Evolutionary quantitative genetics has blossomed over the last 30 years, but it’s relevance to many problems is still unappreciated by most evolutionary biologists. For example, despite astounding discoveries in the evolution of development (evodevo), that field remains a conceptual orphan. Likewise, progress in paleontology has been largely independent of the rest of evolutionary biology. On the flip side, recent advances in quantitative genetic theory for the coevolution of species with trait-mediated interaction are probably not apparent to many ecologists. Part of the reason for these and other disconnects is that conceptual advances in evolutionary quantitative genetics have not been synthesized and made accessible. Students and researchers seeking an introduction are forced into the primary literature where they confront formidable technical hurdles (matrix algebra, advanced multivariate statistics, stochastic processes). In the absence of a comprehensive, accessible overview, investigators may not have a vision of the forest even though they are familiar with particular trees. For all these reasons, phenotypic evolution urgently needs a synthesis. Evolutionary Quantitative Genetics aims to provide that synthesis by using moving optimum models as an organizing principle.