ArXiv TLDR

The AI-Native Large-Scale Agile Software Development Manifesto

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2605.07717

Ricardo Britto, Fredrik Palmgren, Nishrith Saini, Marcus Ohlin

cs.SEcs.AI

TLDR

This paper introduces an AI-Native Large-Scale Agile Software Development Manifesto to redefine large-scale agile using AI as a first-class participant.

Key contributions

  • Presents an AI-Native Large-Scale Agile Software Development Manifesto.
  • Outlines six core principles for AI as a first-class agile participant.
  • Transforms development from manual to intelligent, adaptive, and learning systems.
  • Introduces concepts like intent-driven teams and orchestrated AI agent workforces.

Why it matters

Current large-scale agile frameworks are human-centric and struggle with real-time adaptation. This manifesto leverages AI to redefine large-scale development, making it an intelligent, continuously learning system. It offers a path to true agility by integrating AI as a core participant.

Original 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.

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