A Lean and Spec-Driven AI-Assisted Software Development Lifecycle for Applied AI Education: The AI-SDLC Approach
Organizations: FHNW University of Applied Sciences and Arts Northwestern Switzerland, School of Business, Riggenbachstrasse 16, 4600 Olten, Switzerland
Abstract
AI coding agents increasingly support software development beyond code completion, including planning, implementation, testing, and repository-level task execution. Their practical use, however, often remains only weakly connected to established software engineering practices. The aim of this work is to develop and evaluate a lightweight, spec-driven lifecycle for governed agentic software engineering. The lifecycle combines established software engineering practices with repository-local guidance through specifications, AGENTS.md, and phase-specific agent skill files. The approach was developed in the context of the FHNW course AI-assisted Software Development and applied by students to business-oriented software use cases. Its educational and practical applicability is explored through a student survey combining closed rating items with open-ended questions. The contribution of this work is a process-oriented framework that enables AI coding agents to operate with bounded autonomy within an explicit, reviewable, and test-oriented software development lifecycle.
Figures & tables
| Part | Content |
|---|---|
| A) General questions | Age, degree program, current semester, experience |
| B) Previous experience | Contexts, process models, AI tools, familiarity with terms |
| C-I) Process support | Statements on the AI-SDLC as a whole |
| C-II) Lifecycle artifacts | Statements on user stories, architecture, specifications |
| C-III) Self-instruction files | Statements on AGENTS.md, skills, project-local rules |
| C-IV) Human verification | Statements on review, TDD and traceability |