| dc.contributor.author | Garcia, Fabio | |
| dc.contributor.author | Steilberg, Jackson | |
| dc.date.accessioned | 2026-02-17T20:00:34Z | |
| dc.date.available | 2026-02-17T20:00:34Z | |
| dc.date.issued | 2026-02-17 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/164900 | |
| dc.description.abstract | The 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.sponsorship | The Department of the Air Force Artificial Intelligence Accelerator | en_US |
| dc.language.iso | en_US | en_US |
| dc.subject | Capability, JCIDS, Capabilities Development Directorate, CD&I, MCCDC, Requirements, Acquisition. | en_US |
| dc.title | RAIMOND Requirements AI for Military Operational Needs Development | en_US |
| dc.type | Technical Report | en_US |
| dc.contributor.department | Lincoln Laboratory | en_US |