Is RAG Dead? The Rise of Context Engineering and Semantic Layers for Agentic AI
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RAG (Retrieval-Augmented Generation) is evolving beyond simple vector search into context engineering, where AI agents dynamically write, compress, isolate, and select context across data sources. Knowledge graphs and semantic layers are becoming critical infrastructure for enterprise AI, providing structured, explainable retrieval that respects governance policies. The shift from single-prompt RAG to agentic workflows requires metadata management across all data types, tools, and agent memories, with evaluation expanding beyond accuracy to include relevance, groundedness, provenance, and recency.
Table of contents
IntroductionThe Rise of RAGThe fall of RAG and the rise of context engineeringContext engineering needs a semantic layerThe future of RAGConclusionSort: