I run a Make.com pipeline that produces daily sports betting articles. Odds API in, API-Football in, aggregation in the middle, GPT-4o for the writing, Google Docs out. Looks great on the diagram. Worked beautifully in testing.
Then it shipped. And within a week we had articles confidently telling readers that a Spanish second-division side was "the reigning Champions League winners," that a 38-year-old striker had "just signed his first professional contract," and — my personal favourite — that a match scheduled for Saturday would "kick off this past Tuesday."
Every fact technically plausible. Every fact completely wrong.
This post is what I changed to stop that happening. Not a clever prompt trick. Not a model swap. A structural change in how the data flows into the LLM call.
The cause is almost never "the model"
