Evaluating Vibe Coding as an AI-Orchestrated Development Methodology: A Case Study on Accelerating Complex Web-Based Educational Management Systems

Abstract

The emergence of generative AI has disrupted conventional software development practices, prompting considerable skepticism among IT professionals about whether such tools displace rather than augment human expertise. This study introduces "Vibe Coding" as a collaborative methodology — one in which AI operates as a capable partner, not a substitute — requiring human guidance for review, analysis, and iterative refinement of generated outputs; the primary objective is to assess whether Vibe Coding, when structured through Model Context Protocol (MCP) and schema engineering, can materially reduce development time for complex web systems — including CRUD operations, API integration, and custom business logic — relative to conventional approaches such as Waterfall. Two research questions drive the inquiry: (1) Can Vibe Coding compress development timelines for complex systems from months to days? and (2) How effective is AI as a collaborative partner in sustaining output quality through human-in-the-loop validation? A single case study approach was employed, applying the methodology to develop an ISO 9001:2015-compliant Management Information System (MIS) for Pondok Pesantren Abu Hurairah Mataram as a solo developer project, with metrics tracked across seven days including total development time, time per phase (planning, development, debugging, and deployment), proportion of AI-generated code (70–85%), prompt and iteration counts, bug frequency, debugging duration, total lines of code (LOC), and feature implementation success rate. Results show a completed system in seven days, with 70–85% of the codebase AI-generated and 15–30% manually refined for business logic, debugging, and performance tuning; human intervention effectively countered AI hallucinations throughout, repositioning the developer's role from syntax-level coding toward architectural orchestration and quality control. These findings suggest Vibe Coding raises productivity for solo developers in AI-saturated environments, though rigorous human oversight remains non-negotiable for production-grade systems.

Keywords

Vibe Coding; AI-Assisted Development; Model Context Protocol; Human-in-the-Loop; Software Productivity; Case Study