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Sequoia Capital
@sequoia
We help the daring build legendary companies from idea to IPO and beyond.
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I had a chance to interview @jack on Long Strange Trip and then sit in on his Q&A with a bunch of Sequoia founders yesterday. Here's my take followed by my takeaways. Almost all of us are running a derivative of the playbook laid out in Andy Grove's "High Output Management" book that has been lightly edited down through the generations. Jack's set of ideas is a stark departure from that playbook. It reminds me of the shift I went through at the start of my career (pre web - yes, I'm that old!) to "digital transformation," but this is a much bigger, harder shift. Some of my CEO friends have pushed back on these ideas saying something to the effect that Jack isn't a great CEO so we shouldn't listen to him. First, I'm not sure if that is true, but even if it is true, he is an undeniable innovator and first principles thinker applying that thinking here to org design, not just product design. Second, @brian_armstrong, a consensus great CEO is running something that sounds VERY similar to this playbook as well as almost every startup created in the last 18 months. Third, the first quarter Jack printed after putting this in place was a banger. ...To that end, I think we should all call this new playbook, "Dorsey Mode" after the guy who stuck his neck out. If you want to run Dorsey Mode, a lot of things fall out of it that fall out of it: 1. Strategy - Planning cycles are out the window because the speed increases too much. All those 1 way doors you were procrastinating now look like 2 way doors. 2. Distribution - Given how much easier it is going to get to build products, competition and customer confusion will reign. In this new world, distribution is king. Companies with truly creative distribution strategies (rare!) will gain advantage. Also, long live ye olde enterprise sales. 3. Interviewing - All of the startups I work with have changed their interviewing process. Many have a case with a hard ai problem to solve embedded in it or at least have the prospective employee open their laptop and show them something interesting they built with ai. 4. Profile - There was a split in my group of CEOs at the Q&A -- some were learning hard into pilled jr engineers and some were leaning hard into very senior engineers. It roughly seems like the older companies with more code like Meta and HubSpot, are leaning harder into the very senior engineering types. ...Everyone seems keen to hire "curious" types not afraid to go very deep down rabbit holes. 5. Org shape - Triangle shaped org charts are like democracy, its the least bad system we've got. The biggest problem with triangles is that they get worse with size. The new org chart, in theory, is circular with the world model in the middle and very small teams surrounding it. Very few pure managers in the middle anymore. This seems "early," but directionally right to me. 6. Compensation - The difference between a middling employee and a top one is getting much wider which will necessitate a net new pay scale with a much higher standard deviation. 7. Titles - Jack got rid of them and is trying to focus everyone on the work as opposed to the level. As someone who tried this earlier in my career at HubSpot, I'm a little skeptical of this one, but the meta point of trying to focus people on what they "lead" versus who they "manage" is a good one that I hope sticks. 8 Decisions - Almost all decisions these days are made by carbon based life forms. Dorsey Mode turns an increasing amount of decisions over to the system. 9. IT - This is will totally change as their primary function will be to building the scaffolding for the world model and enable the company to keep feeding it the context and taste it will need to improve. EVERYTHING needs to be "legible" (I hate that I'm using that overused word, but it works) ...Btw, an early sign that a company is in Dorsey Mode is when they record every meeting, including the one on one's, cleverly stripping out some HR bits and centralizing them for use by the model. Btw, Ray Dalio had it right, but was just too early. 10. Slop - As more non-technical people build more things, there will be more slop. I didn't grok Jack's answer to this and I'm not sure the answer myself, but Dorsey Mode companies will need to figure out a system to reign in the badly designed systems. 11. Agency - This another word I cringe at using b/c it is so overused, but hiring folks with high agency that are self motivated will be key. The tricky part is that the beef with the current generation is that they are less like this than their predecessors. 12. CEO - This isn't something that will bubble up. The CEO needs to run hard at it and push it down hard and expect to get pushback from laggards. Jack spends 3 hours every morning building hard things with the new tools. ...AI isn't something that lends itself well to learning by reading or watching a video, so CEOs are running hackathons, show & tell's, building days, office hours, and token leader boards. ...Btw, lots of companies are doing the leader board thing (including mine) -- I think this works until it doesn't! 13. Budgets - Budgets in a lot of software orgs are basically enumerated in headcount. The denomination goes back to dollars. As Jack (and my cofounder @Dharmesh) likes to say, in some cases, it is a lot riskier not to take a risk and this is one of those cases.
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Thrilled to announce a $12.5M strategic investment to meet accelerating demand for crypto wallets and verifiable computing. With participation from @circle_ventures, @archetypevc, and existing investors @BainCapCrypto, @FactionVC, @galaxyhq, @sequoia, and @variantfund.
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Claude Code and @suno have more in common than you might think: "It's fun to build things, and it's fun to use what you build." AI lets people be creative in almost any domain, from coding to making music. Today on Training Data, @MikeyShulman shares his thesis for why generative AI is the newest form of active entertainment (the next 'gaming'), music as a cultural phenomenon vs creative expression platform, and more. My favorite part was Mikey's explanation of why Suno learns music theory implicitly vs explicitly: "In Western music, there are 12 tones. If you tell the model there are 12 tones, it will only ever produce those 12 tones. You will be forever limited. And if you tell the model there's 200 instruments, those are the only sounds that you'll ever be able to make." The more you constrain a model with what humans already know, the less capable it becomes. By treating everything as pure sound, Suno built what Mikey calls a totally generalized "music-making machine." Such is the power of neural nets.
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When you're building a company, fires will always come. Your job isn’t racing between them, it’s mapping the territory, building firebreaks, and designing the whole system so one spark doesn’t burn everything down. "Your team kills today’s flames. You shape the forest that survives them." @dickc
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With AI tools today, CEOs can either be laser focused, and say no to almost everything (like Jobs) or they can use the tools to do even more, and get involved in everything (like Bezos). Which is better? @dickc talks about this on the pod, and how he led at Twitter.
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Every risk you take is a deposit. You don't always know when you'll cash it out. Ex-Twitter CEO @dickc tried to get on Saturday Night Live. Didn't make it. But that risk compounded in ways he didn't expect. When someone asked if he was comfortable going live on the news, the answer was obvious. He'd already been booed at midnight in front of a thousand people in Australia. p.s. @nbcsnl I think this was a mistake!
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The offensive advantage now belongs to teams that can operationalize AI fastest. At @sequoia AI Ascent 2026, XBOW founder and CEO @oegerikus describes the shift from AI-assisted hacking to fully autonomous hacking. He compares the moment to the Battle of Nagashino in 1575: one side adapted quickly to new technology, while the other relied on established tactics and past success. Cybersecurity is entering a similar transition. Teams that can operationalize AI offense effectively will have a significant advantage. Watch the full video:
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Our crowd favorite from last year’s AI Ascent is back for round 2… this time: Robotics The Endgame ♟️ thank you for dazzling us @DrJimFan ! You can see the forest from the trees and are quite the entertaining speaker — a mini Jensen in the making :)
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I promise this will be the best 20 min you spend today! Robotics: Endgame, the sequel to my last year's Sequoia AI Ascent talk, "Physical Turing Test". I laid out the roadmap for solving Physical AGI as a simple parallel to the LLM success story. Be a good scientist, copy homework ;) And stay till the end, more easter eggs and predictions for your polymarket! 00:30 DGX-1 origin story at OpenAI, I was there in 2016 signing with Jensen and Elon. Heading to the Computer History Museum! 01:42 The Great Parallel 03:31 Robotics, the Endgame 03:39 Why VLAs fall short 04:32 Video world models as the 2nd pretraining paradigm 06:09 World Action Models (WAM) 07:46 Strategies for robot data collection and the FSD equivalent to physical data flywheel for robot manipulation 11:06 EgoScale and the Dexterity Scaling Law we discovered recently 14:00 Physical RL: bridging the last mile 15:39 DreamDojo: an end-to-end neural physics engine for scaling RL in silico 17:00 Civilizational Technology Tree and my predictions for the near future. Spoiler: it's closer than you think. Thanks to my friends at Sequoia for inviting me back to AI Ascent this year! I had a blast! Last year's talk is attached in the thread if you missed it.
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Getting to 1000x energy efficiency in AI isn’t about one breakthrough. It’s about solving two hard constraints: 1. Data movement dominates energy 2. Amdahl’s Law caps system-level gains Which means you have to rethink everything: models, hardware, and how they’re designed together. If this kind of problem excites you, you’ll enjoy our latest blog:
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Most companies don't kill ideas by saying No. They kill them by making you ask 14 people for permission. @dickc fixed this at Twitter when he was CEO with one rule: only your direct manager can block you. "Experiments started flying out." That's bias to yes.
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🚨NEW PODCAST EPISODE🚨 Dick Costolo: the man who IPO'ed Twitter. I’ve heard every Twitter war story….but never from the CEO who actually had to take the "drama queen of hypergrowth companies" to IPO. This episode with @dickc is simply perfect.  Zero F's given. That's Dick. Funny, blunt, unsentimental, and perfect for the AI founder era. @dickc ran Twitter when it was not just a company, it was the internet’s live wire. A rocket ship in search of a durable business model. A cultural battlefield. A public company in waiting. A media obsession. Sound familiar? It rhymes with a lot of the scale up AI companies today. He does not give generic CEO advice. It's way better. He gives the kind of advice you only get after running one of the most scrutinized companies in the world: 🐌 Why speed dies when no becomes "go ask 14 people" 🚨 Why "the CEO said so" is a sign your company is broken 🍽️ Why dirty dishes in the office can explain why the site crashes 🪞 Why public-company status can quietly distort a CEO's identity 💸 Why founders today are raising too much money and calling it ambition ⚖️ Why AI companies may need more judgment, not more process Links to the full episode below.
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Fun to speak about data centers in space and @Starcloud_ at @Sequoia’s AI day a few weeks ago. Thanks for having me! 🤓
Had a lot of fun speaking at @sequoia ascent! It was an honor to be included in this excellent event - thanks @stephzhan and @sonyatweetybird for inviting us!
(1/5) Great to be at @sequoia to give a sneak peek of one of our research directions! TL;DR one path to data-efficiency may be to “abuse GPUs like they’ve never been abused before”
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So fun to host @annadgoldie and @Azaliamirh of @RicursiveAI at @sequoia AI Ascent 2026! They share the story of building AlphaChip which was incorporated into multiple generations of the TPU. They walk through their three-phase roadmap: from AI-powered design tools -> a "fabless era" platform for custom silicon -> full vertical integration, and their LT vision of building true recursive AI. 00:00 Neural Nets Meet Chips 00:21 Meet AlphaChip Creators 00:43 Recursive Intelligence Vision 01:31 AlphaChip Real World Impact 02:17 Three Phase Company Roadmap 02:20 Phase One Speeding Design 04:11 Rebuilding Tools for AI 05:05 STA Engine and RL Loop 06:15 Designless Platform and Custom Chips 08:01 Team and Audience Q&A
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View more from AI Ascent 2026 including talks with @karpathy, @demishassabis, @DrJimFan , @dmitri_dolgov, @matiii, @bcherny here:
@amspector100 and @bfspector of @flappyairplanes at AI Ascent 2026: The big AI wins so far (search, coding) happen to be the most data-rich problems on earth. Almost everything else is data-poor. Unlocking the rest of the economy will depend on drastically better data efficiency. 00:00 Introduction 00:33 Meet the Founders 01:14 Not an Airplane Company 01:44 Talk Outline and Thesis 01:57 Why Data Efficiency Matters 02:46 The Long Tail of Low Data 03:28 Compute Scales Easier Than Data 04:20 Data Moats and Competition 05:16 Systems Plus Algorithms Approach 06:25 GPU Primitives and Closing
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@amspector100 and @bfspector of @flappyairplanes at AI Ascent 2026: The big AI wins so far (search, coding) happen to be the most data-rich problems on earth. Almost everything else is data-poor. Unlocking the rest of the economy will depend on drastically better data efficiency. 00:00 Introduction 00:33 Meet the Founders 01:14 Not an Airplane Company 01:44 Talk Outline and Thesis 01:57 Why Data Efficiency Matters 02:46 The Long Tail of Low Data 03:28 Compute Scales Easier Than Data 04:20 Data Moats and Competition 05:16 Systems Plus Algorithms Approach 06:25 GPU Primitives and Closing
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Amazing to speak with Andrew at AI Ascent! Andrew has been a partner and sounding board to me and the ElevenLabs team for three years - first unofficially, and now as a very welcome member of our board! Lots to build together - and we covered some of it in the conversation!
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Yesterday @ElevenLabs announced they'd crossed >$500M ARR. Here's my interview with @matiii from @sequoia AI Ascent a few weeks ago. Mati is a founder who really inspires me. He shares stories about ElevenLabs' history (🇵🇱🇵🇱🇵🇱), the current AI landscape, and his vision for voice and agents (and robots) in the future. 00:00 Introduction 00:49 Poland Dubbing Problem 02:10 Why Audio? 03:52 Monetizing Early 05:17 Building the Audio Stack 07:15 Mati's Wow Moments 10:14 Voice Agents Beyond Support 14:26 Operating an AI Leader at Scale 17:43 Audience Q&A - Future of Voice 24:12 Closing
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