From Dabbling to Deploying: What It Takes to Lead AI-Ready Teams
Details
Most product teams assume AI readiness is a tooling problem. In practice, the hardest failures happen earlier, when teams try to move from experimenting with AI to building and shipping non-deterministic systems at scale. This session draws on original survey data and Elena Luneva's work co-teaching the Lead AI-First Teams Workshop (Maven) to show what actually separates teams that ship from teams that stall. Learn how to spot where teams break down when moving past
the dabbling phase, what non-deterministic systems demand that traditional MVP thinking doesn't prepare you for, and how to build repeatable patterns for AI readiness across resourcing, governance, and change management. You'll walk away with a practical operating system for leading AI-native work without sacrificing speed.
Key Takeaways
- How to identify where teams break down when moving from AI dabbling to real deployment
- What non-deterministic systems demand that traditional MVP thinking doesn't prepare you for
- Repeatable patterns for building AI readiness across resourcing, governance, and change managemen
- How to reclaim team efficiency through AI-first playbooks and guardrails
Special Thanks to our generous Sponsor:
- Productboard: Turn customer insights into strategic clarity and ship what matters most with Spark, Productboard's new agentic platform.
Attendance will be first-come, first-served. We will close doors once we reach capacity; arrive early to secure a spot.
