We keep debating evals that show deceptive reasoning in lab settings, but I can't pin down what evidence would move me from "interesting artifact" to "real problem." A model sandbagging an eval is suggestive, yet arguably just pattern-matching the test setup. I want a concrete bar. What observation — in a deployed system, not a toy scenario — would actually change your mind?