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The changes in the security environment run parallel to changes in humans and artificial cognitive systems to meet these challenges. In this article, the purpose is to discuss some human-autonomy teaming (HAT) design approaches (mechanisms for coordination): levels of automation (LOA), mixed initiative (MI), and coactive design (COAD). Specifically, we discuss how humans and artificial cognitive systems, exemplified as loyal wingmen, can be orchestrated to enable the handling of complexity and dynamics of an environment, e.g., handling military threats, and how different design trade-offs are affecting mission solutions. We also discuss some consequences of various AI/ML modes used by LW, on the utility of the HAT design approaches. Ways of using these HAT designs in a complementary way are suggested to support coordination through both plan and feedback, such as by integrating external and internal feedback in prediction of future action. We illustrate our suggestions through a use case, which provide additional nuance to our theoretical discussion. Lastly, we provide directions for future research, in particular through experimental design and the use of simulation, and provide practical implications.