4 Types of RAG Explained: From Vanilla Retrieval to Agentic Workflows
PawelHuryn · x · 2026-07-30
The author breaks down four mainstream Retrieval-Augmented Generation (RAG) architectures and their specific use cases:
- Vanilla RAG: Embeds docs and retrieves top chunks. Best for lookup questions, demos, and prototypes.
- Adaptive RAG: Cleans the query first and picks a strategy per request. Ideal for messy, varied questions.
- Hybrid RAG: Queries several sources (vectors, SQL, search) and merges them. Used when data is spread across systems.
- Agentic RAG: The agent decides the retrieval logic, accessing files, tables, APIs, or vector stores. The first three are designed pipelines, while Agentic RAG gives the system the flexibility to decide what to read and where from, typically used in workspace agents.
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