Feb 02,2026 Beyond “Don’t Hallucinate”: Engineering True Fidelity in RAG Systems
As we build increasingly sophisticated RAG (Retrieval-Augmented Generation) systems, we encounter a persistent challenge: ensuring the AI stays true to its source material. It’s a common misconception that simply instructing a Large Language Model (LLM) to “answer based only on the provided context” is sufficient. In reality, preventing hallucinations and ensuring high-fidelity answers requires robust engineering mechanisms, not…
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