Latest Interviews
Showing 16–30 of 46 transcripts.
Clear all filters- Sequoia Capital32 min
This is AGI: Sequoia AI Ascent 2026 Keynote
Pat Grady, Sonya Huang, Konstantine Buhler
This analysis outlines a $10 trillion market opportunity driven by a paradigm shift from information distribution to autonomous computation, where AI agents are rapidly replacing cognitive labor with agentic systems capable of long-horizon execution. Founders are advised to leverage the "MAD" model—focusing on customer moats, immediate affordance, and bridging the adoption diffusion gap—to capitalize on a timeline that compresses years of work into days. The event further projects that by 2026, the convergence of these technologies will trigger a cognitive industrial revolution, fundamentally redefining human value from task execution to relationship building and strategic oversight.
- Sequoia Capital20 min
Robotics' End Game: Nvidia's Jim Fan
NVIDIA Robotics is transitioning from language-centric VLA models to World Action Models like Dream Zero, which prioritize learning physical laws through video prediction to enable zero-shot generalization. This architectural shift is supported by a new data collection strategy replacing low-efficiency teleoperation with scalable egocentric video and neural simulators, establishing a log-linear scaling law between training hours and dexterity. Looking toward 2040, Jim Phan projects the industry will achieve a "Physical Turing Test," an orchestration "Physical API" for automated fleets, and "Physical Auto-Research" where robots autonomously improve their own designs.
- Sequoia Capital38 min
Why the Next AI Revolution Will Happen Off-Screen: Samsara CEO Sanjit Biswas
Sanjit Biswas, Sonya Huang, Pat Grady
Samsara leverages its 90-billion-mile fleet dataset to drive a "third shift" in autonomous logistics and physical AI, prioritizing edge-computed safety and behavioral coaching over full automation replacement. With $3 billion reinvested into R&D, the company transforms legacy operations across trucking, construction, and public sector transit by integrating sensor telemetry with cloud-based video language models. This strategy aims to unlock 24/7 productivity while mitigating risk through distributed architectures that balance real-time inference with scalable digital workflow modernization.
- Sequoia Capital10 min
From Early Failures to ‘Clash of Clans’ and ‘Brawl Stars’ - Supercell ft Ilkka Paananen
Ilkka Paananen, Maya Hoffree, Joost van Dreunen, Roelof Botha
Supercell established a unique corporate structure known as "cells" that empowers individual game teams with startup-like autonomy, a strategy that enabled leaders to cancel their initial €8 million investment in the Facebook title *Gunshine* to pivot successfully toward mobile platforms. This bold approach fostered a culture where project failures are celebrated as learning experiments, ultimately leading to the creation of industry-defining hits like *Clash of Clans* and *Hay Day* that currently command 60% of total industry playtime. Now fifteen years old, the company continues to navigate the high barrier of launching new titles by embracing increased risk-taking, aiming to emulate the century-long legacy of Nintendo or LEGO while maintaining operational excellence.
- Sequoia Capital15 min
The $10 Trillion AI Revolution: Why It’s Bigger Than the Industrial Revolution
Sequoia Capital frames the current AI landscape as a "cognitive revolution" poised to expand the $10 trillion U.S. services market by applying the "specialization imperative" to transform general-purpose infrastructure into specific high-value applications. The firm targets startups like Harvey, Factory, and Nominal that deliver tangible leverage in professional roles, while anticipating a shift in investment metrics toward real-world performance, reinforcement learning, and compute efficiency per knowledge worker. Looking 12 to 18 months ahead, Sequoia prioritizes breakthroughs in persistent memory, autonomous agent communication protocols, AI voice interfaces, and comprehensive security layers to accelerate the creation of large-scale public service companies.
- Sequoia Capital38 min
OpenAI Codex Team: From Coding Autocomplete to Asynchronous Autonomous Agents
Hanson Wang, Alexander Embiricos, Sonya Huang, Lauren Reeder
OpenAI has rebranded its Codex system into an agentic coding suite specifically RL-tuned to autonomously execute complex enterprise development tasks like debugging, testing, and deployment within isolated cloud environments. Internal adoption data indicates that professional engineers now leverage the tool to generate multiple parallel code iterations daily, effectively shifting their primary responsibility from writing code to validating agent outputs. This strategic pivot aims to redefine 2025 as the "year of agents" by lowering barriers to bespoke software creation while anticipating a market where human developers manage high-level workflows through future interfaces that blend in-IDE pairing with long-running background automation.
- Sequoia Capital54 min
Google I/O Afterparty: The Future of Human-AI Collaboration, From Veo to Mariner
Thomas Iljic, Jaclyn Konzelmann, Simon Tokumine, Sonya Huang
Google Labs presented a unified vision for AI development featuring Thomas Morton's Wisp and Flow video generation tools that merge cinematic production with interactive gaming, alongside Jacqueline Kanzelman's Mariner project which automates complex browsing tasks through screenshot-based reasoning. Complementing these capabilities, Simon Takamine detailed Notebook LM's evolution into a dynamic personal knowledge platform offering diverse content formats and mobile integration. Collectively, these updates signal a strategic shift from static media consumption to interactive, co-created experiences driven by state-of-the-art multimodal models expected to define 2025 applications.
- Sequoia Capital10 min
How to Scale AI Application Inference 100x ft. Fireworks’ Lin Qiao
Fireworks addresses the critical gap between generic model capabilities and specific application needs by co-optimizing inference across quality, speed, and concurrency for over 100,000 variables. This strategic approach reduces inference costs by 10x to 100x through virtual cloud infrastructure that dynamically selects hardware and aligns data distributions, enabling rapid enterprise scaling. The platform has already demonstrated success in transforming high-cost operations into sustainable models, exemplified by a food chain expanding to 1,000 shops and a software firm serving 25 million developers within three months.
- Sequoia Capital20 min
Will Open Source AI Overtake Closed Models? Ft. Olama, Fireworks and Open Router
Jeff Morgan, Dmytro Dzhulgakov, Alex Atallah, Dima, Matthew Walkerman
Industry leaders from Ollama, Fireworks, and OpenRouter advocate for a balanced future where open-source and closed-source models each command 50% of inference tokens, driven by the strategic advantages of decentralized innovation and lower capital barriers. While current open adoption sits at 30%, panelists predict this share will expand as foundational models improve through reinforcement learning and enterprises prioritize ownership of proprietary fine-tuned artifacts. This shift relies critically on sustainable decentralized inference infrastructure to compete against the entrenched advantages of large, closed-source providers.
- Sequoia Capital32 min
OpenAI’s Sam Altman on Building the ‘Core AI Subscription’ for Your Life
Sam Altman, Jens Nordvigsen, DAN GALPIN, SAM SACCONE
OpenAI has evolved from a 14-person research lab into a commercial powerhouse driven by the GPT-3 API and the viral ChatGPT platform, which now serves 500 million weekly active users. Under Sam Altman's leadership, the organization prioritizes high-impact small teams and a vision of becoming a personalized AI operating system while navigating a market where startups outpace legacy enterprises in agility. The company's roadmap emphasizes the transition from text-based assistants to autonomous agents by 2025, with future infrastructure expected to facilitate seamless agent-to-agent communication and eventual robotics applications.
- Sequoia Capital31 min
Google's Jeff Dean on the Coming Transformations in AI
This presentation outlines the trajectory of deep learning from its 2012 scaling breakthroughs toward a future of multi-modal agents and physical robotics capable of performing thousands of tasks within two years. It details a converging industry landscape where a handful of foundational models drive a secondary ecosystem of efficient, specialized architectures supported by Google's upcoming Ironwood TPU generation and Pathways system. The discussion further projects how these advancements will revolutionize scientific discovery, democratize virtual engineering through junior-level AI assistants, and reshape economic structures via dynamic compute allocation.
- Sequoia Capital7 min
Open Evidence Captures Doctors’ Collective Wisdom with AI ft. Zachary Ziegler
OpenEvidence, a medical search tool used daily by over 25% of US physicians, recently enabled an internal medicine doctor to successfully manage an in-flight emergency for an immunocompromised cancer patient without diverting the aircraft. By synthesizing current literature and CDC data, the platform confirmed the patient did not require immediate intervention and provided a targeted treatment protocol that ensured a positive outcome upon landing. Building on this high-volume, real-time performance, the company is now expanding into direct workflow integration and developing an Aggregate Clinical Wisdom initiative to encode expert consensus from top specialists across various fields.
- Sequoia Capital24 min
Anthropic CPO Mike Krieger: Building AI Products From the Bottom Up
Mike Krieger, Trevor Johnsen, Sam Nelsons, Emily Fortuna, Dave Elliott Smith, Mike McDonald Jr.
At a recent strategic discussion, Anthropic executive Mike McDonald Jr. outlined a paradigm shift where the distinction between AI-generated and human-created content becomes irrelevant, emphasizing instead that provenance via blockchain and compelling human storytelling will define future value. The organization is operationalizing this vision through a "bottoms-up" product philosophy and the development of the Model Context Protocol (MCP), which evolved from engineer-led integrations to establish a standardized, open framework for autonomous agent interactions and economic transactions. Internally, this approach has resulted in massive AI adoption with over 70% of code reviews generated by machines, though leaders note that non-technical organizational bottlenecks now pose the primary constraint on high-velocity development.
- Sequoia Capital10 min
9 Years to AGI? OpenAI’s Dan Roberts Reasons About Emulating Einstein
OpenAI demonstrated a strategic pivot toward test-time compute and reinforcement learning by showcasing models like O1 and O3 that solve complex physics problems, such as quantum electrodynamics and General Relativity, in minutes compared to human timescales. To support this new scaling paradigm where reasoning effort outweighs pre-training data, the organization plans to raise $500 billion to construct massive data center facilities in Abilene, Texas. This infrastructure investment aims to accelerate a timeline predicting that within nine years, systems will evolve from reproducing existing scientific knowledge to generating novel discoveries comparable to Einstein's major breakthroughs.
- Sequoia Capital9 min
How OpenAI Built its Groundbreaking Deep Research Product ft. Isa Fulford
OpenAI's Deep Research introduces an agentic o3 model capable of executing complex, multi-step online investigations over five to thirty minutes to generate analyst-level reports. Targeted at professionals like venture capitalists and academics, the system synthesizes cross-lingual data through interactive clarifications and real-time transparency into its reasoning process. While current versions prioritize read-only browsing and citation granularity, the roadmap outlines plans to integrate these tools into broader reasoning models and enable autonomous action-taking based on findings.