The Personal Software Process in the Generative AI Era

The integration of generative artificial intelligence and autonomous coding agents into software engineering has dramatically compressed the marginal cost of code generation while exposing deep systemic vulnerabilities in software lifecycle governance. While frontier foundation models and agentic workflows allow an individual engineer to achieve implementation velocities previously requiring multi-developer teams, empirical research reveals a concurrent collapse in software maintainability, characterized by surging code churn, refactoring declines, pervasive code duplication, and elevated security vulnerabilities. This divergence defines the Productivity-Reliability Paradox (PRP). This paper demonstrates that the structural resolution to this paradox lies in the formalization of disciplined one-person software engineering methodologies. By synthesizing Watts Humphrey’s Personal Software Process (PSP) with Kent Beck’s Extreme Programming (XP), Specification-Driven Development (SDD), and deterministic context engineering, a solo engineer can neutralize the coordination penalties of Brooks’s Law and exploit the architectural alignment of Conway’s Law. Because a solo engineer operates with zero interpersonal communication channels, unbroken architectural cohesion is inherently preserved. However, realizing this advantage requires replacing informal conversational development with rigorous specification governance, automated verification pipelines, and empirical defect-logging protocols. This paper presents an integrated theoretical framework, evaluates contemporary empirical benchmarks, and outlines an operational architecture demonstrating why disciplined one-person software processes form the indispensable foundation for dependable software development in the generative AI era.

Personal Software Process (PSP); Generative AI in Software Engineering; Specification-Driven Development (SDD)

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