The 4 RAG Architectures: How to Give AI Perfect Memory Without Retraining
Last Updated on February 12, 2026 by Editorial Team
Author(s): TANVEER MUSTAFA
Originally published on Towards AI.
Understanding Naive RAG, Advanced RAG, Modular RAG, and Agentic RAG
Your LLM is brilliant but frustratingly limited.
This article delves into the concept of Retrieval Augmented Generation (RAG), discussing its four architectures—Naive, Advanced, Modular, and Agentic RAG. Each architecture presents its unique methodology for updating and enhancing LLMs by integrating real-time data and internal documents, thus mitigating the limitations of traditional model training. The article outlines the advantages of RAG in terms of cost-effectiveness, current information access, and private data handling, while also addressing the potential accuracy improvements over conventional approaches.
Read the full blog for free on Medium.
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