Hybrid Human AI SDLC for Rapid SaaS Development: Evidence from a 60 Days Case Study

Muhammad Hilmy Haidar Fawwazie; Nathan Daud; Muhammad Iqbal Rabani; Budi Fajar Supriyanto

doi:10.29408/edumatic.v10i1.34361

Authors

Muhammad Hilmy Haidar Fawwazie Universitas Gajayana https://orcid.org/0009-0001-9559-7115
Nathan Daud Universitas Brawijaya https://orcid.org/0009-0004-2141-4138
Muhammad Iqbal Rabani Universitas Brawijaya https://orcid.org/0009-0008-4590-6021
Budi Fajar Supriyanto Politeknik Negeri Jember https://orcid.org/0000-0003-2224-6784

DOI:

https://doi.org/10.29408/edumatic.v10i1.34361

Keywords:

hybrid software development lifecycle, human AI collaboration, AI assisted development, electronic medical records

Abstract

There is a vacuum in the risk of architectural changes in critical systems because macro-architectural governance in AI-based software development is frequently ignored in current scholarly debate. The purpose of this study is to assess how well the Visualize, Integrate, Build, Execute (VIBE) architecture addresses the stability-speed contradiction in SaaS development. This study triangulated data from 465 automated CI/CD pipeline logs, 124 AI instruction tactic documentation records, and 42 test cases using comparative performance analysis and process tracking using an explanatory mixed-methods case study methodology on a stock market analytics platform. The study's key conclusions show a 50% boost in development efficiency, reducing a 60-day cycle to 30 days while preserving system reliability with an average latency of 1.2 seconds and a 99.9 percent availability rate. Specialist synergy was identified where humans became the primary cognitive players in architectural design at 90 percent, and AI as the executor of basic syntax at 85 percent. The research concludes that the architectural anchoring mechanism by humans is crucial for mitigating the risks of non-deterministic AI outputs. Theoretically, this study introduces the concept of human-AI cognitive alignment, while practically providing a validated roadmap for modernization of sensitive infrastructure such as Electronic Medical Records.

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