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Generative AI is revolutionizing coding, but its limitations in accuracy and long-term context retention are becoming increasingly apparent. A promising solution gaining traction involves integrating generative models with retrieval-based systems, enabling AI to access and utilize relevant information on demand. This Retrieval-Augmented Generation (RAG) approach significantly enhances the reliability and relevance of AI-generated code by grounding it in actual code snippets, documentation, and project context. The emerging question is whether RAG represents the next major leap forward for AI coding assistants. Are readily available tools effectively harnessing RAG to provide real-time access to extensive codebases and API documentation? This debate was sparked recently by a discussion initiated by Reddit user /u/Lumpy_Tumbleweed1227.