Learning the reaction coordinate: collective variables from physical intuition to generative models

for mechanistic interpretation. In this Perspective, we trace the arc of CV discovery from intuition-driven heuristics to modern data-driven and generative frameworks, critically assess the strengths and limitations of each class of methods, and outline how the convergence of machine-learned potentials, automated CV learning, generative sampling, and causal interpretability is giving rise to integrated workflows that will reshape predictive molecular simulation across biomolecular, catalytic, and materials systems.