI，审查代码的过程，远不如编写代码有趣。难道正是这种固执地想要享受编码的想法，让我落 在了后面？ 然而，结果不尽人意。尽管有人声称 AI 正以惊人的速度进步，但它与以往相比并没有本质区别。它擅 长编写模板代码，尤其在 JavaScript 中，特别 ...

每经记者｜叶晓丹 每经编辑｜魏官红 8月21日，DeepSeek正式上线DeepSeek-V3.1，支持多种Code Agent框架，开发者可以自己搭建智能体， 官方将之称为迈向Agent时代的第一步。 同时，DeepSeek-V3.1-Thinking在Aider编码测试中，拿下了76.3%高分，远超Claude 4 Opus、Gemini 2.5 Pro（0325）。 8月22日，阿里巴巴面向全球用户发布了Agentic编程平台Qoder。Qoder集成了全球顶尖的编程模型，提 供上下文工程能力，可一次检索10万个代码文件。基于强大的编程智能体，可实现AI自主研发，大幅 提升真实软件的开发效率。值得注意的是，一个月前，阿里开源AI编程模型Qwen3-Coder。 放眼海外，2025年AI编程赛道竞争也尤为激烈。据此前媒体报道，估值超过10亿美元的AI编程独角兽 至少有7家，总融资已超240亿元人民币。OpenAI、Anthropic纷纷卷入。 为何科技企业如此青睐AI编程？东吴证券近期研报分析，AI编程是当前人工智能领域最有用、用户最 愿意付费且增长最快的应用方向之一。它并非简单的提效工具，而是重塑软件生 ...

氛围编程（vibe coding），这个由 Andrej Karpathy 带火的热词，已经成为了一种相当流行的编程方式。但这种编程方式的流行程度究竟如何，目前还没有什么比 较可靠的统计数据。不过，近日的一篇 Reddit 热帖，却可以让我们窥见一些端倪：看起来，氛围编程可能比我们预想的更受欢迎，FAANG 等大型科技公司也不乏 vibe coder—— 虽然人们对这个工作流程算不算是氛围编程存在很大争议。 机器之心报道 编辑：Panda 这篇帖子发布在 r/vibecoding，发帖者 u/TreeTopologyTroubado 自称是一位拥有十多年工作经验的 AI 软件工程师，并且其有一半的时间都是在 FAANG（即 Meta、 亚马逊、苹果、Netflix 和 Alphabet 五大科技巨头）工作。他职业生涯前半段是系统工程师，而不是开发者，不过他现在已有 15 年左右的编程经验了。 然后，他分享了使用 AI 开发产品代码的方法。简单来说，就是 始终从可靠的设计文档和架构开始，然后在此基础上逐步构建。始终先编写测试。 更具体而言： 该帖在 Reddit 和 X 上都引起了广泛讨论。其中一个很大的讨论点 ...

「代码后稀缺时代」里，Karpathy分享了他对AI辅助编程的最新体会：在代码已可低成本生成并随时丢弃的背景下，「写」与「删」的价值被 重新审视。Cursor补全适合日常开发，Claude Code与Codex能完成大块功能但缺乏「品味」，而GPT-5 Pro则是攻克顽固bug的终极防线。 马斯克的好兄弟，我们的好朋友，大神Andrej Karpathy最新「AI编程指南」已出！ 在目前模型能力已经达到博士级的情况下，如何能够最大化AI对编程的帮助？ 当AI能够「低成本生成代码」，你只需要vibe coding的情况，一个新问题来了： 现在是会写代码更重要？还是会删代码更重要？ Karpathy分享了他的「最佳LLM辅助编程」体验和方法。 工具使用理念 首先是建立一种理念，工具是为人服务的。 不执着于单一「完美」工具，更倾向于整合多个工作流，取长补短。 因为不同工具在不同层级的任务中各有优势。 比如Claude Code、Codex等适合大段的难度不高的任务，Tab补全则需要人类先「打好样」。 Cursor（Tab自动补全） Karpathy说这种方式是日常工作的主要使用方式，比例大概占约75%。 因为在代码 ...

Core Viewpoint - The article discusses Coinbase's controversial decision to fire engineers who refused to adopt AI programming tools, emphasizing the company's stance that AI is essential for their operations [5][11]. Group 1: AI Adoption in Programming - The use of AI in programming has become standard among developers, with Google claiming that 50% of its code is AI-generated [2]. - There is a growing community of developers who rely entirely on AI for coding, known as Vibe Coders, while some programmers still prefer traditional coding methods [4]. Group 2: Coinbase's Decision - Coinbase CEO Brian Armstrong announced the firing of engineers who did not use AI programming tools, stating that the company had purchased enterprise licenses for GitHub Copilot and Cursor [6]. - Armstrong expressed shock at the slow adoption rate of AI among engineers and implemented a mandatory trial period for AI tools, leading to the dismissal of those who did not comply [8][10]. Group 3: Reactions and Implications - The decision sparked significant discussion online, with mixed reactions from the tech community, including claims that the prevalence of AI programming is overestimated [13][14]. - Armstrong acknowledged that his approach was high-pressure and not well-received by some employees, but he aimed to convey that using AI is not optional [11].

Group 1: Course Overview - The course "AI Programming Assistant Cursor: Building a Mini Program Similar to Xiaohongshu from Scratch" provides a systematic learning platform for developers to master core skills in mini program development [2] - The course emphasizes a structured learning path that includes understanding the basic architecture of mini program development, effective application of AI tools, implementation of core functionalities, full-stack development capabilities, and cross-platform thinking [6] Group 2: Mini Program Development Framework - The mini program development framework consists of three main components: view layer (WXML and WXSS), logic layer (JavaScript), and configuration layer (JSON) [3] - The course utilizes a case-based teaching method with over 70 teaching cases, significantly enhancing learning efficiency [3] Group 3: AI Programming Assistant Cursor - The course highlights the integration of AI programming assistant Cursor, which represents a new direction in programming [4] - Key skills include natural language description of requirements, understanding and modifying generated code, and debugging and optimization using Cursor [5] Group 4: Core Functionalities of Xiaohongshu - The core functionalities of the Xiaohongshu mini program include content display, social interaction, and personal center modules [5][7] - Important implementation aspects include content waterfall flow display, user interaction design, and multimedia processing [7] Group 5: Full-Stack Development Skills - The course aims to cultivate full-stack development capabilities, expanding from front-end development to full-stack thinking [5] - Data shows that through 32 hours of systematic learning, developers can comprehensively master skills from basics to cloud development [5] Group 6: Cross-Platform and Commercialization - The course encourages learners to develop cross-platform thinking, understanding how to extend core business logic to other platforms [6] - Techniques for traffic conversion and understanding the Xiaohongshu open platform's entry process are also covered [7]

Group 1: Software ETF Performance - The software ETF has a turnover rate of 9.25% during trading, with a transaction volume of 491 million yuan [3] - As of August 15, the software ETF has seen an average daily transaction volume of 488 million yuan over the past week, ranking first among comparable funds [3] - The software ETF has experienced a net inflow of 709 million yuan over the last 21 trading days, with inflows on 12 of those days [3] Group 2: Growth and Returns - The software ETF's net asset value has increased by 10.39% over the past three years [3] - The highest monthly return since inception is 39.35%, with the longest consecutive monthly gain being three months and a maximum cumulative increase of 69.40% [3] - The average return during the months of increase is 9.75% [3] Group 3: AI Programming and Market Potential - AI programming is identified as one of the fastest-growing and most valuable applications in the AI sector, addressing the imbalance between unlimited software demand and limited developer supply [4] - The potential market size for AI programming is projected to reach 15 billion USD by 2030, serving as foundational infrastructure for AI agents [4] Group 4: Key Stocks in Software Service Index - The top ten weighted stocks in the CSI Software Service Index include iFlytek, Kingsoft Office, Tonghuashun, and others, collectively accounting for 61.39% of the index [4] - Notable stock performances include Tonghuashun with a 15.74% increase and Kingsoft Office with a 5.57% increase [6]

Core Insights - Replit's annual recurring revenue (ARR) grew from less than $10 million in early 2024 to over $100 million within nine months in 2025, indicating a rapid growth trajectory that has captured the attention of the developer community [2][41] - The growth of Replit is attributed not only to AI code generation but also to a systematic strategic design focused on platform integration and infrastructure capabilities [4][6] - The evolution of AI programming tools is shifting from mere code editors to comprehensive platforms that facilitate the entire application lifecycle, from code generation to deployment [6][24] Group 1 - Replit's strategy emphasizes backend services such as hosting, databases, deployment, and monitoring, allowing it to monetize through various stages of the application lifecycle [6][10] - The company has experienced a significant transformation, moving from a focus on teaching programming to enabling users to build applications independently, particularly benefiting product managers who can execute tasks without relying on engineers [24][25] - The introduction of Replit Agent has led to a 45% monthly compound growth rate since its launch, reflecting the platform's increasing adoption and user engagement [41][43] Group 2 - Replit aims to lower the barriers to programming, which has resulted in a diverse user base across various industries, including product managers and designers [24][34] - The platform's approach to security includes automatic integration of safety features for user applications, addressing common vulnerabilities associated with AI-generated code [27][29] - Future developments in AI and automation are expected to enhance the capabilities of Replit, allowing for more autonomous programming processes and potentially transforming the SaaS landscape [52][54] Group 3 - The company is focused on building a robust infrastructure that supports its long-term competitive advantage, emphasizing the importance of transactional systems that allow for safe experimentation and rollback capabilities [50][51] - Replit's vision is to become a "universal problem solver," enabling knowledge workers to leverage software solutions without needing extensive technical expertise [34][53] - The future of programming may involve a shift towards more abstract interfaces, where users interact with AI agents rather than directly manipulating code, enhancing accessibility and usability [36][37]

最近，关于 AI 能否让工程师效率提升 10 倍、甚至 100 倍的讨论越来越火爆。各种夸张的 说法铺天盖地，让不少开发者既兴奋又焦虑：到底是真的"生产力飞跃"，还是只是炒作噱 头？一线开发者 Colton Voege 在试用了多款 AI 辅助编码工具后，得出自己的看法：很多夸 大其词的 10 倍效率说法，要么是出于投资和商业利益的宣传，要么是管理层制造焦虑的手 段，真正来自一线开发者的真实体验其实更平淡。 在他看来，AI 是一个有用的工具，但并不是颠覆一切的生产力魔法。工程师应当信任自己 的节奏，既不用因为没用 AI 而焦虑，也不必为了"更高效率"牺牲工作乐趣。 几个月前，我经历了一段情绪低落期。虽然我一直对自己作为工程师的能力很有信心，但每次刷 LinkedIn、Twitter 等社交媒体的内容时，总觉得自己的技术落后得没救了。网上各种说法都让我感觉， 工程师已经不再是简单地敲代码了。那些"真正的工程师"效率比我高十倍、甚至百倍。我写这篇文章， 就是想帮帮也有类似焦虑的朋友们。 我本来是个怀疑主义者，听到这种说法一般都会翻白眼，就像有人跟我说什么草药能治百病一样。但现 在满天飞的"10 倍工程师"传言，开 ...

Core Viewpoint - Cognition AI, co-founded by three talented Chinese entrepreneurs, is on track to become a $10 billion AI unicorn, showcasing rapid growth and significant investment interest in the AI coding sector [5][6][17]. Group 1: Company Overview - Cognition AI was founded in late 2023 by Scott Wu, Walden Yan, and Steven Hao, all of whom are recognized for their exceptional mathematical and programming skills [8][9]. - The company developed "Devin," the world's first AI software engineer, which operates on a subscription model priced at $500 per month per user [12][18]. - Cognition has completed three funding rounds, with the latest round rumored to be in progress, consistently achieving valuation milestones with each round [15][17]. Group 2: Funding and Valuation - Cognition's valuation skyrocketed from $3.5 billion in March 2024 to $20 billion in April 2024, marking a rapid increase in investor confidence [16][17]. - The company has attracted investments from notable firms such as Founders Fund and Khosla Ventures, with the latest funding round reportedly raising over $300 million [5][6][17]. - The strategic release of product milestones has been a key factor in driving valuation increases, with each funding round coinciding with significant product developments [15][16]. Group 3: Product Development and Market Position - Devin AI has received mixed reviews, with some praising its capabilities while others criticize its tendency to produce bugs, reflecting the challenges of AI in software engineering [12][13]. - Cognition's recent acquisition of Windsurf for $220 million has significantly enhanced its market position, adding over 300 paying customers and $80 million in annual recurring revenue (ARR) [20][21]. - The AI coding sector is experiencing intense competition, with major players like GitHub Copilot and Cursor dominating the market, capturing over 80% of the cash flow [26]. Group 4: Industry Trends - The global AI programming sector has seen nearly 20 billion RMB in funding in 2024, with 80% of this capital going to seven leading companies [26]. - The market is expected to evolve into an oligopoly, with a few dominant players controlling the majority of market share, as indicated by the rapid growth and investment in top firms [26]. - Domestic AI coding initiatives are beginning to emerge, with new products like Vinsoo aiming to fill gaps in the market and increase competition [28].