AI-Augmented Detection and Mitigation of Developer Burnout in Remote Software Teams
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AI-Augmented Detection and Mitigation of Developer Burnout in Remote Software Teams
Author: Aishwarya Babu
babu.aishwarya@gmail.com
Abstract
Remote software teams face heightened risks of developer burnout due to communication overload, meeting fatigue, and reduced interpersonal cues. Traditional burnout detection relies heavily on self-reports and post-hoc surveys, which often miss early warning signs. This paper proposes a lightweight, AI-driven framework to identify early burnout signals using natural language processing (NLP), sentiment analysis, and short-interval pulse checks. By integrating insights from Slack, Zoom, and GitHub activity with mood trend aggregation, our system aims to surface actionable team-level interventions before chronic fatigue sets in. We analyze existing literature, identify implementation challenges, and suggest design recommendations for responsible deployment in engineering organizations.
Keywords: Remote work, developer burnout, AI, sentiment analysis, pulse surveys, NLP, engineering management