Sequoia Capital

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21/09/2023

Block ft. Jack Dorsey - A controversial hack week project becomes the #1 financial services app

CEO Jack Dorsey reflects on Block’s origins and defining moments with host Roelof Botha. Dorsey founded Square in 2009 with a clear vision: economic empowerment for all. Their dongle that turns iPhones into credit card readers was just the start. With Square, small business owners were able to reach more customers and better manage their companies. But when Cash App, which emerged from an internal hackathon, started to gain traction, Square had a decision to make: stick to their core focus, or risk building an unproven product for consumers? Dorsey explains how Block succeeded by weaving new products around a core vision, and how a controversial shift in strategy led them to fully deliver on their founding mission. Host: Roelof Botha, Managing Partner of Sequoia Capital Featuring: Jack Dorsey, Alyssa Henry, Brian Grassadonia

21/09/2023

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38 分鐘
12/09/2024

MongoDB ft Dev Ittycheria - How an Early Pivot Catalyzed an Open Source Movement

MongoDB, founded in 2007, originally aimed to create a platform-as-a-service system with a new database layer. Facing competition from Google, the founders pivoted to focus solely on their database product, MongoDB—a new kind of database built for the scale of the internet era. Founder Dwight Merriman built a product that developers loved, but scaling the company proved challenging until Dev Ittycheria took the reins as CEO in 2014. As cloud computing grew, MongoDB transitioned from on-premise software to Atlas, a fully-managed cloud service. Despite initial skepticism, Atlas now represents 70% of MongoDB's revenue. As Atlas scaled, MongoDB faced another controversial decision: whether to change its open source license model to maintain its commercial moat. These pivotal decisions transformed MongoDB from a niche database to nearly $2 billion in annual revenue. Host: Roelof Botha, Sequoia Capital Featuring: Dwight Merriman, Dev Ittycheria and Tom Killalea Transcript: https://www.sequoiacap.com/podcast/crucible-moments-mongodb/ 00:00 - Cold Open 00:19 - Introduction 05:30 - The NoSQL movement 09:52 - Scrapping the platform for the database 14:57 - Launching as MongoDB 19:52 - Moving to the cloud with Atlas 24:52 - Assigning a directly responsible individual 30:15 - How Atlas changed MongoDB 35:03 - Updating the licensing model to avoid “strip mining” 39:50 - Evolving back into a platform 41:26 - Executing on points of leverage

12/09/2024

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44 分鐘
09/07/2024

Microsoft CTO Kevin Scott on How Far Scaling Laws Will Extend

The current LLM era is the result of scaling the size of models in successive waves (and the compute to train them). It is also the result of better-than-Moore’s-Law price vs performance ratios in each new generation of Nvidia GPUs. The largest platform companies are continuing to invest in scaling as the prime driver of AI innovation. Are they right, or will marginal returns level off soon, leaving hyperscalers with too much hardware and too few customer use cases? To find out, we talk to Microsoft CTO Kevin Scott who has led their AI strategy for the past seven years. Scott describes himself as a “short-term pessimist, long-term optimist” and he sees the scaling trend as durable for the industry and critical for the establishment of Microsoft’s AI platform. Scott believes there will be a shift across the compute ecosystem from training to inference as the frontier models continue to improve, serving wider and more reliable use cases. He also discusses the coming business models for training data, and even what ad units might look like for autonomous agents. Hosted by: Pat Grady and Bill Coughran, Sequoia Capital Mentioned: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, the 2018 Google paper that convinced Kevin that Microsoft wasn’t moving fast enough on AI. Dennard scaling: The scaling law that describes the proportional relationship between transistor size and power use; has not held since 2012 and is often confused with Moore’s Law. Textbooks Are All You Need: Microsoft paper that introduces a new large language model for code, phi-1, that achieves smaller size by using higher quality “textbook” data. GPQA and MMLU: Benchmarks for reasoning Copilot: Microsoft product line of GPT consumer assistants from general productivity to design, vacation planning, cooking and fitness. Devin: Autonomous AI code agent from Cognition Labs that Microsoft recently announced a partnership with. Ray Solomonoff: Participant in the 1956 Dartmouth Summer Research Project on Artificial Intelligence that named the field; Kevin admires his prescience about the importance of probabilistic methods decades before anyone else. 00:00 - Introduction 01:20 - Kevin’s backstory 06:56 - The role of PhDs in AI engineering 09:56 - Microsoft’s AI strategy 12:40 - Highlights and lowlights 16:28 - Accelerating investments 18:38 - The OpenAI partnership 22:46 - Soon inference will dwarf training 27:56 - Will the demand/supply balance change? 30:51 - Business models for data 36:54 - The value function 39:58 - Copilots 44:47 - The 98/2 rule 49:34 - Solving zero-sum games 57:13 - Lightning round

09/07/2024

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1 小時
5月1日

OpenAI's Greg Brockman: Why Human Attention Is the New Bottleneck

Greg Brockman, co-founder and president of OpenAI, joins Sequoia partner Alfred Lin at AI Ascent 2026 for a conversation that spans the full OpenAI stack. He explains why the company will never have enough compute, why he believes we're 80% of the way to AGI, and why the agentic coding tools that wrote 20% of your code last December are now writing 80% of it. Also: why human attention is becoming the scarcest resource in AI-augmented work, and what it might be like to one day run an organization of 100,000 agents.

5月1日

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28 分鐘
預告

Crucible Moments Season 2: Coming August 29

In Season 1 of Crucible Moments, we heard from founders like PayPal’s Max Levchin, Block’s Jack Dorsey, Nvidia’s Jensen Huang and more about the turning points and key decisions that shaped their journeys. Now Crucible Moments is back for another exciting season. We’ll get the unvarnished history and inside story from Tony Xu of DoorDash, Drew Houston of Dropbox, Frank Slootman of ServiceNow, Vlad Tenev of Robinhood and more. Hosted by Roelof Botha of Sequoia Capital.

預告

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3 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
05/10/2023

Eventbrite ft. Julia Hartz - A thriving events company took 14 years to build and nearly disappeared in 14 days

What happens to an events company when every event is canceled? “Even if you have spent 14 years building something, it could truly be gone in 14 days.” After working tirelessly to revolutionize how live events are organized, this was the reality Eventbrite CEO Julia Hartz faced in March of 2020 as pandemic lockdowns went into effect, extinguishing the lifeblood of her business. She brought the same strategic thinking and grit that had led the company through its previous inflection points to rally her team and reinvent Eventbrite in the middle of a global shutdown. Host: Roelof Botha, Sequoia Capital Featuring: Julia Hartz, Kevin Hartz Transcript: https://www.sequoiacap.com/podcast/crucible-moments-eventbrite/

05/10/2023

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45 分鐘
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
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
6日前

Notion’s Ivan Zhao: The Refounder

Ivan Zhao, founder and CEO of Notion, joins me to introduce a new contender in the founder mode debate: jazz mode. Ivan has a different take than Jack Dorsey's circular org chart or Brian Armstrong's player-coach approach. He thinks hierarchy is human nature, and that you can't flatten it away but you can build a company that improvises like a jazz band instead of marching in formation. Notion has roughly 60 ex-founders on staff and a deliberately decentralized structure to make that work. We get into why Ivan rebuilt his engineering org around a barbell — super junior ICs paired with very senior architects — which is the opposite of what most AI-pilled CEOs are doing right now. He explains why building with language models is "more like brewing beer than engineering a bridge," and how Notion's first candidate interview no longer involves a resume. Ivan is the king of refoundings. He's done it twice, once from a small apartment in Kyoto with five employees left, once from Cancun the day he got early access to GPT-4. When I was running HubSpot, I described our scale-up years as boring compared to what's happening now. Ivan's advice for any CEO who's calcified and wondering if it's time to blow it up: feel the AGI first, then trust your body when it tells you to move. 00:00 Introduction 02:22 From Founder Mode to AI Org 11:00 Hiring for Taste and Agency 24:28 Refounding Notion in Kyoto 30:27 Craft Versus Commerce 32:26 When to Refound 34:07 GPT-4 Refounding Shock 45:35 Leadership and Founder Energy 53:17 Sales Culture and Closing Thoughts

6日前

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1 小時 3 分鐘

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