The Department of Defense faces a growing challenge to meet the breadth, depth, and tempo of its expanding education and training needs. While budgets are shrinking, the complexity of missions is increasing and demands on personnel are growing. Learning technologies can help address this, but the research and acquisition communities must make informed decisions about which technologies to pursue. Various military offices publish guidance on this question. For instance, some Defense agencies publish “Science and Technology Objectives,â€� including direction on next-generation learning requirements and associated technologies. However, these publications generally lack linkages to one another—particularly those authored by different Services—which leads to duplications of effort and missed opportunities for coordination. Further, because these publications typically derive from high-level strategy guidance (i.e., “top-downâ€� direction), they may inadvertently omit some lower-echelon needs (i.e., “bottom-upâ€� inputs). To address these gaps, the Advanced Distributed Learning (ADL) Initiative executed an interagency requirements campaign to collate existing publications, crosswalk Defense agency needs, and search for yet-undiscovered requirements associated with training, education, and related performance support. As part of this effort, we also conducted interviews with widespread stakeholders across the Department. The results are being assembled into a data visualization, which viewers will be able to access via a government website. Although our Requirements Campaign is still underway, this paper describes our requirements engineering process as well as initial results from it. In particular, we highlight the “top tenâ€� requirements in terms of frequency and apparent priority (for the stakeholders), and we discuss opportunities for developing or acquiring new learning technologies to address the priority objectives.