15 个源文件，5 个依赖，零数据库。把 LLM 当编译器用，Obsidian 当 IDE，Wiki 当代码库。

I built a personal knowledge compiler that treats the LLM as a programmer and your wiki as a codebase. 15 source files, 5 dependencies, zero databases.

The most important file in the Claude Code snapshot isn't a prompt file or a tool definition. It's a state machine. Once you see that, a lot of agent design decisions start making sense.

The most novel thing in the Claude Code snapshot isn't a tool or a prompt. It's how aggressively the runtime is built around preserving prompt-cache identity across forks, compaction, and long-running sessions.

After auditing a publicly posted Claude Code source snapshot and reading OpenAI's harness essays, I came away with one conclusion: the model is only the brain. The product is the runtime around it.

LLM 天生话多。对陪伴产品来说这是个大问题——真人发消息不会写小作文。这是我如何在不杀死人设的前提下控制回复长度的。

LLMs love to talk. For a companion app, that's a problem — real people don't write essays when you text them. Here's how I built a hybrid system to control response length without killing personality.

一个聊了200条就忘了你名字的 AI 不是陪伴，是健忘症患者。这是我如何把 Mio 的记忆从简陋的键值存储重建成真正像人类回忆的系统。

An AI companion that forgets your name after 200 messages isn't a companion — it's a chatbot with amnesia. Here's how I'm rebuilding Mio's memory from a dumb key-value store into something that feels like actual recall.