Prompt Engineering Patents in Software Development: Trends, Themes, and Future Directions

This paper presents the first comprehensive patent landscape of prompt engineering in generative AI–driven software development, analyzing 2,511 patent families filed up until April-2025 from Lens.org. Combining reflexive thematic coding and LDA-based topic modeling, we develop a taxonomy of innovation themes—from AI-assisted code generation and automated debugging to test-case synthesis and prompt optimization frameworks. Our analysis reveals exponential growth in filings, led by industry giants, and uncovers gaps in areas such as legacy code modernization and developer trust. We highlight open challenges in verification, safety, and human–AI collaboration that must be addressed to realize robust AI-augmented development tools. The study provides insights and establishes a reproducible foundation for empirical validation and design of next-generation AI-assisted development environments.