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@article{208091,
        author = {Abhinav Tripathi},
        title = {Hage- AI governed Engineering},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {4},
        pages = {264-273},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=208091},
        abstract = {Software engineering methods such as Agile, DevOps, DevSecOps, and capability-maturity models were established in environments where accountable humans performed most engineering reasoning and deterministic automation executed predefined tasks. Generative AI and agentic AI change this operating assumption. They can interpret intent, create architecture and code, invoke tools, test systems, modify repositories, prepare deployments, and participate in operations. Yet many enterprises continue to insert these capabilities into the same human-centric lifecycle, preserving old queues, ceremonies, responsibility models, and delivery timelines. This paper proposes Human–AI Governed Engineering (HAGE), a governance-centric methodology for allocating work, authority, evidence, and accountability across human participants, generative models, autonomous agents, deterministic automation, and assurance mechanisms. HAGE introduces intent contracts, qualified context, risk-based autonomy, evidence packages, trust gates, continuous operational learning, and a five-level enterprise maturity model. It does not replace Agile or DevOps; it provides an execution and governance layer that allows those approaches to operate safely and efficiently when non-human participants perform material lifecycle responsibilities. HAGE is presented as a research framework requiring empirical validation. Its claimed contribution is not the first use of AI agents in software development, but an integrated enterprise methodology that connects end-to-end responsibility allocation, bounded autonomy, verification, accountable approval, operational learning, and measurable adoption.},
        keywords = {Agentic AI, AI governance, evidence-based engineering, Generative AI, human–AI collaboration, software engineering methodology.},
        month = {September},
        }