Hidden Costs of Vibe Coding: Code Quality, Technical Debt, and Security

This presentation examines the hidden costs and long-term implications of vibe coding, an emerging approach to software development in which artificial intelligence generates software implementations from natural-language instructions with limited human review of the resulting source code. While AI-assisted coding can significantly accelerate initial software development and reduce short-term implementation costs, it may introduce substantial challenges related to code quality, technical debt, cybersecurity, software maintainability, and developer competence. The presentation explores the productivity paradox of AI-generated software, highlighting how immediate efficiency gains may be offset by increased maintenance requirements, architectural complexity, code duplication, and difficulties in understanding and modifying generated solutions. Particular attention is devoted to the accumulation of technical debt and its potential to undermine long-term software engineering productivity. Drawing on recent empirical studies and industry reports, the presentation discusses security vulnerabilities in AI-generated code, including inadequate access controls, exposure of sensitive information, and the gap between functional correctness and security compliance. It also examines the effects of AI-assisted programming on developers' learning outcomes, the unpredictability of AI service costs, and the risks of vendor lock-in. The presentation concludes by emphasizing the importance of responsible AI-assisted software development, including clear specifications, architectural guidelines, human oversight, systematic code review, rigorous testing, security verification, organizational governance, and continuous professional training.