An AI face in profile against a digital background. For years, AI progress has been measured by scale: larger models, bigger datasets, longer context windows. Each new breakthrough promises that if we simply feed systems more data, we’ll get sharper insights. Yet, at least outside of training, that assumption is running into trouble. As models absorb longer prompts, they often become less reliable. The model has more to choose from, which makes it more likely to focus on the wrong thing.