The AI-Native Large-Scale Agile Software Development Manifesto

TL;DR

This paper introduces the AI-Native Large-Scale Agile Software Development Manifesto, redefining organizational agility by integrating AI as a core participant to enable adaptive, continuous learning systems.

Contribution

It proposes a new set of values and principles for large-scale agile development that incorporate AI to enhance real-time adaptation and organizational agility.

Findings

Defines six core principles for AI-native agile development.

Proposes a shift from manual, meeting-driven processes to intelligent, adaptive systems.

Introduces concepts like intent-driven teams and living knowledge for continuous learning.

Abstract

Despite the widespread adoption of agile methods, achieving true agility at scale remains elusive. Large-scale agile frameworks remain largely human-centric and manual, relying on coordination meetings, artifact synchronization, and role-based handoffs that inhibit real-time adaptation. Meanwhile, rapid advances in AI, particularly large language models, have begun transforming software engineering, yet their potential for organizational-level agility remains underexplored. We present the AI-Native Large-Scale Agile Software Development Manifesto: a set of values and principles that redefine how large-scale software development is organized when AI becomes a first-class participant rather than a peripheral tool. The manifesto is grounded in six principles, parallel processes, intent-driven teams, living knowledge, verification-first assurance, orchestrated agent workforces, and reusable blueprints, that together shift development from a meeting-driven, document-heavy, sequential process to an intelligent, adaptive, continuously learning system.