Skills推出不久，OpenAI、微软、腾讯等国内外大厂旗下的产品纷纷跟进支持。1月19日，字节跳动旗下AI Agent平台"扣子"更新，上线"技能商店"，成为第 一个将Skills翻译成"技能"并推出类似功能的国内大厂。 那么，究竟什么是Skills？让大模型学会"技能"后会有什么效果？新京报贝壳财经记者进行了实测。 "传统的五子棋只是把五个子连成一条线，而技能五子棋则是在传统的五子棋中加入了技能"——几个月前，"技能五子棋"出圈。而今年1月，一个以"技 能"（Skills）命名的范式也逐渐从硅谷的AI企业中"出圈"到国内，一时间人人都在学习Skills，不只是开发者，不少职场人士也开始尝试通过这一范式，将固 定流程任务封装为大模型可调用的"技能"。 全球大厂纷纷跟进Skills 值得注意的是，"Skills"可以通过自然语言编辑，如同程序员编程一样，没有编程基础的普通人也可以进行尝试，从而沉淀出属于自己的"技能"，这正是 其"出圈"的关键点。 最初，该功能只在开发者小圈子里流传，像是一次技术实验。但事情发展得比任何人预期都要快。一个月后的12月18日，Claude所属公司Anthropic做了一个 出人 ...

Core Insights - Claude Skills have gained significant popularity, surpassing MCP, with various CLI clients supporting them and products like扣子 and MiniMax launching similar offerings [2] - The value of Claude Skills is still greatly underestimated, as a well-designed Skill can match or exceed the intelligence of complete AI products [3][4] - Skills allow non-technical users to create their own applications, demonstrating the potential for widespread adoption and innovation in AI [4][5] Group 1: Understanding Skills - Skills are modular capabilities that extend the functionality of AI Agents, packaging instructions, metadata, and optional resources for automatic use [22][24] - The architecture of Skills resembles a comprehensive SOP package for task delegation, enabling Agents to execute tasks reliably [24][28] - Skills can be seen as an extension of general Agents, allowing them to perform specialized tasks by loading different Skills [14][16] Group 2: Value and Future of Skills - Skills represent a future-oriented approach to AI applications, enabling Agents to autonomously understand and execute tasks based on human-provided guidelines [28][30] - The design of Skills allows for zero-code development, making it accessible for non-technical users to create intelligent Agents [31][34] - Skills can be combined flexibly, allowing multiple Skills to work together to complete complex tasks [68][69] Group 3: Implementation and Usage - The article provides a comprehensive guide on how to create and use Skills, emphasizing the ease of development and the potential for rapid testing of ideas [105][130] - Users can install Skills from repositories or create their own using tools like skill-creator, which simplifies the development process [121][130] - The article outlines scenarios where Skills are particularly beneficial, such as when specific knowledge or templates are required for task completion [139][141]

Core Insights - The concept of "skills" in the AI context has evolved to represent "operational manuals" and "capability plugins" for AI systems, allowing users to streamline repetitive tasks and enhance efficiency [1][7][20] Group 1: Skills and Their Implementation - Skills are unique tools that encapsulate individual needs, enabling users to automate tasks such as writing and data processing [3][4] - Users can create specialized skills by packaging their expertise into AI systems, which can then execute tasks with minimal input [6][12] - The process of "atomizing" core skills into reusable skill packages allows for significant time savings and efficiency gains [7][13] Group 2: Key Components for AI Efficiency - Three essential components for building a digital workforce in 2026 are MCP (Managed Control Protocol), Skills, and Subagents [8][11] - MCP provides AI with access to local data, while Skills define the professional standards and instructions for task execution [9][10] - Subagents enable AI to manage complex tasks by breaking them down into smaller, independent tasks, improving overall workflow management [11][12] Group 3: Market Trends and Future Outlook - The AI agent market is projected to reach $4.71 billion by 2030, with skills packages expected to capture 15% to 20% of this market, indicating rapid growth in this sector [22] - Major tech companies are developing standardized skills to create a competitive advantage, akin to the evolution of USB interfaces [20][21] - The future of AI tools is moving towards "intention-driven" operations, where users can express vague ideas, and the system automatically selects the most appropriate skills to execute tasks [23][24]

Core Insights - The article discusses the launch of Anthropic's Claude Cowork, highlighting significant issues such as accidental file deletion and security vulnerabilities that have raised concerns among users [2][5][38]. - Claude Cowork aims to provide AI collaboration capabilities similar to Claude Code but tailored for non-technical users, transitioning from a traditional Q&A model to an asynchronous collaboration model [38]. User Experience and Functionality - A user reported that during a test, Claude Cowork deleted approximately 11GB of files without recovery options, raising alarms about its reliability [2]. - Compared to Claude Code, Claude Cowork has been criticized for its cumbersome interaction process and slower efficiency, requiring multiple confirmations for actions that could be streamlined [4][38]. - The product is designed for long-term tasks, allowing users to connect to various services without repeated authentication, enhancing its utility for data-intensive roles [38]. Security Concerns - AI security firm PromptArmor identified vulnerabilities in Claude Cowork that could allow file theft through known but unresolved isolation flaws [5]. - Anthropic acknowledged these risks and advised users to be cautious, especially since the product is in a research preview phase [5][6]. Development and Iteration - The development team, led by Felix Rieseberg, emphasized rapid iteration based on user feedback, having completed the product in just 1.5 weeks [8][10]. - The team aims to create a more generalized interface for future applications, moving away from specialized input fields to a unified entry point for various tasks [21][22]. Product Design Philosophy - The design philosophy includes balancing model flexibility with workflow stability, with a focus on creating reusable knowledge and emergent capabilities [8][19]. - The article discusses the importance of user feedback in shaping the product's future, indicating a willingness to adapt based on how users interact with the tool [17][29]. Evaluation and Feedback - The evaluation team noted that while the concept of Claude Cowork is innovative, its execution has room for improvement, particularly in UI design and task management [38][41]. - Users are encouraged to explore the product's capabilities and provide feedback, as the team is committed to continuous improvement based on user experiences [41].

Core Insights - The article discusses the rising popularity of "Skills" in the AI community, comparing it to the previous trend of "Prompts" [4] - Skills are defined as capabilities designed for agents, allowing for automation and efficiency in various tasks [5][19] - The article provides examples of how Skills can be utilized in practical applications, showcasing their potential value [18][62] Group 1: Definition and Importance of Skills - Skills are essentially a set of functionalities that enhance the capabilities of AI agents, enabling them to perform tasks more effectively [19][24] - The introduction of Skills by Anthropic in December 2022 has led to widespread adoption and integration into various AI tools [21][23] - Skills differ from traditional prompts as they are structured like a folder containing various resources, rather than just a single text command [23][32] Group 2: Practical Applications of Skills - The article presents two case studies demonstrating the use of Skills: an AI topic generation system and a package generator for GitHub projects [5][9] - The AI topic generation system automates the process of identifying trending topics by collecting data from multiple platforms and generating a list of relevant topics [6][7] - The package generator simplifies the use of open-source projects by creating a user-friendly interface for those with limited programming knowledge [18][46] Group 3: Structure and Configuration of Skills - A complete Skill typically includes a core file named SKILL.md, which contains essential information and instructions for the AI agent [37][38] - The structure of SKILL.md is crucial, as it defines how the agent will utilize the Skill, including a YAML header and detailed instructions [38][39] - The article emphasizes the importance of clear and concise descriptions in the SKILL.md file to ensure effective communication with the AI agent [39][40] Group 4: Installation and Usage of Skills - Skills can be installed easily through command prompts or by dragging the Skills folder into the appropriate local directory [48][54] - Once installed, Skills can be activated and utilized by the AI agent to perform specific tasks based on user commands [57][58] - The article encourages users to start creating their own Skills to enhance productivity and streamline workflows [62]

Continual Learning in AI Agents - The industry recognizes the gap between AI agents and human learning capabilities, emphasizing the need for agents to continually learn and improve over time [1] - The industry is exploring different methods for AI systems to learn, including weight updates and learning in context using large language models (LLMs) [2] - Reflection over trajectories is emerging as a key theme, allowing agents to update memories, core instructions, and learn new skills [3][4][5] Skill Learning and Implementation - Skill learning involves reflecting over trajectories to learn skills, exemplified by the skill creator skill adapted from Anthropic [8][9] - Deep agent CLI allows specifying environment variables for logging traces, which is useful for reflection [10][11] - The industry is using Langsmith Fetch to grab recent threads from deep agents for reflection and persistent skill creation [12][13] - A practical example demonstrates how an agent can read a JSON file, reflect on its contents, and create a new deep agent skill, showcasing the utility of continual learning [15][16][17] Benefits and Future Directions - Skill learning enables agents to encapsulate standard operating procedures, such as grabbing Langsmith traces, for repeated use [19][20] - Continual learning loop involves agents reflecting on past trajectories to learn facts, memories, skills, and improve instructions [21][22]

हेलो हाय हेलो एवरीवन देखो इंडिया में स्टार्टअप का बूम बड़ा ही एक्साइटिंग लगता है। है ना. शटक फिर यंग फाउंडर्स एंड रील्स फंडिंग ये सब कुछ देख के हमें ऐसा ही लगता है जैसे हर कोई सक्सेसफुल हो रहा है। लेकिन ऐसा बिल्कुल नहीं है। देखो 95% स्टार्टअप्स इंडिया में 5 साल के अंदर ही बंद हो जाते हैं। तो रीज़ मनी मार्केट या लक नहीं है। रीज़न सिर्फ दो है। या तो उनके पास सही बिजनेस मॉडल नहीं होता या फिर उनको कस्टमर की रियल लाइफ प्रॉब्लम ही नहीं पता है। ये बात मुझे बहुत पहले समझ में आ गई थी। जब मैं खुद एक स्टूडेंट था। 12th क ...

Career & Skill Development - Traditional college life focuses on grades, assignments, and attendance, but the speaker advocates for prioritizing skills over scores [1] - Skills become an individual's identity and can determine their future, leading to numerous opportunities [2] - The speaker encourages choosing a skill, mastering it, and opening doors to 100+ new opportunities [2] Overcoming Failure - The speaker emphasizes not fearing failure but learning from it by analyzing the reasons for failure and working on skills [2][3] - The speaker shares personal experiences of failures in various endeavors like dancing, YouTube, and NDA exams, highlighting the importance of resilience [1][2] Networking - The speaker stresses that "Your network is your net worth," encouraging building connections with professors, juniors, seniors, and even strangers on LinkedIn [4] - Building connections can lead to golden opportunities, as exemplified by the speaker receiving 15+ internship offers through LinkedIn [4] Personal Branding - The speaker advises building one's own identity by creating a digital presence as a second CV, including GitHub repos, YouTube videos, and Instagram posts [4][5] - Documenting one's journey, including failures and achievements, can impact thousands of people [5] Career Guidance - The speaker advises against being distracted like 90% of students who focus solely on placements after college, missing out on other opportunities [5] - The speaker emphasizes the importance of running in the right direction towards one's goal to avoid failure [5]

Generative AI skills can bump up your salary as much as 47%, even in non-tech professions. But the professionals who see the greatest returns usually possess these three skills which enable them to use ChatGPT the right way for work, and make them stand out. Learn more at the link in the bio. https://t.co/u4HqJdGKhr ...

I'm a social scientist. I study human behavior. For the last few years, I've been thinking, what kind of talent do we need to thrive in the age of artificial intelligence? And moreover, will that talent be more specialist in nature or more generalist in nature? At school, I was terrible at maths. My parents told me that um can you do better? And I worked hard and moved from not so good to average, which was a big deal, right? [laughter] And then my parents said, "Yes, but can you do even better. " I said, " ...