Retrieval-Augmented Generation

Generative AI learning path

Master retrieval-augmented generation through 10 carefully ordered interview questions. Each lesson includes a detailed explanation, practical example, common mistakes, and an interview-ready summary.

10 questions3 easy · 3 medium · 4 hard difficulty mix≈ 50 min total study time

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Test your Retrieval-Augmented Generation knowledge

Match five interview questions to their best answers. Your result stays on this device.

Table of contents

Work through the questions in order for a guided path, or jump directly to the concept you want to review.

01What is retrieval-augmented generation?hard · senior level · 5 min read→02How does a RAG pipeline work?medium · mid level · 5 min read→03How should documents be chunked for RAG?easy · junior level · 5 min read→04How do embeddings support semantic search?hard · senior level · 5 min read→05What is hybrid search?medium · mid level · 5 min read→06What is reranking?easy · junior level · 5 min read→07How do you evaluate retrieval quality?hard · senior level · 5 min read→08How do you keep a RAG index fresh?medium · mid level · 5 min read→09How do you cite sources in RAG answers?easy · junior level · 5 min read→10When should you use RAG instead of fine-tuning?hard · senior level · 5 min read→