AI-Native Product Management: Your Experience Is the Multiplier

About this session

Product management is going through its most significant shift in a generation. First drafts of PRDs, research synthesis across thousands of data points, and working prototypes built without engineering support have all become dramatically faster and cheaper. For experienced product managers, this raises an exciting question: when production work takes minutes instead of days, where does your time — and your value — go next?

This story-driven keynote offers a practical answer: the judgment, context, and taste you've built over years of product work are not made obsolete by AI. They are amplified by it. Experience is the multiplier on everything these tools produce. We'll begin with a simple mental model — three levels of AI adoption in product management. Level 1 is productivity: drafting, summarizing, and rewriting. Level 2 is insight: synthesizing months of user interviews, support tickets, and survey data to surface patterns no individual could find alone. Level 3 is strategy: building AI into your product and using rapid prototypes to strengthen roadmap conversations. Through real case studies, we'll explore what Levels 2 and 3 look like in practice and how PMs are using them to grow their influence and their careers.

We'll also have an honest conversation about the human side of this shift: which capabilities remain distinctly yours — stakeholder trust, product taste, organizational context, the courage to say no — and the practical guardrails every PM should know around accuracy, data privacy, and maintaining your own voice.

Attendees will leave with three things: a self-assessment model for their own AI adoption, a lifecycle map of practices and prompts they can apply immediately, and a 90-day plan for moving from everyday productivity gains to genuine strategic leverage — positioning themselves as the person their organization turns to as AI reshapes product work.

Speaker

Key takeaways

  • A three-level model for assessing your own AI adoption — from everyday productivity to insight generation to product strategy — and a clear picture of where the greatest career leverage lies.
  • A lifecycle map of immediately usable practices and prompts for discovery, definition, prioritization, and delivery — including research synthesis rules, pre-mortem prompts, and prototype-first approaches.
  • A 90-day action plan for turning years of product experience into your biggest advantage in the AI era — and becoming the PM your organization turns to as product work evolves.

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