When a model performs well on training data but poorly on new data because it memorized specific examples rather than learning generalizable patterns. Overfitting explains why demo performance may not match production results, and frequently leads to memorization and subsequent regeneration of training material.
See: Evaluation (evals); Generalization; Memorization; Training