The AI-Native Software Development Lifecycle: A Theoretical and Practical New Methodology
Cory Hymel

TL;DR
This paper introduces the V-Bounce model, a new AI-native software development lifecycle that integrates AI throughout all phases, aiming to enhance efficiency and redefine human roles in development.
Contribution
It proposes the V-Bounce model, adapting the traditional V-model to fully incorporate AI, transforming SDLC processes and human roles.
Findings
AI integration reduces implementation time
Emphasizes requirements and validation phases
Redefines human roles in development
Abstract
As AI continues to advance and impact every phase of the software development lifecycle (SDLC), a need for a new way of building software will emerge. By analyzing the factors that influence the current state of the SDLC and how those will change with AI we propose a new model of development. This white paper proposes the emergence of a fully AI-native SDLC, where AI is integrated seamlessly into every phase of development, from planning to deployment. We introduce the V-Bounce model, an adaptation of the traditional V-model that incorporates AI from end to end. The V-Bounce model leverages AI to dramatically reduce time spent in implementation phases, shifting emphasis towards requirements gathering, architecture design, and continuous validation. This model redefines the role of humans from primary implementers to primarily validators and verifiers with AI acting as an implementation…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsScientific Computing and Data Management · Digital Transformation in Industry · Engineering Education and Technology
