The Department of Defense faces increasingly complex mission sets, demanding unprecedented warfighter performance and flexibility in unpredictable situations. Autonomous intelligent agent (AIA) technology promises to significantly relieve these demands, in both training and operational settings. In the future, warfighters and AIAs will work jointly as part of mixed human-machine teaming (HMT) environments, wherein AIAs will routinely assess warfighter cognitive states to optimize learning, task management, feedback delivery, and performance. To meet the desired future state, training must equip humans with HMT skills necessary to optimize this collaboration. Learning environments must allow humans to experience authentic scenarios with HMT interactions that can be measured and assessed to provide real-time and after-action feedback. To ensure HMT skill acquisition and retention, the AIA should meet the following system requirements. It needs to operate autonomously in complex environments, be adaptable, and be able to enhance learning by delivering strategic workload-based personalized feedback. One way of achieving the aforementioned goals is by engineering a testbed that would meet the said system requirements and would train operators to interact with AIA and human teammates. The envisioned testbed would represent a fully deployable live, virtual, and constructive training system featuring integrated inner-loop (during the training scenario) and outer-loop feedback (after the scenario) capabilities along with a multi-modal measurement suite. The testbed would serve dual purpose – one for realizing operational training needs and the other for conducting within-subject multi-trial scenario-based studies to examine whether or not the presence of AIA impacts warfighter performance. Consistent with a growing body of literature which suggests that human performance tends to improve with an addition of an AIA (e.g., Mercado et al., 2016; McKendrick et al., 2014), we predict that warfighter performance will improve when AIA is present. While the research potential of the testbed is limitless, we offer several future research directions in this paper.