How product orgs decide better, not just build faster, with AI

A Miro + Voltage Control session

AI made building cheap, and that is exactly the problem. Engineering, Product, and Design teams adopted AI to move faster, but speed did not remove the friction. It relocated it. The hard part is no longer producing the work. It is deciding the right things to build, aligning on a direction before you build them, and carrying enough shared context that people and AI agents move together instead of in different directions. Speed without alignment just means racing apart, faster.

In this session, Douglas Ferguson brings Voltage Control's "New Friction" thesis to the product development lifecycle. You will get a practical operating model for the three jobs that now decide whether AI makes your team faster or just busier: deciding what to build next, validating and aligning before you build, and building with the full context both teams and agents need. A worked case study of an AI-native operating model in a large product org grounds each job in what it looks like in practice. Come for the frameworks; leave with a way of working.

What you'll learn

• Why AI moved the product-development friction from building to aligning, and what that changes about how you plan.
• How a few "wizards" going 10x faster can actually slow the whole team down, and how to shift from solo speed to multiplayer impact.
• How to keep a team's vectors aligned at AI speed, before small misalignments compound into expensive rework.
• Why shared visual context, not better prompts, is what makes both people and AI agents perform.
• How to define "no-fly zones" that give teams the confidence to move fast everywhere else.
• A worked case study of an AI-native operating model across engineering, PM, and Design.