Latest Interviews
Showing 1–8 of 8 transcripts.
Clear all filters- a16z13 min
AI in 2026: 3 Predictions For What’s To Come (a16z Big Ideas)
Oliver Hsu, Bryan Kim, David Haber
Speakers Oliver Hsu, Brian Kim, and David Haber analyze distinct trajectories for AI adoption, ranging from autonomous scientific discovery in life sciences to consumer platforms shifting focus from productivity to digital connectivity. Hsu identifies the maturation of robot learning and simulation as prerequisites for closing the loop on self-driving labs, while Kim argues that future consumer value hinges on AI agents facilitating human relationships through deep emotional engagement. Concurrently, Haber demonstrates that the most robust business models integrate AI to directly reinforce revenue generation and proprietary data loops, as seen in contingency law firms and loan servicing platforms that scale success rather than merely cutting costs.
- a16z43 min
Where does consumer AI stand at the end of 2025?
Anish Acharya, Olivia Moore, Justine Moore, Bryan Kim
The analysis identifies a "winner-take-most" dynamic in the LLM market where ChatGPT retains dominance with nearly 900 million weekly users, despite significant growth in Google's Gemini desktop base and emerging competition from specialized startups. While major labs struggle with risk-averse product execution and internal compute allocation conflicts, 2026 is projected to trigger a consumer builder boom driven by unified multimodal models and shifting revenue models toward usage-based pricing. Experts predict this landscape will favor opinionated, standalone applications from startups over the incremental improvements offered by big technology incumbents.
- a16z28 min
Health Tech Founders: The Future of Care Is Personalized, Proactive—and AI-Powered
Bryan Kim, Jonathan Swerdlin, Daniel Cahn
Jonathan Sorlin of Function Health and Daniel of Slingshot AI are launching AI-driven platforms that address critical gaps in physical and mental healthcare by transforming reactive medical models into proactive, data-centric prevention systems. Their products prioritize human experience over traditional metrics, utilizing autonomous tools to interpret complex biomarkers and foster therapeutic alliances without replacing human providers. This approach aims to scale access for millions by reducing systemic friction and burnout, ultimately lowering costs while empowering users to maintain autonomy and deepen genuine human connections.
Why a16z Bet $15 Million on THIS Controversial Startup
Bryan Kim, Roy Lee, Molly O'Shea
Brian Kim secured a $15 million investment in Cluely by leveraging a "momentum as a moat" strategy that prioritizes velocity and personal rapport over traditional fundraising pitches. His investment thesis for the AI era emphasizes rapid scaling and efficiency, as evidenced by his high-velocity deals with 11 Labs and Function Health while navigating regulatory headwinds regarding deepfakes. Kim argues that the current technology landscape requires building "in the plane as it falls," with companies achieving profitability through smaller teams and massive growth trajectories.
- a16z42 min
Building Cluely: The Viral AI Startup that raised $15M in 10 Weeks w/ Roy Lee
Roy Lee, Erik Torenberg, Bryan Kim
Roy, a Harvard dropout turned serial entrepreneur, has built Clueless into a venture that generated over $1 million in enterprise revenue within ten weeks by leveraging a unique viral distribution strategy and a semi-translucent AI overlay interface. Despite reportedly declining a billion-dollar acquisition offer from Meta, Roy prioritizes rapid market validation and "radical transparency" over traditional corporate professionalism, employing a network of contractors to generate high-impact content that converts social media awareness into tangible sales. His investor, Brian, backed the company based on the thesis that speed and distribution capability now serve as superior moats compared to product retention, positioning Clueless to dominate the emerging AI interaction landscape through a "flooding the zone" approach.
- a16z43 min
The State of Consumer Tech in the Age of AI
Erik Torenberg, Anish Acharya, Olivia Moore, Justine Moore, Bryan Kim
The discussion frames consumer AI as a velocity-driven market where relentless model updates replace traditional network effects, enabling premium pricing models that capture significant value by substituting high-cost labor. While mobile and wearable hardware currently serve as the primary substrate, the sector is navigating a transition from legacy social structures toward novel paradigms like synthetic selves and agentic actions that prioritize direct user utility over static interfaces. Ultimately, success depends on maintaining a technical frontier and evolving new social norms to support an ecosystem where AI companions and enterprise tools facilitate deeper human connection rather than displacing it.
- a16z26 min
7 Ways to Boost Retention (Both Pre- and Post-AI)
Experts identify seven distinct, cost-efficient retention methodologies that can elevate Day 30 retention rates from a standard 20% to an exceptional 35%. These mechanisms range from accelerating speed-to-value and implementing feature-gated onboarding to leveraging smart notifications, maintaining user streaks, and utilizing AI-driven personalization. By adopting strategies like designing reciprocity and granting status to power users, companies can transform user acquisition costs into sustainable growth while avoiding the "bird forest" pitfall of exhaustible demand.
- a16z49 min
Growth vs Efficiency: Can You Have Both?
Gina Gotthilf, Kieran Flanagan, Bryan Kim
This session synthesizes strategic shifts where founders prioritize sustainable moats like proprietary data and community trust over bloated growth tactics to counter incumbent monopolies. Speakers analyze how AI serves as both a cost-reduction tool and a retention driver while detailing volatile channel dynamics, including the decline of traditional SEO and the rise of interest-based discovery on short-form video platforms. By examining case studies from Snapchat, Duolingo, and Zapier alongside specific experiment frameworks, the discussion outlines a disciplined approach to balancing profitability with iterative product hits in an era of market austerity.