As educators increasingly turn to artificial intelligence to streamline resource creation, the strategy behind prompt formulation determines the final quality of student materials. Relying on generic requests often produces lackluster worksheets requiring extensive revisions. Modern educators are experimenting with structured frameworks like role-specification, targeted constraints, and multi-step reasoning to generate highly tailored learning tools. What specialized instructions, formatting constraints, or iterative workflows have yielded the most accurate, differentiated, and ready-to-print student resources in your experience? Share the specific parameters that transform standard AI outputs into highly effective classroom exercises.