我叫 Jay，正在以扎实的工程基本功为底座，持续构建面向真实问题的 AI 应用。

I’m Jay, building toward becoming an AI Native Builder—grounded in solid engineering fundamentals and focused on AI applications for real problems.

I learn by building: turning questions into small, runnable, testable, and explainable projects.

我相信学习要落到作品上：把问题变成可运行、可验证、可复盘、也能讲清楚的工程实践。

My current direction is AI Agent and RAG application engineering, with Python and backend engineering as long-term foundations.

当前主线是 AI Agent 与 RAG 应用工程，同时持续夯实 Python 与后端工程基础。

A notebook-first learning agent for Python and NumPy that connects learner profiles, staged plans, theory checks, code labs, and evidence-based progression.

一个以 Notebook 为入口的 Python 与 NumPy 学习 Agent：把学习画像、阶段路线、理论检查、代码 Lab 与基于证据的推进机制连接成闭环。

A long-term CS and AI learning lab for project practice, reflection, and reusable learning assets.

一个长期维护的 CS 与 AI 学习实验室，用于项目实践、定期复盘与沉淀可复用的学习资产。

A tested Python CLI for text statistics, chunking, structured JSON output, and mock summarization.

一个经过测试的 Python 文本处理 CLI，支持文本统计、分块、结构化 JSON 输出与模拟摘要。

• AI Agent and RAG application engineering / AI Agent 与 RAG 应用工程
• Python and TypeScript fundamentals through tests and small production-shaped projects / 通过测试和小型工程项目夯实 Python 与 TypeScript
• Typed interfaces, structured model output, observable failures, and reproducible demos / 类型化接口、结构化模型输出、可观测失败路径与可复现演示

Build → verify → document → iterate.

构建 → 验证 → 记录 → 迭代。

I’m early in the journey, but serious about the craft: each project is a deliberate step toward becoming an AI Native Builder.

我仍在成长的起点，但会认真对待每一次工程实践：每个项目，都是向 AI Native Builder 迈进的扎实一步。

• GitHub: @justlearner010