Photo by anna-m. w. on Pexels

While many attribute Retrieval-Augmented Generation (RAG) system failures to shortcomings in the Large Language Model (LLM) itself, the real culprits often lie within the systemic infrastructure. Issues like unmonitored preprocessing pipelines, not the LLM’s intelligence, are frequently the source of RAG performance degradation. According to insights from a recent discussion, crucial areas to monitor include: ingestion drift, chunking drift, metadata drift, embedding drift, and retrieval configuration. Continuous evaluation of these factors is essential for maintaining RAG system reliability. A deeper dive into the topic can be found at [https://old.reddit.com/r/artificial/comments/1pf41nj/the_real_reason_most_rag_systems_mysteriously/](https://old.reddit.com/r/artificial/comments/1pf41nj/the_real_reason_most_rag_systems_mysteriously/).