The overall behavior and nature of complex natural systems is in large part determined by the number and variety of the mechanisms involved – and the complexity of their interactions. Embodied natural communication belongs to this class of systems, encompassing many cognitive mechanisms that interact in highly complex ways, both within and between communicating individuals, constituting a heterogeneous, large, densely-coupled system (HeLD). HeLDs call for finer model granularity than other types of systems, lest we risk them to be not only incomplete but likelyincorrect. Consequently, models of communication must encompass a large subset of the functions and couplings that make up the real system, calling for a powerful methodology for integrating information from multiple fields and for producing runnable models. In this paper I propose such an approach, abstract module hierarchies, that leverages the benefits of modular construction without forcing modularity on the phenomena being modeled.