AI-Friendly Code: The Missing Link for Speed with Quality

Find out what AI-friendly code really means and why code health plays a critical role in making AI-assisted development work in practice.

Key Takeaways

• Why code health directly affects the effectiveness of AI coding tools
• What characteristics make a codebase AI-friendly
• Practical patterns for structuring systems that work well with AI-assisted development

Who It’s For

Developers, architects, and technical leaders working in codebases where AI coding tools are becoming part of the development workflow.

Level

Practitioner to Advanced
Best suited for people actively building and maintaining production systems.

What This Session Covers

• The relationship between code health and AI performance
• Insights from empirical studies of real-world production systems
• Architectural and development patterns that enable effective AI-assisted coding
• How technical debt impacts both human and machine productivity

What It’s Not

• Not a tutorial on prompting AI tools
• Not a product demo
• Not a discussion of AI model internals

Format

• Slides
• Code examples
• Real-world research findings and engineering insights

Full Description

Have you seen early productivity gains from AI, only to watch them disappear under growing complexity and production incidents? You're not alone. There's a common reason: many production systems already struggle with technical debt. When AI agents enter the development loop, that debt becomes a multiplier. Poor-quality code not only increases defects and costs. It dramatically raises AI risk by driving high breakage rates, turning promising AI agents into legacy code generators rather than genuine help.

Fortunately, there's hope on the horizon. In this talk, Adam Tornhill shows how organizations can achieve both speed and quality with AI. Backed by large-scale empirical studies on AI coding and developer productivity, we separate what works from what doesn't in real-world systems. Building on these findings, we then look at a practical framework for driving and sustaining AI-friendly code at scale. The AI revolution is here. Is your code ready?