AI Summary
→ WHAT IT COVERS Twilio CPO Inbal Shani explains why AI adoption alone fails as strategy, how product managers must shift from deterministic flows to behavioral guardrails, and practical frameworks for measuring AI impact on customer engagement outcomes. → KEY INSIGHTS - **AI as Tool Not Strategy:** Start with customer problems first, then apply AI tools second. Define success metrics like customer satisfaction, time to resolution, or ticket reduction before implementing AI solutions, not AI adoption metrics themselves. - **Behavioral vs Deterministic Product Design:** Product managers now define behavioral guardrails instead of exact flows because AI systems are stochastic. Specify what AI agents should and shouldn't do, acceptable behavior ranges, and corpus boundaries rather than step-by-step outcomes. - **Essential Technical Skills for PMs:** Master system design to understand component interactions, learn different AI types from machine learning to agentic AI with their cost tradeoffs, and develop analytical measurement frameworks to track outcomes beyond productivity claims. - **Three-Tier Work Stream Allocation:** Structure product teams across three speeds: maintaining existing customer workloads without breaking services, growing shipped features through enhancements, and fast-moving innovation for new products, each requiring different planning agility levels. → NOTABLE MOMENT Shani reveals that deploying AI agents to handle appointment reminders through the right channel increases patient show-up rates significantly, demonstrating how channel intelligence matters more than message content for driving behavioral outcomes in customer engagement. 💼 SPONSORS [{"name": "Persona", "url": "https://withpersona.com/productschool"}] 🏷️ AI Product Strategy, Customer Engagement Platforms, Product Management Skills, Agentic AI