How to Fix LLM Hallucinations in Production Code
Fixing LLM hallucinations in production requires a layered defense strategy: rigorous Chain-of-Verification steps at inference time, grounding the model’s output in verified external data sources, and automated evaluation suites that give you a hallucination rate you can track and regress against in CI . No single technique eliminates the problem, but combining prompt-level constraints, retrieval-augmented grounding , inference-time self-verification, and architectural validation layers reduces it to a manageable — and measurable — engineering challenge.







