Designing Knowledge Bases for RAG: The Data Architecture Most Teams Skip

This article emphasizes that a RAG knowledge base is not a document dump but a governed data architecture layer. It discusses the importance of source curation, ownership, metadata, chunking strategies, security trimming, freshness controls, retrieval evaluation, and lifecycle management. The article contrasts fast pilot approaches with production-oriented designs, highlighting how metadata creates retrieval boundaries and how security trimming ensures access control. It provides a practical pipeline overview and argues that content quality becomes an operational dependency in RAG systems. The target audience includes developers and architects building AI assistants or agentic workflows.