以下文章来源于算法爱好者 ，作者小蒜 算法爱好者 . 算法是程序员的内功！「算法爱好者」专注分享算法相关文章、工具资源和算法题，帮程序员修炼内功。 微软对当下最受欢迎的程序员编辑器 VS Code 进行了一次大版本更新。 一、 智能体功能成主角，Agent HQ 概念引争议 此次更新的核心亮点集中在智能体辅助编程领域，不仅上线了智能体管理中心（Agent HQ）及十项智能体相关新功能，还同步带来了 TypeScript 7 的预览 版本，同时宣布停用老牌免费代码补全工具 IntelliCode，转而主推付费订阅制的 GitHub Copilot。 智能体辅助编程是当前 AI 开发赛道的绝对热点。就在近期，智能体人工智能基金会（Agentic AI Foundation）刚刚成立，VS Code 的一众竞品也动作频 频，谷歌的 Antigravity、JetBrains 的 Air 等工具都已相继开启预览测试。 为了不被竞争对手甩开，VS Code 此次更新重点强化了智能体能力，支持多个后台智能体同时运行，并推出 Agent HQ 作为统一管理入口。但令人费解的 是，尽管更新日志将"VS Code 内置 Age ...

毕竟写代码太枯燥的，整点不一样的放松心情～ 1、vscode-pets vscode-pets 把养宠物搬进代码编辑器，安装后，你可以在侧边栏或面板里召唤一群像素风的小动物（猫、狗、蛇、橡皮鸭、纸夹助手 Clippy、 龙猫、螃蟹 Ferris 等），它们会来回走动、睡觉、抓蝴蝶，还能陪你玩扔球游戏。 扩展搜索关键词：vscode-pets 插件链接地址： https://marketplace.visualstudio.com/items?itemName=tonybaloney.vscode-pets Github 地址： https://github.com/tonybaloney/vscode-pets 大家都知道 VS Code 的扩展多如牛毛，今天咱们不聊那些正经的代码神器，来点没啥用却让人上头的小玩意儿～ 2、Power Mode Power Mode 是给 VS Code 加特效的扩展。 Power Mode 作用是让编辑器在你敲键盘时触发视觉反馈，包括爆炸粒子、抖动、火花、能量尾迹等。 编辑逻辑不变，只叠加动画 ，写个代码像打仗似的 。 扩展搜索关键词： Power Mode 插件链接地址： ...

Core Viewpoint - JetBrains has decided to discontinue the development of its IDE Fleet, which has been in public preview since its launch in 2021, and will focus on a new development environment called Air aimed at agentic development [2][6]. Group 1: JetBrains and Fleet - JetBrains has a comprehensive suite of IDE products primarily based on the IntelliJ core platform, which has been in use since 2001 [4]. - Fleet was intended to be a lightweight, collaborative IDE to compete with Microsoft's Visual Studio Code (VS Code), which has gained popularity for its features [4][5]. - Despite some initial interest, most developers remained loyal to the IntelliJ series due to its robust plugin ecosystem and Fleet's prolonged public testing status [5]. Group 2: Discontinuation of Fleet - JetBrains announced that Fleet will no longer be available for download starting December 22, 2025, as maintaining two IDE product lines was causing user confusion and internal resource dilution [6]. - The company acknowledged that it failed to replace IntelliJ IDEA with Fleet or narrow its focus to a clear, differentiated niche [6]. - Although Fleet is being discontinued, its components will be integrated into other JetBrains IDEs, and the new product Air is an evolution of the Fleet platform [6]. Group 3: Introduction of Air - Air is designed to focus on a new workflow that leverages AI capabilities, allowing developers to delegate significant tasks to agents, which contrasts with traditional IDE workflows [7][8]. - The agentic workflow involves structured task definitions and asynchronous execution, which necessitates a different tool experience than traditional IDEs [8]. - Air is currently in public testing and will support multiple operating systems and cloud execution, enhancing its functionality beyond what Fleet offered [8]. Group 4: Developer Reactions and Market Position - Some developers expressed disappointment over the discontinuation of Fleet, believing it had the potential to compete effectively with VS Code and other emerging tools [10]. - The shift from Fleet to Air reflects a recurring pattern in JetBrains' strategy to adapt to evolving software development paradigms, particularly in the AI programming tool space [11]. - There are concerns about the necessity of creating a new tool rather than enhancing existing IDEs with AI features, raising questions about developer migration to Air [11].

Core Insights - The Linux Foundation has launched the Agentic AI Foundation (AAIF), marking a shift in the AI field towards collaborative autonomous agents, seen as the "Linux moment" for AI [2] - AAIF aims to serve as a neutral hosting platform for open-source projects related to AI agents, with major tech companies like Amazon, Google, and Microsoft joining as members [2] - The foundation's initial technical pillars include three core open-source projects: MCP protocol, AGENTS.md specification, and Goose framework, contributed by Anthropic, OpenAI, and Block [2][3] Group 1 - MCP (Model Context Protocol) is designed to standardize the connection between AI agents and external data sources, likened to a "USB-C interface" for AI [3] - AGENTS.md provides a Markdown-based standard for defining agent behavior in specific projects, while the Goose framework offers a structured workflow for agent development [3] - The AAIF aims to prevent monopolization of AI agent ecosystems by establishing interoperability standards and best practices [3] Group 2 - MCP has already been implemented in over 10,000 servers, with support from major products like ChatGPT and Microsoft Copilot, indicating strong industry recognition of the open protocol [4] - Despite skepticism about the collaboration being merely a "brand alliance," proponents argue that the protocol facilitates collaboration without redundant integration efforts [4] - The AAIF's funding model includes tiered membership fees, but control over project direction is maintained by a technical steering committee, ensuring that no single member can dictate the development path [5] Group 3 - The importance of shared standards is underscored by a UiPath report indicating that 65% of enterprises will initiate agent pilot programs by mid-2025, yet only 5% have seen financial returns [5] - The AAIF aims to promote compatibility among agent development frameworks, cloud service providers, and developer tools, emphasizing that the scale of AI is determined by solution construction rather than model size [6] - Challenges remain, including concerns about the maintenance of protocols and the practical utility of the Goose framework, but the focus is on creating a sustainable ecosystem rather than perfect standards [6]

just doesn't make sense to me that human beings would stop interacting at all with source code until we get to like AGI, I guess, where human beings aren't going to be doing a lot of different things. Um, but until then, I think we need to we need to look at code. And so then the question is what's the best user interface for doing that.Today we're talking with Nathan Sobo, founder of Zed, who spent nearly two decades building idees. First building Atom at GitHub and now Zed. Zed is a modern IDE written in ...

Core Viewpoint - The article presents a critical diagnosis of the current state of software quality, highlighting a systemic collapse exacerbated by increasing abstraction layers, AI automation, and energy consumption issues. It questions whether the current engineering quality can support the future digital world. Group 1: Software Quality Decline - Software quality is experiencing an exponential decline rather than a linear one, with many software incidents indicating that memory consumption metrics have lost their significance due to unaddressed memory leak bugs [7][8] - System-level crashes have become commonplace, with examples including Windows 11 updates causing failures and macOS Spotlight writing 26TB to SSDs in one night, exceeding normal levels by 52,000% [9][10] - A notable incident involved CrowdStrike, where a simple bug led to a global outage affecting 8.5 million Windows computers, resulting in at least $10 billion in economic losses [11][12] Group 2: AI's Role in Software Quality - The introduction of AI coding assistants has worsened the already precarious software quality situation, with AI-generated code exhibiting a 322% higher rate of security bugs compared to human-written code [21] - AI tools are amplifying the issues, as developers increasingly trust AI outputs over their own coding skills, leading to a potential crisis in the developer ecosystem [28][30] Group 3: Underlying Causes - The article identifies two main physical constraints affecting software quality: the "exponential tax" of abstraction layers, which can increase performance loss by 2 to 6 times, and the reality of energy consumption, with data centers consuming over 200 terawatt-hours annually [18][20] - Companies are spending 30% of their revenue on infrastructure to cope with these issues, a significant increase from the historical average of 12.5%, indicating a retreat rather than a proactive investment in quality [24] Group 4: Development Culture and Future Implications - The development culture has shifted to a mindset of "release first, fix later," leading to a lack of accountability and a growing gap in the developer ecosystem as junior developers are replaced by AI [11][28] - The article emphasizes the need for a return to fundamental engineering principles, such as proper memory management and algorithm complexity, to ensure sustainable software development practices [35][36]

And we'll roll in those cameras. >> Great. Thank you.>> Yeah. >> Hey everyone, I'm Roma. We've been steadily improving Codex to make it feel like a more capable and reliable coding collaborator.And for us, it's very important for Codex to be everywhere you work. And that's why we launched an ID extension. You can now have codeex right in your code editor, whether it's like VS Code, Cursor, Windsor, or many others.And with me today, I have Gabriel, engineering lead on the extension to give us a quick tour. W ...

Core Viewpoint - OpenAI has launched the GPT-5-Codex model, which significantly enhances programming capabilities, allowing for independent continuous programming for up to 7 hours, and introduces a new "dynamic thinking" ability that adjusts computational resources in real-time during task execution [1][4][5]. Group 1: Model Enhancements - The new GPT-5-Codex model is specifically trained for complex engineering tasks, including building complete projects from scratch, adding features, testing, debugging, and executing large-scale refactoring [8]. - In testing, GPT-5-Codex demonstrated a nearly 20% improvement in success rates for code refactoring tasks compared to the original GPT-5 [9]. - For simple tasks, GPT-5-Codex reduced output token count by 93.7%, resulting in a 10-fold speed increase in response time [11]. Group 2: Dynamic Thinking Capability - GPT-5-Codex can spend double the time reasoning, editing, and testing code for complex tasks, leading to a 102.2% increase in output token volume [12]. - The model's dynamic thinking capability allows it to adjust its computational approach during task execution, enhancing its problem-solving efficiency [4]. Group 3: Code Review and Quality Improvement - GPT-5-Codex underwent specialized training for code review, reducing the error comment rate from 13.7% to 4.4% and increasing the proportion of high-impact comments from 39.4% to 52.4% [15]. - The model can understand the true intent of pull requests (PRs) and traverse entire codebases to validate behavior through testing [15][17]. Group 4: Ecosystem and Tool Integration - OpenAI has restructured the entire Codex product ecosystem, introducing features like image input support, allowing users to input screenshots and design drafts for implementation [18]. - The updated Codex CLI now tracks progress with to-do lists and integrates tools like web search and MCP for enhanced task management [19]. - New IDE extensions bring Codex directly into editors like VS Code and Cursor, enabling seamless cloud and local task management [23]. Group 5: Market Positioning - The timing of this upgrade coincides with a decline in user subscriptions for Claude Code due to quality issues, positioning OpenAI to capture market share in AI programming [25][26].

RT Tetsuo (@tetsuoai)How to Install Cline & Use Grok-Code in VS Code. https://t.co/NFuEmVAhsX ...

Core Points - The article provides a comprehensive list of commonly used keyboard shortcuts for Visual Studio Code on Windows, aimed at improving coding efficiency and productivity [3][6][13]. Group 1: Common Operations - Key shortcuts for general operations include: - Ctrl + Shift + P / F1: Command Palette - Ctrl + P: Quick Open file - Ctrl + Shift + N: New window - Ctrl + Shift + W: Close current window [6][13]. Group 2: Basic Editing - Essential editing shortcuts include: - Ctrl + X: Cut line without selection - Ctrl + C: Copy line without selection - Alt + ↑ / ↓: Move line up or down - Ctrl + Shift + K: Delete line [6][13]. Group 3: Navigation - Navigation shortcuts facilitate quick movement within the code: - Ctrl + T: Show all symbols - Ctrl + G: Go to a specific line - Ctrl + Shift + O: Jump to symbols within a file [7][13]. Group 4: Search and Replace - Search and replace functionalities are enhanced with: - Ctrl + F: Find - Ctrl + H: Replace - Alt + Enter: Select all occurrences of the search term [14][38]. Group 5: Multi-Cursor and Selection - Multi-cursor editing is supported by: - Alt + Click: Insert additional cursor - Ctrl + Shift + L: Select all occurrences of the current selection - Ctrl + F2: Select all occurrences of the current word [15][36]. Group 6: Code Intelligence - Code intelligence features include: - Ctrl + Space: Trigger suggestions - F12: Go to definition - Ctrl + K Ctrl + F: Format selection [8][16]. Group 7: Editor Management - Editor management shortcuts allow for efficient workspace organization: - Ctrl + \: Split editor - Ctrl + K Ctrl + ← / →: Switch between editor groups - Ctrl + W: Close editor [9][40]. Group 8: File Management - File management shortcuts streamline file operations: - Ctrl + N: New file - Ctrl + O: Open file - Ctrl + S: Save file [18][41]. Group 9: Display and Debugging - Display and debugging shortcuts enhance user experience: - F11: Toggle full screen - F5: Start or continue debugging - Ctrl + `: Open integrated terminal [10][42].