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dc.contributor.authorGarcia, Fabio
dc.contributor.authorSteilberg, Jackson
dc.date.accessioned2026-02-17T20:00:34Z
dc.date.available2026-02-17T20:00:34Z
dc.date.issued2026-02-17
dc.identifier.urihttps://hdl.handle.net/1721.1/164900
dc.description.abstractThe Joint Capabilities Integration and Development System (JCIDS) was created as a means to overhaul military procurement processes. Ideally, the requirements development process is meant to take a total of 2-4 years from concept to manufacturing. However the actual length of concept development is much longer. As a result, technologies that are conceptualized through the analytical process often enter the acquisition too late to need for the warrior. To reduce the lengthy timeline in requirements development, we used Large Language Models (LLMs) to conduct the necessary research and synthesize documents that abide by strict JCIDS guidelines. Prompt engineering can achieve these results as a proof of concept. However, the output responses lack the content length and depth necessary to pass through the requirements validation process. Therefore, a combination of agentic workflows, prompt engineering, and sufficient context is needed to achieve the desired outcomes. This project utilizes a novel framework to derive Capabilities Based Assessments (CBAs) at an approximate 80 percent readiness level requiring the final steps of validation and verification by subject matter experts.en_US
dc.description.sponsorshipThe Department of the Air Force Artificial Intelligence Acceleratoren_US
dc.language.isoen_USen_US
dc.subjectCapability, JCIDS, Capabilities Development Directorate, CD&I, MCCDC, Requirements, Acquisition.en_US
dc.titleRAIMOND Requirements AI for Military Operational Needs Developmenten_US
dc.typeTechnical Reporten_US
dc.contributor.departmentLincoln Laboratoryen_US


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