The AI-Powered PM :
A Practical Toolkit for Product Excellence

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What will be the coverage

  • This session moves beyond the hype and provides a practical, hands-on guide for integrating AI into your daily product management workflow. 

  • The speaker will showcase how AI can act as a PM’s personal intern, helping uncover deep user insights during discovery, draft better requirements during execution, and craft compelling narratives for launch. 

  • Attendees will walk away with actionable strategies, prompt examples, and a clear framework for using AI to build better products, faster.

Major highlights

Learn how to use AI as your personal PM intern across discovery, execution, and launch

Build better PRDs, user stories, and technical specs in minutes with AI

Understand AI pitfalls (privacy, bias, hallucinations) and how to avoid them responsibly

Master AI techniques to synthesize customer insights and accelerate product strategy

Elevate GTM efforts with AI-powered storytelling, content creation, and metrics design

About the SPEAKER

Mukesh Marodia

Product Manager

Google

Mukesh Marodia is a Product Manager at Google, leading AI and Observability for GCP Cloud SQL. He previously drove innovations in cloud security with Security Command Center, including multi-cloud security posture, AI security, and IaC validation. With 18+ years of experience across AI, cloud security, and data intelligence at Google, Alation, Informatica, and OpenText, Mukesh combines deep technical expertise with strategic vision.

His work has impacted millions, earning industry recognition and propelling multi-million dollar products. Mukesh is known for actionable insights, strategic vision, and is passionate about helping product leaders & teams to harness AI for real-world impact & build impactful products.

Agenda

Introduction – The PM’s New Superpower
Why AI is no longer optional for high-performing PMs. Setting the stage: AI as a productivity multiplier, not a replacement.
Introduction – The PM’s New Superpower
Phase 1 – AI in Product Discovery & Strategy
  • Synthesizing chaos: Turning raw user interviews, surveys, and support tickets into actionable insights
  • Market intelligence: Rapid competitive analysis and identifying market gaps
Phase 1 – AI in Product Discovery & Strategy
Phase 2 – AI in Product Execution
  • From idea to spec: Drafting PRDs, user stories, and acceptance criteria in minutes
  • Technical partnership: Using AI to “speak engineer” with technical considerations and API design ideas
Phase 2 – AI in Product Execution
Phase 3 – AI in Go-To-Market (GTM) & Launch
  • Crafting the narrative: Blog posts, release notes, and documentation
  • Data-driven decisions: Defining success metrics and A/B test hypotheses
Phase 3 – AI in Go-To-Market (GTM) & Launch
Wrap-Up & Takeaways:
Quick guide on navigating data privacy, bias, and AI “hallucinations” responsibly & room for Q&A
Wrap-Up & Takeaways:

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