AI Product / LLM App / RAG / Agent Builder
Wu Feng
I design and build AI products from idea to demoable MVP.
I focus on turning AI capability into usable workflows: defining the problem, breaking down requirements, shaping interaction logic, building the MVP, and making outputs explainable enough to review, trust, and iterate.
CareerPilot
01AI career co-pilot for JD parsing, resume tailoring, and interview prep
StyleSnap
02Multimodal wardrobe assistant for explainable daily looks
MedRAFT Medical RAG QA System
03Medical RAG workflow for evidence-grounded Chinese QA
Multi-Agent Quant Research System
04Agent-driven decision support for fund rotation research
Flagship Work
Four AI product case studies built around workflow design, MVP validation, and explainable outcomes.
Each project shows how I translate model capability into a concrete user journey, decision logic, visible interface, and measurable product output.
Capabilities
A practical stack for shipping AI products from requirement framing to interface delivery.
My work combines product thinking with implementation depth across LLM applications, RAG pipelines, multimodal UX, agent workflows, and full-stack MVP delivery.
LLM Applications
RAG Systems
AI Agents
Multimodal AI
Full-stack Engineering
Data Science
Working Style
Product-first AI building, with enough engineering depth to make the demo real.
I care about AI systems that can actually be shown, inspected, and discussed: clear user flows, grounded outputs, visible decision logic, and interfaces that make the model behavior easier to understand.
Looking for AI product internships, while staying hands-on with LLM application building.
I am especially interested in teams building applied AI products, intelligent workflow tools, multimodal assistants, RAG experiences, and agent systems with real user value.