While autonomous agents and large-scale reasoning models are currently attracting significant attention and investment, I find that Retrieval-Augmented Generation (RAG) and its variants remain foundational to building practical, knowledge-intensive AI applications. The RAG space isn’t static; it’s continually evolving, offering compelling solutions for real-world AI challenges. Take GraphRAG, for instance—a design pattern that garnered attentionContinue reading "RAG’s Next Chapter: Ag...
