Latest Interviews
Showing 1–15 of 41 interview transcripts.
Clear all filters- Sequoia Capital52 min
Making Cities Awesome: Peregrine’s Nick Noone & Ben Rudolph
Nick Noone, Ben Rudolph, Sonya Huang
Founded by ex-Palantir and UNHCR veterans Nick Benes and Ben Hallowell, Peregrine deploys a "forward-deployed" engineering model to help municipalities build privacy-preserving data infrastructure without creating a surveillance state. The company leverages agentic AI to automate 95% of complex data integration and execute rapid analytics, such as identifying hidden crime patterns in Florida or simulating hurricane impacts for local leaders. By maintaining strict local data sovereignty and reducing delivery costs below one million dollars annually, Peregrine enables thousands of unique cities to preserve institutional memory and solve specific community safety challenges.
- Sequoia Capital55 min
Parallel’s Parag Agrawal: Building a New Web for AI Agents
Parag Agrawal, Sonya Huang, Andrew Reed
Parallel, founded by ex-Twitter CEO Parag Agrawal, is building a "web systems" infrastructure that replaces human click data with direct agent feedback to optimize search indexing and ranking for software agents. The company has launched a specialized search agent product and secured a strategic partnership with Google Cloud to serve as the primary grounding provider for enterprise AI, achieving retrieval speeds of 200 milliseconds for top-relevant tokens from a trillion-page web. By shifting from traditional advertising economics to a "Shapley value" model for content attribution, Parallel aims to monetize high-quality data extraction for workflows ranging from financial modeling to autonomous agent triggering.
- Sequoia Capital54 min
Rich Sutton and Khurram Javed: Why AI Models Stop Learning, and How to Start It Again
Rich Sutton, Khurram Javed, Sonya Huang, Alfred Lin
Rich Sutton and Oak Lab advocate for "continual learning" as the essential default for true intelligence, critiquing current Large Language Models for freezing weights and relying on finite human-curated data rather than adapting through real-world experience. To overcome the barrier of catastrophic forgetting, the lab proposes a 12-step research agenda utilizing individual step-size optimization and meta-learning to enable neural networks to continuously update their internal world models. This approach aims to create energy-efficient, self-maintaining agents capable of forming general abstractions across diverse domains, moving the field beyond static training paradigms toward systems that evolve alongside their environments.
- Sequoia Capital49 min
Building the Automated AGI Lab: Core Automation's Jerry Tworek and Rohan Anil
Jerry Tworek, Rohan Anil, Sonya Huang, Pat Grady
Founded by Jerry Liu and Rohan Ramachandran, Core Automation aims to replace static Transformer models with a new class of AI systems capable of continual, test-time learning. The organization is building an automated research lab designed to overcome architectural bottlenecks by developing hardware-efficient kernels and enabling models to autonomously optimize their own code. Success for the venture is defined by the system's ability to self-improve without human intervention, effectively extending the team's operations while bypassing the diminishing returns of current scaling methods.
- Sequoia Capital52 min
Factory's Matan Grinberg: The Coming ‘Dark Factory’ Where Software Builds Itself
Matan Grinberg, Sonya Huang, Pat Grady
Factory CEO Matan Cohen refunded nearly $2 million in early revenue to pivot the company from premature autonomous agents to a model-agnostic architecture that prioritizes customer obsession over vendor lock-in. By launching the Droid CLI and implementing a "Model Router" that dynamically allocates tasks between open-weight and frontier models, the firm has shifted its business model toward outcome-based pricing that replaces token consumption with result-oriented billing. This strategy positions Factory to navigate an impending market correction while transitioning enterprises from synchronous tool usage to asynchronous "dark factories" that autonomously resolve complex issues.
- Sequoia Capital49 min
Anthropic's Katelyn Lesse & Angela Jiang: Building an Ecosystem, not a Walled Garden
Katelyn Lesse, Angela Jiang, Sonya Huang, Lauren Reeder, Caitlin
Anthropic is pivoting its platform strategy from a knowledge-centric foundation to an execution and coordination layer, aiming to democratize custom software development through a unified architecture for both internal and external users. This roadmap introduces specialized primitives for "token-heavy" verticals like coding and finance while enabling flexible model routing and ecosystem interoperability through standards like the Model Context Protocol. By prioritizing cost optimization and advanced workflow orchestration, the company seeks to make the last mile of AI-driven development economically viable for builders ranging from individual developers to large enterprises.
- Sequoia Capital1h 10m
Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis
Dylan Patel, Shaun Maguire, Sonya Huang
Semi-Analysis, founded by Dylan Patel after a period of homelessness and a stint in quantitative trading, has grown to a 90-person team generating nearly $100 million in revenue by blending engineering expertise with hedge fund economics. The firm leverages Patel's annual attendance at over 40 global semiconductor conferences to gather proprietary supply chain data and launched InferenceX, a living benchmarking platform supported by over $50 million in compute donations from major tech firms. Looking ahead, the company projects critical shifts in the industry driven by power grid limitations, the obsolescence of single-architecture hardware, and a strategic pivot toward software-hardware co-design to navigate the escalating demands of artificial intelligence.
- Sequoia Capital51 min
Google DeepMind's Logan Kilpatrick: Why the Model Eats the Harness
Google has launched its "agentic era" centered on the Anti-Gravity harness and the new Omni unified model, enabling autonomous actions across its ecosystem rather than simple API interactions. Key shifts include the introduction of the 3.5 Flash coding model, the transition from maximizing user time to optimizing task completion, and the deployment of a single system for diverse generative media tasks. Led by leadership emphasizing scientific rigor under Demis Hassabis and Sundar Pichai, the initiative aims to replace specialized legacy tools with native, world-understanding agents that augment rather than cannibalize human activity.
- Sequoia Capital46 min
How Cursor Trained Composer on Fireworks: Distributed Infrastructure for High-Performance RL
Federico Cassano, Dmytro Dzhulgakov, Sonya Huang
Cursor has pivoted from a pure application company to a foundation model developer by training Composer 2, a specialized software engineering model built on a Kimi 2.5 base using a global, asynchronous pipeline to maximize compute efficiency. The team deployed a custom infrastructure that integrates Reinforcement Learning from real-time user feedback and simulated rollouts while overcoming synchronization challenges through lossless delta compression and custom GPU kernels. This strategic approach allows Cursor to saturate model capacity with high-value coding data, achieving competitive performance at a fraction of the cost of general-purpose models while moving the industry toward baked-in specialized behaviors rather than prompt engineering.
- Sequoia Capital58 min
How Autonomous Labs Will Transform Scientific Research: Ginkgo Bioworks’ Jason Kelly
Jason Kelly, Sonya Huang, Pat Grady, Anya
Ginkgo Bioworks is executing a strategic pivot from traditional biological design to AI-driven autonomous laboratories, partnering with OpenAI to demonstrate that reasoning models can conduct high-volume experiments with 40% greater efficiency than current state-of-the-art benchmarks. Founder Jason Kelly argues that this shift addresses critical inefficiencies in global science by replacing costly human overhead with 24/7 robotic operations, a move he views as a national security imperative to compete with China's rapidly scaling biotech sector. By transitioning to a cloud-based, usage-pricing model and leveraging specialized robotics over humanoids, the company aims to democratize access to experimental science while fundamentally altering the economics of drug discovery and industrial biotechnology.
- Sequoia Capital48 min
Making the Case for the Terminal as AI's Workbench: Warp’s Zach Lloyd
Warp CEO Zach Lloyd has pivoted the terminal-focused startup from a collaborative code editor into an agentic workbench serving 700,000 developers by leveraging its unique time-based interface for complex software orchestration. The company distinguishes itself from competitors like Cursor by targeting professional engineers and adopting a consumption-based pricing model that prioritizes unit economics over subsidized credit races. Looking ahead, Warp is shifting toward ambient cloud agents and an Agent SDK to manage swarm operations, aiming to solve the "context engineering" bottleneck where human intent translation remains the primary constraint on AI adoption.
- Sequoia Capital1h 2m
Training General Robots for Any Task: Physical Intelligence’s Karol Hausman and Tobi Springenberg
Karol Hausman, Tobi Springenberg, Alfred Lin, Sonya Huang
Physical Intelligence is deploying Pi-Star 0.6, a general-purpose robotic foundation model that achieves end-to-end task execution through RL from real-world experience. Founders Carol and Toby highlight this system's 2x throughput increase in tasks like coffee preparation and laundry folding, enabled by a "bootstrap" data strategy that prioritizes diverse human corrections over simulation. While zero-shot generalization allows operation in unseen environments, the company targets initial commercial releases in controlled settings before addressing safety challenges associated with full household integration.
- Sequoia Capital1h 2m
The Rise of Generative Media: fal's Bet on Video, Infrastructure, and Speed
Gorkem Yurtseven, Burkay Gur, Batuhan Taskaya, Sonya Huang
FAL's platform hosts over 600 generative models across 35 data centers, leveraging a custom distributed supercomputer to optimize video generation against the extreme compute demands of tasks like 4K rendering. By utilizing a dual-model strategy and specialized kernel optimizations, the infrastructure supports complex workflows where customers chain over 14 models to produce content for sectors ranging from education to high-production advertising. This technical approach addresses the rapid 30-day half-life of video AI models, enabling studios and enterprises to integrate real-time generative video into existing pipelines while bypassing the limitations of standard frameworks like PyTorch.
- Sequoia Capital1h 0m
OpenAI Sora 2 Team: How Generative Video Will Unlock Creativity and World Models
Bill Peebles, Thomas Dimson, Rohan Sahai, Konstantine Buhler, Sonya Huang
OpenAI's Sora leverages Diffusion Transformers and space-time tokens to generate coherent videos that increasingly respect physical laws, driving a daily output of seven million clips through an iterative deployment strategy. The platform prioritizes user creation over consumption via algorithmic incentives and the viral "Cameo" feature, while a dedicated API and emerging IP monetization frameworks support diverse enterprise and creator ecosystems. Looking forward, the technology aims to facilitate scientific discovery in physical sciences and evolve into a persistent digital clone platform for social interaction and knowledge work.
- Sequoia Capital1h 0m
Block CTO Dhanji Prasanna: Building the AI-First Enterprise with Goose, their Open Source Agent
Dhanji Prasanna, Sonya Huang, Roelof Botha
Block CTO Dhanji Prasanna drives a strategic shift from a siloed management model to a centralized AI-first architecture, spearheading the "Goose" project that functions as an open-source agent to orchestrate workflows across internal systems. This initiative, which evolved from an internal hack week, enables high autonomy for engineers by integrating diverse LLMs and saving 25% of manual hours through shared, self-learning scripts. Looking forward, Block aims to transition from single-agent co-pilots to collaborative swarm intelligence by 2030, while simultaneously extending this technology to its public-facing Square AI for merchant financial simulations.