Everyone is looking for AI metrics. Organizations are tracking token consumption, AI adoption rates, generated code volume, and agent activity in an attempt to measure engineering performance. Yet, many teams still struggle to answer a simple question: what does quality look like with AI?
This talk argues that AI changed how software is produced, not what good software looks like. We'll explore why many AI KPIs miss the point and how to distinguish productivity, quality, and business outcomes when measuring engineering success.
This talk has been presented at AI Coding Summit NYC, check out the latest edition of this Tech Conference.






















