A published academic decision theorist proposes a pragmatic version of Functional Decision Theory to resolve existing definitional gaps. The author challenges the skepticism of academic theorists who largely reject FDT. This refined framework aims to stabilize how AI agents predict outcomes in game-theoretic scenarios. It offers a more rigorous foundation for alignment research.