Sequoia Capital

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頻道 • 3 個節目

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科技

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2月3日

What’s the Future of Vertical SaaS in an AGI World? Jamie Cuffe, CEO of Pace

Jamie Cuffe is solving one of AI's hardest problems: getting conservative, regulated industries to trust autonomous agents with mission-critical work. At Pace, he's building AI that replaces traditional BPOs in insurance, handling everything from email triage to claims processing with 50-75% cost savings. Drawing on his experience at Retool, Jamie emphasizes the importance of "closing the distance" with customers through forward-deployed engineering and being "the rock" that clients can rely on. He shares how focusing on top-tier insurance carriers and maintaining exceptionally high standards is enabling Pace to capture a meaningful share of the $400 billion BPO market while building a durable business model - at AI-native velocity. Hosted by Lauren Reeder and Pat Grady, Sequoia Capital

2月3日

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52 分鐘
3月17日

Greetings, Earthlings: Philip Johnston of Starcloud on Data Centers in Space

Philip Johnston, founder and CEO of Starcloud, explains why space will become the primary location for AI compute infrastructure within the next decade. After witnessing SpaceX's massive manufacturing scale at Starbase, Philip realized that declining launch costs would make space-based data centers cheaper than terrestrial ones. He breaks down the physics of heat dissipation in vacuum, the economics of solar power without atmosphere, and why the marginal cost of space infrastructure decreases while Earth-based costs increase. Philip previews a future where close to a trillion dollars per year in CapEx flows to space compute. And, yes, we get his take on aliens. Hosted by: Sonya Huang and Pat Grady, Sequoia Capital.

3月17日

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44 分鐘
1月21日

Context Engineering Our Way to Long-Horizon Agents: LangChain’s Harrison Chase

Harrison Chase, cofounder of LangChain and pioneer of AI agent frameworks, discusses the emergence of long-horizon agents that can work autonomously for extended periods. Harrison breaks down the evolution from early scaffolding approaches to today's harness-based architectures, explaining why context engineering - not just better models - has become fundamental to agent development. He shares insights on why coding agents are leading the way, the role of file systems in agent workflows, and how building agents differs from traditional software development - from the importance of traces as the new source of truth to memory systems that enable agents to improve themselves over time. Hosted by Sonya Huang and Pat Grady

1月21日

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40 分鐘
2日前

Oura’s Tom Hale: What People Don’t Tell You About Being CEO

Tom Hale didn't originally set out to be a CEO - then he put it on his bucket list to prove something to himself. Now he runs Oura, the Finnish health tech company behind the most talked-about wearable on the market - the Oura ring. In this conversation, we get into what the job actually feels like from the inside (spoiler: the kibble-to-champagne ratio is not what you think), and Tom shares some of the sharpest frameworks I've heard for scaling a company through the 200-to-2,000 employee gauntlet. We dig into Oura's controversial pivot to a subscription model - the Reddit flames, the one moment Tom almost blinked, and why he's now calling it an unqualified success. He breaks down the asymmetry between work and headcount that causes politics to metastasize in growing companies, what he looks for in middle managers to keep bureaucracy from setting in, and how he thinks about staying close to customers as layers accumulate between you and them. We also get into the Gucci partnership, what a Roman emperor has to do with it, and the unexpected retail insight that came out of it. And Tom shares why he sleeps soundly despite Apple being the 800-pound gorilla in wearables. If you're a founder navigating the messy middle of company building, this one is worth your time.

2日前

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1 小時
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
18/12/2025

Goldman Sachs CEO David Solomon: What Startup Founders Get Wrong About the CEO Job

David Solomon, CEO of Goldman Sachs, says that no easy decisions reach the CEO’s desk - only “51/49” decisions. When I was leading HubSpot, I described the job as “choosing between two shitty options.” David discusses some of the tough calls he’s had to make in the CEO seat, including the difficult decision to wind down Goldman's consumer banking ambitions. His perspective coming from a 156-year old banking giant is a little different than the common Silicon Valley wisdom. Hear why he thinks experience is vastly underrated in Silicon Valley, why "smart enough" matters more than being the smartest person in the room, and why serendipity and timing play bigger roles in being a great CEO than people realize. David reflects on mentorship from Lloyd Blankfein and Hank Paulson and how he thinks apprenticeship culture will evolve with AI. There are some great, unexpected lessons here for founders who are scaling, confronting the messy reality of building enduring companies.

18/12/2025

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57 分鐘
1月6日

Training General Robots for Any Task: Physical Intelligence’s Karol Hausman and Tobi Springenberg

Physical Intelligence’s Karol Hausman and Tobi Springenberg believe that robotics has been held back not by hardware limitations, but by an intelligence bottleneck that foundation models can solve. Their end-to-end learning approach combines vision, language, and action into models like π0 and π*0.6, enabling robots to learn generalizable behaviors rather than task-specific programs. The team prioritizes real-world deployment and uses RL from experience to push beyond what imitation learning alone can achieve. Their philosophy—that a single general-purpose model can handle diverse physical tasks across different robot embodiments—represents a fundamental shift in how we think about building intelligent machines for the physical world. Hosted by Alfred Lin and Sonya Huang, Sequoia Capital

1月6日

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1 小時 2 分鐘
3月12日

The Most Founder Mode CEO Working Today Isn’t the Founder: Opendoor’s Kaz Nejatian

Kaz Nejatian reveals how he left Shopify to pull off a highly unusual feat: refounding a struggling public company in just 16 days. From first attempting to take the company private and then becoming CEO with an unwavering commitment to prioritizing product, Kaz shares his unconventional playbook and approach to life. We go deep on why most enduring companies are built on "first derivatives" of their core business and not the obvious thing everyone focuses on. Kaz explains why he reads the Bible every day, how overriding life's defaults requires going full force (not halfway), and why founder mode means taking responsibility for outcomes, not processes. He breaks down the mechanics of the Opendoor turnaround, why he tethered his compensation to stock performance, and how he’s making the company AI-native. Essential listening for understanding true founder mode, or for anyone building something that matters.

3月12日

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1 小時 3 分鐘
2月26日

Ben Horowitz On What Makes a Great Founder

A16z’s Ben Horowitz joins me for a raw, unfiltered conversation on what actually breaks founder CEOs, and what separates the great ones from the rest. We unpack founder mode, where it works and where people are taking it too far. Ben shares why overly deferring to experienced executives creates politics and fiefdoms, but avoiding senior talent altogether is just as risky. Founder mode is not about micromanaging. It’s really about taking responsibility for outcomes and having the confidence to manage people who may have more experience than you. Ben goes deep on “constructive confrontation” and why running away from the truth to preserve feelings is one of the most dangerous things you can do in a tech company. He explains why bad news has to travel fast, how decision debt paralyzes organizations, and why hesitation, not lack of intelligence, is what usually gets CEOs replaced. We also dive deep into hiring, especially the VP of Sales role founders mess up more than any other. Ben breaks down why great sales leaders qualify you in the interview, why references matter more than charisma, and why selling a hard product builds a different kind of operator. Along the way, we cover the psychology of being a first-time CEO, what Zuckerberg, Jensen, and Elon actually have in common, why culture is defined by behavior not values, and why feeling like you don’t know what you’re doing is more normal than most founders admit.

2月26日

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49 分鐘
2月10日

Building the GitHub for RL Environments: Prime Intellect's Will Brown & Johannes Hagemann

Will Brown and Johannes Hagemann of Prime Intellect discuss the shift from static prompting to "environment-based" AI development, and their Environments Hub, a platform designed to democratize frontier-level training. The conversation highlights a major shift: AI progress is moving toward Recursive Language Models that manage their own context and agentic RL that scales through trial and error. Will and Johannes describe their vision for the future in which every company will become an AI research lab. By leveraging institutional knowledge as training data, businesses can build models with decades of experience that far outperform generic, off-the-shelf systems.Hosted by Sonya Huang, Sequoia Capital

2月10日

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45 分鐘

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