Your AI Writes Code Faster – But Can Your Team Maintain It?

How much of your codebase do your developers actually understand? AI coding assistants generate solutions in seconds, but every accepted suggestion adds code that nobody reviewed deeply. What happens six months later when that code breaks at 2 AM?

This session exposes the three invisible debts AI tools create: comprehension gaps where teams cannot explain their own systems, false confidence from tests that pass but verify nothing meaningful, and architectural drift that no linter catches.

You will learn a practical framework to measure your AI-generated code risk, spot warning signs before they become production incidents, and build review practices that preserve both speed and quality. Walk away with a checklist you can use on Monday morning.