In this talk, we survey the active area of copositive optimization, focusing on two key features: (i) its ability to model difficult problems as equivalent convex problems, for example, broad classes of quadratic programs and also integer programs with uncertain data; (ii) its approximability by linear and semidefinite optimization. We discuss specific applications, recent generalizations, and important obstacles. If time permits, we will also vote on standardizing notation in the area. Come let your voice be heard!