In this session, you’ll learn to:

Abstract

In this webinar, we’ll explore the findings and what it takes to make AI-assisted development safe, predictable, and scalable. We’ll show how CodeHealth™ has emerged as the missing foundation for AI performance, and introduce an AI framework that helps organizations understand when and where AI coding is safe to use, how to enforce quality safeguards inside the agent loop, and how to uplift unhealthy code so AI can accelerate delivery rather than amplify risk.

You’ll also hear directly from loveholidays, who put these ideas into practice. They’ll share how early agentic coding without guardrails led to declining code health, and how they reversed the trend, scaling AI adoption while maintaining (and improving) code quality in production.

This webinar combines peer-reviewed research, practical engineering workflows and tools, and real-world lessons from a high-performing engineering organization.