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add: Loop Engineering methodology from @AYi_AInotes
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source_url: https://x.com/AYi_AInotes/status/2069831601668915323
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ingested: 2026-07-15
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status: inbox
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tags: [tech/agent, tech/llm]
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---
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# Loop Engineering
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## 来源
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@AYi_AInotes 推文 (2026-06-24, 61K views) + @akshay_pachaar 文章 "Loop Engineering Clearly Explained"
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## 核心概念
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Prompt Engineering 已死,Loop Engineering 接棒。从"指挥 AI 一步步走"变成"设计一个能自己跑完的系统"。
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@bcherny (Claude Code 构建者): "I don't prompt Claude anymore. I write loops, then let them run."
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模型正在变成标准件——同一个模型配上更好的循环设计,效果能从中等拉到顶级。
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## 四个支柱
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### 1. 上下文管理
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- Compact: 每 N 轮摘要压缩
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- Offload: 大输出写文件,context 只放路径+摘要
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- Sub-agents: 混乱子任务 spawn 子 Agent 隔离
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### 2. 刹车机制
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- max_iterations (硬上限)
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- budget + time (token/钱/时间)
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- no-progress detection (同调用同参数=卡死)
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- completion check (测试通过才是真完成)
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### 3. Maker-Checker 分离
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- 干活的 Agent 和检查的 Agent 必须分开
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- 不同的 prompt,Checker 的任务是挑错不是认可
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- 自己不批改自己的作业
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### 4. 工具收敛
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- 少而精,不重叠 (5-8 个核心工具)
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- 写入操作幂等
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- 错误信息写给 Agent 看(结构化)
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- 禁止 wildcard 执行 (npx *, bun run *)
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## Hermes 实现
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- delegate_task 分 Maker + Checker 两个 Agent
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- /new 开新会话 = context 压缩
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- cron job 天然有 max_iterations 和时间预算
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- Memory 精简 = 工具收敛
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## 检查清单
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- [ ] 硬性 max_iterations
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- [ ] token/time 预算
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- [ ] no-progress 检测
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- [ ] objective completion check
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- [ ] Maker ≠ Checker
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- [ ] 定期 context 压缩
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- [ ] 大输出 offload
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- [ ] 工具 ≤ 10 且不重叠
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- [ ] 写入幂等
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- [ ] Agent-readable errors
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