Virtual ecosystems, where natural selection is used to evolve complex agent behavior, are often preferred to traditional genetic algorithms because the absence of an explicitly de-fined fitness allows for a less constrained evolutionary pro-cess. However, these model ecosystems typically pre-specify a discrete set of possible action primitives the agents can per-form. We think that this also constrains the evolutionary pro-cess with the modellers preconceptions of what possible so-lutions could be. Therefore, we propose an ecosystem model to evolve complete agents where all higher-level behavior results strictly from the interplay between extremely simple components and where no ‘behavior primitives’ are defined. On the basis of four distinct survival strategies we show that such primitives are not necessary to evolve behavioral diver-sity even in a simple and homogeneous environment.