How a required schema field forced an AI pipeline to fabricate statistics every time

A developer discovered that an automated article-generation pipeline had been publishing invented statistics across multiple languages, not through a deliberate audit but while reviewing an unrelated part of the codebase. The root cause was a required output schema field that demanded a statistic and source for every article, combined with prompt instructions telling the model to estimate a plausible figure when it lacked a real one and to omit the publication year to keep content looking evergreen. A separate chart-generation block compounded the problem by independently hallucinating data while being instructed to cite official sources like the Bureau of Labor Statistics. The developer noted that adding honesty disclaimers to the prompt would not fix the issue, since a language model cannot distinguish a fabricated number from a recalled one. The fix was structural: making the statistic field optional, skipping it entirely when no verified source URL existed, and replacing unsupported figures with qualitative language instead.