Blog 博客
2026
- Documentation Rots. Skills Stay Alive.Documentation is write-once-read-maybe-update-never. A Skill is a persisted human-agent contract — agents write them, humans curate them, and knowledge stays alive in the loop. Why Skill marketplaces will inevitably fail, and why everyone needs their own Skill library.--
- 文档写完就落灰了,Skill 越用越活文档是 write-once-read-maybe-update-never。Skill 是 human-agent contract 的持久化形式——agent 写、人 curate、知识在循环中活起来。Skill marketplace 为什么必然失败,每个人为什么需要自己的 Skill library。--
- Harness Engineering II: When Tasks Go From Minutes to HoursPrompt engineering hits a cliff in long-run tasks. Not because your prompts are bad — because attention decay, context rot, and drift accumulation are physics. Harness engineering is the complete answer.--
- Harness Engineering II: 当任务从分钟级变成小时级Prompt engineering 在 long-run task 面前断崖式失效。不是因为 prompt 写得不好,是因为 attention decay、context rot、drift accumulation 三重物理极限。Harness engineering 是完整的答案。--
- The Continued Evolution of the Agent EraFrom the Cognition Ladder to the Capability × Validation Matrix: New thoughts on the Agent era, one year later--
- Agent 时代的持续进化从认知阶梯到能力×验证矩阵:一年之后,我对 Agent 时代的新思考--
- Harness Engineering: Don't Hope Your AI Behaves — Build a Structure Where It Can't NotLLMs satisfice by default. Harness engineering constrains agent behavior with structure, not prompts. A four-layer architecture and how we landed it in OPC.--
- Harness Engineering: 别期望 AI 行为正确,构造一个结构让它想不正确都难LLM 的默认行为是 satisfice,不是 optimize。Harness engineering 用结构约束 agent 行为,而不是用 prompt 期望 agent 行为。一个四层架构的设计理念和 OPC 落地。--
- OPC — Your AI Review Team in One Slash CommandI built a Claude Code skill that dispatches 11 specialist AI agents to review code from different perspectives. Here's an honest comparison with just asking Claude directly.--
- OPC — 一个斜杠命令召唤你的 AI Review 团队我做了一个 Claude Code skill,用 11 个 AI 专家并行 review 代码。这是一个诚实的对比:OPC vs 直接问 Claude。--
- Your AI Agent Has Amnesia — Here's How I Fixed ItAI agents start from scratch every session. I built memex — a Zettelkasten-based persistent memory system that needs no vector DB. Here's the design philosophy and trade-offs behind it.--
- 你的 AI Agent 每次都失忆 —— 我是这样修好的AI agent 每次新 session 都从零开始。我用 Zettelkasten 方法构建了 memex —— 一个不需要 vector DB 的 agent 持久记忆系统,背后的设计哲学和技术取舍。--
- What we can learn from SuperpowersSuperpowers 是一套 Claude Code 的 skill 插件。深入分析其设计哲学:从流程强制到 Zero Trust 架构,再到用 AI 弱点约束 AI 的元层机制。--
- What We Can Learn from SuperpowersSuperpowers is a set of skill plugins for Claude Code. A deep dive into its design philosophy — from enforced workflows to Zero Trust architecture, to a meta-layer mechanism that uses AI's weaknesses to constrain AI.--