这篇文章很重要‼️。但大家又没看！ 曰 日小分 / // // /// /// 国内的大模型场可以借鉴啦，手机端 os 虚拟机, 云+终端 ai 结合, 那 就 拥有了个性 化, 多好。 质上是 间 非 发 员 AI 编 — 具 Claude Code。Cowork 的大部分功能都由 Claude Code 自行构建, 这使得 AI 既成为 产品本身,也成为开发流程的关键组成部分。 1、它面向普通人 不需要懂编程,编程执行这一步,它已经 内嵌到了工作流本身，也就是Claude code 自从构建。无需编写软件，只需授予 Claude 访问其计算机上某个文件夹的权限,并要求它 执行实际工作,例如整理文件、撰写报告、根 据屏幕截图创建电子表格或清理文档。与普通 聊天工具不同,Cowork 的运行更加自主。您 分配任务后,Claude 会逐步规划并执行,并 随时向您汇报进度。 ai目前把编程变成了英语一类的存在，每 个人都会。或者说ai把编程变成了电,不需 要自己会发电, 你会用就行。 最近我使用 qwen 的内测版做小程序就是这 ------------- 1 . 1 -- 出 a ♡ C 小熊跑的快 赞 今天有 ...

Core Viewpoint - Cowork, the latest product from Anthropic, is an AI coding tool designed for non-developers, integrating AI into the development process itself [1] Group 1 - Cowork is aimed at ordinary users who do not need programming knowledge, as it automates coding tasks within the workflow [2] - Users can grant Cowork access to specific folders on their computers, allowing it to perform tasks such as organizing files, writing reports, and creating spreadsheets based on screenshots [2] - The tool operates more autonomously than typical chat applications, planning and executing tasks while providing progress updates [2] Group 2 - Currently, Cowork is only compatible with macOS, utilizing a local virtual machine to read documents with fine-grained permission control [2] - This integration of cloud AI with local documents enhances both intelligence and security, creating significant potential for future applications [3] - The overseas reception of Cowork has been very positive, suggesting that domestic AI models could learn from this approach to combine cloud and terminal AI for personalized experiences [3]

Core Insights - The consensus emerging from the Sequoia Capital AI Summit is that the next phase of AI will focus on selling outcomes rather than just tools, indicating a shift towards "Software as an Outcome" [1] - Major tech companies are accelerating their development of AI agents, with ByteDance, Baidu, and Alibaba leading the charge in creating applications that leverage agent technology [2][3] Group 1: Industry Trends - The year 2025 is marked as a pivotal year for the explosion of AI agents, with significant attention drawn to Manus, a domestic agent team that gained global recognition for its practical applications [3] - ByteDance has rapidly expanded its agent development teams from five to seven, indicating a strong push towards creating collaborative AI tools [3] - Baidu's introduction of its general-purpose agent, Xinxiang, highlights the company's commitment to integrating AI capabilities into user needs [5] Group 2: Competitive Landscape - The competition among major players is intensifying, with Alibaba positioning its Quark as a "super agent" and focusing on both B2B and B2C markets [2][7] - The success of agents will depend on the depth of their ecosystems and the ability to capture user habits and preferences [2] - The emergence of vertical agents, such as those in legal and travel sectors, suggests a diversification of applications beyond general-purpose tools [8][21] Group 3: Key Factors for Success - The foundational model capabilities, ecosystem depth, and cost efficiency are critical for agents to succeed in the market [19] - The ability to autonomously complete tasks will be a determining factor in the effectiveness of AI agents [19] - User experience varies significantly, with some vertical applications showing promise while general-purpose agents struggle with complex tasks [21] Group 4: Current Challenges - The industry has not yet reached a "GPT moment," as agents still face hurdles in technical maturity, business model implementation, and user acceptance [20][23] - The fragmentation of the ecosystem and lack of unified interfaces for tool integration hinder the development of a cohesive agent experience [20] - Users often have unrealistic expectations of agents, believing they can fully replace human intervention, which is not currently feasible [23]