AI is fundamentally changing the role of the product manager. While core skills like solving customer problems and using human judgment remain, many traditional and entry-level tasks are being automated. Tom Leung, Director of Product Management at Meta, joins me to share his thoughts on the evolving role of the product manager. He also explains his Flare Wide, Focus Hard, Ship Less framework to help product managers make better prioritization decisions.

The way we build products is shifting rapidly, and relying on the old playbook is a fast track to being replaced by AI. Today, we are discussing how AI is impacting the role of the Product Manager—the good and the ugly. 

If you are feeling overwhelmed by the flood of new AI tools, or if you are feeling pressure from stakeholders to just build faster because “AI makes it easy,” you are navigating a very common friction point. In this discussion, you’ll learn actionable steps to adapt your role and a timely new framework called “Flare Wide. Focus Hard. Ship Less.” 

Tom Leung is back with us. He is a Director of Product Management at Meta and Managing Partner at Palo Alto Foundry, which makes startup investments and provides startup advisory services. With past product leadership roles at Google and YouTube, he has spent over two decades driving innovation and is actively charting the future of AI in product management. He also has a podcast called Fireside Product Management. 

Tom brings a wealth of knowledge as a two-time startup founder with successful exits and as an executive product leader. While he is currently a product leader at Meta, he’s joining us today to share his personal frameworks and industry perspective, not as a company spokesperson.

How AI Is Disrupting Product Management:
Tom and I open the conversation by discussing AI’s impact on product development. Many skills once vital to the product manager toolkit, especially early-career and administrative activities, are being replaced by AI agents. Tasks like competitive research and note-taking now require less human input, reducing demand for entry-level PMs but also freeing up time for higher-impact work. However, customer problem-solving, measurable impact, and sound judgment remain essential for product managers.

Product Management Careers in Entrepreneurship:
According to Tom, the old route of early-career PMs joining large organizations for foundational training is fading. Fewer early-career PM roles means aspiring PMs may need to build skills at startups or small businesses, where they can develop their use of AI. If aspiring PMs own an enterprise, they can celebrate advances in AI because they help their entire business, rather than worrying about being replaced by AI. Tom points out that this ownership mindset requires more entrepreneurial courage.

New Key Skills for PMs:
A critical new skill is managing and critically reviewing the output from AI agents. PMs must catch mistakes hallucinations and avoid outsourcing their judgment to AI. Humans are still needed for prioritization and decision-making, while AI accelerates prototyping and documentation. Tom suggests that early-career PMs today who are less involved in prototyping may still be able to develop pattern-recognition and intuition similar to their older colleagues because AI will enable them to rapidly prototype and ship many more feature and products.

Evolving Product Development Processes:
Tom notes that current documentation and roadmap practices were originally designed for a pre-AI world. AI enables the creation of more artifacts and prototypes in less time, but organizations haven’t yet redefined how to process or prioritize this expanded output. This calls for a re-architecture of product processes and more strategic focus.

Using AI Tools to Write Product Requirements Documents:
Tom shares his experience using AI tools such as Claude to write product requirements documents (PRD). He recommends giving the AI tool a long prompt with a lot of context and telling it to ask you five follow-up questions to make the PRD better. Rather than outsourcing your thinking to an AI agent, use it as a brainstorming and writing partner.

Tom’s “Flare Wide, Focus Hard, Ship Less” Framework:
Tom introduces his Flare Wide, Focus Hard, Ship Less framework: Leverage AI’s capacity to explore, but don’t lose sight of solving actual customer problems and smart prioritization. With the ability to build much more than before, product teams need to be judicious: Just because you can ship more doesn’t mean you should.

“The product manager of the future is going to be more like a hedge fund manager than a builder.” – Tom Leung

Tom Leung is a Director of Product Management at Meta and Managing Partner at Palo Alto Foundry, which makes startup investments and provides startup advisory services. With past product leadership roles at Google and YouTube, he has spent over two decades driving innovation and is actively charting the future of AI in product management. He also has a podcast called Fireside Product Management.

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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