Pervasive service ecosystems are emerging as a new paradigm for understanding and designing future pervasive computing systems featuring high degrees of scale, openness, adaptivity and toleration of long-term evolution. A key issue in this context is making certain patterns of behaviour emerge without any supervision or design-time intention, and a primary example is the fully-spontaneous composition of services, possibly at multiple levels. We argue that this can be successfully achieved only by a comprehensive approach exploiting together the main ingredients proposed so far in literature:  existence of intel- ligent components finding proper (semantic) matches of service descriptions, (ii) use of distributed evolutionary techniques to dynamically select appropriate ways of composing services, and (iii) approaches in which rating quality of composition is solely based on their successful exploitation. This proposal is presented through an example of spontaneous composition in crowd steering services.