GenAI is fundamentally transforming software development, but the narrative that it will replace engineers or solve all our problems is misleading. In this talk, we’ll explore how leaders should approach the “70% Problem” – how AI excels at routine coding tasks but still requires significant human expertise for the critical remaining 30% that makes the difference between functional code and excellent software. How teams approach the “30% that matters” will be vital moving forward.
Drawing from real-world case studies at companies like Google, GitHub, and Microsoft, I’ll share practical strategies for engineering leaders navigating this new landscape. We’ll examine how the role of technical leadership is evolving from hands-on problem-solving to strategic guidance and ethical oversight.
You’ll learn:
- How to establish effective “trust but verify” processes for AI-generated code
- Strategies to prevent skill erosion and maintain code quality
- Approaches for upskilling both junior and senior developers to thrive alongside AI
- Techniques for measuring impact beyond speed to ensure long-term code quality
- Frameworks for responsible AI governance and usage in your organization
Whether you’re skeptical or enthusiastic about AI coding tools, this talk will provide a balanced, pragmatic guide to leading effective engineering teams in an era where the question isn’t whether to use AI, but how to use it to build better software while keeping humans at the center of the creative process.
