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juzikuwei/README.md

🖥️ ~/whoami

我构建 AI-native 应用,要求它们可测试、可观测、有证据支撑——是能在失败里活下来的工作流,而不是只在 demo 里好看的东西。

我不手写代码——这里的每一行代码都由 AI(Claude Code 和 Codex)编写。 架构设计、技术决策和验收测试由我负责。Vibe coding,按工程标准交付。

  • 🔭 正在做AI/Agent Tech Radar:混合检索(E5 + BM25 + RRF + cross-encoder)、有界 tool-calling ReAct agent、确定性引用校验、只读 MCP server
  • 🧪 在探索 — LangGraph、会话上下文压缩、agent 评测闭环、claim-level groundedness
  • 🌏 工作语言 — 中文 & English · UTC+8
  • 📫 联系我juzidekuwei@outlook.com

🚀 ~/projects

AI/Agent Tech Radar

Python FastAPI React RAG MCP

Vibe-coded with Claude Code & Codex — human-owned architecture and acceptance.

Focus Lab

JavaScript LangChain Streaming LLM applications

Vibe-coded with Claude Code & Codex — human-owned architecture and acceptance.

🤖 ~/how-i-build

这里的每一行代码都由 AI 编写——与 Claude Code、Codex 和 Cursor 一起 vibe coding。分工如下:

Mine AI's
架构、范围与 spec 实现——全部代码
代码审查与设计质询 重构与样板代码
验收:测试、评测套件、Trace 测试脚手架
决策记录与权衡取舍(ADR) 文档草稿,由我编辑定稿

Claude Code Codex Cursor Vibe Coding

🏗️ ~/mental-model

构建一个 agent 系统,就是在盖一栋房子:

房子比喻:工程原理是地基,LangGraph 是脚手架,你自己的代码是室内装修

脚手架从不决定房间住起来的感觉。框架解决的是编排;让 agent 值得信任的那些决策,没有现成脚手架。

两条轴线:横轴是构建能力,纵轴是可靠性——真正的功夫是从惊艳的 demo 走到可以被信任的系统
scope before framework
evidence before confidence
failure paths are product behavior
small experiments before large abstractions
ai writes, i verify

这里的代码由 AI 写——思考不是。

📊 ~/stats

GitHub statistics Top languages
GitHub contribution streak
GitHub trophies

🎨 ~/contribution-art

3D contribution graph Contribution snake animation

🤝 ~/connect

我边做边分享真实过程:架构决策、别扭的边界情况、评测里的缺口,以及每一个让 AI 工作流更可信的小改进。

See all projects Email

公开地构建——一次一个可度量的工作流。

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