Cancer therapy outcomes are increasingly limited by the evolution of resistance rather than lack of effective drugs. Integrating principles from evolutionary biology and game theory, adaptive treatment strategies aim to delay or prevent resistance by maintaining populations of drug-sensitive cells to suppress resistant clones. Conventional maximum tolerated dose approaches often accelerate competitive release of resistant populations, whereas evolution-informed dosing can prolong control, reduce toxicity, and lower costs. Resistance arises through genetic, epigenetic, and ecological mechanisms, including transient survival states and microenvironmental protection. Quantitative modeling and longitudinal data enable “after-action” optimization of therapy. Emerging approaches, such as androgen cycling and testosterone-driven re-sensitization, suggest new pathways toward durable control and potentially curative strategies.