One surprising insight is that the issue often isn't the retrieval system itself, but rather how it's integrated with decision-making agents. We've observed that when retrieval-augmented generation (RAG) architectures employ agentic behaviors to validate their own responses, there's a significant drop in these "polite hallucinations." By allowing retrieval systems to autonomously check and cross-verify data against multiple sources, you can dramatically improve accuracy. I wrote more about this here: enterprise.colaberry.ai/i/oc-hashnode-4dab489b