Agile Project Management Using Large Language Models
G Dhruva, Ishaan Shettigar, Srikrshna Parthasarthy, V M Sapna · 2024
Agile data-driven methodology encourages engineering leaders to measure their teams’ performance by leveraging metrics for improving visibility, identifying potential roadblocks, and increasing delivery velocity. The work presented here introduces a cutting-edge paradigm of a data-driven approach to Agile project management, contributing to the evolving research in project management methodologies. As organizations strive to consolidate the competitive market, their success is often measured by their agility and resilience. Such agility stems from the underlying management practices that an organization embraces and is crucial for the effective planning and delivery of large-scale projects. While management philosophies have continued to evolve, organizations specializing in software development have increasingly adopted Agile project management practices to keep up with a disruptive landscape inundated with rapidly emerging technological advancements. As organizations have continued to expand globally, the existing Agile practices have been laggard and sluggish, unable to keep up with the demands of a modern market. In this context, the authors introduce an Agile project management framework driven by Large Language Models (LLMs) to facilitate efficient management of large projects.