Retrieval-Augmented Generation (RAG) promises to combine external knowledge sources with the capabilities of large language models. In theory, the concept is simple: retrieve the right information, provide it to the model, and generate an answer. In practice, many implementations fail to deliver the expected results. The problem is rarely the model itself. It is rarely… more