8月11日，Github CEO Thomas Dohmke宣布卸任，而后微软宣布不会有继任者。 当时，他的公司已经被微软收购，成为微软移动业务中的一环。Thomas本人也加入了微软，并在2021年成为了Github的首席产品官。 几个月后，CEO Nat Friedman宣布离职，并在推特上表示要"回归自己的创业初心"，而Thomas则代替Friedman成为了Github的CEO。 随之到来的，是Github宣布并入微软的Core AI部门。这一举措，在科技界引起轩然大波。 自2018年被微软收购以来，Github一直保持独立运营，并始终坚持自己的开源文化。 而如今这一举动不得不让开发者们发出疑问，Github在未来是否还能继续保持独立？这个开源乌托邦是否终将迎来落幕？ 本期文章，我们就来聊聊，这个全球开发者们的理想社区为何行至于此？而微软又为何走出这步？AI的发展，是否必然意味着开源精神的终结？ Github并入微软，独立性的挑战？ 八年前，一个名叫Thomas Dohmke的程序员在Reddit上发帖：我是Thomas Dohmke，HockeyApp的联合创始人。我们的软件旨在方便开发者进行移动Ap ...

Core Insights - The article discusses the evolution of AI agents and their integration into Integrated Development Environments (IDEs), highlighting the transition from traditional coding to AI-assisted coding [2][3][4] - It emphasizes the importance of building a scalable ecosystem through the use of Multi-Channel Protocol (MCP) and custom agents, which enhance engineering efficiency and platform capabilities [2][3][4] Group 1: AI and IDE Integration - The integration of AI into IDEs has transformed coding practices, moving from manual coding to AI-assisted coding, significantly improving user experience [6][9] - Trae, a notable AI IDE, has introduced new features such as MCP mode and custom agent mode, expanding user application scenarios [3][10] - The article outlines the evolution of AI capabilities in IDEs, including code completion and decision support, which enhance coding efficiency [9][12][13] Group 2: Agent Functionality and Design - The design of agents focuses on their ability to perceive, plan, and execute tasks, with a feedback loop that enhances their performance [16][17][19] - Different application scenarios require varying implementations of agents, emphasizing the need for context awareness and tool invocation capabilities [19][21] - The article discusses the challenges of user trust in AI models, with some users preferring manual control while others embrace full automation [22][25] Group 3: MCP and Tool Integration - The introduction of MCP has facilitated the integration of first-party and third-party tools, addressing user demands for tool reuse [35][36] - The article highlights the importance of maintaining a consistent structure for tools to avoid confusion and enhance model understanding [36][40] - Solutions to historical session limitations and context window constraints are discussed, emphasizing the need for efficient information management [40][41] Group 4: Future Directions - The future of AI agents is expected to involve multi-modal integration, expanding input methods beyond text to include voice and other forms [53][54] - The potential for collaborative multi-agent systems is explored, suggesting that agents may evolve to autonomously solve complex problems [53][54] - The article concludes with a positive outlook on the future capabilities of AI models, anticipating significant advancements that will enhance work and life [54]

Core Viewpoint - The evolution of programming has transitioned from manual coding to AI-assisted development, significantly changing the role of programmers and the tools they use [4][6][8]. Group 1: Stages of Programming Evolution - **First Stage: Manual Craftsmanship** Early programming involved basic languages like Basic, Pascal, and C, with no IDE support, leading to a high dependency on accuracy [4][5]. - **Second Stage: Copy and Paste Dominance** The rise of graphical IDEs and the internet allowed programmers to leverage search engines and online resources, shifting the focus from original coding to code assembly [6][7]. - **Third Stage: The Era of AI** The introduction of AI programming tools has transformed coding practices, allowing programmers to rely on AI for code generation and optimization, reducing the need for traditional coding skills [8][10]. Group 2: AI Programming Tools - **Cursor** An AI IDE optimized for VS Code, known for its strong code understanding and project-level analysis capabilities [13]. - **Windsurf** An AI tool with long-term memory, capable of understanding project context and suitable for complex tasks [14]. - **Trae** Developed by ByteDance, this AI IDE integrates deeply with AI to provide intelligent Q&A and code auto-completion features [15]. - **Lingma IDE** An Alibaba product that integrates cloud services, allowing AI to automatically call tools for end-to-end task completion [16]. - **VS Code + Copilot** This combination offers a rich plugin ecosystem, enhancing AI capabilities through the Copilot plugin [17].

每年初夏，科技圈总会迎来一波"新品大秀"，尤其是 5 月和 6 月几乎成了开发者的"小春晚"的热闹时刻——微软 Build、Google I/O、苹果 WWDC 轮番登 场，带来一大波新技术、新工具，想方设法吸引开发者的注意。今年是微软打头阵，Build 2025 大会于 5 月 20 日凌晨 12:05 率先登场。 这场大会上，微软 CEO 纳德拉和 CTO Kevin Scott 亲自上阵，令人意外的是，一直不太对付的 OpenAI CEO Sam Altman 和特斯拉 CEO 马斯克，还有英伟 达 CEO 黄仁勋，也都"出现"在这场大会上，只是以线上视频接入的形式，分别与纳德拉来了场关于合作、大模型、芯片等维度的简短对话。 整体来看，AI 无疑是微软最重要的战略方向。不过，今年「开源」也成了另一大贯穿全场的关键词，其不仅将 VS Code 上 Copilot 的核心功能开放了出 来，就连适用于 Linux 的 Windows 子系统（WSL）也重磅开源了，实属令人意外！ 当然，除了这些重磅发布，微软在这场大会上还有不少值得关注的技术创新。从产品体验到底层工具，AI 又为整个行业带来了哪些新变化？下面就 ...

Core Insights - The global market for intelligent programming is estimated to be in the tens of billions of dollars, with Julia Liusion being a key figure at Microsoft overseeing major developer services [1] - GitHub Copilot, driven by GenAI, has become the first large-scale intelligent programming application, reaching over 15 million users by May 2025 [1] Group 1: Julia Liusion's Role and Vision - Julia Liusion has been with Microsoft for over 30 years, shaping the developer culture and leading significant products [1] - Julia emphasizes the importance of adapting to the rapid evolution of AI, suggesting that architects should let go of traditional design obsessions to embrace GenAI capabilities [2][10] - Julia believes that the future will see a billion new emerging developers, driven by the optimism surrounding GenAI [2] Group 2: Changes in Engineering and Recruitment - The importance of traditional coding interview practices, such as "brushing questions," is diminishing, with proficiency in AI tools becoming essential [3][19] - Microsoft’s recruitment process has evolved to focus on candidates' familiarity with AI tools rather than traditional coding tests [18][19] - Julia suggests that engineers need to understand the "what" of projects rather than just the "how," emphasizing the importance of business understanding [16] Group 3: AI's Impact on Development Processes - Microsoft views itself as a pioneer in intelligent programming, with GitHub Copilot being the first major GenAI application in the industry [8] - The understanding of AI within Microsoft has deepened over the past three years, leading to significant changes in product design and functionality [9] - Julia predicts that AI will increasingly automate repetitive tasks, allowing engineers to focus on more complex issues [17] Group 4: Future Predictions and Challenges - Julia expresses uncertainty about future predictions due to the rapid pace of AI development but warns that developers who do not start learning AI technologies will be at risk of obsolescence in three to five years [21][22] - The challenge remains for AI to understand the context of code, which is crucial for solving complex engineering problems [11]

【编者按】GitHub Copilot 智能体模式 (agent mode) 正式登录 Visual Studio！ 责编 | 梦依丹 出品丨AI 科技大本营（ID：rgznai100） 微软 Visual Studio 官方 X 上正式宣布，备受期待的 GitHub Copilot 智能体模式 (agent mode) 正 式登陆 Visual Studio 17.14 预览版！ 开发者通过一个提示即可让 Copilot 自主处理从计划、构 建、测试到修复的整个开发流程。 自主确定上下文与编辑文件： 无需你手动指定，Copilot 能智能判断并找到需要编辑的相 关上下文和文件； 建议终端命令供你审批执行： 它会为你生成必要的终端命令，并在你确认后执行； 持续迭代直至任务完成： 它会不断检查错误，运行构建/测试来验证结果，直到任务最终搞 定； 通过 MCP 服务器调用可信工具： 它能够调用你开发环境中的 linter（代码风格检查工 具）、test runner（测试运行器）和 static analyzer（静态分析器）等受信任的工具。 在 Copilot Chat 窗口中，切换到"Agent (智能体)" ...