The AI-Native Large-Scale Agile Software Development Manifesto
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 0 of its 9 references that are in the map. First posted on arXiv 8 May 2026.
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Citing papers per year: 2026: 2.
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- 2026AI-Native Product Management: A Vision10 Oct 2026
- 2026Using Agentic AI for contextualized and multifaceted code review at Ericsson14 Sep 2026