Presented on March 27th, 2019 at Stanford Medical School video version at https://vimeo.com/332532193 Distributed networks, populated by individual agents following set rules, can create highly organized, scalable systems. Patterns that mimic natural systems can be created using agent-based modeling (ABM) algorithms with scant rules. Humans, and in particular networks of humans, also exhibit patterns of behavior. A shift in human-based systems to distributed networks for decision-making (ie from top-down hierarchical systems to ‘flat’ organizations) is part of the current cultural zeitgeist. An extreme example of this is Morning Star, a tomato processing company, which began practicing organizational self-management in 1990. At Morning Star, everyone is equally empowered to communicate, initiate action, innovate, and execute. There are no bosses, only ‘colleagues.’ A common element between mathematical models for complex, self-organizing patterning and human organizational constructs in flat workplaces is the role of simple rule sets. These rules create dynamic flows that can be both patterned and purposeful. Academic science is by necessity a top-down organizational structure, investing time and attention from expert educators to educate and train the novice student-learner – or is it?