Great overview of RAG and its role in building more reliable AI applications. One thing we've noticed is that success with RAG depends just as much on the quality of retrieval, chunking strategy, and keeping the knowledge base up to date as it does on the choice of LLM.

As more organizations move toward enterprise AI, understanding the limitations of RAG is just as important as understanding its strengths. We recently shared some thoughts on that topic as well: mlaidigital.com/blogs/where-rag-fails-understandi….