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42:44ENThey Paid $7.7 Billion for a Broker — and Intend to Do One Deal a YearPresenta: Sarah Guo, Elad GilSequence Holdings co-founder Michael Lee tells No Priors why owning a market leader, not selling it software, is how AI actually remakes an incumbent.
1:19:04ENDaniel Dines on AI Agents, Enterprise Work and the Limits of AutomationInvitado: Daniel Dines · Presenta: Harry StebbingsThe UiPath co-founder argues that companies need a map of work and reliable automation alongside AI, while Harry Stebbings challenges his assumptions about how fast jobs will change.
1:06:47ENEighty percent of what agents do should still be ordinary codePresenta: Nathan LabenzZapier CEO Wade Foster tells Nathan Labenz that models top out at 40% on real automation tasks, users will not leave their daily driver, and the winning move is headless tools delivered through MCP.
34:30ENNetic's Agents Answer the Phone When the Heat BreaksPresenta: Sarah Guo, Elad GilFounder Melisa Tokmak tells Elad Gil how a two-year-old platform became the AI operations layer for HVAC, roofing, pet care, and other essential services.
2:23:43ENHe Bought an Android, Two SIMs, and Left Claude Watching His InboxPresenta: Nathan LabenzNathan Labenz asked a dozen friends how to visit China and got two irreconcilable answers.
1:29:35ENFred Turner on Curative’s Pandemic Pivot, Health Insurance and AI AutomationInvitado: Fred Turner · Presenta: Harry StebbingsCurative’s CEO recounts building a COVID testing operation, moving into health insurance and using AI agents across the company’s workflows.
1:20:59ENFlexport CEO Ryan Petersen on Logistics, AI and FundraisingInvitado: Ryan Petersen · Presenta: Harry StebbingsPetersen discusses the economics of global freight, automating operational work, venture financing and the lessons he has taken from building Flexport.
38:24ENServal's Bet: Keep ServiceNow's Primitives, Take Humans Out of the BuildJake Stauch tells Sequoia's Pat Grady how a two-year-old ITSM startup uses codegen agents, boring enterprise controls, and "fewer, better" hiring to rebuild employee support for the AI era.
2:12:51ENSteve Newman’s fifteen-app stack exists so he only has to look at one screenPresenta: Nathan LabenzThe Writely founder walks Nathan Labenz through a vibe-coded attention firewall, a conservative security stance, and why astonishing models still leave him far from AGI.
57:28ENCopying One ServiceNow App with a Language Model Costs Ten Times as MuchPresenta: Sarah Guo, Elad GilBill McDermott tells Sarah Guo why the SaaS apocalypse fails a cost test, why models still cannot close a case, and how agents are already doing most of ServiceNow’s customer-service work.
29:26ENChatGPT Almost Became a Meeting Bot. Its Co-Creator Is Now Rearranging AtomsPresenta: Sarah Guo, Elad GilLiam Fedus tells No Priors how Periodic Labs is connecting language models to experiments so materials science can run in a closed loop.
51:56ENInsurance Spends $70 Billion on BPOs. Pace Wants 80% Gross Margins InsteadJamie Cuffe tells Sequoia's Training Data how Pace is turning insurance back-office work into agentic process outsourcing—and why every one of its pilots has reached production.
59:43ENGoose is writing its own pull requests: how Block is trying to save a quarter of the weekCTO Dhanji Prasanna tells Sequoia how an open-source agent, a functional reorg, and a weekly hours-saved metric are turning Block into an AI-first company.
35:45ENSix Years of Revenue, Then Four Times That in Eight Monthsn8n CEO Jan Oberhauser tells Sequoia how two bets — becoming an AI-agent builder, then deleting the leads metric — turned a workflow tool into a default orchestration layer.
1:27:01ENThe $16 Trillion Services Market Is Being Bought, Not Sold ToPresenta: Nathan LabenzMarc Bhargava of General Catalyst explains how AI-enabled rollups turn low-margin service firms into compounding, software-like businesses.
1:28:48ENDoctors code at 45%. The model beat them by 12 points — then 4,000 physicians had to try it once.Presenta: Nathan LabenzAmbience Healthcare and Cleveland Clinic walk through the AI scribe that cut pajama time, climbed ICD-10 with reinforcement fine-tuning, and won 75% voluntary use.
3:08:35ENo3 isn't AGI. Zvi Mowshowitz still put p(doom) at 70 percentPresenta: Nathan LabenzOn his ninth visit to The Cognitive Revolution, Zvi Mowshowitz argues that OpenAI's o3 is a tool-use leap rather than AGI, then explains why he raised the probability of AI catastrophe anyway.
1:11:05ENThe Man Who Took HubSpot CRM to $40 Million Says the Data Model Has to Be Thrown OutDay.ai founder Christopher O’Donnell tells Sequoia’s Pat Grady why classic CRM is compressed pixel art, why full self-driving scared his users, and why every line of code has to make every other line more valuable.
43:04EN750 Million Excel Users, 30 Million Engineers: Wordware's Bet on Word ArtisansFilip Kozera tells Sequoia why English is the assembly language of LLMs, and why the people who win will be the ones who can encode taste into structured prompts.
54:47ENNinety Thousand Games a Day: Roblox's Bet That AI Should Wash the DishesStef Corazza, head of generative AI at Roblox, tells Sequoia how a free Studio assistant, a community data bargain, and a 3D foundation model are meant to teach AI game development.
38:48ENWho Wants to Chat With an Expense Report?Ramp CEO Eric Glyman tells Sequoia why the chatbot gold rush missed the point, and why the better analogy for company finance is a Waymo: self-driving money.
51:38ENClay Wants to Be a Guitar, Not a Microwave, for Go-to-Market TeamsKareem Amin tells Sequoia’s Alfred Lin why Clay is building a system of action for growth rather than an AI that replaces SDRs.
55:05EN400,000 Customers, 100 Million AI Tasks: Zapier’s CEO on Making Computers Do More WorkPresenta: Nathan LabenzWade Foster tells Nathan Labenz how a no-code automation company absorbed LLMs, cloned its CEO with a prompt, and is trying to turn a DIY toolkit into packaged solutions.
2:03:55ENThe More You Constrain an Agent, the More You Can Trust ItPresenta: Nathan LabenzAgent.ai engineering lead Andrei Oprisan tells Nathan Labenz why narrow, highly prescribed workflows beat open-ended autonomy — and how a 12-person team shipped a free agent network past 40,000 users in a few months.
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