The exponential growth of processing power and memory capacity has fundamentally reshaped modern software systems, particularly those driven by artificial intelligence (AI). While these advances have enabled unprecedented scale and functionality, they have also introduced a subtle but systemic degradation of software quality. This paper critically examines how hardware abundance encourages inefficient design practices, masks architectural deficiencies, and shifts the definition of software quality away from efficiency, robustness, and maintainability. Focusing on AI systems and large-scale modern applications, the study argues that reliance on computational surplus has fostered complacency rather than engineering rigor. Through analysis of real-world software and AI deployments, this paper contends that sustainable software quality requires a deliberate reintroduction of constraint-driven design principles, even in resource-rich environments.
Sabarieswar V (2026) studied this question.