"Don't Be Afraid, Just Learn": Insights from Industry Practitioners to Prepare Software Engineers in the Age of Generative AI

TL;DR

This study explores how generative AI impacts software engineering education and industry skills, providing empirical insights and recommendations for curriculum improvements.

Contribution

It offers empirical data from industry practitioners on skill shifts due to GenAI and proposes actionable educational strategies.

Findings

GenAI increases demand for prompting and output evaluation skills.

Soft skills like problem solving and critical thinking remain crucial.

Recommendations include integrating GenAI into curricula and redesigning assessments.

Abstract

Although tension between university curricula and industry expectations has existed in some form for decades, the rapid integration of generative AI (GenAI) tools into software development has recently widened the gap between the two domains. To better understand this disconnect, we surveyed 51 industry practitioners (software developers, technical leads, upper management, \etc) and conducted 11 follow-up interviews focused on hiring practices, required job skills, perceived shortcomings in university curricula, and views on how university learning outcomes can be improved. Our results suggest that GenAI creates demand for new skills (\eg prompting and output evaluation), while strengthening the importance of soft-skills (\eg problem solving and critical thinking) and traditional competencies (\eg architecture design and debugging). We synthesize these findings into actionable recommendations for academia (\eg how to incorporate GenAI into curricula and evaluation redesign). Our work offers empirical guidance to help educators prepare students for modern software engineering environments.