About this Session
Modern product teams are highly cross-functional, yet engineers, product managers, and designers often operate with different mental models of the same product. In AI-driven products, these gaps are amplified in assumptions about data, model behavior, and tradeoffs that can directly impact user experience and business outcomes.
This talk explores how engineers can go beyond code to create shared product understanding across teams. Drawing from real-world AI product environments, it introduces practical techniques for making technical thinking visible, bridging language gaps, and aligning priorities across engineering, product, and design.
In this session, you will learn how to:
- Align early and continuously with product and design teams, even in the presence of AI complexity
- Translate complex AI decisions, such as model tradeoffs, data limitations, and ethical considerations into product-level conversations for non-engineering stakeholders
- Leverage strong cross-functional understanding to drive better product decisions and more impactful AI outcomes.
