System Design: Retrieval-Augmented Generation (RAG) Pipeline at Scale

Name: How to Build a Scalable RAG System for AI Apps
Uploaded: 2026-02-08T03:00:06-08:00
Duration: 15 min 52 s
Channel: ByteMonk
Description: Ingestion, chunking, embedding storage and query-time retrieval as one production pipeline.

Design a RAG system that lets an LLM answer questions grounded in a company's internal documents (docs, tickets, wikis) — millions of documents, updated continuously, with citations and sub-second retrieval at query time.

System Design: Retrieval-Augmented Generation (RAG) Pipeline at Scale

What clarifying questions would you ask the interviewer?