Measuring AI coding adoption: What I learned as a manager

📰 Dev.to · Andrew Shu

Learn to measure AI coding adoption effectively and avoid adoption theater as an engineering manager

intermediate Published 27 Apr 2026

Action Steps

Identify key performance indicators (KPIs) for AI coding adoption
Distinguish between actual adoption and adoption theater
Set up tracking for meaningful metrics such as code quality and developer productivity
Regularly review and adjust metrics to ensure accurate measurement
Implement changes to encourage genuine adoption of AI coding tools

Who Needs to Know This

Engineering managers and teams looking to implement AI coding tools can benefit from understanding what metrics to track and how to avoid superficial adoption

Key Insight

💡 Measuring AI coding adoption requires tracking meaningful metrics beyond superficial indicators