AgentOS：从应用孤岛到自然语言驱动的数据生态系统

The rapid emergence of open-source, locally hosted intelligent agents marks a critical inflection point in human-computer interaction. Systems like OpenClaw demonstrate that Large Language Model (LLM)-based agents can autonomously operate local computing environments, orchestrate workflows, and integrate external tools. However, these agents currently function as conventional applications running on legacy operating systems designed for Graphical User Interfaces (GUIs) or Command Line Interfaces (CLIs). This architectural mismatch results in fragmented interaction models, poorly structured permission management often referred to as 'Shadow AI', and significant context fragmentation. A new paradigm is proposed: a natural language-driven data ecosystem aimed at addressing these issues and enhancing the efficiency and flexibility of human-computer interaction.