Generative AI agile assistant

Darrell L. Young; Perry Boyette; James Moreland Jr.; Jason Teske

doi:10.1117/12.3011173

6 June 2024 Generative AI agile assistant

Darrell L. Young, Perry Boyette, James Moreland Jr., Jason Teske

Proceedings Volume 13058, Disruptive Technologies in Information Sciences VIII; 1305809 (2024) https://doi.org/10.1117/12.3011173
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Large Language Models (LLMs) provide new capabilities to rapidly reform, regroup; and reskill for new missions, opportunities, and respond to an ever-changing operational landscape. Agile contracts can enable larger flow of value in new development contexts. These methods of engagement and partnership enable the establishment of high performing teams through the forming, storming, norming, and performing stages that then inform the best liberating structures that exceed traditional rigid hierarchical models or even established mission engineering methods. Use of Generative AI based on LLMs coupled with modern agile model-based engineering in design allows for automated requirements decomposition trained in the lingua franca of the development team and translation to the dialects of other domain disciplines with the business acumen afforded by proven approaches in industry. Cutting-edge AI automations to track and adapt knowledge, skills, and abilities across ever changing jobs and roles will be illustrated using prevailing architecture frameworks, model-based system engineering, simulation, and decision-making assisted approaches to emergent objectives.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Darrell L. Young, Perry Boyette, James Moreland Jr., and Jason Teske "Generative AI agile assistant", Proc. SPIE 13058, Disruptive Technologies in Information Sciences VIII, 1305809 (6 June 2024); https://doi.org/10.1117/12.3011173

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