AI Product Case Study: Driving Range Ball Allocation
Role: Product Manager
Designed and built an AI-assisted web application to help golfers create more efficient driving range sessions by intelligently allocating a fixed number of balls across different shot types. Leveraged large language models to accelerate product decisions, including market research, gap analysis, feature prioritization, and UX design. Integrated AI-driven recommendations to generate personalized practice plans based on user goals while maintaining full user control, and used AI to develop testing strategies, define success metrics, and iterate quickly on the product experience.
AI Golf Caddy Web App (RAG + LLM)
Role: Developer, Prototype Manager
Built an AI-powered golf caddy assistant using Retrieval-Augmented Generation (RAG) and OpenAI APIs to deliver personalized, hole-by-hole strategy recommendations. Developed a pipeline to ingest structured course data (CSV), generate embeddings, and retrieve relevant context using a vector database (FAISS). Implemented prompt engineering with in-context learning and controlled reasoning to produce concise, actionable golf advice tailored to player handicap and distance. Deployed an interactive web interface using Python and Streamlit.
Automated Job Seeker
Role: Developer
Built a weekly job search automation tool that scrapes top Toronto job postings matching my resume and delivers a curated digest to my inbox every Saturday morning. The script uses AI to rank and filter roles against my resume — covering Product Owner, Product Manager, and AI PM positions — and emails a formatted summary with match scores and direct apply links. Runs on a cron schedule with full logging.