AI made you ship faster. But did it make you a better engineer?

In this session, we’ll challenge the way teams measure developer productivity in the age of AI. More commits, faster pull requests, and shorter implementation time may look impressive on a dashboard. But they can also hide new costs in the areas that matter most to modern software engineering: maintainability, security, team collaboration, and developer well-being. We’ll explore a practical framework for measuring AI era engineering effectiveness, by combining quantitative and qualitative signals and separating them from vanity metrics. The methodology is based on practical experiences running and measuring AI development tools within our organization.

This talk is rated at level 300. It is designed for engineers, engineering managers, and technology leaders who want to move beyond AI productivity hype and make better decisions using meaningful engineering signals. No specific AI knowledge is required, only a solid understanding of modern software delivery challenges.