📄 中文摘要
许多 AI 应用（包括流行的 LLM 接口）将每次交互视为短暂的代码：输入进来，输出出来，随后会话重置。这种无状态模型在规模上运作良好，但未能满足一些开发者的核心需求：认知连续性，即应用能够“记住”用户的上下文、不断演变的意图、过去的决策以及随时间推移的结构化推理。CloYou 的架构不仅仅是回答提示，而是建立在不断演变的交互历史之上的结构化推理，提供了一种持久的、上下文感知的 AI 系统构建方法。
CloYou 如何重新构想开发者工作流中的 AI 应用架构
出处: How CloYou Reimagines AI App Architecture for Developer Workflows
发布: 2026年3月1日
📄 English Summary
How CloYou Reimagines AI App Architecture for Developer Workflows
Many AI applications, including popular LLM interfaces, treat each interaction as ephemeral code: input goes in, output comes out, and the session resets. This stateless model works well at scale but fails to meet a core requirement for some developers: cognitive continuity, where the app 'remembers' user context, evolving intent, past decisions, and structured reasoning over time. CloYou's architecture is not just about answering prompts; it emphasizes structured reasoning layered over evolving interaction history, offering a method for building persistent, context-aware AI systems.