Frontend & AI-product engineer·Guangdong, China
I build AI products and learning-first engineering projects.
Turning complex ideas into small, traceable steps — framework internals, build tools, compilers, and practical AI applications. A running record kept in public, mostly on GitHub, occasionally in essays.
“Talk is cheap. Show me the code.”
Products I'm shipping right now. Each one is live somewhere you can click; each one commits small.
An AI agent that reads your PDFs and draws editable mind maps. A visible multi-step tool-calling loop, built-in RAG (no LangChain), bring-your-own-key, multi-provider — the reasoning is legible, the output is yours to keep.
Previewable Flutter animations — real running Flutter web, not GIFs — each one paired with its traceable pitfalls and a parameter playground. Reachable from Claude Code or Cursor as a remote MCP tool.
A multi-provider AI image playground — text-to-image, edit, inpaint. Entirely client-side: bring your own API key; nothing ever touches my server.
Convert an API's documentation into a working MCP service, so AI coding IDEs — Claude Code, Cursor — can call your APIs directly, without you writing any plumbing.
Reads a 1,000-year-old system as a data problem: it renders a person's 八字 (BaZi) as a stock-style K-line chart. Enter a birth date and it plots a life's fortunes as candlesticks, with AI-written readings across character, career, wealth, and health.
A deliberately minimal tennis scorer — offline-first and installable, with no account and no network required. Games, sets, and tiebreaks are tracked with state kept entirely on-device, so it never drops a point courtside.
Work landed in projects I use every day — small, defensible patches to codebases many multiples my size.
The best way I know to understand a tool is to write a small, honest version of it. Each of these is short enough to read in one sitting and complete enough to run.
↳github.com/xianjianlf2/<name>