What do professional software developers need to know to succeed in an age of Artificial Intelligence?

TL;DR

This paper explores the skills and knowledge software developers need to effectively work with Generative AI, highlighting four key domains and proposing educational strategies to future-proof the workforce amidst AI-driven productivity changes.

Contribution

It identifies the essential skills across four domains for AI-enhanced software development and offers insights into training approaches to mitigate deskilling risks.

Findings

Skills are organized into four domains for AI success

Developers use AI at critical points in a six-step workflow

Educational initiatives should target both soft and technical skills

Abstract

Generative AI is showing early evidence of productivity gains for software developers, but concerns persist regarding workforce disruption and deskilling. We describe our research with 21 developers at the cutting edge of using AI, summarizing 12 of their work goals we uncovered, together with 75 associated tasks and the skills & knowledge for each, illustrating how developers use AI at work. From all of these, we distilled our findings in the form of 5 insights. We found that the skills & knowledge to be a successful AI-enhanced developer are organized into four domains (using Generative AI effectively, core software engineering, adjacent engineering, and adjacent non-engineering) deployed at critical junctures throughout a 6-step task workflow. In order to "future proof" developers for this age of AI, on-the-job learning initiatives and computer science degree programs will need to target both "soft" skills and the technical skills & knowledge in all four domains to reskill, upskill and safeguard against deskilling.