Universal learnable → PAC learnable. Proof sketch: UniversalLearnable gives learner L with rate → 0 and Pr[error ≤ rate(m)] ≥ 2/3. Two components: 1. Event containment: rate(m) < ε ⟹ {error ≤ rate(m)} ⊆ {error ≤ ε} (monotonicity). 2. Confidence boosting: 2/3 → 1-δ via median-of-means (Γ₆₇, sorry'd in boost_two_thirds_to_pac). Routes through boost_two_thirds_to_pac which encapsulates the Chernoff-based boosting.