Join us as we train our neural nets on the theme of the century: AI. Sonya Huang, Pat Grady and more Sequoia Capital partners host conversations with leading AI...
From Software Engineers to AI Word Artisans: Filip Kozera of Wordware
Filip Kozera sees parallels between Excel’s democratization of data analytics and Wordware’s mission to put AI development in the hands of knowledge workers. Drawing inspiration from Excel’s 750 million users (compared to 30 million software developers), Wordware is creating tools that balance the rigid structure of programming with the fuzziness of natural language. Filip explains why effective AI development requires working across multiple abstraction layers—from high-level concepts to detailed implementation—while preserving human creative control. He shares his vision for “word artisans” who will use AI to amplify their creative impact.
Hosted by Sonya Huang, Sequoia Capital
Mentioned in this episode:
Lovable: Generative AI app that builds UIs and web apps
Her: 2013 Spike Jonze film that Filip uses as an example of how voice will not be the best modality to express knowledge work.
Descript: AI video editing app that Filip uses a lot.
Granola: AI notetaking app Filip uses every day..
Gemini 2.0 Pro: Google’s newest long context model that can handle 6000 page pdfs.
Limitless pendant: Wearable device for collecting personal conversational context to drive AI experiences that Filip can’t wait for to ship.
DeepLearning.AI: Andrew Ng’s amazing resource for learning about AI
3Blue1Brown: Grant Sanderson’s incredible channel on YouTube that explains math and AI visually.
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43:04
Josh Woodward: Google Labs is Rapidly Building AI Products from 0-to-1
As VP of Google Labs, Josh Woodward leads teams exploring the frontiers of AI applications. He shares insights on their rapid development process, why today’s written prompts will become outdated and how AI is transforming everything from video generation to computer control. He reveals that 25% of Google’s code is now written by AI and explains why coding could see major leaps forward this year. He emphasizes the importance of taste, design and human values in building AI tools that will shape how future generations work and create.
Mentioned in this episode:
Notebook LM: Personal research product based on Gemini 2 (previously discussed on Training Data.)
Veo 2: Google DeepMind’s new video generation model.
Paul Graham on X replying to Aaron Levie’s post that “One approach to take in building in AI is to do something that's too expensive to be reasonably practical right now, and just bet that the costs will drop by 10X or 100X over time. The cost curve is on your side.”
Where Good Ideas Come From: Book on the history of innovation by Steven Johnson.
Project Mariner: Google DeepMind’s research prototype exploring human-agent interaction starting with browser use.
Replit Agent: Josh’s favorite new AI app
The Lego Story: Book on the history of Lego.
Hosted by: Ravi Gupta and Sonya Huang, Sequoia Capital
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51:16
How AI Breakout Harvey is Transforming Legal Services, with CEO Winston Weinberg
Harvey CEO Winston Weinberg explains why success in legal AI requires more than just model capabilities—it demands deep process expertise that doesn’t exist online. He shares how Harvey balances rapid product development with earning trust from law firms through hyper-personalized demos and deep industry expertise. The discussion covers Harvey’s approach to product development—expanding specialized capabilities then collapsing them into unified workflows—and why focusing on complex work like international mergers creates the most defensible position in legal AI.
Hosted by: Sonya Huang and Pat Grady, Sequoia Capital
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54:09
The AI Product Going Viral With Doctors: OpenEvidence, with CEO Daniel Nadler
OpenEvidence is transforming how doctors access medical knowledge at the point of care, from the biggest medical establishments to small practices serving rural communities. Founder Daniel Nadler explains his team’s insight that training smaller, specialized AI models on peer-reviewed literature outperforms large general models for medical applications. He discusses how making the platform freely available to all physicians led to widespread organic adoption and strategic partnerships with publishers like the New England Journal of Medicine. In an industry where organizations move glacially, 10-20% of all U.S. doctors began using OpenEvidence overnight to find information buried deep in the long tail of new medical studies, to validate edge cases and improve diagnoses. Nadler emphasizes the importance of accuracy and transparency in AI healthcare applications.
Hosted by: Pat Grady, Sequoia Capital
Mentioned in this episode:
Do We Still Need Clinical Language Models?: Paper from OpenEvidence founders showing that small, specialized models outperformed large models for healthcare diagnostics
Chinchilla paper: Seminal 2022 paper about scaling laws in large language models
Understand: Ted Chiang sci-fi novella published in 1991
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1:04:52
OpenAI’s Deep Research Team on Why Reinforcement Learning is the Future for AI Agents
OpenAI’s Isa Fulford and Josh Tobin discuss how the company’s newest agent, Deep Research, represents a breakthrough in AI research capabilities by training models end-to-end rather than using hand-coded operational graphs. The product leads explain how high-quality training data and the o3 model’s reasoning abilities enable adaptable research strategies, and why OpenAI thinks Deep Research will capture a meaningful percentage of knowledge work. Key product decisions that build transparency and trust include citations and clarification flows. By compressing hours of work into minutes, Deep Research transforms what’s possible for many business and consumer use cases.
Hosted by: Sonya Huang and Lauren Reeder, Sequoia Capital
Mentioned in this episode:
Yann Lecun’s Cake: An analogy Meta AI’s leader shared in his 2016 NIPS keynote
Join us as we train our neural nets on the theme of the century: AI. Sonya Huang, Pat Grady and more Sequoia Capital partners host conversations with leading AI builders and researchers to ask critical questions and develop a deeper understanding of the evolving technologies—and their implications for technology, business and society.
The content of this podcast does not constitute investment advice, an offer to provide investment advisory services, or an offer to sell or solicitation of an offer to buy an interest in any investment fund.
Brasil