Show Notes
Ashwin Sreenivas spent his childhood in India waking up at 5am and studying until 8:30 at night. History, geography, physics, chemistry, math. Every day, from 4th grade through 12th grade, through the Olympiads and the National Talent Search Exam. He says now, three years into building one of the more successful post-ChatGPT companies in the world, that all of that is precisely why what he does today feels almost easy. "I get to come in here and there's a lot of people and I'm having fun." That mode is what Decagon runs on. The company Ashwin co-founded with Jesse Zhang in 2023 is now valued at $4.5 billion, has crossed 450 employees in three years, and works with some of the largest enterprises on the planet. The path there has in some ways been simple: don't theorize about where AI is going, talk to customers until the pain is unmistakable, build for that, ship, repeat. Decagon went from zero to $1 million in ARR with two co-founders and no employees. In this conversation, Ashwin walks through what that means in practice. How Decagon operationalizes a single cultural priority: speed, even when it costs coordination. How they hire 450 people without breaking the bar. How AI has reshaped the IC engineer, the AE, and the VP of EPD. And why, after a year of running 6+ days a week, the thing he and Jesse would tell their earlier selves is: go faster. Ashwin Sreenivas is the co-founder and CTO of Decagon, the AI customer concierge platform founded in 2023 that serves enterprise customers including Substack, Eventbrite, Duolingo, and Notion and is valued at $4.5 billion. Decagon Labs, the company's in-house model development effort, now powers around 90% of Decagon's model traffic. Before Decagon, Sreenivas co-founded Helia in 2019, an AI startup acquired by Scale AI a year later. He started his career as a strategist at Palantir Technologies in New York. Sreenivas holds a Bachelor's degree (2017) and Master's degree (2019) in Computer Science from Stanford University. Decagon raised $35M in 2024 and has scaled to over 450 employees.
Where to find Ashwin Sreenivas: • Decagon • X • LinkedIn
Where to find Nakul: • Audacious Ventures • X • LinkedIn
Where to find Audacious Ventures: • Website • LinkedIn
In this conversation with Ashwin Sreenivas: 00:00 Who is Ashwin Sreenivas? 02:10 How did Jesse and Ashwin decide what to work on at Decagon? 04:19 Why did they reject the top-down market-sizing approach? 13:16 What does Decagon give up to keep moving fast? 17:54 Does Decagon expect their team to be 6-days in-office? 23:33 Why didn't they hire a single employee until $1M in ARR? 27:12 How do you hire 450 people in three years without breaking the bar? 31:20 Are Decagon engineers even writing code anymore? 35:08 How does the IC engineer role change with Claude Code and Cursor? 36:32 Shipping in two days: how does EPD leadership change? 40:15 What are the two types of FDE, and which one do most AI companies actually need? 49:21 How will the human role at Decagon evolve over three years? 57:15 Why did Decagon build its own models in Decagon Labs? 1:00:50 What worries Ashwin most about Decagon today? 1:03:52 How does Ashwin manage his psyche while running this fast? 1:08:00 What hiccups has Decagon had that no one sees from the outside? 1:09:50 Quickfire: overrated advice, AI products, books, red flags 1:12:43 What would Ashwin tell his younger self about Decagon's journey?
Ashwin's sharpest lines from this conversation... On what actually matters: "If you build a company doing something that your customers care about, you can mess up everything else in a way and it doesn't really matter." On founder market fit: "If you pick the right market, the market will pull the problem and product out of the founding team." On what Decagon traded for speed: "The pace of building has changed so quickly. With AI, there isn't that much time for coordination. You have to give somewhere, and we gave for speed." On packing desks tight: "I specifically a
More from Knuckle Up with Nakul
Jake Cooper never set out to start a company. After leaving Uber in 2020, he put together a box of databases for his own side projects, kept coming back to it, and eventually posted it on Twitter asking who he should talk to about a job working on it. He got no job offers, just a few angel checks. That side project became Railway, the cloud platform now used by millions of developers, and Jake still runs it as a solo founder. Railway is run by around 40 people and is closing in on $100 million in annual revenue. The path there wasn’t a straight line. In the free-tier era, Railway was losing about $500K a month, and it switched the free tier off until owning its own bare-metal data centers made the economics work. The throughline since has been focus: say no to 90% of ideas, find the biggest problem each week, and move it forward, brick by brick. In this conversation, Jake walks through the operating system behind that leverage. Why he won’t look at how other companies solve a problem until Railway has tried its own answer. Why he thinks two co-founders is the worst number of co-founders. How a six-week onboarding built on trust, clarity, and judgment turns new hires into owners. And why his phone goes on do not disturb from Friday night to Sunday afternoon, because 996 buys 20% more cycles at best, but stillness is where the step-change ideas show up. Listen on YouTube, Spotify, and Apple Podcasts Jake Cooper is the founder and CEO of Railway, the cloud platform for deploying applications, databases, and agents, which he founded in 2020. Railway runs on its own bare-metal data centers, serves more than 2 million developers, and counts companies including MGM Resorts, Bilt, and TripAdvisor’s Cruise Critic among its customers. In January 2026, Railway raised a $100 million Series B, bringing its total funding to roughly $124 million. Before founding Railway, Cooper worked as a software engineer at Wolfram Research, Bloomberg, and Uber, where he scaled infrastructure for Jump bikes and scooters. He studied engineering at the University of Victoria in Canada.
David Paffenholz says Juicebox has not lost a single employee in two years, at a company that has grown from three people to ninety. He credits it to a formula: independence, visible impact, and real equity, what he calls the preconditions for a place where someone feels they can do their life’s work. That formula sits inside a deliberately intense culture: five days a week in the office, no exceptions, but explicitly not 996. Paffenholz co-founded the company in 2022 with Ishan Gupta, first as PeopleGPT, on a narrow bet: that the hardest part of recruiting was never the workflow, it was search, and that large language models would make search fundamentally different from what LinkedIn and Indeed had already built. That bet has taken Juicebox from $1.5 million in ARR with a three-person team to an $850 million valuation on an $80 million Series B, serving more than 5,000 customers from AI-native startups to large financial services and defense organizations, and positioning itself as the agent-native alternative to LinkedIn’s roughly $8 billion Talent Solutions business. In this conversation, David walks through why he thinks the “AI recruiter” hype mostly missed the point, how much autonomy he’s willing to give Juicebox’s own agents, why there are still zero engineering managers at a 90-person company, and what changed once he could no longer track what everyone was working on day to day. He’s candid about the calls he’s gotten wrong, including the MCP server he resisted and then had to reverse, and what he’d tell his 22-year-old-self who bet his company on a search bar. Listen on YouTube, Spotify, and Apple Podcasts David Paffenholz is the co-founder and CEO of Juicebox, the AI-native recruiting platform he built with co-founder Ishan Gupta out of Y Combinator’s Summer 2022 batch, first under the name PeopleGPT. Juicebox raised an $80 million Series B led by DST Global in 2026 at an $850 million valuation, with Sequoia Capital, Coatue, Y Combinator, and others also participating, and now serves more than 5,000 customers, from early-stage AI startups to large enterprises in financial services and defense. Before founding Juicebox at 22, Paffenholz worked at New Enterprise Associates and Moonfare and on international expansion at Snap Inc., and studied economics at Harvard University. He grew up in Germany. Juicebox has since opened an office in London and grown to roughly 90 employees without losing one in the past two years.
In 2024, OpenAI asked its own investors to avoid funding five companies it saw as competitive threats: Anthropic, Elon Musk's xAI, Ilya Sutskever's Safe Superintelligence, the search engine Perplexity, and one enterprise AI company, Glean. Arvind Jain built Glean after a decade as a distinguished engineer at Google and after co-founding the data security company Rubrik, starting it in 2019, years before most of the world had heard of generative AI. – Glean is now valued at $7.2 billion, generates more than $300 million in annual recurring revenue, and employs roughly 1,500 people, one of the largest pure-play enterprise AI companies in the world. Its bet is that enterprises don't need Glean to build its own frontier model. They need it to be the context and intelligence layer that plugs into whichever model, Claude, GPT, Gemini, or an open source one, actually gets the job done. – In this conversation, Arvind walks through why he doesn't believe AI will let companies meaningfully shrink their workforce, even as it reshapes what people do all day. How Glean's own leaders, not just its engineers, are required to build their own AI agents, no exceptions. And why, after seven years running one of the most AI-native companies in the world, the feeling of having "arrived" still hasn't shown up. – Arvind Jain is the founder and CEO of Glean, an enterprise AI platform valued at $7.2 billion that he founded in 2019 after spending more than a decade at Google as a distinguished engineer, leading teams across Search, Maps, and YouTube. Before Glean, Jain co-founded Rubrik, the publicly traded cloud data security company, where he led R&D. Glean has raised more than $765 million from investors including Sequoia Capital, Kleiner Perkins, Lightspeed Venture Partners, ICONIQ, and Wellington Management, most recently a $150 million Series F in June 2025. In 2024, OpenAI reportedly asked its own investors not to fund Glean, placing it on a list alongside Anthropic, xAI, and Safe Superintelligence. Jain holds a BTech in computer science from the Indian Institute of Technology, Delhi, and a master's in computer science from the University of Washington. – Where to find Arvind Jain: • Glean • X • LinkedIn – Where to find Nakul: • Audacious Ventures • X • LinkedIn – Where to find Audacious Ventures: • Website • LinkedIn – In this conversation with Arvind Jain: 00:00 Who is Arvind Jain? 01:56 What is Glean's edge as OpenAI, Google, and Notion pile in? 04:56 MCP vs. context graphs: why did Glean go its own way? 07:56 What structural advantage does Glean claim over the frontier labs themselves? 11:00 How does Glean stack up against AI-native platforms like Notion? 12:38 What happens to the SaaS stack by 2027 and 2028? 14:52 Is Glean an app, an agent platform, or core infrastructure? 19:22 How much of Glean's use today is questions versus real agent work? 20:52 What does a knowledge worker's life look like in three years? 24:08 Why doesn't Arvind think AI will let companies shrink their workforce? 27:32 How does Arvind self-serve strategy, talent, and customer insight with AI? 33:19 Is every department at Glean AI-native, not just engineering? 36:44 What did Arvind find flawed in the AI SDR dream? 38:19 How has AI reshaped hiring at Glean, and who thrives there now? 41:07 Are Glean's 1,500 employees secretly doing the work of 2,500? 41:55 Why does Arvind say you never feel like you've "arrived"? 45:38 What's Arvind's advice for anyone who wants his life? – Arvind's sharpest lines from this conversation: On why headcount survives AI: "Ultimately, the business success is indeed proportional to the human capital that you have inside the company." – On AI closing the skill gap: "Take a calculator. Does everyone know how to use it today equally well? I think that's what's gonna happen with AI." – On the real job of a CEO: "As a CEO, most of my job is understanding, and I think these are actually harder problems, frankly." – On AI SDRs and human judgment: "
Guillermo Rauch’s kindergarten teachers had a question for his parents: “What do you guys give this kid? He’s a freaking ball of energy.” Today Guillermo is at the gym every morning, has five kids with a sixth on the way, does Vercel’s customer support rotations himself, and measures his own keystrokes with an app he vibe coded. He is also the founder and CEO of one of the defining infrastructure companies of the AI era. – If you have built anything on the internet, you have probably touched his work. Guillermo created Socket.IO, co-created Next.js, the most popular React framework in the world, and founded Vercel, now valued at $9.3 billion with a revenue run rate of more than $500 million, powering frontends for OpenAI, Stripe, and Nike. The throughline of this episode is his answer to Paul Graham’s Founder Mode essay: founder mode doesn’t scale, so Vercel runs on what Guillermo calls Recursive Founder Mode, finding people who are founders at heart and making them the CEOs of their own products. It’s the machine that builds the machine. – In this conversation, Guillermo walks through what that looks like in practice. Why he is still involved in every hire at nearly 800 people, and why nobody at Vercel except security can stop a launch. How V, the internal agent the company runs on, replaced ticket queues and bent the headcount curve. What the new engineering meta skill is when models write the code. And the inner game: the energy budget, the lulls, and why he calls 996 rookie numbers. – Guillermo Rauch is the founder and CEO of Vercel, the AI cloud company behind Next.js, v0, the AI SDK, and the AI Gateway, valued at $9.3 billion following a $300 million Series F led by Accel and GIC in September 2025. Rauch created Socket.IO and Mongoose, two of the most widely used libraries in the JavaScript ecosystem, and co-created Next.js, the most popular React framework. Born in Lanús, Argentina, he taught himself to program, moved to San Francisco at 18, and co-founded LearnBoost and Cloudup, acquired by Automattic in 2013. He founded Vercel, originally called ZEIT, in 2015; the company now employs nearly 800 people and serves customers including OpenAI, Stripe, and Nike. – Where to find Guillermo Rauch: • Vercel • X • LinkedIn – Where to find Nakul: • Audacious Ventures • X • LinkedIn – Where to find Audacious Ventures: • Website • LinkedIn – In this conversation with Guillermo Rauch: 00:00 Who is Guillermo Rauch? 02:01 What is Recursive Founder Mode? 07:28 Why did Vercel open source its playbook with skills.sh? 10:14 What is a “work prompt” interview? 14:33 Why is Guillermo still involved in every hire at nearly 800 people? 18:17 What keeps founders at Vercel when seed money is everywhere? 23:41 Do urgency and taste pull against each other? 26:43 What is the new engineering meta skill? 32:21 How does a 17-year-old show they’re exceptional today? 35:47 Why does Vercel route the whole company through one agent? 38:47 Which software survives the agent era? 42:11 How has AI changed Guillermo’s job as CEO? 51:39 Does Vercel even need executives anymore? 54:40 If Guillermo started Vercel today, what would he build first? 57:45 What’s the story behind v0? 1:03:48 Are there still moats when anyone can build fast? 1:11:24 How does a legendary coder learn the inner game of being a CEO? 1:19:21 Where does Guillermo’s energy actually come from? 1:23:07 Quickfire: overrated advice, Chrome, voice AI, Demo Fridays 1:28:38 What does the journey actually require? – Guillermo’s sharpest lines from this conversation: On scaling founder mode: “The founder CEO can only go so far. You kind of want to build the machine that builds the machine.” – On agents being the first port of call: “If I DM you, it probably meant that my agent couldn’t figure it out.” – On AI and taste: “I think people sometimes create this false dichotomy between AI and taste. You know what’s tasteless is grabbing the model and having it output as it is.” – On why AI doesn’t write
Will Bryk was working as one of the first engineers at Cresta, writing a book about the history of civilization on the side, when the research started to feel absurd. “Google is great for surface-level investigations,” he says. “But it is not built to find every article on what people ate in medieval times across different regions of the world.” The frustration with accessibility of information went back to high school. He recalls thinking how ridiculous it is that we can split the atom and get to the moon, but still find it hard to understand what is happening at the border. To him, that’s an error in humanity. – Then GPT-3 arrived, and with it, the possibility of a different kind of search engine. Will and his college roommate Jeff Wang started Exa in 2021 with the lofty goal of building one better than Google. Five years on, Exa has raised $250 million at a $2.2 billion valuation led by a16z, its crawlers track over 500 billion URLs, and it powers search for Cursor, Cognition, HubSpot and more than 5,000 companies. – In this conversation, Will walks through how he runs the company making that bet. Why he gets genuinely upset when someone tries to introduce a process. What a non-playable character is and why Exa screens them out. Why the “bitter lesson” works on compute but not on people. And why a founder whose role models are Spider-Man and Ethan Hunt from Mission Impossible says he has not had a single thought about burnout in the past couple of years. – Listen on: • Spotify: https://open.spotify.com/show/5KorHDryscDzLwPkWEgAH1 • Apple Podcasts: https://podcasts.apple.com/us/podcast/knuckle-up-with-nakul/id1893213920 – Will Bryk is the co-founder and CEO of Exa, which builds web search infrastructure for AI agents. Exa’s search API powers Cursor, Cognition, HubSpot, OpenRouter and Monday.com, and the company says it serves more than 400,000 developers. Bryk co-founded Exa with Jeff Wang out of Y Combinator’s Summer 2021 batch, and the company raised its $250 million round from Andreessen Horowitz in May 2026. Before Exa he was one of the first engineers at Cresta, where he built real-time AI products. He studied computer science and physics at Harvard University, where he researched human-AI interaction and led the robotics club. – Where to find Will Bryk: • Exa: https://exa.ai • X: https://x.com/WilliamBryk • LinkedIn: https://www.linkedin.com/in/william-bryk – Where to find Nakul: • Audacious Ventures: https://www.audacious.co/ • X: https://x.com/nakul • LinkedIn: https://www.linkedin.com/in/nakulmandan/ – Where to find Audacious Ventures: • Website: https://www.audacious.co/ • LinkedIn: https://www.linkedin.com/company/audaciousventures/ – In this conversation with Will Bryk: 00:00 Who is Will Bryk? 01:49 Why do agents need a different search engine than humans? 02:53 How can an independent search company survive the big labs? 07:33 What does the internet look like when agents do the searching? 10:19 How did writing a book on the history of civilization lead to Exa? 15:39 Why does Exa hire first-principles thinkers, not rebels? 18:05 What is a “non-playable character,” and why does Exa screen for it? 19:49 How does Exa win engineers against the labs’ packages? 21:30 Why does Will kill process “before it lays eggs”? 26:27 Does the “bitter lesson” apply to humans? 29:52 What breaks when a company outgrows a single room? 34:47 Are there 100x and 1000x engineers now, not just 10x? 37:32 Why should nothing at Exa ever take a month to ship? 45:30 Where does Will’s drive actually come from? 48:28 Why are Will’s role models fictional, not real? 51:05 What does “We’ll figure it out” mean at Exa? 54:05 Why do Will’s best thoughts happen at 2:00 AM? 57:47 Quickfire: red flags, young founder myths, and Will’s mission impossible – Will’s sharpest lines from this conversation: On why information is the mission: “That to me is just an error in humanity. Why can’t they figure out how to share information in a normal way? Why is everyt