We study delegation rules by principals uninformed of the underlying state (external uncertainty) and the preferences of better-informed agents (internal uncertainty). Evaluating delegation sets with a max?min criterion, we show that in multidimensional environments optimal delegation sets are simple: for broad classes of preference uncertainty, optimal delegation sets are convex. Thus, interval delegation is always (robustly) optimal when the action space is unidimensional. Internal uncertainty can justify greater discretion, allowing actions that are never optimal for the principal in any state; and a version of the ally principle holds: alignment along enough dimensions implies unconstrained delegation along all dimensions.