Latest Interviews
Showing 61–75 of 79 interview transcripts.
Clear all filters- Sequoia Capital1h 3m
Getting the Most From AI With Multiple Custom Agents ft Dust’s Gabriel Hubert and Stanislas Polu
Gabriel Hubert, Stanislas Polu, Konstantine Buhler, Pat Grady
Dust positions itself as a horizontal platform for AI adoption, predicting a bimodal future where enterprise users seamlessly switch between frontier APIs and local models to navigate varying technological plateaus. By prioritizing product-market fit over proprietary model training and leveraging Retrieval-Augmented Generation to unlock data silos, the company enables diverse teams to build specialized agents that augment human work rather than replace it. This strategy targets a demographic of young power users and aims to scale from isolated pilots to organization-wide adoption, facilitating everything from cross-functional translation to global expansion despite current limitations in reasoning breakthroughs.
- Sequoia Capital53 min
Natera ft. Matthew Rabinowitz - A Personal Mission That Led to a Biotech Revolution
Matthew Rabinowitz, Roelof Botha, Jonathan Sheena, Steve Chapman, Chitra Kotwaliwale, Sarah Elliot, Rolof Buerta
Co-founded by Matthew Rabinovitz and Jonathan Sheena, Natera has evolved from a specialized IVF testing provider into a global leader in genetic diagnostics, now processing 40% of U.S. pregnancies and capturing nearly half of oncologists' orders for its Signatera cancer monitoring test. The company successfully navigated significant financial volatility and strategic pivots to achieve a $1.5 billion revenue forecast, with its stock appreciating from $7 to over $100 per share following the clinical validation and market adoption of its oncology division. Today, Natera maintains a dominant market position in women's health genetics and minimal residual disease monitoring while leveraging AI to further expand its early detection capabilities across solid tumors.
- Sequoia Capital52 min
Building the Sales ‘System of Action’ with AI ft Clay’s Kareem Amin
Founded in 2017 by physicist Karim Amin, Clay has grown into an AI-native growth platform for go-to-market teams, currently serving over 4,500 customers with an estimated annual recurring revenue exceeding $20 million. The company differentiates itself by acting as a "system of action" that blends human creativity with automation to craft personalized outreach, enabling clients like Anthropic and Verkata to significantly boost data coverage and engagement rates. Supported by a "chill high achiever" culture and a network of specialized agencies, Clay is expanding its capabilities to unify sales, marketing, and customer success while pioneering recursive AI applications for long-term market disruption.
- Sequoia Capital47 min
Decart’s Dean Leitersdorf on AI-Generated Video Games and Worlds
Dean Leitersdorf, Sonya Huang, Shaun Maguire, Sean McGuire
Descartes has unveiled Oasis, a fully playable AI game engine that executes real-time video model inference on standard H100 hardware without requiring specialized Blackwell chips or traditional game engines. By leveraging a vertically integrated architecture and a custom prompt-to-pixels approach, the company converges training in 20 hours compared to the industry standard of two weeks, positioning the technology to transition users from static interfaces to dynamically generated experiences. Founding team members Dean Leiterstorff and Sean McGuire argue that this low-level systems mastery and the rapid convergence of transformer and pixel-based models will establish a durable competitive moat as the firm moves toward a "generated experience" future.
- Sequoia Capital53 min
DoorDash ft. Tony Xu – The “Wrong” Moves That Built a Giant
Tony Xu, Roelof Botha, Keith Yandell, Miki Kuusi, Alfred Lin, Rolof Guedan
Founded in 2013 by Tony Xu and three Stanford classmates, DoorDash disrupted the food delivery industry by targeting suburban markets with a merchant-first strategy before navigating severe capital shortages that nearly caused the company to collapse. Facing a critical 2018 cash crisis, the leadership accepted simultaneous term sheets from SoftBank and Sequoia Capital to secure a $535 million war chest, a move that enabled rapid expansion and allowed the firm to surpass competitors like Grubhub and Uber Eats by 2019. The company subsequently leveraged its operational efficiency and underdog mentality to pivot from a single restaurant category to a global logistics platform, a trajectory solidified by its pandemic-era support of merchants and the 2022 acquisition of Finland's Volt.
- Sequoia Capital1h 0m
Snowflake CEO Sridhar Ramaswamy on Using Data to Create Simple, Reliable AI for Businesses
Sridhar Ramaswamy, Sonya Huang, Pat Grady, Sonia
Snowflake CEO Sridhar Ramaswamy is driving the company's transformation into an "AI data cloud" that integrates acquired search technology from Neva to serve over 10,000 enterprise customers. The organization addresses reliability concerns in generative AI by prioritizing context engineering and managed governance, enabling business users to access data through grounded chatbots without extensive custom software development. This strategic pivot aims to democratize software creation by embedding AI directly into data workflows, positioning Snowflake to capitalize on the shift toward interoperable cloud storage and controlled mobile ecosystems.
- Sequoia Capital45 min
OpenAI's Noam Brown, Ilge Akkaya and Hunter Lightman on o1 and Teaching LLMs to Reason Better
Noam Brown, Ilge Akkaya, Hunter Lightman, Sonya Huang, Pat Grady
OpenAI's O1 model, internally codenamed Project Strawberry, introduces a paradigm shift by employing "inference time compute" to enable systems to engage in extended, self-correcting reasoning processes akin to human System 2 thinking. This architecture has delivered unprecedented capabilities in STEM domains, allowing the AI to solve complex Olympiad-level programming problems, pass research engineer interviews, and assist in scientific discovery by bridging the gap between difficulty in generation versus verification. While the project faces limitations in speed and creative tasks compared to predecessors like GPT-4, its demonstrated ability to scale performance through increased thinking time marks a significant advancement toward the operational goal of Artificial General Intelligence.
- Sequoia Capital49 min
Jim Fan on Nvidia’s Embodied AI Lab and Jensen Huang’s Prediction that All Robots will be Autonomous
Jim Fan, Jensen Huang, Fei-Fei Li, Stephanie Zhan, Sonya Huang
NVIDIA is constructing a unified computing platform centered on the Jensen Thor chip family and Project Groot, aiming to create a "GPT-3 moment" for humanoid robotics by developing foundation models that generalize abstract motor skills across diverse environments. Led by Jim Phan's GEAR team, this strategy leverages a three-bucket data approach combining internet-scale knowledge, accelerated simulation, and real-world robot footage to bridge the sim-to-real gap and replace specialist models with a single generalist agent. The initiative projects that within a decade, these scalable systems will enable affordable, reliable humanoid robots capable of performing daily tasks like elderly care by exploiting the fact that 99% of the built environment is designed for the human form factor.
- Sequoia Capital51 min
Founder Eric Steinberger on Magic’s Counterintuitive Approach to Pursuing AGI
Eric Steinberger, Sonya Huang, Noam Brown, Sonia
Former DeepMind collaborator Eric Steinberger founded Magic to develop vertically integrated AI software engineers capable of achieving general-domain, long-horizon reliability through increased inference-time compute. Challenging the industry's reliance on standard benchmarks, the company recently open-sourced a "hashless eval" methodology that forces models to process entire context windows rather than exploiting retrieval heuristics. Steinberger's strategy prioritizes a lean, high-velocity research team focused on proprietary model training to build "colleague-tier" agents that automate complex software tasks with over 99% reliability.
- Sequoia Capital1h 13m
Sierra co-founder Clay Bavor on Making Customer-Facing AI Agents Delightful
Clay Bavor, Ravi Gupta, Pat Grady, Brett Taylor, Karthik Narasimhan, Robbie
Former Google leader Clay Bavore and Brett Taylor founded Sierra in late 2022 to deploy proprietary AgentOS-branded AI agents that replace traditional navigation with natural language interactions for major brands like Weight Watchers and Sonos. The company addresses specific large language model limitations, such as hallucinations and data silos, by utilizing supervisor agents and a declarative SDK to achieve over 70% autonomous resolution rates for complex customer tasks. Sierra's unique resolution-based pricing model and proprietary TAU Bench benchmark underscore a strategic shift toward industrial-grade AI that prioritizes factual accuracy and task reliability over raw model size.
- Sequoia Capital51 min
Phaidra’s Jim Gao on Building the Fourth Industrial Revolution with Reinforcement Learning
Jim Gao, Sonya Huang, Pat Grady
Phaedra CEO Jim Gow leverages reinforcement learning to deploy autonomous "virtual plant operators" that optimize mission-critical industrial facilities like Google's data centers and Merck's vaccine manufacturing plants, achieving up to 40% energy reductions while strictly maintaining safety constraints. By inserting cloud-based intelligence layers over legacy hardware, the system moves beyond simple recommendations to issue direct commands that adapt in real-time to physical changes, effectively solving complex constraint optimization problems without new sensor infrastructure. Looking ahead, Gow targets broader climate impact through AI-driven grid balancing to manage renewable energy volatility, while noting that widespread adoption depends on overcoming historical data storage gaps in the industrial sector.
- Sequoia Capital1h 8m
GitHub CEO Thomas Dohmke on Building Copilot, and the the Future of Software Development
Thomas Dohmke, Stephanie Zhan, Sonya Huang
GitHub CEO Thomas Domke outlines a strategic vision to empower one billion developers by 2030 through AI integration, highlighting that Copilot has already secured over 1.8 million paid subscribers and drives significant productivity gains by automating up to 40% of current coding tasks. The platform is expanding beyond basic code generation with new Enterprise customization, Autofix security protocols, and a multi-agent Workspace designed to guide workflows from specification to implementation. Domke anticipates a hybrid model of open and closed-source architectures and a future beyond transformers, while maintaining a philosophy that AI should augment rather than replace human developers in an ecosystem spanning software to physical robotics.
- Sequoia Capital52 min
Klarna CEO Sebastian Siemiatkowski on Getting AI to Do the Work of 700 Customer Service Reps
Sebastian Siemiatkowski, Sonya Huang, Pat Grady
Klarna CEO Sebastian Gunnarsson leveraged a direct partnership with OpenAI to transform the payments platform's dispute resolution from a 14-minute human process to a two-minute autonomous AI system, resulting in a $40 million annual profit increase and the elimination of 700 contracts. Beyond customer service, the company has centralized its operations into a proprietary knowledge graph to power an internal chatbot named Kiki while simultaneously replacing legacy enterprise software to accelerate marketing campaigns from months to days. Gunnarsson frames this strategic shift not as a total replacement of human roles but as a necessary evolution to enforce higher documentation standards and create a "digital financial assistant" that proactively drives savings for consumers.
- Sequoia Capital1h 7m
Reflection AI’s Misha Laskin on the AlphaGo Moment for LLMs | Training Data
Misha Laskin, Ioannis Antonoglou, Stephanie Zhan, Sonya Huang, Peter Abbeel, Rich Sutton, Joe Bardeen, Einstein, Michael Jordan
Founders Misha Laskin and Giannis, leveraging their DeepMind and Google experience, established Reflection AI to solve the reliability bottleneck in autonomous agents by replacing heuristic prompting with scalable search and reinforcement learning. The company addresses the "depth problem" in current LLMs by treating post-training as an AlphaGo-style pipeline that minimizes error accumulation to transition task completion rates from approximately 13% to near-perfect reliability. With a strategic vision targeting digital AGI within three years, Reflection aims to deploy universal agents capable of complex multi-step reasoning while prioritizing pragmatic safety through operational consistency.
- Sequoia Capital1h 0m
Microsoft CTO Kevin Scott on How Far Scaling Laws Will Extend | Training Data
Kevin Scott, Pat Grady, Bill Coughran
Microsoft CTO Kevin Scott outlined the company's strategic pivot to a comprehensive AI ecosystem driven by the belief that scaling data and compute will continue to yield exponential capability improvements despite market saturation. Through key partnerships like the one with OpenAI and a focus on hardware efficiency, the organization aims to transition from training-heavy infrastructure to cost-effective inference that augments human cognition across healthcare, education, and scientific research. Scott emphasized that while full autonomy remains a challenge, flexible architectural design and new economic models for data will enable widespread deployment to solve complex societal problems without forcing developers into proprietary traps.