Researchers prove the NP-hardness of the Universal Clustering Problem (UCP), a common optimization core in various clustering paradigms. This result explains characteristic failure modes in clustering methods, such as local optima and greedy merge-order traps. The study motivates a shift towards stability-aware objectives and interaction-driven formulations with explicit guarantees.