In evidence-gated AI, the dangerous failure is not that a public claim meets a valid counterexample. The dangerous failure is keeping the same public claim after the evidence boundary has changed.
A counterexample should therefore become infrastructure. It should name the target claim, show the minimum failing case, identify the missing receipt or overreach, and force a clear boundary update.