两个主案例
面向专业材料的 RAG 知识构建，与基于静态 SQL 证据的字段级血缘治理——把知识与 SQL 分别收束为可核验、可审计的结论。
进入项目索引AI Native · independent work · public portfolio
方法先于模型，
证据先于结论。
以 AI Native 作为工作方式，把工程判断归纳成可检验的方法。这里整理围绕 Agent、数据平台与工程交付的独立研究和匿名化案例——重点不在技术清单，而在问题如何被界定、边界如何收束、结论如何验证。
从三个入口开始。
AI Native · independent work · public portfolio
Methods before models,
evidence before conclusions.
I work AI-native and turn engineering judgment into methods that can be checked. This site collects independent research and anonymized cases around agents, data platforms, and engineering delivery — the point is not a technology list, but how a problem is framed, how its boundary is narrowed, and how a conclusion is verified.
Start from three entrances.
Two flagship cases
RAG knowledge building for professional material, and field-level lineage governance grounded in static SQL evidence — each reduced to a verifiable, auditable conclusion.
Open the project indexTwo articles
The agentic boundary paradox and loop engineering — how the human–machine boundary moves, and how agent development becomes an acceptable loop.
Read the articlesA decade of practice
These judgments come from more than ten years of data and agent engineering practice. Roles, stacks, and project details unfold along a timeline.
View the resume