Sequoia Capital

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3月10日

Physics Gets a Vote: Nominal Cofounders on Hardware Development in an AI World

Nominal’s cofounders (Cameron McCord, Jason Hoch and Bryce Strauss) realized that the new age of reindustrialization requires a new approach to hardware engineering and testing that’s closer to how software is developed. They founded Nominal with the insight that while SpaceX, Tesla, and Anduril built proprietary internal platforms for hardware testing, the thousands of new hardware entrants can't afford to replicate that work. Nominal serves as the system of record for hardware testing, helping companies move from PDF-based workflows to modern data infrastructure that catalogs telemetry from sensors producing millions of data points per second. The platform enables engineers to author validation logic that follows hardware systems from initial testing through manufacturing and field deployment. We discuss their belief that all hardware companies will become physical AI companies, and why they think Nominal's role as the verification layer will be critical - because unlike a video game, physical products require rigorous validation before they enter the real world. Hosted by: Alfred Lin and Sonya Huang, Sequoia Capital

3月10日

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41 分鐘
23/10/2025

Zipline ft Keller Cliffton - Reinventing Delivery with Instant Drone Transport

In 2014, Keller Cliffton made an audacious pivot: shut down his robotic toy company and rebuild it as an autonomous drone delivery system for life-saving medical supplies. Investors were skeptical: The team knew nothing about drones, healthcare, or logistics. But they pushed forward anyway. This is the story of Zipline's journey from near-death to delivering blood to remote hospitals in Rwanda, battling volatile weather and regulatory hurdles, and eventually becoming a global leader in autonomous delivery: This year Zipline began delivering household items directly to front doors with its new Platform 2 in the US for the likes of Walmart and Chipotle. From fixing broken launchers at 3 AM before the Rwandan president's visit to winning unprecedented FAA approval, Zipline's founders bet everything—multiple times—on their vision. Their story proves that if you just keep going, even when everyone's written you off, you can build something truly transformational. Host: Roelof Botha, Sequoia Capital Featuring: Keller Cliffton, Keenan Wyrobek, Ryan Oxenhorn, Maggie Jim, Alfred Lin

23/10/2025

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46 分鐘
4月2日

Jack Dorsey: Every Company Can Now Be a Mini-AGI

Jack Dorsey (Block CEO) and Roelof Botha (Sequoia partner and Block board member) join to discuss a bold claim they wrote about recently: the traditional corporate hierarchy isn't just inefficient — it's obsolete. Jack made one of the toughest calls in recent business history: cutting 40% of his workforce and rebuilding the company from the ground up around what he calls an AI "intelligence layer." We get into how that conversation went down, the math they used to land on a number, and why he's convinced that acting from a position of strength beats reacting from one of weakness. Jack breaks down his vision for simplifying into just three roles, and what it means to replace a pyramid org chart with a circle — AI at the center, and people at the edge. Roelof, who helped think through the restructuring, shares his perspective on how AI-native startups are building differently, and what CEO qualities are timeless. I've eliminated org charts before. I know how hard this is. But Jack is doing something I never had the tools to pull off. If you're a founder wondering whether your hierarchy is working for you or against you, this one will make you uncomfortable in the best way.

4月2日

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1 小時 4 分鐘
28/10/2025

Nvidia CTO Michael Kagan: Scaling Beyond Moore's Law to Million-GPU Clusters

Recorded live at Sequoia’s Europe100 event: Michael Kagan, co-founder of Mellanox and CTO of Nvidia, explains how the $7 billion Mellanox acquisition helped transform Nvidia from a chip company into the architect of AI infrastructure. Kagan breaks down the technical challenges of scaling from single GPUs to 100K and eventually million-GPU data centers. He reveals why network performance—not just compute power—determines AI system efficiency. He discusses the shift from training to inference workloads, and his vision for AI as humanity's "spaceship of the mind," and why he thinks AI may help us discover laws of physics we haven’t yet imagined. Hosted by Sonya Huang and Pat Grady

28/10/2025

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42 分鐘
13/02/2025

MongoDB’s Sahir Azam: Vector Databases and the Data Structure of AI

MongoDB product leader Sahir Azam explains how vector databases have evolved from semantic search to become the essential memory and state layer for AI applications. He describes his view of how AI is transforming software development generally, and how combining vectors, graphs and traditional data structures enables high-quality retrieval needed for mission-critical enterprise AI use cases. Drawing from MongoDB's successful cloud transformation, Azam shares his vision for democratizing AI development by making sophisticated capabilities accessible to mainstream developers through integrated tools and abstractions. Hosted by: Sonya Huang and Pat Grady, Sequoia Capital Mentioned in this episode: Introducing ambient agents: Blog post by Langchain on a new UX pattern where AI agents can listen to an event stream and act on it Google Gemini Deep Research: Sahir enjoys its amazing product experience Perplexity: AI search app that Sahir admires for its product craft Snipd: AI powered podcast app Sahir likes

13/02/2025

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44 分鐘
5月19日

Rebuilding IT From the Ground Up for the AI Age: Serval's Jake Stauch

Jake Stauch, founder and CEO of Serval, is building a ServiceNow for the AI era. His most contrarian bet is that the product should look like boring old enterprise software, but with unlimited intelligence. Serval's architecture splits work between two agents: an admin agent that uses code generation to spin up workflows from natural language, and a help desk agent that can only act through the tools admins explicitly approve. Jake explains why his team uses OpenAI models for end-user interaction and Anthropic models for code generation, why new model releases sometimes have to be rolled back when prompt tuning breaks, and why he's not worried the foundation labs will come downmarket. He also makes the case for "fewer, better" hiring as the only durable moat in a world where products may need to be rebuilt every six months. Hosted by Pat Grady, Sequoia Capital

5月19日

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38 分鐘
5月7日

Surviving Twitter's Growing Pains: Ex-CEO Dick Costolo

Dick Costolo took over as CEO of Twitter in 2010, inheriting what he calls "the drama queen of hypergrowth companies." Hired as the adult in the room behind founders Jack Dorsey and Ev Williams, Dick spent five years dragging Twitter from a chaotic collective into a public company, and learned a scale-up CEO playbook in the process. We get into how he killed group decision-making and replaced it with what he calls "bias to yes"—only your direct manager can tell you no. Why he stopped solving problems with processes ("the launch checklist was 17 pages long") and started solving them with DRIs and operating control. How he managed by walking around the engineering floor at 9:30 PM to figure out what was actually getting built. And the Steve Jobs trick he stole from Pixar for finding out what's really going on inside a team. Dick is candid about the misses, too, including trying to buy Instagram for around $700 million before Facebook did, and his own struggles to fire fast. When I was running HubSpot, I fired slow almost every time and regretted it. Dick did better, but he'll tell you it never gets easier. If you're scaling past 150 people and feeling the organizational barnacles build up, this one's for you.

5月7日

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1 小時 8 分鐘
2日前

Memory and Continual Learning: Engram's Dan Biderman and Jessy Lin

Dan Biderman and Jessy Lin, co-founders of Engram, are building a neolab around memory and continual learning, which they call two sides of the same coin. Their contrarian premise: instead of stuffing ever-larger prompts into the context window or bolting on RAG, bake a team's knowledge directly into the model's weights, so it knows your company the way an employee of several years does. The payoff: matching or beating frontier models while consuming up to 100x fewer tokens. Working with partners like Microsoft, Notion, and Harvey, the team draws on roots in computational neuroscience and state-space architectures to attack what they see as the real bottleneck in AI — not raw intelligence, but memory and continual learning. In contrast to the frontier labs' race toward one ever-bigger model and AGI, Dan and Jessy imagine a world where everyone has their own model — privately trained, always learning, and good at the things you actually care about. The real ChatGPT moment for memory, they argue, is the day your model feels like an intern that genuinely got smarter overnight. Hosted by Sonya Huang and Shaun Maguire, Sequoia Capital

2日前

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45 分鐘
10/09/2024

Founder Eric Steinberger on Magic’s Counterintuitive Approach to Pursuing AGI

There’s a new archetype in Silicon Valley, the AI researcher turned founder. Instead of tinkering in a garage they write papers that earn them the right to collaborate with cutting-edge labs until they break out and start their own. This is the story of wunderkind Eric Steinberger, the founder and CEO of Magic.dev. Eric came to programming through his obsession with AI and caught the attention of DeepMind researchers as a high school student. In 2022 he realized that AGI was closer than he had previously thought and started Magic to automate the software engineering necessary to get there. Among his counterintuitive ideas are the need to train proprietary large models, that value will not accrue in the application layer and that the best agents will manage themselves. Eric also talks about Magic’s recent 100M token context window model and the HashHop eval they’re open sourcing. Hosted by: Sonya Huang, Sequoia Capital Mentioned in this episode: David Silver: DeepMind researcher that led the AlphaGo team Johannes Heinrich: a PhD student of Silver’s and DeepMind researcher who mentored Eric as a highschooler Reinforcement Learning from Self-Play in Imperfect-Information Games: Johannes’s dissertation that inspired Eric Noam Brown: DeepMind, Meta and now OpenAI reinforcement learning researcher who eventually collaborated with Eric and brought him to FAIR ClimateScience: NGO that Eric co-founded in 2019 while a university student Noam Shazeer: One of the original Transformers researchers at Google and founder of Charater.ai DeepStack: Expert-Level Artificial Intelligence in Heads-Up No-Limit Poker: the first AI paper Eric ever tried to deeply understand LTM-2-mini: Magic’s first 100M token context model, build using the HashHop eval (now available open source) 00:00 - Introduction 01:39 - Vienna-born wunderkind 04:56 - Working with Noam Brown 8:00 - “I can do two things. I cannot do three.” 10:37 - AGI to-do list 13:27 - Advice for young researchers 20:35 - Reading every paper voraciously 23:06 - The army of Noams 26:46 - The leaps still needed in research 29:59 - What is Magic? 36:12 - Competing against the 800-pound gorillas 38:21 - Ideal team size for researchers 40:10 - AI that feels like a colleague 44:30 - Lightning round 47:50 - Bonus round: 200M token context announcement

10/09/2024

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51 分鐘
2月12日

Bayer’s Bill Anderson: Turning a 168 Year-Old Tanker Like a Speedboat

Bill Anderson runs Bayer, a 160-year-old pharmaceutical giant that had 100,000+ employees when Bill took the helm. In just two years after becoming CEO, he flattened 11 layers of management, expanded managers' direct reports from 6 to 90, and eliminated annual budgeting in favor of 90-day cycles. Bill offers up some gems on how to scale without becoming bureaucratic, explains why "professional managers" kill startups, why peer feedback beats manager reviews, and why bureaucracy isn’t a virus that infects healthy companies but rather something that grows from within the heart of your org chart. If you're scaling from 100 to 1,000 employees and want to avoid the death spiral that slows most growing companies, this is essential listening. Bill's created a playbook for organizational transformation that challenges what you think you know about building companies.

2月12日

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1 小時 13 分鐘

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