From managing people to managing AI: The leadership skills everyone needs now | Julie Zhuo (Facebook VP, Sundial CEO, The Making of a Manager author)
Timestamps are as accurate as they can be but may be slightly off. We encourage you to listen to the full context.
Podcast Summary
In this episode, product leader Julie Xu returns to share insights on how AI is transforming the role of managers and product builders. Julie, former head of design at Meta and author of "The Making of a Manager," discusses her current startup Sundial, an AI-powered data analysis platform. (00:00) The conversation explores how management skills directly translate to effectively using AI tools, the flattening of organizational structures, and the evolution from traditional roles to "builders." (08:30) Julie emphasizes that modern management requires the same core principles—clear goals, understanding strengths of resources, and effective processes—whether managing people or AI agents.
- Main theme: The convergence of management skills and AI proficiency in creating more empowered, versatile teams where traditional role boundaries dissolve in favor of builder-focused collaboration.
Speakers
Julie Xu
Julie Xu is the former head of design for the Facebook app used by over 3 billion people and author of the bestselling book "The Making of a Manager." She currently runs Sundial, an AI-powered data analysis startup serving companies like OpenAI, Gamma, and Character AI. Julie also writes The Looking Glass newsletter, which has inspired numerous product leaders and was the original inspiration for Lenny's newsletter.
Lenny Rachitsky
Lenny is the host of Lenny's Podcast and author of Lenny's Newsletter, one of the most popular product management publications. A former Airbnb product manager, he now focuses on sharing insights from top product leaders and helping professionals master their craft through interviews, analysis, and actionable advice.
Key Takeaways
Management Skills Translate Directly to AI Proficiency
Julie explains that the core principles of management—defining clear outcomes, understanding resource strengths, and establishing effective processes—are identical to working effectively with AI agents. (09:45) Just as managers need to "assemble the Avengers" with the right mix of human skills, working with AI requires understanding different model strengths and using the right tools for specific purposes. This parallel means experienced managers already possess the foundational skills needed to excel in an AI-driven workplace, making the transition more natural than many realize.
Dissolve Traditional Role Boundaries to Become "Builders"
Organizations should eliminate rigid role distinctions and embrace the concept of "builders" who can leverage AI to perform multiple functions previously requiring specialists. (14:20) Julie's startup intentionally avoids hiring product managers, instead empowering engineers to handle product decisions with AI assistance. This approach forces team members to develop broader skills while maintaining their core expertise, creating more versatile and empowered individuals who can adapt to changing technological landscapes.
Define Crystal Clear Success Criteria for Both Humans and AI
The most critical skill for working with AI systems is articulating precisely what success looks like in objective, measurable terms. (13:05) Julie emphasizes that vague goals like "make this amazing" fail with both human teams and AI agents. Success requires breaking down high-level visions into specific, testable criteria that leave no ambiguity about whether objectives have been met. This skill becomes even more important with AI because agents cannot rely on human intuition to fill in gaps.
Use AI as a Personalized Learning Accelerator
Rather than just using AI for task completion, leverage it as a customized educational tool to rapidly acquire new skills. (23:31) Julie describes feeding curriculum into ChatGPT and asking it to personalize learning approaches based on individual learning styles—like requesting more examples for visual learners. This approach allows team members to quickly develop competencies outside their traditional expertise, supporting the builder mindset and enabling smaller, more versatile teams.
Diagnose with Data, Treat with Design
Data should inform what problems exist and where opportunities lie, but creative problem-solving still requires human intuition and design thinking. (33:01) Julie's framework emphasizes that data helps capture reality and identify issues, but it cannot prescribe solutions or tell you what to build. The most effective approach combines rigorous data analysis to understand what's happening with creative, human-centered design processes to determine how to address those insights meaningfully.
Statistics & Facts
- The Facebook app that Julie led design for serves over 3 billion people globally, demonstrating the massive scale of her design leadership experience. (01:54)
- Google has eliminated many middle management positions from smaller teams as part of the organizational flattening trend that Julie discusses. (14:14)
- When asked about driving skills, 70-80% of people claim to be better than average drivers, illustrating the pervasive nature of cognitive biases that Julie references when discussing the importance of feedback. (59:53)
