As part of my transition from QA into AI Engineering, I built AskMyCar, a practice project to go deeper into LLMs and RAG. The idea is simple: you pick your car (brand, model, year) and ask questions about its owner's manual in plain language, like "how often should I change the oil?" or "what tire pressure do I need?". It answers using only the manual and cites the sources, instead of making things up. How it works: a Playwright scraper pulls the official manual, it's stored in AWS S3, and a RAG pipeline built with LangChain and Chroma retrieves the relevant parts to answer. It runs on Claude when an API key is set, or a local Ollama model as fallback. Exposed through a FastAPI backend with auth and rate limiting, and a React + TypeScript frontend deployed on Vercel. The whole pipeline is traced with LangSmith. Next step is automated evaluation with LangSmith to measure groundedness and correctness, where my QA background becomes a real advantage. Demo in the video. Feedback is welcome.