Latest Interviews
Showing 61–75 of 105 transcripts.
Clear all filters- Sequoia Capital49 min
The Breakthroughs Needed for AGI Have Already Been Made: OpenAI Former Research Head Bob McGrew
Bob McGrew, Stephanie Zhan, Sonya Huang
Bob McGrew defines 2025 as the "year of reasoning," a pivotal shift where immediate compute utilization and tool-augmented chain-of-thought capabilities drive rapid progress toward AGI while pre-training faces diminishing returns. This paradigm reframes post-training as a behavioral challenge and positions AI agents to democratize intelligence by pricing services at compute costs rather than professional market rates. Consequently, economic value accrues to application layers requiring proprietary enterprise context, while sectors ranging from robotics to software engineering transition to hybrid human-agent workflows that leverage these new efficiency gains.
- 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 Capital38 min
From Data Centers to Dyson Spheres: P-1 AI's Path to Hardware Engineering AGI
Paul Eremenko, Sonya Huang, Pat Grady
P1.ai is launching its AI engineering agent "Archie," which addresses the scarcity of physical design data by synthesizing massive, physics-informed datasets to train specialized models for hardware creation. Initially targeting data center cooling applications in 2025, the system operates as a collaborative team member that orchestrates existing CAD and simulation tools to perform complex design synthesis and error correction at entry-level engineer proficiency. With angel investment from Jeff Dean, the company aims to scale the agent's capabilities from residential cooling to aerospace domains over the next four years, ultimately striving for Engineering AGI defined by self-reflection and domain generalization.
- 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 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 Capital34 min
How AI is Reinventing Software Business Models ft. Bret Taylor of Sierra
Bret Taylor, Ravi, Robin Wright, Clay, DAN GALPIN, BRETT HESTERBERG
Brett Taylor, formerly CTO of Facebook and current leader of Sierra, outlines a transformative vision for the AI sector where specialized, outcome-based agents replace traditional websites and software subscriptions. Taylor advises entrepreneurs to evolve beyond personal technical expertise to avoid stagnation, emphasizing that the next trillion-dollar opportunities lie in vertical-specific solutions that deliver tangible business results rather than generic productivity tools. Through Sierra's innovative pricing model that charges only for autonomous resolutions, the company exemplifies a strategic shift toward selling outcomes, positioning startups to outmaneuver legacy incumbents struggling to adapt their business models to this new era.
- Sequoia Capital19 min
The Data Center is the New Unit of Compute: Crusoe CEO Chase Lochmiller
Chase Lochmiller, David Kahn, Pat
Crusoe Energy is rapidly constructing massive AI factories in Abilene, Texas, leveraging a vertically integrated supply chain to deliver gigawatts of power capacity decades ahead of traditional utility timelines. By repurposing stranded renewable energy and deploying advanced cooling architectures, the company accelerates the shift toward sovereign AI infrastructure while addressing critical bottlenecks in power and hardware availability. Founder Chase Lockmiller positions this industrial-scale approach as the mechanism to manufacture intelligence, creating a resilient foundation for the next phase of artificial general intelligence.
- Sequoia Capital48 min
Building the System of Record for the AI Era ft Workday CEO Carl Eschenbach
Carl Eschenbach, Sonya Huang, Pat Grady
Workday CEO Carl Eschenbach is redefining the platform as a unified "Agent System of Record" to govern both human employees and AI agents across its database of over 70 million users. To monetize this shift, the company is deploying a multi-faceted pricing model involving seat-based uplifts, role-based agent fees, and consumption-based API access while utilizing strategic acquisitions like HiredScore to drive measurable productivity gains. Despite an 8% workforce restructuring to fund reinvestment, Eschenbach emphasizes that AI will serve as a growth engine rather than a cost-cutting tool, maintaining a human-in-the-loop approach for critical decisions to preserve the company's core values.
- Sequoia Capital56 min
The Quest to ‘Solve All Diseases’ with AI: Isomorphic Labs’ Max Jaderberg
Founded to construct a general AI-driven drug design engine, Isomorphic Labs has leveraged Demis Hassabis's Nobel Prize-winning leadership and Max Yoderberg's AI expertise to release AlphaFold 3, a diffusion-based model that predicts the 3D structures of proteins, DNA, RNA, and small molecules. By replacing months of traditional crystallization with instant in-silico analysis, the company collaborates with industry partners like Eli Lilly and Novartis to navigate the 10^60-sized chemical space and advance programs in oncology and immunology without operating its own wet labs. This approach positions AI as a fundamental, indispensable tool for the entire pharmaceutical industry within five years, while the firm advocates for new regulatory frameworks to validate these predictive models for clinical trials.
- Sequoia Capital46 min
Pricing in the AI Era: From Inputs to Outcomes, with Paid CEO Manny Medina
Manny Medina, Pat Grady, Lauren Reeder
Manny Medina outlines a strategic pivot for AI success toward narrow, high-utility applications that replace specific Business Process Outsourcing roles rather than general-purpose creative tasks. He details four emerging pricing frameworks, particularly agent-based billing that allows companies to allocate AI costs to human resources budgets, while warning that rising inference costs are compressing margins unless vendors shift to outcome-based revenue models. Medina concludes that sustainable growth requires founders to abandon broad market ambitions in favor of deep vertical expertise, utilizing paid to track unit economics as the industry transitions from trial-based excitement to contract renewals.
- Sequoia Capital43 min
From Software Engineers to AI Word Artisans: Filip Kozera of Wordware
Philip Kizera, co-founder of WordWare, positions his platform as a programmable document system that enables analytical creatives to encode human intent and structured logic into AI agents, treating English as the assembly language for Large Language Models. The company distinguishes its approach by moving beyond simple chat interfaces to offer deployment as an API, an AI-native workflow engine, and a collaborative ecosystem for sharing agent components, thereby targeting a user base of 500 million to 1 billion by democratizing complex AI deployment. By framing the future human role as setting strategic taste while AI executes operational details, WordWare aims to replace raw prompting with repeatable, structured workflows capable of handling massive document ingestion and deep reflection loops.
- Sequoia Capital51 min
Josh Woodward: Google Labs is Rapidly Building AI Products from 0-to-1
Josh Woodward, Ravi Gupta, Sonya Huang
Google Labs operates as an autonomous unit dedicated to rapidly prototyping frontier AI products, prioritizing market validation over immediate technological perfection. Key initiatives include Mariner, a computer-use agent currently targeting enterprise automation, alongside Veo, a generative video model solving physics constraints while shifting industry models toward pay-per-output. The organization accelerates innovation by blending veteran engineering with diverse creative talent to launch ideas within 50 to 100 days, ultimately aiming to replace passive consumption with steerable, asset-driven user experiences.
- Sequoia Capital33 min
OpenAI’s Deep Research Team on Why Reinforcement Learning is the Future for AI Agents
Isa Fulford, Josh Tobin, Sonya Huang, Lauren Reeder
Launched three weeks ago, OpenAI's Deep Research is an agentic system powered by a fine-tuned O3 model that executes complex, multi-hour tasks like market analysis and medical research in 5 to 30 minutes. Utilizing reinforcement learning to optimize browsing and coding strategies, the tool distinguishes itself through a pre-research clarification flow that refines user prompts for higher-quality synthesis. As part of a broader 2025 shift toward agent-driven workflows, this technology aims to amplify knowledge workers by automating information-intensive processes previously deemed too time-consuming.
- Sequoia Capital53 min
From AlphaGo to AGI ft ReflectionAI Founder Ioannis Antonoglou
Ioannis Antonoglou, Stephanie Zhan, Sonya Huang, Giannis Antinoglou
DeepMind founders Demis Hassabis and Shane Legg pioneered Artificial General Intelligence research by utilizing video games as controlled testbeds, evolving from AlphaGo's human-supervised neural networks to the self-learning AlphaZero and MuZero architectures. This strategic shift addressed critical limitations like hallucination and the "data wall" by prioritizing reinforcement learning and planning over static data pre-training, a methodology now considered essential for future AGI development. Looking ahead, experts predict that within five years, increased compute will directly yield higher intelligence in autonomous agents, marking a transition toward systems capable of independent reasoning and novel scientific discovery.