Lenny's Podcast: Product | Career | Growth
Why every company now needs to think and operate like a lab team | Josh Woodward (Google Labs, Gemini, AI Studio)
· Summarized
Key takeaways
- Every company needs to adopt a labs-style approach to stay competitive in the rapidly changing AI landscape.
- Great ideas often emerge from curiosity-driven side projects and passion, not from formal brainstorming sessions.
- Maintaining a list of adjacent technological and behavioral 'almost possible' opportunities helps teams act quickly when conditions align.
- Early signs of product-market fit include user engagement cues like eye contact and team passion rather than just traditional metrics.
- Recognizing when an idea isn’t working often comes from team signals and user reactions, sometimes before leadership notices.
- Google’s labs focus on zero-to-one innovation and experimentation across AI and related hardware, emphasizing a user-centric approach.
- In the AI era, skills like high unlearning rate, sustained pace, and trust-building become increasingly valuable.
- Building independent, experimental labs within larger organizations allows for rapid innovation and testing of new ideas.
- Future product strategies may evolve toward either highly consolidated super apps or more modular, spoke-like AI experiences.
- In an environment of rapid AI advancement, continuous experimentation and flexible planning are critical to long-term success.
- Fostering a culture that encourages 'good trouble'—challenging norms and experimenting—is crucial for innovation.
- Attention to team chemistry, passion, and trust is essential in building effective, adaptable AI teams.
Summary
Introduction and Premise: Why Labs Culture is Essential for All Companies
The episode opens with a central thesis: every company should operate with a labs-style mindset to stay competitive, especially as AI and technology evolve rapidly. The host notes that this mindset involves experimenting with the latest models, trying multiple approaches, and being prepared to pivot or kill ideas early. Josh Woodward, the guest, shares insights from his role at Google, emphasizing that labs need independence from traditional business units to foster innovation. The conversation sets the stage for understanding how recognizing opportunities early, creating space for risk-taking, and adopting a lab’s experimental culture are vital for future success.
Where Great Ideas Come From and the 'Almost Possible' Framework
Josh explains that the best ideas rarely originate from formal meetings or structured brainstorming; instead, they emerge when curious individuals explore side projects and passions. Continuous vigilance and being on alert to new experiences help catch ideas when they are near 'almost possible.' The 'almost possible' framework involves tracking technological and behavioral shifts to identify opportunities before they fully materialize. Josh describes how his team maintains lists of emerging capabilities and trends, like immersive entertainment, to be ready to act when the moment is right, blending foresight with active experimentation.
Recognizing Product-Market Fit and When to Kill Ideas
The discussion covers the importance of intuition and perceptive cues in early product validation. Josh highlights that team members often recognize when an idea isn’t working before leadership does, through signs like waning passion or the inability to demonstrate surprising progress. He emphasizes observing users' reactions—particularly their eyes or pupils—as a concrete indicator of engagement. The team cultures encouragement and openness to dropping projects that no longer excite or deliver value, exemplified by a recent Gemini feature that wasn’t ready after early testing. The key lesson is that early signals from users and team sentiment are vital for making go/no-go decisions.
Google Labs, the Gemini App, and the Focus on AI
Josh discusses how Google’s labs operate at the frontier of experimentation and product development, with some projects reaching over a billion users. Despite the scale, the core team culture remains focused on zero-to-one innovation, emphasizing curiosity and iterative testing. The Gemini app exemplifies this: it’s a major product built on the same innovation-driven approach. Currently, all their projects are AI-based, reflecting Google’s strategic focus. Josh notes that experimentation extends into adjacent areas like AI hardware with projects like Google Beam. He emphasizes that Google maintains a core belief in user-centricity, with product decisions driven by user feedback—such as observable signals like engagement and excitement—over purely benchmark-driven metrics.
Future of Consumer AI and Overhyped AI Aspects
The conversation explores potential breakthroughs in consumer AI, highlighting areas like immersive entertainment, messaging, and solving large-scale personal problems. Josh argues that despite perceptions of the consumer market being saturated or competitive, AI unlocks new opportunities for personalization and engagement. They discuss how the current wave of AI products often mimics existing data-heavy models (like Gmail or Calendar), but Google is working toward more seamless, integrated, and privacy-conscious interfaces. Josh warns against over-hyping benchmark scores, advocating instead for building compelling products that deliver tangible value to users. The episode emphasizes thoughtful planning and problem-focused innovation over chasing benchmarks.
Valuable Skills in the AI Era and Organizational Insights
Josh identifies emerging attributes that are highly valuable in AI-centric teams: high unlearning rates, 'explosive endurance' (the ability to sustain pace over time), and trust-building skills. He notes a shift in the traditional role of PMs—that they must excel not only at managing projects but also at collaborating across functions, bridging specialists and generalists. The importance of team chemistry and trust-building is stressed, especially as roles blur and individuals work more fluidly as 'free agents' or in small, multifunctional teams. These skills are essential to adapt to rapid changes and capitalize on AI advancements.
Setting Up Labs Teams and Navigating Organizational Challenges
Practical advice is provided for establishing effective labs units within larger organizations. Josh recommends keeping labs independent and separate from core business units to foster experimentation without immediate pressure for commercialization. Clear goals—such as whether to graduate projects into existing products or invent entirely new categories—are crucial. He underscores the value of creating a culture that encourages 'good trouble'—challenging organizational norms and experimenting with new roles, processes, and structures. Selecting passionate, curious, and collaborative individuals who thrive on building and unlearning is key. Josh also discusses the pitfalls of rapid hiring and the importance of balancing exploration with focus.
The Long-Term Vision: Future Product Strategies and the Role of AI
Towards the end, the episode delves into strategic visions of the future. Josh debates whether Google will have thousands of individual products or fewer, more integrated experiences, such as super apps or AI-driven 'spokes' that serve as interfaces to various functions. He emphasizes flexibility, acknowledging that product landscapes can change swiftly in AI, making multi-year plans challenging. The conversation advocates for experimenting with different models—fragmented versus integrated—and relying on emergent insights rather than rigid roadmaps. Overall, Josh advocates for a culture of continuous experimentation and adaptation to the rapidly evolving AI ecosystem.
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Show notes
Josh Woodward is the head of Google Labs, the Gemini app, and AI Studio. He has spent over 17 years at Google and oversees its longest-running and largest labs team, whose products include NotebookLM (now Gemini Notebook), Project Genie, and Flow. His job is to find, experiment with, and scale new AI products, and he has built one of the most distinctive product cultures in the industry for generating ideas, running experiments, and, even more importantly, knowing when to quit.
In our in-depth conversation, we discuss:
1. Why every company now needs to think and operate like a labs team
2. Where the best ideas really come from
3. The “almost possible” framework
4. How to recognize genuine product-market fit early
5. When to kill an idea
6. What skills are rising in value in the AI era
7. Why roles are not actually blurring into one universal builder role
8. How to set up your internal labs team
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Brought to you by:
WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more
DX—Engineering intelligence for the AI era
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Episode transcript: https://www.lennysnewsletter.com/p/why-every-company-now-needs-to-think
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Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0
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Highlights: https://lennyspodcast.com/mostreplayedmoments
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Where to find Josh Woodward:
• X: https://x.com/joshwoodward
• LinkedIn: https://www.linkedin.com/in/joshwoodward
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Where to find Lenny:
• Newsletter: https://www.lennysnewsletter.com
• X: https://twitter.com/lennysan
• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/
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In this episode, we cover:
(00:00) Introduction
(02:53) Why every company now needs to think like a labs team
(05:43) Where great ideas come from
(07:43) The “almost possible” framework
(11:52) Finding product-market fit
(16:09) Falling in love with the problem, not the solution
(17:57) When to kill an idea
(19:35) Overseeing Google Labs and the Gemini app
(22:21) Next consumer AI breakthroughs
(24:32) Google’s vision for a personal assistant
(27:18) What is overhyped and underhyped in AI right now
(31:36) Skills rising in value: unlearning rate, explosive endurance, trust
(35:45) Why roles are not blurring into one universal builder role
(38:59) Explosive endurance rhythms
(41:31) How planning has changed: rolling windows and 100-day milestones
(43:37) Labs lifecycle stages
(47:37) Tips for setting up an internal lab
(54:00) The future of products in an AI world
(56:26) Google Labs culture, rituals, and closing thoughts
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References: https://www.lennysnewsletter.com/p/why-every-company-now-needs-to-think
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
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Lenny may be an investor in the companies discussed.
To hear more, visit www.lennysnewsletter.com
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