RAG Techniques You Must Know in 2025

Author(s): Ahmed Boulahia

Originally published on Towards AI.

RAG is no longer just about answering questions; here are the top techniques in 2025 that every AI builder should know.

By now, you’ve probably seen tons of videos and projects about RAG (Retrieval-Augmented Generation). Most of them either recycle the same old RAG techniques or dive into overly complex retrieval methods that are hard to follow.
But in reality RAG is no longer just a question-answering demo. In 2025, it’s becoming the backbone of AI agents and production-ready RAG pipelines. And if you want to stay ahead, you need to understand the RAG workflows that actually matter.

The article discusses the evolving landscape of Retrieval-Augmented Generation (RAG) techniques that AI developers should adopt in 2025. It introduces three main approaches: Contextual Retrieval, which enhances data relevance; Agentic RAG, which incorporates agent layers for multi-step queries; and Hybrid Retrieval + Re-ranking, combining semantic and keyword searches for accurate results. Overall, it emphasizes that RAG is transforming into a more robust, intelligent framework capable of handling complex queries and ensuring relevant outputs for AI applications.

Read the full blog for free on Medium.

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Published via Towards AI