Retrieval-Augmented Generation (RAG) — Roadmap Step & Resources
Grounding an LLM's answers in a client's actual documents and data instead of its training data alone
- Level: advanced
- Estimated time: 2 days
- Roadmap: Forward Deployed Engineer (FDE)
Before this step
Mini projects
- Build a small RAG pipeline over a client's document set
Interview questions
- Walk me through how you'd design a RAG system for a client's internal knowledge base.
Study resources
- Learn RAG From Scratch – Python AI Tutorial from a LangChain Engineer (Video) — A comprehensive RAG course taught directly by a LangChain engineer.
- Retrieval (Article) — The official LangChain documentation's conceptual guide to retrieval and RAG.
Part of
- AI and LLM Application Building — section
- Forward Deployed Engineer (FDE) roadmap — the full learning path