Generative Intelligence in Software Design: Navigating the Promise and Pitfalls of LLM-Driven Architectures

Abstract

The rise of generative intelligence, driven by Large Language Models (LLMs), is revolutionizing software design. No longer limited to traditional logic and data structures, software systems can now incorporate dynamic reasoning, contextual awareness, and content generation at scale. From automating code generation and enhancing UX to powering conversational interfaces and adaptive APIs, LLMs are becoming integral to how modern software is conceived and constructed. However, this promise is accompanied by significant pitfalls—ranging from model unpredictability and latency to data security, ethical risks, and architectural complexity. This paper explores the intersection of generative AI and software design, outlining the opportunities it presents, the challenges it creates, and the best practices for integrating LLMs responsibly and effectively into evolving system architectures.