Large-scale service networks exhibit phase transitions in complexity that conventional software architecture does not account for. This paper describes three observed phase transitions (at approximately 15, 50, and 300 services) and a theoretical fourth at 800–1,200 services, based on a live experiment: 223 services built by a single human director in 9 months on one virtual machine. We propose a genome metaphor as a more precise framework than microservices architecture for understanding how such systems grow, express capability, and self-regulate. Central to this framework is the role of the human as catalyst — not user, not builder — whose CAPA configuration multiplies with AI Aptitude to produce directed emergence that neither can achieve alone. We describe the conditions under which a routing layer (the ribosome) self-elects from the network without being designed, and derive a testable prediction: chaos_risk = f(connection_density / description_coverage), with chaos bounded when description_coverage approaches 1.0.