Core Viewpoint - The article discusses the emerging concept of "Vibe Coding," which allows individuals to create software applications using AI tools without extensive programming knowledge, highlighting its potential to democratize software development and enhance productivity [1][9]. Group 1: Concept of Vibe Coding - "Vibe Coding" is introduced as a method where AI assists in coding, enabling users to develop applications quickly, as demonstrated by Andrej Karpathy's example of creating an iOS app in one hour without prior knowledge of Swift [1][3]. - The rise of AI-assisted coding tools, such as Cursor and Tencent's CodeBuddy, indicates a competitive landscape in the AI programming assistant market, enhancing developers' capabilities [3][4]. Group 2: Success Stories and Frameworks - Developers are sharing their success stories using Vibe Coding, with one user reporting a monthly recurring revenue (MRR) of $7,000 within 30 days of launching an AI product solely using AI tools [5][7]. - The "Vibe Coding entrepreneurial framework" is outlined as a simple process involving one AI tool for building, another for email outreach, and ChatGPT for market insights, showcasing a streamlined approach to product development [7][8]. Group 3: Perspectives on AI in Coding - David Heinemeier Hansson (DHH) emphasizes the importance of maintaining a human touch in coding, arguing that while AI can assist, it should not replace the joy of programming [11][15]. - The article presents contrasting views from developers, with some appreciating AI for alleviating repetitive coding tasks, while others express concern about losing the essence of coding as a creative endeavor [18][21]. Group 4: Market Implications and Future of Coding - The discussion highlights that AI is not just a tool but a new layer of abstraction in programming, suggesting that the future of coding may involve a blend of human creativity and AI efficiency [22]. - The potential of Vibe Coding to lower barriers for non-programmers to engage in software development is noted, indicating a shift towards a more inclusive tech landscape [24].

Preparation Phase - Clearly define requirements: Determine the app's functions and target user groups, such as financial applications for digital currency trading or traceability applications for tracking supply chain information [2] - Technology selection: Choose appropriate blockchain platforms and development languages, with common platforms including Ethereum and Hyperledger Fabric; development languages vary by platform, such as Solidity for Ethereum smart contracts and Java or Swift for mobile app development [2] - Team formation: Assemble a team that includes blockchain developers, mobile application developers, UI/UX designers, and testers [3] Design Phase - Architecture design: Plan the overall architecture of the app and determine the interaction method between the blockchain network and the mobile end, such as using RESTful API or WebSocket for data transmission [4] - Database design: Design a local database to store user information and transaction records, while considering synchronization mechanisms with blockchain data [4] - Interface design: Create a simple, aesthetically pleasing, and user-friendly interface, focusing on user experience to ensure smooth operational processes [5] Development Phase - Blockchain infrastructure setup or integration: If choosing to build a blockchain network independently, configure nodes and set consensus mechanisms; if integrating with an existing platform, follow the platform documentation for integration [6] - Smart contract development: Write smart contracts using the selected language to implement business logic, such as creating tokens and managing assets, followed by rigorous testing [6] - Mobile development: Based on design drafts, use the appropriate development languages and frameworks to develop the app's front-end and back-end, enabling user registration, login, transaction operations, and data display [6] - Interface development: Create interfaces between the blockchain network and the mobile end to ensure secure data transmission and interaction [7] Testing Phase - Functional testing: Conduct comprehensive testing of all app functions to ensure normal operation and compliance with design requirements [8] - Performance testing: Evaluate the app's response time, throughput, and other performance metrics under different network conditions, optimizing system performance [9] - Security testing: Check for security vulnerabilities in the app, such as preventing hacking attacks and data leaks, to protect user assets and information [10] Launch and Maintenance - Launch release: Submit the tested app to app stores for review, and officially launch it after approval [11] - Continuous maintenance: Monitor the app's operational status, promptly fix vulnerabilities and faults, and continuously optimize and update app functions based on user feedback and market changes [11]

Core Viewpoint - Vibe Coding has emerged as a significant trend in Silicon Valley, emphasizing a shift from traditional coding to describing requirements in natural language, allowing AI to generate code automatically [1][2][3]. Group 1: Concept and Evolution - The concept of Vibe Coding was introduced by Andrej Karpathy, highlighting a process where developers interact with AI to create applications without needing to write code themselves [1][2]. - Vibe Coding allows individuals without technical backgrounds to participate in programming, making the idea of "everyone is a programmer" more attainable [1][4]. - The capabilities of large models have evolved, enabling them to accurately understand user needs and generate runnable projects, marking a shift from code completion to comprehensive project development [2][4]. Group 2: Tools and Applications - Various tools have emerged in the Vibe Coding space, including Cursor, GitHub Copilot, and CodeBuddy, which is developed by Tencent [5][6]. - CodeBuddy's Craft mode can autonomously generate and modify multi-file code, enhancing the development process by allowing developers to focus on user experience rather than coding details [6][9]. - CodeBuddy has been widely adopted within Tencent, with 85% of developers using it, resulting in an average coding time reduction of over 40% and a productivity increase of 16% [20]. Group 3: Challenges and Future Outlook - Despite the advantages, challenges such as code quality and maintainability persist, with increasing code change rates leading to potential issues in code structure and readability [16][17]. - The rise of AI-generated code has led to a significant increase in code change rates, projected to be double that of pre-AI levels by 2024 [16][17]. - The future of Vibe Coding looks promising, with a growing number of startups indicating that a substantial portion of their code is AI-generated, suggesting a potential mainstream adoption of this approach in software development [21].

最近好几个哥们儿问我："现在学UI还是前端更有前途？"这个问题就像在问"吃火锅选麻辣还是番茄锅底"，关键得看你舌头受不受得了辣。今天就掏心窝 子跟大家唠唠，普通男生转行到底怎么选才不踩坑。 UI设计师就像互联网界的装修师傅，负责把APP、网页打扮得漂漂亮亮。每天跟PS、Sketch、Figma这些工具打交道，得考虑配色能不能让用户看着舒 服，按钮放左边还是右边更容易点到。 手残党慎选UI：如果你连PPT配色都像东北大花袄，做张海报要用5小时，那UI可能虐哭你 数学渣别碰前端：看见代码就头晕，遇到bug就暴躁的老铁，写JavaScript分分钟想砸键盘 1. 打开招聘网站，把UI和前端岗位要求各抄10条 2. 去B站找免费教程各学3天 3. 哪个学起来不骂娘就选哪个 | | UI设计 | 前端开发 | | --- | --- | --- | | 入行门槛 | ★★★ | ★★★★ | | 薪资天花板 | 20-25k | 30-35k | | 加班强度 | 项目上线前要命 | 改需求时要命 | 现在企业招人越来越精，既要UI会点交互设计，又要前端懂些用户体验。不过说实在的，只要技术够硬，这两个岗位找工作都不虚。 ...

Core Insights - The article discusses nine emerging trends for developers driven by AI Agents, indicating a shift from traditional coding practices to a new paradigm where AI plays a central role in software development [1][2][34]. Group 1: AI-Driven Development - AI Agents are reshaping version control, focusing on the output of code rather than the specific lines of code written, leading to a concept called "truth elevation" where prompts and tests become the new truth [2][3][6]. - The traditional static dashboards are evolving into dynamic, AI-driven interfaces that adapt based on user tasks and behaviors, enhancing user experience and efficiency [8][9][10]. - Documentation is transitioning into interactive knowledge systems that support both human readers and AI Agents, requiring a dual approach to meet the needs of both [11][12][34]. Group 2: New Development Paradigms - The shift from static templates to "vibe coding" allows developers to describe their desired outcomes and receive customized project scaffolding almost instantly, reflecting a move towards personalized development [15][16][34]. - The management of secrets is evolving from traditional .env files to capability-oriented security systems, emphasizing precise permissions and auditability for AI Agents [18][20][34]. - The emergence of accessibility APIs as a universal interface for AI Agents indicates a significant shift in how applications are designed, catering to both human users and AI [21][22][34]. Group 3: Collaboration and Standards - The rise of asynchronous workflows signifies a fundamental change in collaboration, where developers delegate tasks to AI Agents that operate in the background, enhancing productivity [25][26][34]. - The Model Context Protocol (MCP) is gaining traction as a standard for AI Agent capabilities, similar to how HTTP standardized web communication, facilitating interoperability among tools [28][29][34]. - The concept of declarative infrastructure is emerging, allowing AI Agents to specify needs without detailing implementation, streamlining the development process [31][33][34]. Group 4: Future of Software Development - The trends indicate a broader transformation in software development roles, with developers becoming more like conductors coordinating multiple AI Agents rather than solo performers [34][35]. - The article emphasizes the importance of adapting to these changes while maintaining core values of problem-solving and user service, highlighting the potential for new opportunities in the evolving landscape of software development [35][36].

【编者按】如今生成式 AI 逐渐融入软件开发流程，越来越多 AI 生成的代码出现在实际工程中——但你有没有想过，这些由 AI 写出来的代码，从一开始 就可能被视为"遗留代码"？本文作者从工程经验出发，结合 AI 的生成机制，提出一个颇具启发性的观点： AI 生成的代码缺乏上下文记忆和维护连续性， 因此一 诞生就处于"他人旧作"的状态 。 这 不仅是对当前 AI 编码能力的冷静观察，也为我们理解未来软件开发形态提供了一种新视角。 原文链接： https://text-incubation.com/AI+code+is+legacy+code+from+day+one 翻译 | 郑丽媛 出品 | CSDN（ID：CSDNnews） 在软件开发中，代码的"可改进性"往往取 决于其所处的生命周期阶段。通常可以分为以下几类情况： 总的来看， 代码的演进速度，通常取决于离它的编写时间有多近、维护者是不是原作者。 其实 ， 这种状态是合理的：对于一个运行稳定、经过验证的软件系统而言，贸然进行"改进"往往带来额外风险，尤其是当你对系统的整体脉络不甚了 解时，原作者通常才最清楚其潜在逻辑和 开发 背景。 AI 生成的代码 ， ...

过去十年，程序员群体享受了互联网扩张期的技术红利，但这一红利正在快速消退。 三个核心矛盾正在加速技术人的职业危机： 技术迭代 ，低代码与AI抢占初级开发岗位； 在技术的暗流中， 一群清醒的技术人正在构建自己的"第二曲线" 。当你在为KPI加班时，有人已 经用爬虫获得了丰厚的报酬： 为什么爬虫是程序员破局的最优解？ 1. 技术复利效应最强 ：一套成熟的爬虫系统可以同时服务于 金融、电商、舆情监测等10+行业； 2. 市场需求呈爆发式增长： 金融领域、电商行业、地方政府等； 3. 技术门槛与收益错配： 爬虫的核心技术学习周期短，但市场定价却充满想象力； 4. 合规边界清晰： 《数据安全法》实施后，合规爬虫需求反而暴涨。 01 爬虫商业接单方案 人才供给 ，市场供过于求； 成本控制 ，使用云服务导致运维及 高级研发岗 需求减少； 程序员永远不缺技术，缺的是将技术嵌入商业链条的思维。 如果你也想通过爬虫技术实现副业创收，那么这一次的 爬虫商业接单 实训营 你一定不能错过！ 扫码加小助理 免费报名 ... 官方特训费399元，立即报名 免费学习 ！ 这是一套包含 爬虫逆向破解技术 和 爬虫商业接单详解 的爬虫接单实战课 ...

Core Viewpoint - JetBrains' AI Assistant, despite having 22 million downloads, has a low rating of 2.3 out of 5, leading to significant criticism and user dissatisfaction [2][4][11]. Group 1: Product Performance and User Feedback - JetBrains released the AI Assistant plugin in December 2023, aiming to assist programmers in coding, but it has faced backlash due to poor performance and integration issues [2][11]. - Users have reported numerous bugs, slow performance, and a lack of essential features, leading to a high volume of one-star reviews [4][8]. - The AI Assistant has been criticized for automatically installing without user consent, causing frustration among existing users [6][7]. Group 2: Company Response and Controversy - JetBrains has been accused of deleting negative reviews to manipulate the product's rating, which has further eroded user trust [3][4][5]. - The company defended its actions by stating that some comments were removed for being outdated or violating policies, but acknowledged that the process could have been handled better [5][9]. - Users expressed concerns about the AI Assistant's integration with third-party tools, leading to a perception of it as bloatware that could pose security risks [9][10]. Group 3: Competitive Landscape - The introduction of a free tier for the AI Assistant is seen as a response to competitive pressures from other tools like GitHub Copilot, which launched a free version earlier [11][14]. - JetBrains is under pressure from free alternatives in the market, prompting the company to enhance its offerings to retain users [12][14]. - The launch of Junie, a new AI agent, aims to improve user experience, but concerns about its pricing and token limits have been raised [14].

Core Viewpoint - ProStar Holdings Inc. has successfully closed a non-brokered private placement, raising gross proceeds of C$775,000 through the sale of 5,535,714 units at a price of C$0.14 per unit, with plans to use the funds to enhance sales and marketing efforts and for general working capital [1][3][4]. Group 1: Offering Details - The Offering consists of units, each comprising one common share and one warrant, with each warrant allowing the purchase of one common share at C$0.20 for 36 months [2]. - The Offering was increased from an initial target of C$750,000 to C$775,000, receiving approval from the TSX Venture Exchange [1]. - The securities issued in the Offering are subject to a hold period of four months and one day from the date of issuance [6]. Group 2: Use of Proceeds - ProStar plans to utilize the proceeds from the Offering to onboard resources aimed at ramping up sales and marketing efforts, as well as for general working capital requirements [3][4]. Group 3: Management and Participation - The CEO and Founder of ProStar expressed satisfaction with the financing, highlighting strong participation from board members and existing shareholders [4]. - Certain directors and senior officers purchased a total of 2,085,714 units as part of the Offering, which is classified as a related party transaction [5]. Group 4: Company Overview - ProStar is recognized as a leader in Precision Mapping Solutions, focusing on critical infrastructure management through its flagship product, PointMan [9][10]. - The company has developed a significant intellectual property portfolio, including 16 issued patents in the United States and Canada, aimed at enhancing the management of critical infrastructure assets [10].

近日，curl 项目（一款用于通过 URL 传输数据的命令行工具和库）创始人 Daniel Stenberg 在领英发帖称，已经受够了由 AI 生成的大量"垃圾"漏洞报告， 因此近期引入额外复选框，用以过滤此类平白浪费维护人员时间的低效提交内容。 1 curl 创始人被 AI 垃圾"逼疯了" Stenberg 表示，项目维护人员需要花费大量时间对每一份通过 HackerOne 提交的 AI 辅助漏洞报告进行分类，但往往发现这些报告的内容一无可取，在效 果上约等于针对项目发起的 DDoS 攻击。 Stenberg 在 LinkedIn 上引用了近期一份"令他忍无可忍"的报告，并表示"到此为止吧，我受够了。我要坚决制止这种疯狂行为。" 在 HackerOne 上提交 curl 相关安全报告有了一些新规定，例如所有通过 HackerOne 提交 Curl 安全报告的研究人员，现在必须回答以下问题： "您是否使用 AI 来发现该漏洞或生成此报告？" 如果选择"是"，bug 报告者将会面临一连串后续问题，包括要求他们提供相关证据以证明该 bug 真实存在，而后 curl 团队才会花时间加以验证。 Stenberg 补充 ...