4.1 初始化：从零到一

理论讲完了，现在来动手。一个 AI Context Workspace 初始化需要几步？

第一步：创建目录结构。

一个最小的工作区只需要这些：

my-workspace/
├── AGENTS.md        # 入口路由文件
├── background/      # 背景知识
├── conventions/     # 约定规范
├── artifacts/       # 任务状态
└── projects/        # 实际工作材料和交付物

AGENTS.md 是路由表，告诉 AI 每个目录是干什么的。background/ 放项目背景。conventions/ 放工作规范。artifacts/ 放任务状态。projects/ 放实际产出。

第二步：写背景。

把项目的基本信息写进 background/。不需要多，但需要准：

  • 这个项目是干什么的？
  • 技术栈是什么？
  • 关键的业务概念有哪些？
  • 有什么需要特别注意的约束？

背景文档不需要一次性写完，可以随着项目推进逐步补充。但一开始至少要有一个概览，让 AI 知道"这是谁的地盘"。

第三步：写约定。

把做事的方式写进 conventions/。也是从最少开始：

  • 工作流怎么走？（可以用本书介绍的 L0-L3）
  • 代码风格有什么要求？
  • 文档格式有什么要求？
  • 检查标准是什么？

约定也是逐步完善的。发现一个问题，就加一条约定。不要一开始就追求完备。

第四步：初始化 Artifact 索引。

artifacts/index.json 初始为空数组。第一个任务开始后，往里面添加一条记录。

初始化工具

如果你在用支持 AI 指令的客户端（如 OpenCode、Codex），可以写一个初始化脚本，让 AI 自动完成上述步骤。你只需要说"初始化工作区"，AI 就会分析你的项目、生成背景、建立路由。

不要追求完美初始化

很多人初始化项目时，花大量时间想把背景和约定一次性写好。这是错误的。你甚至不知道一个项目需要什么约定，直到你遇到第一个问题。所以，从最小集开始，迭代完善。

一个初始化的 AI Context Workspace，可能只有三五行背景、一条约定、一个空的任务列表。但它已经是一个可用的工作区了。其他的，在做任务的过程中逐步补充。

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