How AI is reshaping product management from idea to launch? The panel digs into strategy, PRDs, research, prototyping, analytics, guardrails, and the human judgment that still holds it all together.
“AI gives you what you give it. It can enhance your voice, but it cannot replace your thinking or your voice.” — Namisha Balagopal
Guests
Namisha Balagopal — Product leader across HP, Twitch, Amazon, and digital health
Mayan Shay May-Raz — Principal Product Manager, Amazon Search, former AR and VR PM at Lenovo and Meta startup
Dr. Nancy Li — Founder, PM Accelerator, YouTube and LinkedIn Top Voice
Jasmeen Bal — Product leader in the EV charging industry, former automotive engineering
Hosts
Reut Lazo, Cofounder and Co-CEO, WOMEN x AI
Jenny Kay Pollock, Cofounder and Co-CEO, WOMEN x AI
What We Cover
- How AI speeds strategy, PRDs, and stakeholder buy-in
- Research at scale with interview synthesis and insight mapping
- Prototyping and UI flows with AI design helpers
- Data quality, cleansing, and why your inputs determine your outputs
- Hallucinations, bias, and practical guardrails in production
- The evolving PM role, specialization, and parallelized build cycles
- Blending AI insight with human empathy and product taste
Key Takeaways
- AI is a force multiplier for PMs who stay in the loop and think critically.
- Inputs matter. Define personas, context, and goals to get useful outputs.
- Use AI to compress time, then spend the saved time on deeper questions.
- Guardrails require humans. Validate facts, monitor outputs, and design for failure cases.
- Clean data beats big data. Aggregate, de-dupe, and cleanse before you trust.
- The PM toolkit is changing, but storytelling and empathy still win rooms.
- Product orgs will specialize. Core feature PMs, growth PMs, and internal tooling PMs can move faster with AI.
- Parallelize more. Strategy, research, prototype, and QA can run together with AI assistance.
Tools Mentioned
Dovetail — Customer interviews, synthesis, and insights
Lovable — Prompt to clickable prototype for faster stakeholder alignment
Claude — Reasoned writing, persona-aware drafting, and analysis
Amplitude — Product analytics and auto-captured events for faster decisions
Fathom — Meeting records, notes, and action items
Also referenced: Miro AI, Figma, GitHub Copilot, Cursor, Google Vertex AI, RAG and multi-agent patterns
Resources and Recs
Storyworthy by Matthew Dicks, on storytelling that lands with stakeholders
On Purpose with Jay Shetty — Madonna interview on resilience and belief
Power and Prediction by Agrawal, Gans, and Goldfarb, on how AI shifts decision making
Chapters
00:00 Intro and why AI in product matters now
01:09 Guest intros
05:06 How AI changes PM work and team velocity
08:44 First moments when AI changed their product practice
14:36 Strategy, speed, and decision making with AI
15:13 Research at scale and the Dovetail workflow
16:53 Blending AI insight with human intuition
20:21 Designing an AI-native product process end to end
23:29 Specialization and faster iterations across the lifecycle
24:40 Parallelizing strategy, prototyping, research, and QA
26:32 Risks and challenges, overreliance, and “vanilla” docs
28:01 Hallucinations and practical guardrails in production
33:39 Tool favorites of the week
37:40 Non-AI recommendations and why empathy still matters
41:02 How WOMEN x AI helps members grow
43:07 Closing and final quote
Recorded for the WOMEN x AI community. Learn more and join at www.womenxai.com.
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