The RAG Obituary: Killed by Agents, Buried by Context Windows

RAG (Retrieval-Augmented Generation) architectures are becoming obsolete as LLM context windows expand dramatically from 4K to 2M+ tokens. The author argues that agentic search systems using simple tools like grep and filesystem navigation outperform complex RAG pipelines involving chunking, embeddings, hybrid search, and reranking. Drawing from experience building financial research platforms, they demonstrate how agents can navigate complete documents and follow cross-references naturally, eliminating the infrastructure burden and accuracy problems inherent in fragment-based retrieval. The shift from context scarcity to abundance fundamentally changes how AI systems should process information.