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]