The Validation Trap: Why Structured Output Feels Safe But Isn't

As LLM-based data extraction scales across industries, schema validation proves dangerously insufficient—it checks structure but not truth. Modern language models generate syntactically perfect hallucinations that bypass all standard checks, such as fabricating a '7' rating on a 5-star scale, because validation only examines the shape of data, not its accuracy. Organizations need to implement value-level sanity gates that verify realistic ranges, dates, and cross-field consistency to catch these 'plausibly false' values before they corrupt production databases.