📄 中文摘要
大多数 AI 代理构建者选择框架（如 LangChain、CrewAI、AutoGen）作为整个技术栈。然而，框架仅提供基本构件，如工具调用、记忆接口、代理循环和链组合，而操作系统则提供不同的功能，包括进程间的隔离、调度、资源管理和故障边界。大多数生产环境中的代理失败是由于操作系统层面的问题，例如代理 A 在代理 B 读取共享资源时写入数据，导致隔离问题；一个卡住的循环阻塞下游代理，造成调度问题。因此，理解框架与操作系统之间的区别对于构建可靠的 AI 代理至关重要。
代理框架与代理操作系统：生产环境中区分的重要性
📄 English Summary
Agent Framework vs. Agent OS: Why the Distinction Matters in Production
Most AI agent builders opt for frameworks like LangChain, CrewAI, and AutoGen, treating them as the entire stack. However, frameworks provide only primitives such as tool calling, memory interfaces, agent loops, and chain composition. In contrast, an operating system offers functionalities like isolation between processes, scheduling, resource management, and fault boundaries. Most production agent failures stem from OS-level issues, such as when Agent A writes to a shared resource while Agent B is reading it, leading to isolation problems, or when a stuck loop blocks downstream agents, causing scheduling issues. Understanding the distinction between frameworks and operating systems is crucial for building reliable AI agents.