Founders in Arms

This week, we're bringing back one of our most loved episodes on Founders in Arms. Ryan Gariépy is the co-founder and former CTO of Clearpath Robotics and Otto Motors, acquired by Rockwell Automation for $600M+ in 2023. He bootstrapped the company for five years with only $300K in funding, reached profitability in 18 months, and spent 14 years building mobile robotics platforms that became the industry standard for research and industrial automation. What you'll learn: Why robotics is a systems discipline where progress stacks rather than explodes How to bootstrap a hardware company to $10M revenue before raising venture capital Why robotics follows 20-50% sustained growth for decades vs. software's boom-bust cycles The "promise problem" with humanoid robots and why form factor shapes user expectations How manufacturing in Canada (not China) became a strategic advantage for Clearpath Why founders overestimate 2-year progress but underestimate 10-year impact in robotics The real economics of humanoid robots: $20K cost becomes $80K landed price How robotics investment differs from software: less competitive, more defensible Why experience compounds in hardware but expires in software careers Investment criteria for robotics: engineering risk vs. technical risk and go-to-market strategy In this episode, we cover: (00:00) Introduction and live event announcement (03:29) Ryan's background: Clearpath Robotics and Otto Motors (04:06) Building two brands under one company (06:29) The 14-year journey: challenges and non-linear growth (07:11) Bootstrapping robotics when "nobody thought you could make money" (08:17) Reaching profitability in 18 months with research customers (10:28) Building robotics platforms for MIT, universities, and research labs (11:03) Manufacturing in Canada vs. outsourcing to Asia (15:05) Reconnecting after 20 years: the Waterloo entrepreneurship connection (16:17) Working at Kiva Systems (now Amazon Robotics) (18:10) Why robotics is more exciting now than ever in history (19:21) Robotics as systems discipline: no single breakthrough technology (21:22) The overhype cycle and realistic expectations (22:14) Software explodes then crashes; robotics compounds for decades (23:36) Why hardware is harder but more mission-driven (25:27) The talent pool advantage: people irrationally love hardware (27:30) Physical AI and real-world impact beyond software optimization (28:07) Humanoid robots: incredible tech, miscalibrated expectations (32:41) The "promise problem": form factors make promises to users (34:35) Consumer robotics examples: Matic cleaning robot (35:59) Asia leading in restaurant and airport robotics deployment (38:37) Training challenges and precursor technologies needed (39:20) China's role in robotics and humanoid development (41:08) Venture capital structures forcing "ridiculous things" in robotics (42:36) Robotics for entertainment vs. utility as consumer use case (43:52) Imad's robotics investments: Embark, Gecko Robotics, vertical AVs (45:23) Why robotics is less competitive than software (47:21) Operational design domain and technology risk assessment (48:19) The AV journey: Waymo, Zoox, and the importance of experience (49:39) Experience compounds in hardware, expires in software (50:31) Rapid fire: biggest mistake, following gut over charisma (51:47) Founder inspiration: Rodney Brooks (52:20) Uncomfortable feedback at Honda co-op job (53:17) Investment criteria: engineering risk, go-to-market, team understanding

Marco Zapacosta is the co-founder and CEO of Thumbtack, the home services marketplace connecting homeowners with local pros for everything from plumbing to renovation. Started three weeks before Lehman Brothers collapsed in 2008, Thumbtack has grown to over $500M in annual run rate across 17 years of building.What you'll learn:Why Marco believes Thumbtack is still pre-product market fit at $500M in revenueHow AI is shifting Thumbtack from a search engine to a matchmakerWhy word of mouth is still the biggest competitor to every home services marketplace — and how AI finally evens the scoreWhy convenience doesn't win when someone's spending $1,000 and entering your homeMarco's take on practitioners vs. projectors — and why he doesn't trust most AI predictionsWhy AI agents won't disintermediate high-trust marketplacesHow Thumbtack's operating model evolved from Google to Facebook to their own matrix structureWhat's kept Marco going for 17 years — and why he scores zero on neuroticismWhy Marco wants to stay private a little longer before an inevitable IPOWhy AI applied to robotics is overhyped and synthetic biology is massively underratedIn this episode, we cover:(00:00) AI as substitute vs. complement — the flaw in our collective thinking(01:00) Introduction to Marco Zapacosta(02:12) Practitioners vs. projectors on AI(04:14) Real anxiety about AI job loss — engineers at birthday parties(07:21) Why Marco doesn't trust Block's layoff messaging(09:46) How AI is a massive accelerant for Thumbtack(10:02) Why home services is still pre-product market fit at $500M(11:02) Word of mouth is Thumbtack's biggest competitor(12:40) Will AI agents disintermediate marketplaces?(15:17) Why choice still matters in high-trust purchases(17:34) Why humans still want to read reviews themselves(19:15) Thumbtack's origin story — starting 3 weeks before Lehman collapsed(23:16) What's kept Marco going for 17 years(24:42) Entrepreneur parents and raising entrepreneurial kids(30:20) How Marco runs the company — the matrix model explained(35:25) Four co-founders: how responsibilities divided over time(37:02) Is Thumbtack going public?(39:33) The real downsides of being a public company(45:21) Rapid fire: who inspires Marco, what's overhyped, what's underhyped(47:12) The hardest part of leadership is self-awareness, not skills(49:02) Why struggling early builds staying power

Noah Smith is a writer and Substack blogger behind Noahpinion, known for his contrarian, data-grounded takes on economics, technology, and geopolitics.What you'll learn:Why the viral Citrini "2028 Global Intelligence Crisis" post moved markets — and whether it should haveThe psychology behind why "AI causes 2008" scared Wall Street more than killer robotsWhy Noah thinks an AI-driven financial crisis is possible but unlikelyHow a productivity boom could paradoxically trigger a mild recession through "sticky prices"Why AI-enabled bioterrorism — not economic disruption — is Noah's biggest fearWhat Block's 4,000-person layoff and Mercury's hiring shifts reveal about AI's real impact on jobsWhy software job losses in 2023-24 may have been driven by uncertainty, not AI capabilityNoah's take on deflation, GDP growth, and where inflation goes from hereWhy intellectual humility has been Noah's biggest edge as a forecasterThe "dinosaur and the meteor" theory — why we're worrying about the economy while a much bigger threat flies overheadIn this episode, we cover:(00:00) The meteor meme — AI's real threat vs. the economy(01:07) Introduction to Noah Smith(02:14) What the Citrini post actually argued(04:30) Why markets missed Covid — and what that tells us about AI(06:17) Why Citrini moved markets: the power of pattern matching to 2008(07:51) Breaking down Citrini's financial crisis domino theory(08:38) Noah's verdict: possible but unlikely(11:04) Block lays off 4,000 — how does AI-driven unemployment play out macro?(17:42) How a productivity boom could cause a recession: sticky prices explained(19:46) Noah's real AI fear: vibe-coded bioweapons(24:55) Has bioterror surpassed China-Taiwan as Noah's top worry?(25:10) The economy today: inflation, deflation, and GDP(28:44) What Mercury's hiring strategy reveals about AI's effect on headcount(31:32) Why software job losses in 2023-24 may have been forward-looking uncertainty(34:38) The threat to blue collar jobs — are truck drivers next?(35:52) Why intellectual humility is Noah's competitive edge(39:26) The meteor meme closing: we created zombie gods for a 2.7% productivity boost

We're bringing back one of our most loved episode on Founders in Arms. Parag Agrawal is the co-founder and CEO of Parallel, building infrastructure for the agentic web. Previously CEO of Twitter, Parag now leads a company architecting how AI agents will interact with the open web at orders of magnitude beyond current human scale. Two years after founding in stealth mode, Parallel recently announced a $100M Series B co-led by Kleiner Perkins and Index Ventures.What you'll learn:Why everything built for human web consumption will become irrelevant when agents become the primary usersHow Parallel's APIs enable agents to search, fetch, and monitor the web with unprecedented scale and speedThe evolution from simple tool calls to autonomous sub-agents with real decision-making capabilityWhy the web must transition from "pull" (searching on demand) to "push" (alerting when conditions are met)The new business models needed to compensate content creators in an agent-driven webParag's counterintuitive approach to fundraising: why VC rejections don't sting but customer rejections doThe rational game VCs play that founders misinterpret as genuine enthusiasmWhy Parag believes we're not in an AI bubble—but an overreaction is coming (and it'll be faster than dot-com)How Parallel built quietly for a year before product-market fit arrived with the agent explosionThe operational philosophy of extreme in-person collaboration that shaped Parallel's early cultureIn this episode, we cover:(00:00) Introduction and Parallel's mission (01:02) What Parallel's APIs enable for AI agents (02:43) Practical examples: coding agents, sales automation, research (04:57) The conviction bet on agents before the market existed (10:54) New business models for content in the agentic web (20:22) The $100M Series B fundraise and going public (23:03) Why Parallel built in stealth with carefully chosen early customers (24:55) Current scale and product offerings (30:42) The evolution from tools to sub-agents to push-based web (33:13) Are we in an AI bubble? Parag's nuanced perspective (36:34) The mental models behind fundraising vs customer rejections (38:37) Why VC enthusiasm is rational strategy, not signal (45:37) Biggest career mistake: delaying Twitter's algorithmic timeline (48:28) The compounding cost of six-month delays (50:09) Finding inspiration in "re-founders" like Satya Nadella (51:54) The most rewarding part: watching customers do unexpected things (52:43) In-person culture and the transition to remote-friendly

Vishwas Prabhakara is the co-founder and CEO of Honey Homes, a subscription home maintenance service that's reimagining how Americans care for their homes. After spending four years at Yelp running the restaurant business, Vishwas saw firsthand why marketplaces fail for skilled home services—and built a contrarian solution. Now operating across San Francisco, LA, Chicago, Dallas, and Austin with 3,000+ members, Honey Homes creates quality jobs for skilled workers while delivering consistent, reliable home maintenance to homeowners.What you'll learn:Why the marketplace model fundamentally fails for skilled labor and home servicesThe counterintuitive insight behind every successful consumer business (the Airbnb lesson)How Vishwas discovered workers were shocked that "nobody's yelled at me yet" after joining Honey HomesWhy solving both sides of the market—customer experience AND worker quality of life—is essentialThe role of AI in leveling up service workers and automating operations without replacing humansWhy early compromises on hiring and standards compound into major problems laterThe distribution challenge: getting consumers to prioritize chronic home maintenance needsHow altruism, not just incentives, drives consumer referrals and growthWhy companies like Yelp, Peloton, and Lyft deserve more respect for building culturally relevant businessesThe mental model shift required to sell subscription home services vs. one-time fixesIn this episode, we cover:(00:00) Introduction and the respect successful companies deserve (01:12) YC batch memories and feeling "late" to tech trends (03:05) The genesis of Honey Homes and why Immad and Raj invested (04:50) Growing up with a handy dad and discovering the home services gap (06:30) The counterintuitive consumer insight behind Honey Homes (07:03) "Nobody's yelled at me yet"—the worker experience problem (08:11) Why marketplaces don't work for skilled home services (09:48) Hiring only 1% of handyman applicants (14:07) Building trust through consistent quality and W2 employment (19:31) How altruism drives consumer referrals, not just incentives (21:51) Getting AI-pilled at Vinod Khosla's CEO retreat (23:01) Using AI to level up workers and automate operations (27:54) Overcoming the mental model barrier for subscription home services (30:07) The vision compromise lesson: don't settle on quality early (31:44) The critical importance of distribution for consumer businesses (32:26) Why partnerships aren't the answer (yet) for Honey Homes (38:41) Defending Yelp, Peloton, and Lyft against Silicon Valley discourse (42:18) Unit economics challenges in services businesses (47:10) Role models: Jeremy Stoppelman and Ramit Sethi (48:08) Hope that divisiveness is a passing trend (49:35) The daily challenge of building before the world sees it (51:04) Getting feedback about being "unpredictable" and staying in your head (52:33) Bringing people along for the journey in your mind

What does it take to build a company in a category where everyone says the idea is dead? In this special live recording from Mercury's San Francisco office, Immad Akhund and Raj Suri sit down with Max Mullen, co-founder and former Chief Product Officer at Instacart, for an honest conversation about the founder journey. Max shares how Instacart started in 2012 when there was no gig economy, no Uber X, and investors repeatedly told them grocery delivery was a dead idea after Webvan's failure. The conversation explores the controversial early days of building Instacart, why Max believes founder pain tolerance is the biggest moat, and the critical importance of market timing even when you're executing well. Max opens up about the challenges of being a technical co-founder without deep technical skills, navigating co-founder dynamics, and the reality that many startup outcomes are heavily influenced by timing and luck. The discussion shifts to AI's transformative potential, with Max offering a compelling framework: software engineers are experiencing "the tip of the spear" of AI capabilities today, and this same 10x productivity leap will soon apply to lawyers, doctors, accountants, and every other profession. He explores what AI-native companies will look like and why the next wave of startups will be built around professionals orchestrating fleets of agents. This episode offers essential insights for founders building in challenging markets, navigating co-founder relationships, timing market opportunities, and understanding where AI is creating the biggest opportunities for new companies.

SaaS companies are down dramatically—Figma is 77% off its peak. In this candid conversation, Immad Akhund (CEO of Mercury) and Raj Suri (co-founder of Lima and Tribe) unpack what's really happening in tech as we head into 2026.They explore why the SaaS business model is under attack (hint: it's not just AI building software faster), the shift from per-seat pricing to API-driven usage, and why enterprises actually buy SaaS products—spoiler, it's not about the software. The conversation reveals how startups can now stay lean with fewer employees for much longer, with companies like OpenAI reaching $500B valuations with just 4,000 people.Immad and Raj also dive into their personal experiences with AI agents, discussing what actually works versus the hype, why they're skeptical of consumer AI hardware, and how AI is changing daily productivity for founders. They debate Google's quiet win with the Apple-Gemini deal, why Siri is dead, and whether one AI model controlling all handsets should concern us.The episode wraps with practical advice on what makes a compelling VC pitch in 2026, why crazy promises still work (even when timelines are wildly optimistic), and how to think about your startup's valuation as a call option rather than current worth. From Elon's humanoid robot bet to the new growth expectations (0 to $5M in 12 months), this conversation offers an honest founder-to-founder take on navigating the current landscape.Key Topics:Why SaaS companies are struggling and what survivesThe real reason enterprises buy software (risk offloading, not features)AI agents in practice: what works, what doesn'tGoogle's strategic win with Apple's Gemini integrationHow to pitch VCs when expectations are 5x higher than beforeWhy crazy promises and long timelines still attract capitalThe shift to leaner startups and API-first business models

Mehul Nariyawala is the co-founder and President of Matic Robotics, a home robotics company building what he calls “robotics 2.0” — intelligent, vision-first robots designed to actually work in real homes. After early careers at Nest and a prior acquisition by Google, Mehul and his team spent seven years building Matic, challenging the assumptions behind robot vacuums, consumer hardware, and how robotics companies should scale.In this conversation, Mehul breaks down why robotics is far harder than software, why most home robots quietly fail, and how Matic approached everything differently — from vision-only robotics and in-house manufacturing to avoiding subscriptions, ads, and premature market creation.What you’ll learn:Why robotics is “100× harder than software” — and where most teams underestimate the workThe difference between automation and true intelligence in home robotsWhy negative-NPS categories can hide massive opportunitiesHow Matic beat entrenched incumbents like Roomba by fixing fundamentals, not adding featuresWhy vision-only robotics was a risky but necessary betThe real reason humanoid robots are still far from consumer-readyLessons from Nest on why some hardware categories stay defensible for decadesWhy creating a new market can be fatal for hardware startupsHow Matic built robots in-house in California instead of outsourcing manufacturingThe tradeoffs between subscriptions, ownership, and consumer trustWhy great hardware products must earn word-of-mouth before growthIn this episode, we cover:(00:00) Introduction to Mehul Naryawala and Matic Robotics(01:10) Why robotics is dramatically harder than software(03:00) The failure modes of early robot vacuums(05:10) Identifying opportunity in negative-NPS markets(07:45) Automation vs. intelligence in consumer robotics(10:15) Why vision-only robotics was a foundational bet(14:00) Lessons from Nest on defensible hardware categories(17:30) Why Matic avoided creating a new market(20:45) In-house manufacturing and vertical integration(24:30) Scaling hardware without inventory risk(28:10) The long road from demo to product(32:00) Why humanoid robots are still overhyped(36:20) Word-of-mouth, product-led growth, and brand trust(40:15) Subscription fatigue and consumer psychology(44:30) The future of home robotics and where Matic goes next

Jack Zhang is the co-founder and CEO of Airwallex, a global payments and financial platform valued at $5.5 billion. Founded in Melbourne, Airwallex processes billions in cross-border transactions and serves businesses expanding internationally. Jack shares his journey from starting the company to competing with giants like Stripe, navigating the complexities of global payments infrastructure, and building across multiple regulated markets.What you'll learn:Why cross-border payments remain broken despite decades of fintech innovationHow Airwallex competes against Stripe and other established payment platformsThe challenge of building financial infrastructure across multiple countries and regulationsJack's perspective on fair competition versus FUD (fear, uncertainty, doubt) tactics in businessWhy Airwallex is deploying $1 billion in the US market over the next three yearsThe reality of being a foreign founder building in America during geopolitical tensionsHow payment infrastructure for global businesses differs from consumer fintechThe trade-offs between growth velocity and sustainable business buildingJack's philosophy on money, success, and what matters after achieving wealth at 30Why he chose to stay in Melbourne instead of relocating to San FranciscoIn this episode, we cover:(00:00) Introduction to Jack Zhang and Airwallex(02:34) Early days of Airwallex and the founding story(05:12) The problem with cross-border payments(08:45) Competing with Stripe and other payment platforms(12:18) Building in regulated markets and compliance challenges(16:23) FUD (fear, uncertainty, doubt) tactics in business competition(19:13) Raj's experience with FUD at Lyft vs Uber(22:47) Navigating geopolitical tensions as a Chinese-Australian founder(25:36) The $1 billion US market investment commitment(27:41) Product philosophy and fair competition(31:15) Going upmarket vs staying with SMBs(35:22) Life choices: Melbourne vs San Francisco(37:49) Perspective on wealth - "not about the money"(42:18) The future of payments infrastructure(45:30) Advice for founders building in competitive markets

Ryan Gariepy is the co-founder and former CTO of Clearpath Robotics and Otto Motors, acquired by Rockwell Automation for $600M+ in 2023. He bootstrapped the company for five years with only $300K in funding, reached profitability in 18 months, and spent 14 years building mobile robotics platforms that became the industry standard for research and industrial automation.(If you’re looking for inspiration and lessons from other founders, Founders in Arms is hosting a founders roundtable with Rajat Suri, Immad Akhund, and Max Mullen next Wed Jan 14th at Mercury HQ. Discussing war stories and sharing lessons with a group of founders, as part of Founders-in-Arms podcast. Will be food and drinks. Capacity strictly limited at 50 so apply early if you’re interested: https://luma.com/dk97inyk )What you'll learn:Why robotics is a systems discipline where progress stacks rather than explodesHow to bootstrap a hardware company to $10M revenue before raising venture capitalWhy robotics follows 20-50% sustained growth for decades vs. software's boom-bust cyclesThe "promise problem" with humanoid robots and why form factor shapes user expectationsHow manufacturing in Canada (not China) became a strategic advantage for ClearpathWhy founders overestimate 2-year progress but underestimate 10-year impact in roboticsThe real economics of humanoid robots: $20K cost becomes $80K landed priceHow robotics investment differs from software: less competitive, more defensibleWhy experience compounds in hardware but expires in software careersInvestment criteria for robotics: engineering risk vs. technical risk and go-to-market strategyIn this episode, we cover:(00:00) Introduction and live event announcement(03:29) Ryan's background: Clearpath Robotics and Otto Motors(04:06) Building two brands under one company(06:29) The 14-year journey: challenges and non-linear growth(07:11) Bootstrapping robotics when "nobody thought you could make money"(08:17) Reaching profitability in 18 months with research customers(10:28) Building robotics platforms for MIT, universities, and research labs(11:03) Manufacturing in Canada vs. outsourcing to Asia(15:05) Reconnecting after 20 years: the Waterloo entrepreneurship connection(16:17) Working at Kiva Systems (now Amazon Robotics)(18:10) Why robotics is more exciting now than ever in history(19:21) Robotics as systems discipline: no single breakthrough technology(21:22) The overhype cycle and realistic expectations(22:14) Software explodes then crashes; robotics compounds for decades(23:36) Why hardware is harder but more mission-driven(25:27) The talent pool advantage: people irrationally love hardware(27:30) Physical AI and real-world impact beyond software optimization(28:07) Humanoid robots: incredible tech, miscalibrated expectations(32:41) The "promise problem": form factors make promises to users(34:35) Consumer robotics examples: Matic cleaning robot(35:59) Asia leading in restaurant and airport robotics deployment(38:37) Training challenges and precursor technologies needed(39:20) China's role in robotics and humanoid development(41:08) Venture capital structures forcing "ridiculous things" in robotics(42:36) Robotics for entertainment vs. utility as consumer use case(43:52) Imad's robotics investments: Embark, Gecko Robotics, vertical AVs(45:23) Why robotics is less competitive than software(47:21) Operational design domain and technology risk assessment(48:19) The AV journey: Waymo, Zoox, and the importance of experience(49:39) Experience compounds in hardware, expires in software(50:31) Rapid fire: biggest mistake, following gut over charisma(51:47) Founder inspiration: Rodney Brooks(52:20) Uncomfortable feedback at Honda co-op job(53:17) Investment criteria: engineering risk, go-to-market, team understanding

Emmett Shear is the founder and CEO of Softmax, an alignment research company, and previously co-founded and led Twitch as CEO. He was also a Y Combinator partner and briefly served as interim CEO of OpenAI.What you'll learn:Why AI alignment and AGI are fundamentally the same problemHow theory of mind is the critical missing piece in current AI systemsWhy continuous learning requires self-modeling capabilitiesThe dangerous truth: alignment is a capacity for both great good and great evilWhy "aligned AI" really means "aligned to me"—and why that's concerningHow societies of smaller AIs will outcompete singleton superintelligencesWhy AI needs to be integrated with humans, not segregated into AI-only societiesThe Twitch lesson: people don't want easy, they want goodWhy 99% of AI startups are building labor-saving tools instead of value-creating productsHow parenting and AI development mirror each other in surprising waysWhy current AI labs are confused about continuous learningConway's Law applied to AI: you ship your org chartThe problem with mode collapse in self-learning systemsWhy emotions are training signals, not irrational noiseEmmett's biggest mistake at Twitch: chasing new products instead of perfecting the coreIn this episode, we cover:(00:00) The dangerous truth about AI alignment(01:13) Introduction to Softmax and organic alignment(02:05) What alignment actually means (and why most people are confused)(03:33) The output: training environments for theory of mind(05:01) Continuous learning and why it's so hard(06:25) Multiplayer reasoning training in open-ended environments(07:14) Aligned to what? The critical question everyone ignores(08:40) Why alignment is always relative to the aligning being(11:07) Cooperation vs. competition: training for the real world(12:56) Is AGI an urgent problem or do we have time?(13:15) AGI and alignment are the same problem(15:25) Alignment capacity enables both good and evil(17:13) The singleton problem and why societies of AIs make sense(20:41) Building alignment between AIs and humans(22:09) Why Elon's "biggest cluster" strategy might be wrong(23:06) AI must be aligned to individual humans, not humanity(25:03) What does the atomic unit of AI look like?(28:02) Adding a new kind of person to society(29:06) Everything will be alive: from spreadsheets to cars(30:00) From Twitch retirement to Softmax founding(31:26) Research vs. product engineering at early-stage startups(32:41) Raising money for AI research in the current era(34:30) Why Softmax will ship products(34:50) Ilya's closed-loop research vs. open-loop learning(36:36) How you do anything is how you do everything(37:28) The continuous learning problem explained simply(38:29) Mode collapse: why AIs become stereotypes of themselves(39:33) The reward problem and why humans need emotions(40:48) Why LLMs are trained to avoid emotions(41:52) Watching children learn while building learning AI(43:04) Advice for first-time AI founders(45:08) Treat AI as clay to be molded, not a genie granting wishes(45:50) The Twitch lesson: people want good things, not easy things(47:22) Why 99% of AI companies are building the wrong thing(48:16) Rapid fire: biggest career mistake at Twitch(50:15) Which founders inspire Emmett most(50:56) The passing fad: AI slop generators

Immad Akhund and Raj Suri reunite for a one-on-one conversation covering the biggest tech shifts of 2025, from Mercury's public launch of Personal Banking to the quieting of AGI doom discussions. This wide-ranging episode explores why self-driving cars may matter more than AGI, how vibe coding is changing software development, and the strategic decisions founders make when everyone else disagrees.What you'll learn:Why Immad launched Mercury Personal despite investor and team skepticism—and the founder lesson about following convictionHow Mercury Personal brings business-grade financial controls to personal banking (collaboration features, automatic categorization, 3.5% savings rates)The existential threat facing OpenAI and Anthropic as AI models commoditize and Google leverages distribution advantagesRaj's vibe coding experiment: Building a full-stack app with Postgres backend using just prompts (and why Replit won)Why Tribe is rejecting the $30/user ad model to build a premium, ad-free group chat platformThe retention metrics showing Tribe's product-market fit (20-40% six-month retention with minimal marketing)How AI hype shifted from AGI doom conversations to practical commercial applications in 2025Why self-driving technology (Waymo, Tesla FSD) represents a more immediate transformation than AGIThe best and worst of 2025: renewed tech energy vs. immigration scapegoating and Doge's failure to deliver government efficiencyWhy supply constraints (chips, power) signal AI demand is real, not a bubbleIn this episode, we cover:(00:00) AGI conversations cooling down in 2025(01:50) Mercury Personal launch after year-long waitlist(02:42) Business-grade controls for personal banking(04:30) 3.5% savings rates and Treasury/Invest products(06:15) Following founder conviction despite opposition(07:33) Balancing product shipping with polish(08:26) OpenAI's Code Red and focus strategy(09:23) Google's distribution advantage vs. OpenAI(10:33) The API commoditization threat to Anthropic(12:34) Why ad economics dominate the internet(14:58) Facebook's $30/user vs. subscription models(17:22) Tribe's progress: retention, AI features, monetization plans(21:42) Vibe coding experiment: Replit vs. Lovable vs. Wix(26:31) Why Replit might own the vibe coding market(28:05) Enterprise use cases for AI-generated apps(33:26) 2025's best: renewed tech energy and deregulation(34:51) 2025's worst: immigration scapegoating and Doge's failure(40:48) Self-driving breakthrough: Waymo and Tesla FSD(42:31) Why AGI talk has quieted down(43:43) Supply constraints proving AI demand is real

Noah Glass is the founder and CEO of Olo, an enterprise platform for mobile and online ordering that powers digital commerce for 800+ restaurant brands and nearly 90,000 locations. Founded in 2005, Olo went public in 2021 at a $3.5B valuation and was acquired by Thoma Bravo in 2024—a 20-year journey from scrappy startup to category leader.What you'll learn:Why Olo's first 10 years required extreme "pain tolerance" waiting for product-market fitThe B2C to B2B pivot that transformed their unit economics from burning $15 per customer to earning revenue while scalingHow "embrace the suck"—borrowed from the Marine Corps—became the cultural mantra that kept the team goingWhy going public was about customer confidence and long-term credibility, not exit or liquidityThe role of industry advisors in bridging credibility gaps when selling to traditional enterprisesHow adding delivery-as-a-service (Dispatch) in 2015 unlocked escape velocity and scale advantageThe challenges and benefits of operating as a public company in a misunderstood industryWhy partnering with Thoma Bravo PE offers better alignment than quarterly public market pressuresNoah's philosophy on founder loyalty and the lifelong bonds formed with early team membersWhy the current "homegrown tech stack" trend in enterprise is a passing fad that misses SaaS fundamentalsIn this episode, we cover:(00:00) Introduction and the "embrace the suck" mentality(01:03) Early days and the long wait for product-market fit(05:30) Why YC's "grow fast or quit" advice doesn't apply to every company(08:06) The deep bonds formed with early team members(12:14) Deciding between B2B vs B2C business models(13:34) The B2C beginning and Good Morning America moment(16:08) The pivot to B2B enterprise software(20:43) How third-party delivery and DoorDash changed the industry(23:04) The journey as a public company (2021-2024)(27:49) Why going public signaled long-term stability to enterprise customers(30:15) Operating under private equity with Thoma Bravo(36:10) Breaking into enterprise sales with industry advisors(44:45) The importance of reliability at scale for enterprise(46:58) Thinking about market size and expansion in vertical software(48:25) Rapid fire: Which founder inspires you most(49:01) Uncomfortable feedback on being overly loyal(50:48) Current trend prediction: Homegrown enterprise software is a fad

Parag Agrawal is the co-founder and CEO of Parallel, building infrastructure for the agentic web. Previously CEO of Twitter, Parag now leads a company architecting how AI agents will interact with the open web at orders of magnitude beyond current human scale. Two years after founding in stealth mode, Parallel recently announced a $100M Series B co-led by Kleiner Perkins and Index Ventures.What you'll learn:Why everything built for human web consumption will become irrelevant when agents become the primary usersHow Parallel's APIs enable agents to search, fetch, and monitor the web with unprecedented scale and speedThe evolution from simple tool calls to autonomous sub-agents with real decision-making capabilityWhy the web must transition from "pull" (searching on demand) to "push" (alerting when conditions are met)The new business models needed to compensate content creators in an agent-driven webParag's counterintuitive approach to fundraising: why VC rejections don't sting but customer rejections doThe rational game VCs play that founders misinterpret as genuine enthusiasmWhy Parag believes we're not in an AI bubble—but an overreaction is coming (and it'll be faster than dot-com)How Parallel built quietly for a year before product-market fit arrived with the agent explosionThe operational philosophy of extreme in-person collaboration that shaped Parallel's early cultureIn this episode, we cover:(00:00) Introduction and Parallel's mission(01:02) What Parallel's APIs enable for AI agents(02:43) Practical examples: coding agents, sales automation, research(04:57) The conviction bet on agents before the market existed(10:54) New business models for content in the agentic web(20:22) The $100M Series B fundraise and going public(23:03) Why Parallel built in stealth with carefully chosen early customers(24:55) Current scale and product offerings(30:42) The evolution from tools to sub-agents to push-based web(33:13) Are we in an AI bubble? Parag's nuanced perspective(36:34) The mental models behind fundraising vs customer rejections(38:37) Why VC enthusiasm is rational strategy, not signal(45:37) Biggest career mistake: delaying Twitter's algorithmic timeline(48:28) The compounding cost of six-month delays(50:09) Finding inspiration in "re-founders" like Satya Nadella(51:54) The most rewarding part: watching customers do unexpected things(52:43) In-person culture and the transition to remote-friendly

Nicholas Rudder is the co-founder and CEO of Sphere, an AI-powered cross-border tax compliance platform that helps businesses navigate international sales tax, VAT, and GST regulations. After pivoting from a failed EdTech marketplace and losing his technical co-founder, Nicholas just raised $21M in Series A funding from Andreessen Horowitz—a remarkable comeback story that includes selling his first five contracts using only a Figma prototype.What you'll learn:How Sphere is becoming the "Deel of revenue compliance" for global businessesWhy Nicholas pivoted from EdTech after 18 months and what made him choose tax complianceThe strategy of selling contracts with a high-fidelity Figma prototype before building the productHow to convince investors to back a pivot when your co-founder has leftWhy businesses struggle with international tax compliance and how AI solves itThe importance of hiring an internal recruiter once you raise significant fundingWhy San Francisco remains the best place to build a startup despite the challengesHow YC's network helped navigate a critical health insurance crisisThe advantage of being a solo founder when recruiting high-quality founding engineersWhy raising from a position of strength creates better fundraising dynamicsIn this episode, we cover:(00:00) Introduction to Nicholas Rudder and Sphere(01:10) The EdTech marketplace that didn't work(03:08) Why EdTech is such a difficult market(09:16) The hard pivot to tax compliance(10:56) Selling five contracts with a Figma prototype(13:10) When the co-founder left and twins arrived early(21:58) Why international tax compliance is broken(27:10) Sphere's vision as the "Deel of revenue compliance"(31:34) The unintentional path to Andreessen Horowitz(38:54) Why VCs all know when you're raising(41:37) Building Sphere in SF vs. the UK or Australia(46:23) Immad's advice on hiring internal recruiters(51:14) Rapid fire: Founder inspirations and lessons learned

Sumir Meghani is the founder and CEO of Instawork, a staffing marketplace connecting 9 million hourly workers with businesses that need flexible labor. Starting with just line cooks in San Francisco restaurants, Instawork now serves warehouses, stadiums, hotels, and hospitality businesses across the country, creating what Sumir calls "employment at the touch of a button."What you'll learn:Why starting "boring and narrow" (one city, one job type) is the key to marketplace successHow Instawork is building a "LinkedIn for hourly workers" with hundreds of data points per profileThe hidden costs of 100%+ annual turnover in restaurants and hospitalityWhy people actually want to work MORE hours when friction is removedThe concept of "robot wranglers" as the next major labor categoryHow Instawork is using its worker pool to train physical AI and robotics modelsThe difference between "leading by disappointment" vs. celebrating wins as a CEOWhy labor costs range from 30% (restaurants) to 80% (hospitals) of revenueThe labor market as a "Tetris board" of micro-jobs and available workersWhy Silicon Valley undervalues hourly work despite 100 million workers depending on itIn this episode, we cover:(00:00) Introduction and YPO CEO forum discussion(03:42) Sumir's journey from Groupon to founding InstaWork(04:58) The restaurant visit that sparked the idea(06:28) Why the hourly labor shortage is a global problem(08:07) Building profiles for 9 million workers(08:54) Starting narrow: San Francisco restaurants and line cooks only(12:28) The hourly worker crisis in hospitality(13:04) Why wages haven't risen despite labor shortages(15:58) The true cost of labor beyond hourly rates(17:48) AI's role in reducing onboarding friction(19:42) Physical AI and the future of robotics(20:16) Introducing "robot wranglers" as a new labor category(22:36) Using InstaWork's workforce to train robot models(23:34) Navigating the AI hype cycle as a consumer(26:47) White collar vs. blue collar labor market dynamics(29:29) Why more jobs will shift to physical industries(30:43) The cultural bias against hourly work in Silicon Valley(32:11) Rapid fire: Biggest entrepreneurial mistakes(33:36) Most rewarding parts of the founder journey(34:30) Why Silicon Valley should start simple, not big(36:30) The uncomfortable feedback: "Leading by disappointment"(38:50) Balancing high standards with celebration(39:58) What inspires Sumir: Physical AI and robotics innovation

We're reposting this episode following major news: Pebble officially relaunched its companion app on iOS and Android, bringing exciting and new apps and watch faces to both new Pebble devices and original watches. The Pebble 2 Duo has begun shipping to customers who preordered earlier this year.Eric Migicovsky is the Founder of Core Devices, and the original founder of Pebble, the pioneering smartwatch that raised $10 million on Kickstarter before being acquired. Eric has launched Core Devices to continue building the smartwatch platform he believes in, complete with Google's newly open-sourced Pebble operating system.What you'll learn:1. The Kickstarter phenomenon: How Pebble became one of the first massive Kickstarter successes, raising $600K in the first day with a $100K goal2. Hardware's inventory trap: Why missing revenue projections by 20% ($80M vs $100M target) created a $20M inventory crisis that nearly sank Pebble3. The sustainable hardware model: Eric's new approach of targeting profitability at 5,000 units and eliminating inventory risk through pre-orders4. Inventor vs. founder mindset: The difference between building products you love versus building scalable companies5. Fighting Big Tech: How Eric's Beeper Mini challenged Apple's iMessage monopoly and led to DOJ antitrust action6. Getting software from Google: The surprising story of how Google open-sourced Pebble's operating system to enable Core Devices7. Hardware manufacturing today: Why building smartwatches is easier now than in 2011, and what's still challenging8. The artisanal hardware movement: Building premium, limited-run products for passionate niche audiences9. Regulatory battles: Apple's API restrictions and how they limit third-party smartwatch functionality10. AI integration: Adding ChatGPT and voice capabilities to modern smartwatchesIn this episode, we cover:(00:00) Introduction and reconnecting with Eric(01:18) The Core Devices relaunch and getting Pebble IP from Google(02:33) Eric and Raj's Waterloo connection and early entrepreneurship(04:48) From Pebble's precursor to YC and the smartwatch vision(09:30) The legendary Kickstarter launch day and calling Raj at 2am(14:00) Five years of overnight success and authentic marketing(16:07) Inventor vs. founder mindset and product obsession(19:21) The 2015 inventory crisis that changed everything(27:20) Eric's new sustainable hardware model with Core Devices(32:00) Using existing Pebble cases and Google's open-source software(36:58) The artisanal approach: 3 people, no VCs, limited production runs(41:14) AI integration and ChatGPT on the wrist(49:36) Secondary markets and public company trading restrictions

Iqram Magdon-Ismail is the co-founder of Venmo and current founder of Jelly, a video-first social app. After building Venmo from a text-message prototype to a verb used by millions (ultimately acquired by PayPal via Braintree), Iqram is now tackling what he sees as social media's biggest problem: it became all ads, influencers, and flexing instead of genuine connection.What you'll learn:How Venmo started from forgetting a wallet at dinner and evolved into a cultural phenomenonThe near-shutdown moments when Wells Fargo threatened to close their accountWhy Venmo raised only $3.4M total before the Braintree acquisitionThe strategy behind keeping Venmo invite-only for five yearsHow the team's close friendship shaped Venmo's personality as a productWhy Iqram believes AI made startups polished but soullessThe shift from building for purpose (helping musicians) to building for metrics (ARR, funding)What it's like working at PayPal after selling your startupHow Jelly uses crypto infrastructure to enable global money movement through videoWhy immigrant founders bring a different hunger and work ethic to building companiesIn this episode, we cover:(00:00) Introduction to Iqram and his founder journey(00:49) The origin story of Venmo - forgetting a wallet(03:08) Building on Google Voice and eating credit card fees(08:40) The near-death moment with Wells Fargo(12:01) How the Braintree acquisition saved Venmo(16:56) Working with Bryan Johnson at Braintree(18:57) The regret of not having more equity in Venmo's success(21:06) What makes Venmo feel different than other payment apps(22:16) Why modern startups lost their personality and purpose(26:00) Life at PayPal after the acquisition(27:38) Consumer vs B2B founder-product fit(30:23) Social media became a nightmare of ads and flexing(32:20) Demo and vision for Jelly(39:06) Using crypto and meme coins in social apps(41:15) Why invite-only launches create quality users(42:38) Rapid fire questions on inspiration and mistakes(45:28) What it means to be an immigrant entrepreneur

In this one-on-one episode, Immad and Raj catch up on what's happening in tech, and what founders should actually be paying attention to right now.Fresh from DC, Immad shares a surprising disconnect he observed about AI regulation and market sentiment. The conversation moves through whether we're in another bubble, the startup metrics that are being gamed again, and the infrastructure realities that might change everyone's timelines.They also get into the fundamentals that separate sustainable companies from hype-driven ones: why retention matters more than growth, what to do after raising at a high valuation, and the frameworks they actually use to make spending decisions.Plus updates on what they're building at Mercury, Tribe, and Lima—and the lessons they're learning along the way.A candid founder-to-founder conversation about navigating uncertainty and building for the long term.

Dan Wang is a research fellow at Stanford's Hoover Institute and author of "Breakneck: China's Quest to Engineer the Future." After spending six years living in Hong Kong, Beijing, and Shanghai (2017-2023), Dan witnessed China's technology growth, the US-China trade and tech war, Xi Jinping's increasing authoritarianism, and three years of zero-COVID pandemic controls firsthand.What you'll learn:Dan's framework of "engineering societies vs lawyerly societies" for understanding the US-China competitionHow China deliberately promoted engineers to power—by 2002, all nine Politburo Standing Committee members had engineering degreesWhy the one-child policy and zero-COVID demonstrate the dangers of literal-minded engineering applied to societyHow America transformed from building the transcontinental railroad and Apollo missions to being unable to fix its subway systemsWhy lawyers took over American governance in the 1960s and created a self-reinforcing systemThe stark reality: China builds 500 gigawatts of solar capacity annually vs America's 50, and has 30 nuclear plants under construction vs zeroWhy China's electricity advantage could determine who wins the AI race—not just better modelsHow American AI leadership is threatened by power constraints and Chinese researchers potentially returning homeWhy robotics applications of AI matter more than reasoning models for geopolitical competitionThe dual reality of America: trillion-dollar tech companies exist alongside broken infrastructure that only works for the wealthyDan's writing process: traveling, eating (twice), reading novels and history, and being deliberately provocativeThe future of US-China competition in semiconductors, aviation, manufacturing, and whether America's technological lead is sustainableIn this episode, we cover:(00:00) Introduction and Dan's AI/electricity thesis(01:15) Dan's journey from San Francisco tech to China analyst(03:40) Engineering society vs lawyerly society framework(04:21) Why engineers running governments can be dangerous(05:46) The one-child policy: designed by a missile scientist(06:56) China's path from Mao to engineering-focused leadership(09:51) America's transformation from builder to regulator (1960s shift)(11:08) Can the pendulum swing back? Housing, transit, and infrastructure failures(13:12) The self-reinforcing nature of lawyerly societies(14:12) Yale Law ambition vs Stanford engineering ambition(16:13) Is there bipartisan consensus on building?(17:41) Why left and right can't agree on solutions(19:32) China's engineering design flaws and authoritarian feedback loops(22:19) US technological advantages: semiconductors, AI, aviation(23:07) The electricity bottleneck: China's massive power advantage(24:31) If AI is everything, what should America do?(26:29) Why Dan doesn't buy the "AI is everything" premise(27:27) Robotics as the real AI battleground(29:35) Silicon Valley codes, China builds power plants(30:37) Anti-AI populism emerging on left and right(33:41) Dan's meta process: philosophy, eating, traveling, reading, being provocative(37:20) China's rural infrastructure and redistribution through building(40:39) Peter Thiel question: acknowledging China's dual reality(44:54) America's core tension: works great for the rich, broken for everyone else(46:35) Will China get stuck in the 2010s like Japan in the 1980s?