Multispecies bacterial communities often perform functions arising from the interactions among their members. These community functions can, in principle, be improved via directed evolution. Yet, current selection methods for improved community function have shown limited success. One reason for this limited success might be that methods of community selection rely on the assumption that bacterial communities are individuals in selection. However, competition among species members within these communities is pervasive and, as a consequence, selection at the level of member species can override selection at the community level. Here, we have begun designing an artificial selection strategy based on evolutionary individuality first, improved function second. Specifically, our aim is to simulate a community selection method driving the transition in individuality by decreasing competition within communities and increasing competition between them. Once within-community competition is diminished, we will select the transitioned communities for improved community function using classic breeding methods. Even though selection for improved function might reverse the transition in individuality, we hypothesise that communities whose transition is irreversible will outcompete those in which within-community competition reemerges. It remains to be seen whether our hypothesis holds. We hope to have enough data for its verdict on time for the workshop.