A guide to detecting hallucinations in AI agent workflows

n8n releases a guide outlining methods to detect hallucinations in AI agent workflows, categorizing them into factual, contextual, fabricated, and self-contradictory types. Detection techniques include fidelity and grounding checks based on DeepEval, self-consistency checks, semantic entropy and uncertainty estimation, source and retrieval verification, confidence thresholds, and human intervention. The guide emphasizes that no single detector covers all failure modes, requiring layered combinations of multiple checks based on failure type.