
Lessons In Product Management
When AI Becomes the User: Building Products for an Agentic Future with Kimberly Logan
AI isn’t just changing how we use software, it's changing who software is built for. In this episode of Lessons in Product Management , John Fontenot sits down with Kimberly Logan, Head of Product at the Walrus Foundation and former Google leader, to explore the evolution of product leadership and what happens as AI agents increasingly become users of software themselves. Kim shares lessons from her transition from technical program management into product leadership, including the shift from focusing on execution and the “how” to owning the “what” and “why.” They also discuss product-market fit, building better customer feedback loops, prioritizing under resource constraints, and how AI can make strong product managers even more effective. Then the conversation turns toward the emerging infrastructure of an agentic world: persistent AI memory, data ownership, portability between AI systems, verifiability, and the trust problems that arise when agents begin operating across organizational boundaries. What does product management look like when intelligence becomes cheap, but trust becomes increasingly valuable? That’s the question at the center of this conversation. Outline: 00:00 — Introduction & Kimberly Logan’s background 01:29 — From Technical Program Manager to Product Leader 05:15 — Making the transition into Product Management 07:10 — Skills aspiring PMs should develop 09:40 — AI as a force multiplier for Product Managers 10:35 — Is AI a tool or a fundamental technological shift? 12:31 — What happens when AI agents become the users? 13:58 — What is Walrus? 15:26 — Why your data becomes more valuable in the AI era 17:40 — Portable, programmable & verifiable data 18:44 — Solving AI platform risk with portable memory 20:47 — Verifiable AI memory 21:50 — Where AI memory is being used today 24:44 — Finding real Product-Market Fit 26:18 — How do you prioritize with limited resources? 28:32 — Ruthless prioritization & product trade-offs 30:16 — Where AI goes next 31:45 — The cross-company trust problem for AI agents

