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[2602.20684] Agile V: A Compliance-Ready Framework for AI-Augmented Engineering -- From Concept to Audit-Ready Delivery
Summary
The paper presents Agile V, a framework integrating AI in engineering workflows to ensure compliance and verification at machine-speed delivery, enhancing efficiency and reducing costs.
Why It Matters
As AI technologies increasingly integrate into engineering processes, maintaining compliance and verification becomes critical. Agile V addresses these challenges by embedding verification mechanisms directly into development cycles, potentially transforming how engineering teams operate and ensuring regulatory adherence.
Key Takeaways
- Agile V merges Agile methodologies with V-Model verification for continuous compliance.
- The framework automates the generation of audit-ready documentation, enhancing efficiency.
- Independent verification can achieve a 100% requirement-level pass rate with minimal human interaction.
Computer Science > Software Engineering arXiv:2602.20684 (cs) [Submitted on 24 Feb 2026] Title:Agile V: A Compliance-Ready Framework for AI-Augmented Engineering -- From Concept to Audit-Ready Delivery Authors:Christopher Koch, Joshua Andreas Wellbrock View a PDF of the paper titled Agile V: A Compliance-Ready Framework for AI-Augmented Engineering -- From Concept to Audit-Ready Delivery, by Christopher Koch and Joshua Andreas Wellbrock View PDF HTML (experimental) Abstract:Current AI-assisted engineering workflows lack a built-in mechanism to maintain task-level verification and regulatory traceability at machine-speed delivery. Agile V addresses this gap by embedding independent verification and audit artifact generation into each task cycle. The framework merges Agile iteration with V-Model verification into a continuous Infinity Loop, deploying specialized AI agents for requirements, design, build, test, and compliance, governed by mandatory human approval gates. We evaluate three hypotheses: (H1) audit-ready artifacts emerge as a by-product of development, (H2) 100% requirement-level verification is achievable with independent test generation, and (H3) verified increments can be delivered with single-digit human interactions per cycle. A feasibility case study on a Hardware-in-the-Loop system (about 500 LOC, 8 requirements, 54 tests) supports all three hypotheses: audit-ready documentation was generated automatically (H1), 100% requirement-level pass rate was achieved...