Podcast appearances and mentions of Patrick Collison

The Board of the Young Scientist & Technology Exhibition (YSTE) has announced that Stripe, the programmable financial services company with dual headquarters in Dublin and San Francisco, has been appointed as the new title sponsor of Ireland's most prestigious and well-loved STEM exhibition. Signing a 5-year agreement, Stripe assumes the role of title sponsor for YSTE from BT Ireland who, up until this year, was custodian, sponsor and organiser of the exhibition for the past twenty five years. Following a competitive selection process, Stripe secured the title sponsorship thanks to its shared passion with YSTE and commitment to promoting STEM education in Ireland - values exemplified by co-founder Patrick Collison, a former YSTE winner, and his brother John, who also won a category award at the exhibition. Stripe was also chosen for its clear vision for YSTE, its multi-year sponsorship commitment, and its ability to support the large volunteer force required for the delivery of an exhibition and event of this scale. Founded by Dr Tony Scott and Rev Dr Tom Burke in 1965, the exhibition is a staple in the academic, scientific and technological calendar every year, and attracts on average over 40,000 visitors, thus making it one of the biggest events of its kind both in Europe and worldwide. The winners of the Young Scientist and Technology Exhibition advance to participate in prestigious international events such as the European Union Contest for Young Scientists. Professor Pat Guiry, Chairperson of the Young Scientist & Technology Exhibition Board, said, "I would like to congratulate Stripe on their selection as the new title sponsor of the Young Scientist & Technology Exhibition. What really struck the Board was the level of commitment and passion Stripe displayed in wanting to honour the legacy and vision that Dr Tony Scott and Rev Dr Tom Burke created more than sixty years ago." "Collaborating with BT Ireland has been a true privilege for our Board and their dedication in shaping the exhibition into what it is today has been nothing short of inspiring. While they leave a remarkable legacy, we are confident that Stripe will be exceptional partners in the years ahead - not only given Stripe's global reputation as a leader in tech innovation, but also given its strong connection to YSTE through Patrick and John Collison, who are both past participants in the competition, with Patrick taking home the overall top prize in 2005." Patrick Collison, Co-founder and CEO of Stripe, also said, "YSTE is a special institution for me and John. It amplified our curiosity and reinforced our confidence at a critical juncture. We're honoured that Stripe has been selected to help preserve it for generations to come." Speaking about the appointment, Minister for Education, Helen McEntee TD, said, "The Young Scientist & Technology Exhibition has grown to become one of the most successful, and respected events focused on Science, Technology, Engineering and Mathematics (STEM) in Europe, if not the world. The incredible legacy it has left to date is immeasurable and I have no doubt it will continue to inspire and promote STEM and innovation for many more years to come." "I would like to thank BT Ireland for delivering an exhibition of such a high standard for over 25 years. We look forward to continuing our strategic partnership with the YTSE and working with Stripe as they continue to empower students to embrace new ideas, foster curiosity and encourage a love of learning." Dr Tony Scott, Co-founder of the Young Scientist & Technology Exhibition, said, "We are delighted to welcome Stripe as a partner in shaping the next chapter of our exhibition. Their support ensures we can continue to inspire the next generation of scientists, technologists, engineers, and innovators. It's vital that we not only sustain the strong reputation and level of interest in the exhibition year-on-year, but continue to evolve and engage young inquiring minds in new an...

Krithika Shankarraman was the first marketing hire at OpenAI and Stripe and led marketing at Retool. At OpenAI, she established marketing foundations for ChatGPT for consumers and enterprises, as well as their developer API platform. While at Stripe, she spent over eight years building and scaling their marketing function from scratch. An engineer turned marketer, Krithika brings a uniquely analytical approach to marketing. She currently serves as Entrepreneur in Residence at Thrive Capital, where she helps portfolio companies on all things marketing.What you will learn:1. Why do most marketing playbooks often fail, and what's a better way?2. Which marketing lever should I pull first?3. Why is trying to be better than competitors usually a losing strategy?4. How do I craft positioning that actually converts?5. What makes messaging stick with developers, enterprises, and consumers?6. What pricing experiments actually move revenue?7. What is working at OpenAI really like?8. Why does consistency and quality matter more than speed?—Brought to you by:Eppo — Run reliable, impactful experimentsAirtable ProductCentral—Launch to new heights with a unified system for product developmentLinkedIn Ads—Reach professionals and drive results for your business—Where to find Krithika Shankarraman:• X: https://x.com/krithix• LinkedIn: https://www.linkedin.com/in/krithix/• Website: https://krithix.com/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Krithika(04:22) Early marketing lessons from OpenAI(11:17) Diagnosing marketing needs(15:06) The DATE framework and why being cheaper is a race to the bottom(17:11) Marketing strategies at Retool(22:29) Insights from marketing at Stripe(32:33) The importance of consistent marketing communication(39:55) Criteria for hiring a marketing expert(41:43) “Capital M” vs. “lowercase m” marketing(43:05) ChatGPT vs. Claude: market dominance(45:31) The future of AI and its societal impact(47:09) Work-life balance(48:41) Transitioning to Thrive(52:35) Career advice for marketers(55:00) The importance of taste and creativity in the AI era(01:00:04) AI product pricing(01:03:21) AI tools in marketing(01:05:17) Failure corner(01:08:46) Lightning round and final thoughts—Referenced:• OpenAI: https://openai.com/• Stripe: https://stripe.com/• Retool: https://retool.com/• Dropbox: https://www.dropbox.com/• Sam Altman talks about his business model: https://www.youtube.com/watch?v=pLnyjxgFxew• The art and science of pricing | Madhavan Ramanujam (Monetizing Innovation, Simon-Kucher): https://www.lennysnewsletter.com/p/the-art-and-science-of-pricing-madhavan• Pricing your SaaS product: https://www.lennysnewsletter.com/p/saas-pricing-strategy• Netflix: https://www.netflix.com/• Stripe Connect: https://stripe.com/connect• John Collison on X: https://x.com/collision• Patrick Collison on X: https://x.com/patrickc• Cristina Cordova on LinkedIn: https://www.linkedin.com/in/cristinajcordova/• Hackpad: https://en.wikipedia.org/wiki/Hackpad• Building Wiz: the fastest-growing startup in history | Raaz Herzberg (CMO and VP Product Strategy): https://www.lennysnewsletter.com/p/building-wiz-raaz-herzberg• Wiz: https://www.wiz.io/• Thrive Capital: https://thrivecap.com/• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• Claude: https://claude.ai/new• ChatGPT: https://chatgpt.com/• Lessons from scaling Stripe | Claire Hughes Johnson (former COO of Stripe): https://www.lennysnewsletter.com/p/lessons-from-scaling-stripe-tactics• Databricks: https://www.databricks.com/• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Tobi Lütke's leadership playbook: Playing infinite games, operating from first principles, and maximizing human potential (founder and CEO of Shopify): https://www.lennysnewsletter.com/p/tobi-lutkes-leadership-playbook• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• April Dunford on product positioning, segmentation, and optimizing your sales process: https://www.lennysnewsletter.com/p/april-dunford-on-product-positioning• A step-by-step guide to crafting a sales pitch that wins | April Dunford (author of Obviously Awesome and Sales Pitch): https://www.lennysnewsletter.com/p/a-step-by-step-guide-to-crafting• Severance on AppleTV+: https://tv.apple.com/us/show/severance/• Granola: https://www.granola.ai/• Some people think AI writing has a tell—the em dash. Writers disagree: https://www.washingtonpost.com/technology/2025/04/09/ai-em-dash-writing-punctuation-chatgpt/—Recommended books:• Obviously Awesome: How to Nail Product Positioning So Customers Get It, Buy It, Love It: https://www.amazon.com/Obviously-Awesome-Product-Positioning-Customers/dp/1999023005• Circe: https://www.amazon.com/Circe-Madeline-Miller/dp/0316556327/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.lennysnewsletter.com/subscribe

Repasamos la entrevista de Jony Ive con Patrick Collison de Stripe. Destacamos sus reflexiones sobre el impacto no deseado de los smartphones en la sociedad, su colaboración con OpenAI para crear un dispositivo físico de IA. También especulamos sobre su salud, observando temblores en sus manos, pero son solo conjeturas sin base médica.Abordamos las tensiones legales y comerciales de Apple, especialmente el juicio antimonopolio contra Google por su acuerdo de búsquedas exclusivas en Safari. Discutimos cómo una sentencia adversa podría afectar los $20,000 millones anuales que recibe Apple de Google, y cómo la IA está reduciendo las búsquedas tradicionales.Nos vamos con los rumores de subidas en los precios de los iPhone, los posibles rediseños radicales del iPhone para su 20° aniversario en 2027 (incluyendo pantallas curvas y componentes bajo el cristal), el lanzamiento del CarPlay Ultra en asociación con Aston Martin. El creador del iPhone admite que su mayor invento tuvo consecuencias inesperadas. Ahora trabaja en "su sustituto" junto a OpenAI A conversation with Jony Ive - YouTube Apple Tries to Save $20 Billion Google Search Deal By Saying It's Unnecessary - Bloomberg Google's statement on May 7 press reports about Search traffic Apple trabaja en un nuevo iPhone curvado fabricado principalmente con vidrio para su vigésimo aniversario en 2027 Comprar un iPhone podría ser (todavía) más caro: Apple se plantea incrementar los precios con o sin aranceles Apple considers raising iPhone prices, WSJ reports | Reuters CarPlay Ultra, the next generation of CarPlay, begins rolling out today - Apple Driving just got more productive — and fun — with Gemini and more

Story of the Week (DR):Berkshire board names Greg Abel as CEO, Buffett to remain chairWarren Buffett says he'll propose Greg Abel take over as Berkshire Hathaway CEO at year-endWarren Buffett makes surprise announcement: He's stepping down as Berkshire Hathaway CEOOpenAI backs off push to become for-profit companyIn a nutshell, with help from its chatbot: “OpenAI has restructured into a hybrid model with a nonprofit parent company, OpenAI Inc., and a for-profit subsidiary now called a Public Benefit Corporation (PBC). This shift allows for investment while keeping a focus on its mission of developing AGI for the benefit of humanity. The change responds to previous criticism about reducing nonprofit oversight.”OpenAI's nonprofit mission fades further into the rearviewSam Altman urges lawmakers against regulations that could ‘slow down' U.S. in AI race against ChinaKohl's CEO Fired After Investigation Finds 'Highly Unusual' Business Deal with Former Romantic PartnerKohl's CEO Ashley Buchanan was fired after an internal investigation revealed he violated the company's conflict-of-interest policies. The probe found that Buchanan directed business to a former romantic partner, Chandra Holt, who is the CEO of Beyond Inc. and founder of Incredibrew. Holt secured a multimillion-dollar consulting deal with Kohl's under unusually favorable terms, which Buchanan failed to disclose.As a result, Buchanan was dismissed for cause, forfeiting equity awards and required to repay a portion of his $2.5 million signing bonus.This marks the third CEO departure at Kohl's in just three years, highlighting ongoing leadership instability amid declining sales.Proxy Firms Split on Harley-Davidson Board Shake-Up MMGlass Lewis= Withhold; ISS = What's happening at Harley exactly?We have a fun twist at the proxy cage match between Harley Davidson and H Partners, who are 9% shareholders and have started a withhold vote campaign against long-tenured directors Jochen Zeitz, Thomas Linebarger, and Sara Levinson: Glass Lewis says “withhold” but ISS says “support”?Through lackluster reasoning based on hunches and not performance analytics, ISS revealed, without satire, that "[T]here are compelling reasons to believe that as a group [the targeted directors] still have a perspective that can be valuable” and, in discussing the candidacy of departing CEO Jochen Zeitz: “[I]t appears that his time in the role has been more positive than negative, which makes it hard to argue that his vote on a successor is worthless.”Testimony in House Hearing: “Exposing the Proxy Advisory Cartel: How ISS & Glass Lewis Influence Markets”A 2015 study found that 25 percent of institutional investors vote “indiscriminately” with ISS [1].In 2016, a study estimated that a negative recommendation from ISS leads to a 25-percentage point reduction in voting support for say-on-pay proposals [2].A 2018 study demonstrated that a negative recommendation from ISS was associated with a reduction in support of 17 percentage points for equity-plan proposals, 18 points for uncontested director elections, and 27 points for say-on-pay [3].In 2021, a study examining “robo-voting”—the practice of fund managers voting in lockstep with the recommendations of ISS—identified 114 financial institutions managing $5 trillion in assets that automated their votes in a manner aligned with ISS recommendations 99.5% of the time [4].A 2022 study provided further evidence that institutional investors are highly sensitive to an opposing recommendation from a proxy advisory firm. Opposition from ISS was associated with a 51 percent difference in institutional voting support compared with only a 2 percent difference among retail investors [5].During the 12 months ending June 30, 2024, negative recommendations from the two proxy advisory firms were associated with (1) a 17-percentage point difference in support for directors in uncontested elections at the S&P 500 (96.9% with the firms' support vs. 79.7% without); (2) a 35-percentage point gap for say-on-pay proposals (92.8% vs. 58.0%); and (3) a 36-percentage point difference for shareholder proposals (42.4% vs. 6.6%)Why Leo XIV? Pope's chosen name suggests commitment to social justicePope NamesLeo: Many Pope Leos were reformers or defenders of Church teachings.John: often linked to pastoral care and modernization.Paul: Reflects missionary zeal and intellectual work.Gregory: Reform, liturgy, and missionary outreach.Benedict: Benedict XVI emphasized faith and reason in a skeptical age.Pius: Emphasis on traditional piety and Church authority.Clement: Reconciliation and peacemaking.Innocent: Ironically, several Popes named Innocent wielded immense political power.Urban: Engagement with worldly and civic matters.Francis: Poverty, simplicity, ecological concern.CEO NamesWarren: cuddly billionaires who control everything, put family members on board, and say pithy thingsJamie: blowhard control freaks bankers who think they should be President and have something to say about everythingMark: college dropout social media dictators who have no oversight while charting humanity's demiseElon: arrogant and childish Wizard of Ozzian leaders who pretend to be company founders with world domination delusionsSundar: East Asian stewards meant to distract from actual Tech dictatorsTim: Genteel Southern cruise ship captains who keep a steady hand after replacing legendsEtc.Goodliest of the Week (MM/DR):DR: Bill Gates to give away $200 billion by 2045, says Musk is 'killing' world's poorest childrenDR: This Subaru has an external airbag to protect cyclists: The design helps protect both pedestrians and cyclists in a crash MM DRMM: Proxy Firms Split on Harley-Davidson Board Shake-UpThe other major proxy firm, Glass Lewis, reached a different conclusion. It said Tuesday that the directors had “overseen starkly suboptimal shareholder returns,” and that removing them from the eight-person board likely wouldn't create any problems.MM: 80% of Gen Z, Millennials Plan to Increase Allocations to Sustainable Investments: Morgan Stanley SurveyAssholiest of the Week (MM):All Zuckerberg editionCertified watch guy ZuckMark Zuckerberg is a certified watch guy. Here are some of his standout timepieces, from a $120 Casio to a $900,000 Greubel Forse.These are the stories as Trump, whose ass Zuck's lips are firmly planted on, says you should only have 3 dolls - Zuck's watches, C.E.O. Pay Raise Sparks Outrage Among Teachers and Public Officers, 58 crypto wallets have made millions on Trump's meme coin. 764,000 have lost money, data shows, The best and worst looks billionaires wore to the 2025 Met GalaFriend maker Zuck DRMark Zuckerberg wants you to have more friends — but AI friendsMark Zuckerberg destroyed friendship. Now he wants to replace it with AI.Meanwhile, no wonder: Mark Zuckerberg says his management style involves no 1-on-1s, few direct reports, and a 'core army' of 30 running MetaMan with no friends says you need more and will provide fake ones?Human picker ZuckZuck's version of human friends probably the reason he wants to make you fake ones - hand-selected fake friends on the board (Patrick Collison and Dina Powell McCormick to Join Meta Board of Directors):4 tech bro dictators (Tan, Houston, Collison, Xu)3 tech bro suck ups (Andreessen, Alford, Songhurst)1 nepo baby dictator (Elkann)1 family dictator suck up (Travis)2 DJT suck ups (White, Powell McCormick)2 US govt suck ups (Killefer, Kimmitt)Prediction - Zuck to have the first true AI board member?Empathetic ZuckGaslighting, golden handcuffs, and toxicity: Former Meta employees shared what it was like to be laid off as low performersA former senior machine learning engineer at Meta described the shock of being laid off, only for a Meta recruiter to invite her to reapply three days later and skip the interview process.Two weeks before the layoffs, he said, his new manager told the team everyone was "safe." Then came the termination email — and a performance rating of "Meets Some Expectations," low on Meta's end-of-year rating scale. "How could they evaluate my performance when I'd only worked 10 weeks in 2024?" he said, adding that an HR director had said he was "too new to evaluate."An engineer was laid off after five months of leave for a serious health crisis while in the middle of disability-related negotiations.Meta exec apologizes to conservative activist Robby StarbuckLover ZuckMark Zuckerberg's Wife Was Weirded Out by His Strange Gift to HerHe made it for her not out of love, but because…The billionaire is apparently a huge fan of the sculptor behind the statue, the pop artist Daniel Arsham, but decided to go with his wife's likeness, he said on the podcast, because a statue of himself would have been "crazy."Academic ZuckMark Zuckerberg says college isn't preparing students for the job marketHeadliniest of the WeekDR: Olivia and John Randal Tyson Named to Tyson Foods Board of DirectorsDR: This new mental health service targets burned-out content creators: CreatorCare offers affordable therapy tailored to influencers and digital creators—addressing the rising mental health toll of life online.DR: Costco co-founder still goes into the office weekly at age 89: ‘To be successful, you've got to be pretty focused'Costco co-founder Jim Sinegal stepped down from his role in 2012. But Sinegal still goes to the office some TuesdaysDR: Billionaire KKR cofounders say 'emotional intelligence' should be a focus for young investorsKKR leadership page:1 of 8 are women: It HAS to be head of marketing, head of people, or head of legal stuff: so which is it? It's Chief Legal Officer Kathryn SudolBoard is 14:4F; no F in leadership role MM: Elon Musk's Urgent Concern: That the Earth Is Going to Get Swallowed by the Sun"Mars is life insurance for life collectively," Musk said. "So, eventually, all life on Earth will be destroyed by the Sun. The Sun is gradually expanding, and so we do at some point need to be a multi-planet civilization because Earth will be incinerated."It is slated to happen in 6 billion yearsMM: Elon Musk is responsible for “killing the world's poorest children,” says Bill GatesWho Won the Week?DR: Pope #-267, duh. The world's greatest vampire CEO. And Villanova students (who are not openly gay or have vaginas), who all suddenly now believe they will eventually be the pope. MM: Your shitty washer/dryer, which no longer looks horrible: E.P.A. Plans to Shut Down the Energy Star ProgramPredictionsDR: Open AI's CEO, Mark VII, creates a deepfake video showing the country of China eating his baby at one of his homes in Hawaii causing the Trump administration to completely dismantle the SEC.MM: Sit tight for this, I have two: Euronext rebrands ESG in drive to help European defence firms - “energy, security, and geo-strategy” flops, so to LSEG rebrands its ESG Scores to “Emitting, Smoking, Gambling” so that investors can finally do ESG investing and feel good about itMusk gets his Texas wish. SpaceX launch site is approved as the new city of Starbase - I predict in 12 months, Musk is offering SpaceX employees that live in Starbase (a company town) crypto tokens instead of pay that are redeemable at stores in Starbase. To avoid them being called scrips, which were outlawed in the US in 1938 but still used anyway through the 1960s, Musk will list them on crypto exchanges that can be used to trade for dollars (but are totally worthless). Eventually, so indebted to the space plantation and Musk, there is a new renaissance of “resistance music” (a la “We Shall Overcome” and “Sixteen Tons”) with a song ranking number 1 in the US by the end of 2026.

Gaurav Misra is the co-founder and CEO of Captions, an AI-powered video creation company and one of the most successful consumer AI products in the world today. Previously he was a product leader at Snap, where he created the design engineering function and spent years helping develop features used by hundreds of millions of users worldwide. With a background in both engineering and design, Gaurav brings a unique cross-functional perspective to product development.What you'll learn:1. Why the “ship a marketable feature every week” approach helps his team stay focused and the product stay top of mind for users amid constant AI breakthroughs2. How to balance rapid shipping with maintaining quality by cutting scope rather than compromising on timelines3. The “secret roadmap” strategy that helps Captions develop breakthrough features competitors never see coming4. Why taking on strategic technical debt is essential for startups to outpace larger companies5. How Captions accidentally ignored their most successful product for 1.5 years (and why it still grew to 500K users with no updates or support)6. How Snap's unique product development approach—with designers functioning as PMs—enabled their success as the last major social network to break through7. Why AI video will transform marketing before other industries—Brought to you by:• Brex — The banking solution for startups• Paragon—Ship every SaaS integration your customers want• Coda—The all-in-one collaborative workspace—Find the transcript at: https://www.lennysnewsletter.com/p/how-to-win-in-the-ai-era-gaurav-misra—Where to find Gaurav Misra:• X: https://x.com/gmharhar• LinkedIn: https://www.linkedin.com/in/gamisra1/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Gaurav's background(04:47) The exciting era of AI and startups(09:30) Staying top of mind(11:26) Tips for staying focused(13:14) Shipping marketable features weekly(19:03) Managing technical debt in startups(25:31) Snap's unique product development approach(32:09) Brainstorming with AI(35:09) What Snap got right(41:06) Scaling with a small, agile team(49:33) The shift toward prototyping in product management(51:47) The product manager role(55:40) Snap's mission and product decisions(01:02:13) The future of AI-generated video(01:10:20) Leveraging AI for marketing(01:14:37) Failure corner(01:20:21) Lightning round and closing thoughts—Referenced:• Snap: https://www.snap.com/• Captions: https://www.captions.ai/• Iron Man on Disney+: https://www.disneyplus.com/movies/iron-man/6aM2a8mZATiu• J.A.R.V.I.S.: https://en.wikipedia.org/wiki/J.A.R.V.I.S.• Cursor: https://www.cursor.com/• Devin: https://devin.ai/• Eye contact: https://www.captions.ai/eye-contact• Nvidia: https://www.nvidia.com• Descript: https://www.descript.com• Evan Spiegel on LinkedIn: https://www.linkedin.com/in/evan-spiegel-8ab74034a/• TikTok: https://www.tiktok.com/• Spotlight: https://www.snapchat.com/spotlight/• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• Patrick Collison on X: https://x.com/patrickc• DeepSeek: https://www.deepseek.com/• ByteDance Goku: New video generation AI model, better than OpenAI Sora: https://medium.com/data-science-in-your-pocket/bytedance-goku-new-video-generation-ai-model-better-than-openai-sora-56c017a320a5• Will Smith eating spaghetti and other weird AI benchmarks that took off in 2024: https://techcrunch.com/2024/12/31/will-smith-eating-spaghetti-and-other-weird-ai-benchmarks-that-took-off-in-2024/• Silo on AppleTV+: https://tv.apple.com/us/show/silo/umc.cmc.3yksgc857px0k0rqe5zd4jice• Severance on AppleTV+: https://tv.apple.com/us/show/severance/umc.cmc.1srk2goyh2q2zdxcx605w8vtx• Linear: https://linear.app/• Superhuman: https://superhuman.com/• Notion: https://www.notion.com• Perplexity: https://www.perplexity.ai/• OmniHuman-1 AI Video Generation Looks Too Real: https://www.youtube.com/watch?v=fY0KB516m-E—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Eeke de Milliano is the Head of Global Product at Stripe, helping drive innovation and success in the company's product line. Before this role, she was Head of Product at Retool and co-founded Constellate. Eeke previously spent 6 years as Product Lead at Stripe, working with the company during their hyper-growth era. – In today's episode, we discuss: Eeke's wealth of experience as an executive leader The challenges companies face when hiring new executives Common hiring red flags and pitfalls Practical advice for measuring success Why learning your strengths is an underrated piece of the process – Referenced: ASML: https://www.asml.com/en Claire Hughes Johnson: https://www.linkedin.com/in/claire-hughes-johnson-7058/ Constellate: https://constellate.team/ John Collison: https://www.linkedin.com/in/johnbcollison/ Mike Maples Jr.: https://www.linkedin.com/in/maples/ Patrick Collison: https://www.linkedin.com/in/patrickcollison/ Retool: https://retool.com/ Stripe: https://stripe.com/ Will Gaybrik: https://www.linkedin.com/in/william-gaybrick-5730347/ – Where to find Eeke: LinkedIn: https://www.linkedin.com/in/eeke-de-milliano-3b05a629/ – Where to find Brett: LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/ Twitter/X: https://twitter.com/brettberson – Where to find First Round Capital: Website: https://firstround.com/ First Round Review: https://review.firstround.com/ Twitter/X: https://twitter.com/firstround YouTube: https://www.youtube.com/@FirstRoundCapital This podcast on all platforms: https://review.firstround.com/podcast – Timestamps: (00:00) Should you ‘buy or build' a leader (03:45) Why do executive hires fail so often? (09:35) Why the stakes are so high for leadership hires (12:26) The hardest document Eeke ever wrote (14:06) Two red flags in a new hire (17:27) An example of an outstanding leader (21:40) What creates dysfunctional exec relationships (22:38) The three steps towards hiring successful leaders (30:30) What you should know about outside hires (33:12) Eeke's advice for easing leadership transitions (42:06) How to notice success patterns (47:21) Why high-functioning executive teams are like parents (52:02) The most surprising lesson from Eeke's first stint at Stripe (55:11) The leadership data Eeke wishes we had

(0:00) The Besties welcome John and Patrick Collison! (4:28) Stripe's business evolution: $1T in volume/year, stablecoins, challenging the Visa/Mastercard duopoly, publishing economic indicators (20:31) Jamie Dimon's leaked rant on remote work and bureaucracy (34:22) DOGE for Defense: Trump ordered the Pentagon to look at cutting the defense budget by 8%/year over the next five years (43:51) Crypto Corner: Milei's Memecoin embarrassment (1:00:18) John and Patrick break down the Arc Institute and its new Evo 2 AI model (1:18:04) Grok 3 takes the LLM lead, lessons learned from Elon's Colossus scale up (1:30:22) Science Corner: Asteroid update (1:35:42) Why Stripe hasn't gone public yet, despite great metrics Register for All-In at SXSW: https://allin.com/events Follow John: https://x.com/collision Follow Patrick: https://x.com/patrickc Follow the besties: https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@theallinpod Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg Intro Video Credit: https://x.com/TheZachEffect Referenced in the show: https://www.cnbc.com/2024/10/23/stripes-1point1-billion-deal-for-bridge-marks-much-needed-win-for-vc.html https://x.com/Zigmanfreud/status/1890202488596492620 https://www.coworker.org/petitions/professional-dignity https://www.bloomberg.com/news/articles/2023-01-03/shopify-ceo-tobi-lutke-tells-employees-to-just-say-no-to-meetings https://www.washingtonpost.com/national-security/2025/02/19/trump-pentagon-budget-cuts https://www.amazon.com/Boyd-Fighter-Pilot-Who-Changed/dp/0316796883 https://www.cnn.com/2025/02/16/americas/argentina-milei-libra-cryptocurrency-impeachment-calls-intl-latam/index.html https://www.cnn.com/2025/02/18/americas/argentina-milei-defends-libra-crypto-tweet-intl-latam/index.html https://arcinstitute.org https://blogs.nvidia.com/blog/evo-2-biomolecular-ai https://artificialanalysis.ai/models/grok-3 https://x.com/GavinSBaker/status/1891721991444447343 https://www.amazon.com/Henry-J-Kaiser-Builder-American/dp/0292742266 https://x.com/AsteroidWatch/status/1892338055354159256 https://x.com/AsteroidWatch/status/1892631907646447746

This week, Noah Smith and Stripe CEO Patrick Collison recorded a live conversation on Substack covering topics such as American technological leadership, global competition, industrial policy, foreign direct investment, post-financial crisis productivity trends, US financial system advantages, progressive policies, the middle class, tariffs, immigration, technological advancements like humanoid robots, Gen Z's well-being, and key policy recommendations for economic and social progress. This conversation first aired in Noah's substack Noahpinion, so be sure to subscribe if you aren't already. --

Nan Yu is the head of product at Linear, one of the most beloved and fastest-growing B2B SaaS products out there today, and the gold standard for high-performing tech teams. In our conversation, we discuss:• Why speed and quality aren't actually at odds• Linear's unique approach to product development• Nan's systematic approach to creativity• Linear's philosophy on deadlines• The “double triangle” framework for product management• Nan's approach to landing his dream product roles• Much more—Brought to you by:• Sinch—Build messaging, email, and calling into your product• Paragon—Ship every SaaS integration your customers want• Wix Studio—The web creation platform built for agencies—Find the transcript at: https://www.lennysnewsletter.com/p/linears-secret-to-building-beloved-b2b-products-nan-yu—Where to find Nan Yu:• X: https://x.com/thenanyu• LinkedIn: https://www.linkedin.com/in/thenanyu/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Nan Yu and Linear(04:54) Survey insights: Linear vs. Jira(07:51) The speed vs. quality myth(09:24) Building and iterating quickly(15:31) Avoiding bloat in enterprise software(23:57) Understanding user needs deeply(30:09) How to approach customer calls(34:10) Creating strong emotional hooks(40:31) Managing the product backlog(44:46) Systemizing creativity(48:16) Demo: Saving drafts in Linear(51:38) Breaking constraints and building at extremes(54:15) Adopting new tools(58:22) The “double triangle” framework for product management(01:04:23) Effective job-hunting strategies for PMs(01:09:15) Thoughts on deadlines(01:14:15) Lightning round—Referenced:• Jira: https://www.atlassian.com/software/jira• Linear: https://linear.app/• Patrick Collison's post on X: https://x.com/patrickc/status/1869422495985750459• Magnus Carlsen on X: https://x.com/magnuscarlsen• Hikaru Nakamura on X: https://x.com/gmhikaru• Geoffrey Moore on finding your beachhead, crossing the chasm, and dominating a market: https://www.lennysnewsletter.com/p/geoffrey-moore-on-finding-your-beachhead• Customer Request feature on Linear: https://linear.app/customer-requests• Everlane: https://www.everlane.com/• Schlep Blindness: https://paulgraham.com/schlep.html• Linear's triage tool: https://linear.app/docs/triage• Patrick Collison's post about mental models on X: https://x.com/patrickc/status/1443215022029619200• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• Unpacking Amazon's unique ways of working | Bill Carr (author of Working Backwards): https://www.lennysnewsletter.com/p/unpacking-amazons-unique-ways-of• Mode: https://mode.com/• The Diplomat on Netflix: https://www.netflix.com/title/81288983• Sakura Micron pens: https://www.amazon.com/SAKURA-PIGMA-MICRON-ESSENTIAL-COLORS/dp/B07VJFXT3C/—Recommended books:• Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers: https://www.amazon.com/Crossing-Chasm-3rd-Disruptive-Mainstream/dp/0062292986• The Design of Everyday Things: https://www.amazon.com/Design-Everyday-Things-Revised-Expanded/dp/0465050654/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

To conclude our trilogy of interviews with prominent tech journalists to celebrate the upcoming twentieth anniversary of the DLD Conference, today's interview is with David Kirkpatrick, author of The Facebook Effect and founder of Techonomy Media. In contrast with Steven Levy and John Markoff, whose attitude toward Silicon Valley doesn't seem have dramatically changed, Kirkpatrick's thinking has undergone quite a radical shift over the last twenty years. As he acknowledges, he's been transformed from a Facebook believer into one of its most acute critics. And, in contrast with Levy and Markoff, Kirkpatrick's intellectual attention has also broadened, shifting from the internet to focusing on technological fixes for global warming.David Kirkpatrick is a longtime technology and business journalist, author and media entrepreneur, known for his work connecting technology developments to societal impact and progress. He is an expert on internet companies and social media, and is now focusing especially on climate tech and the climate economy. He is also known for moderating on-stage conversations with tech leaders. Kirkpatrick's bestselling 2010 book, The Facebook Effect: The Inside Story of the Company that is Connecting the World, was published in 32 languages, including Catalan and Vietnamese. It was a finalist for the Financial Times/Goldman Sachs Business Book of the Year as well as the Gerald Loeb Award. In subsequent years, he has written extensively about the growing societal harms caused by Facebook/Meta and social media broadly. His articles include 2018's Facing Facebook's Failure for Techonomy, and earlier that same year, The Facebook Defect, in Time Magazine. In December 2023 he published Vinod Khosla Can See the Future: It Just Got Hazy for a Minute in The Information. Kirkpatrick founded and for 12 years led Techonomy Media, which hosted conferences on technology, innovation, business, and their connection to social progress. Techonomy's mission was to highlight ways technology could improve society and human lives. Among his numerous onstage interviews there were Mark Zuckerberg, Marc Benioff, John Chambers, Commerce Sec. Penny Pritzker, economist Jeffrey Sachs, Patrick Collison, DARPA Chief Arati Prabhakar, Sen. Cory Booker, Nandan Nilekani, and Sean Parker. He also has served as a moderator at Burda Media's DLD conference for 19 years, interviewing a wide range of leaders including Mark Zuckerberg. Kirkpatrick worked for Time Inc. for 30 years, mostly at Fortune Magazine, where he was for many years senior editor for internet and technology. Many years earlier, while serving as a copy clerk at Life Magazine, he served as unit chairperson of The Newspaper Guild at Time Inc. He founded and hosted Fortune's Brainstorm conference series beginning in 2001 and for six years wrote its Fast Forward column. At Brainstorm he hosted and interviewed Pres. Bill Clinton, Israeli Pres. Shimon Peres, Senator John McCain, and numerous technology and business CEOs. He was a formal participant and moderator at the World Economic Forum in Davos for 21 years, and for 13 years was a member of the Forum's International Media Council, consisting of 100 top global media leaders. He also served for many years as a contributing editor at Bloomberg Television. He is a recipient of the 2012 Silicon Valley Visionary Award, awarded alongside Elon Musk, Jim Breyer, and Sal Khan. He is a member of the Council on Foreign Relations.Named as one of the "100 most connected men" by GQ magazine, Andrew Keen is amongst the world's best known broadcasters and commentators. In addition to presenting KEEN ON, he is the host of the long-running How To Fix Democracy show. He is also the author of four prescient books about digital technology: CULT OF THE AMATEUR, DIGITAL VERTIGO, THE INTERNET IS NOT THE ANSWER and HOW TO FIX THE FUTURE. Andrew lives in San Francisco, is married to Cassandra Knight, Google's VP of Litigation & Discovery, and has two grown children.Keen On is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit keenon.substack.com/subscribe

Alessio will be at AWS re:Invent next week and hosting a casual coffee meetup on Wednesday, RSVP here! And subscribe to our calendar for our Singapore, NeurIPS, and all upcoming meetups!We are still taking questions for our next big recap episode! Submit questions and messages on Speakpipe here for a chance to appear on the show!If you've been following the AI agents space, you have heard of Lindy AI; while founder Flo Crivello is hesitant to call it "blowing up," when folks like Andrew Wilkinson start obsessing over your product, you're definitely onto something.In our latest episode, Flo walked us through Lindy's evolution from late 2022 to now, revealing some design choices about agent platform design that go against conventional wisdom in the space.The Great Reset: From Text Fields to RailsRemember late 2022? Everyone was "LLM-pilled," believing that if you just gave a language model enough context and tools, it could do anything. Lindy 1.0 followed this pattern:* Big prompt field ✅* Bunch of tools ✅* Prayer to the LLM gods ✅Fast forward to today, and Lindy 2.0 looks radically different. As Flo put it (~17:00 in the episode): "The more you can put your agent on rails, one, the more reliable it's going to be, obviously, but two, it's also going to be easier to use for the user."Instead of a giant, intimidating text field, users now build workflows visually:* Trigger (e.g., "Zendesk ticket received")* Required actions (e.g., "Check knowledge base")* Response generationThis isn't just a UI change - it's a fundamental rethinking of how to make AI agents reliable. As Swyx noted during our discussion: "Put Shoggoth in a box and make it a very small, minimal viable box. Everything else should be traditional if-this-then-that software."The Surprising Truth About Model LimitationsHere's something that might shock folks building in the space: with Claude 3.5 Sonnet, the model is no longer the bottleneck. Flo's exact words (~31:00): "It is actually shocking the extent to which the model is no longer the limit. It was the limit a year ago. It was too expensive. The context window was too small."Some context: Lindy started when context windows were 4K tokens. Today, their system prompt alone is larger than that. But what's really interesting is what this means for platform builders:* Raw capabilities aren't the constraint anymore* Integration quality matters more than model performance* User experience and workflow design are the new bottlenecksThe Search Engine Parallel: Why Horizontal Platforms Might WinOne of the spiciest takes from our conversation was Flo's thesis on horizontal vs. vertical agent platforms. He draws a fascinating parallel to search engines (~56:00):"I find it surprising the extent to which a horizontal search engine has won... You go through Google to search Reddit. You go through Google to search Wikipedia... search in each vertical has more in common with search than it does with each vertical."His argument: agent platforms might follow the same pattern because:* Agents across verticals share more commonalities than differences* There's value in having agents that can work together under one roof* The R&D cost of getting agents right is better amortized across use casesThis might explain why we're seeing early vertical AI companies starting to expand horizontally. The core agent capabilities - reliability, context management, tool integration - are universal needs.What This Means for BuildersIf you're building in the AI agents space, here are the key takeaways:* Constrain First: Rather than maximizing capabilities, focus on reliable execution within narrow bounds* Integration Quality Matters: With model capabilities plateauing, your competitive advantage lies in how well you integrate with existing tools* Memory Management is Key: Flo revealed they actively prune agent memories - even with larger context windows, not all memories are useful* Design for Discovery: Lindy's visual workflow builder shows how important interface design is for adoptionThe Meta LayerThere's a broader lesson here about AI product development. Just as Lindy evolved from "give the LLM everything" to "constrain intelligently," we might see similar evolution across the AI tooling space. The winners might not be those with the most powerful models, but those who best understand how to package AI capabilities in ways that solve real problems reliably.Full Video PodcastFlo's talk at AI Engineer SummitChapters* 00:00:00 Introductions * 00:04:05 AI engineering and deterministic software * 00:08:36 Lindys demo* 00:13:21 Memory management in AI agents * 00:18:48 Hierarchy and collaboration between Lindys * 00:21:19 Vertical vs. horizontal AI tools * 00:24:03 Community and user engagement strategies * 00:26:16 Rickrolling incident with Lindy * 00:28:12 Evals and quality control in AI systems * 00:31:52 Model capabilities and their impact on Lindy * 00:39:27 Competition and market positioning * 00:42:40 Relationship between Factorio and business strategy * 00:44:05 Remote work vs. in-person collaboration * 00:49:03 Europe vs US Tech* 00:58:59 Testing the Overton window and free speech * 01:04:20 Balancing AI safety concerns with business innovation Show Notes* Lindy.ai* Rick Rolling* Flo on X* TeamFlow* Andrew Wilkinson* Dust* Poolside.ai* SB1047* Gathertown* Sid Sijbrandij* Matt Mullenweg* Factorio* Seeing Like a StateTranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.Swyx [00:00:12]: Hey, and today we're joined in the studio by Florent Crivello. Welcome.Flo [00:00:15]: Hey, yeah, thanks for having me.Swyx [00:00:17]: Also known as Altimore. I always wanted to ask, what is Altimore?Flo [00:00:21]: It was the name of my character when I was playing Dungeons & Dragons. Always. I was like 11 years old.Swyx [00:00:26]: What was your classes?Flo [00:00:27]: I was an elf. I was a magician elf.Swyx [00:00:30]: Well, you're still spinning magic. Right now, you're a solo founder and CEO of Lindy.ai. What is Lindy?Flo [00:00:36]: Yeah, we are a no-code platform letting you build your own AI agents easily. So you can think of we are to LangChain as Airtable is to MySQL. Like you can just pin up AI agents super easily by clicking around and no code required. You don't have to be an engineer and you can automate business workflows that you simply could not automate before in a few minutes.Swyx [00:00:55]: You've been in our orbit a few times. I think you spoke at our Latent Space anniversary. You spoke at my summit, the first summit, which was a really good keynote. And most recently, like we actually already scheduled this podcast before this happened. But Andrew Wilkinson was like, I'm obsessed by Lindy. He's just created a whole bunch of agents. So basically, why are you blowing up?Flo [00:01:16]: Well, thank you. I think we are having a little bit of a moment. I think it's a bit premature to say we're blowing up. But why are things going well? We revamped the product majorly. We called it Lindy 2.0. I would say we started working on that six months ago. We've actually not really announced it yet. It's just, I guess, I guess that's what we're doing now. And so we've basically been cooking for the last six months, like really rebuilding the product from scratch. I think I'll list you, actually, the last time you tried the product, it was still Lindy 1.0. Oh, yeah. If you log in now, the platform looks very different. There's like a ton more features. And I think one realization that we made, and I think a lot of folks in the agent space made the same realization, is that there is such a thing as too much of a good thing. I think many people, when they started working on agents, they were very LLM peeled and chat GPT peeled, right? They got ahead of themselves in a way, and us included, and they thought that agents were actually, and LLMs were actually more advanced than they actually were. And so the first version of Lindy was like just a giant prompt and a bunch of tools. And then the realization we had was like, hey, actually, the more you can put your agent on Rails, one, the more reliable it's going to be, obviously, but two, it's also going to be easier to use for the user, because you can really, as a user, you get, instead of just getting this big, giant, intimidating text field, and you type words in there, and you have no idea if you're typing the right word or not, here you can really click and select step by step, and tell your agent what to do, and really give as narrow or as wide a guardrail as you want for your agent. We started working on that. We called it Lindy on Rails about six months ago, and we started putting it into the hands of users over the last, I would say, two months or so, and I think things really started going pretty well at that point. The agent is way more reliable, way easier to set up, and we're already seeing a ton of new use cases pop up.Swyx [00:03:00]: Yeah, just a quick follow-up on that. You launched the first Lindy in November last year, and you were already talking about having a DSL, right? I remember having this discussion with you, and you were like, it's just much more reliable. Is this still the DSL under the hood? Is this a UI-level change, or is it a bigger rewrite?Flo [00:03:17]: No, it is a much bigger rewrite. I'll give you a concrete example. Suppose you want to have an agent that observes your Zendesk tickets, and it's like, hey, every time you receive a Zendesk ticket, I want you to check my knowledge base, so it's like a RAG module and whatnot, and then answer the ticket. The way it used to work with Lindy before was, you would type the prompt asking it to do that. You check my knowledge base, and so on and so forth. The problem with doing that is that it can always go wrong. You're praying the LLM gods that they will actually invoke your knowledge base, but I don't want to ask it. I want it to always, 100% of the time, consult the knowledge base after it receives a Zendesk ticket. And so with Lindy, you can actually have the trigger, which is Zendesk ticket received, have the knowledge base consult, which is always there, and then have the agent. So you can really set up your agent any way you want like that.Swyx [00:04:05]: This is something I think about for AI engineering as well, which is the big labs want you to hand over everything in the prompts, and only code of English, and then the smaller brains, the GPU pours, always want to write more code to make things more deterministic and reliable and controllable. One way I put it is put Shoggoth in a box and make it a very small, the minimal viable box. Everything else should be traditional, if this, then that software.Flo [00:04:29]: I love that characterization, put the Shoggoth in the box. Yeah, we talk about using as much AI as necessary and as little as possible.Alessio [00:04:37]: And what was the choosing between kind of like this drag and drop, low code, whatever, super code-driven, maybe like the Lang chains, auto-GPT of the world, and maybe the flip side of it, which you don't really do, it's like just text to agent, it's like build the workflow for me. Like what have you learned actually putting this in front of users and figuring out how much do they actually want to add it versus like how much, you know, kind of like Ruby on Rails instead of Lindy on Rails, it's kind of like, you know, defaults over configuration.Flo [00:05:06]: I actually used to dislike when people said, oh, text is not a great interface. I was like, ah, this is such a mid-take, I think text is awesome. And I've actually come around, I actually sort of agree now that text is really not great. I think for people like you and me, because we sort of have a mental model, okay, when I type a prompt into this text box, this is what it's going to do, it's going to map it to this kind of data structure under the hood and so forth. I guess it's a little bit blackmailing towards humans. You jump on these calls with humans and you're like, here's a text box, this is going to set up an agent for you, do it. And then they type words like, I want you to help me put order in my inbox. Oh, actually, this is a good one. This is actually a good one. What's a bad one? I would say 60 or 70% of the prompts that people type don't mean anything. Me as a human, as AGI, I don't understand what they mean. I don't know what they mean. It is actually, I think whenever you can have a GUI, it is better than to have just a pure text interface.Alessio [00:05:58]: And then how do you decide how much to expose? So even with the tools, you have Slack, you have Google Calendar, you have Gmail. Should people by default just turn over access to everything and then you help them figure out what to use? I think that's the question. When I tried to set up Slack, it was like, hey, give me access to all channels and everything, which for the average person probably makes sense because you don't want to re-prompt them every time you add new channels. But at the same time, for maybe the more sophisticated enterprise use cases, people are like, hey, I want to really limit what you have access to. How do you kind of thread that balance?Flo [00:06:35]: The general philosophy is we ask for the least amount of permissions needed at any given moment. I don't think Slack, I could be mistaken, but I don't think Slack lets you request permissions for just one channel. But for example, for Google, obviously there are hundreds of scopes that you could require for Google. There's a lot of scopes. And sometimes it's actually painful to set up your Lindy because you're going to have to ask Google and add scopes five or six times. We've had sessions like this. But that's what we do because, for example, the Lindy email drafter, she's going to ask you for your authorization once for, I need to be able to read your email so I can draft a reply, and then another time for I need to be able to write a draft for them. We just try to do it very incrementally like that.Alessio [00:07:15]: Do you think OAuth is just overall going to change? I think maybe before it was like, hey, we need to set up OAuth that humans only want to kind of do once. So we try to jam-pack things all at once versus what if you could on-demand get different permissions every time from different parts? Do you ever think about designing things knowing that maybe AI will use it instead of humans will use it? Yeah, for sure.Flo [00:07:37]: One pattern we've started to see is people provisioning accounts for their AI agents. And so, in particular, Google Workspace accounts. So, for example, Lindy can be used as a scheduling assistant. So you can just CC her to your emails when you're trying to find time with someone. And just like a human assistant, she's going to go back and forth and offer other abilities and so forth. Very often, people don't want the other party to know that it's an AI. So it's actually funny. They introduce delays. They ask the agent to wait before replying, so it's not too obvious that it's an AI. And they provision an account on Google Suite, which costs them like $10 a month or something like that. So we're seeing that pattern more and more. I think that does the job for now. I'm not optimistic on us actually patching OAuth. Because I agree with you, ultimately, we would want to patch OAuth because the new account thing is kind of a clutch. It's really a hack. You would want to patch OAuth to have more granular access control and really be able to put your sugar in the box. I'm not optimistic on us doing that before AGI, I think. That's a very close timeline.Swyx [00:08:36]: I'm mindful of talking about a thing without showing it. And we already have the setup to show it. Why don't we jump into a screen share? For listeners, you can jump on the YouTube and like and subscribe. But also, let's have a look at how you show off Lindy. Yeah, absolutely.Flo [00:08:51]: I'll give an example of a very simple Lindy and then I'll graduate to a much more complicated one. A super simple Lindy that I have is, I unfortunately bought some investment properties in the south of France. It was a really, really bad idea. And I put them on a Holydew, which is like the French Airbnb, if you will. And so I received these emails from time to time telling me like, oh, hey, you made 200 bucks. Someone booked your place. When I receive these emails, I want to log this reservation in a spreadsheet. Doing this without an AI agent or without AI in general is a pain in the butt because you must write an HTML parser for this email. And so it's just hard. You may not be able to do it and it's going to break the moment the email changes. By contrast, the way it works with Lindy, it's really simple. It's two steps. It's like, okay, I receive an email. If it is a reservation confirmation, I have this filter here. Then I append a row to this spreadsheet. And so this is where you can see the AI part where the way this action is configured here, you see these purple fields on the right. Each of these fields is a prompt. And so I can say, okay, you extract from the email the day the reservation begins on. You extract the amount of the reservation. You extract the number of travelers of the reservation. And now you can see when I look at the task history of this Lindy, it's really simple. It's like, okay, you do this and boom, appending this row to this spreadsheet. And this is the information extracted. So effectively, this node here, this append row node is a mini agent. It can see everything that just happened. It has context over the task and it's appending the row. And then it's going to send a reply to the thread. That's a very simple example of an agent.Swyx [00:10:34]: A quick follow-up question on this one while we're still on this page. Is that one call? Is that a structured output call? Yeah. Okay, nice. Yeah.Flo [00:10:41]: And you can see here for every node, you can configure which model you want to power the node. Here I use cloud. For this, I use GPT-4 Turbo. Much more complex example, my meeting recorder. It looks very complex because I've added to it over time, but at a high level, it's really simple. It's like when a meeting begins, you record the meeting. And after the meeting, you send me a summary and you send me coaching notes. So I receive, like my Lindy is constantly coaching me. And so you can see here in the prompt of the coaching notes, I've told it, hey, you know, was I unnecessarily confrontational at any point? I'm French, so I have to watch out for that. Or not confrontational enough. Should I have double-clicked on any issue, right? So I can really give it exactly the kind of coaching that I'm expecting. And then the interesting thing here is, like, you can see the agent here, after it sent me these coaching notes, moves on. And it does a bunch of other stuff. So it goes on Slack. It disseminates the notes on Slack. It does a bunch of other stuff. But it's actually able to backtrack and resume the automation at the coaching notes email if I responded to that email. So I'll give a super concrete example. This is an actual coaching feedback that I received from Lindy. She was like, hey, this was a sales call I had with a customer. And she was like, I found your explanation of Lindy too technical. And I was able to follow up and just ask a follow-up question in the thread here. And I was like, why did you find too technical about my explanation? And Lindy restored the context. And so she basically picked up the automation back up here in the tree. And she has all of the context of everything that happened, including the meeting in which I was. So she was like, oh, you used the words deterministic and context window and agent state. And that concept exists at every level for every channel and every action that Lindy takes. So another example here is, I mentioned she also disseminates the notes on Slack. So this was a meeting where I was not, right? So this was a teammate. He's an indie meeting recorder, posts the meeting notes in this customer discovery channel on Slack. So you can see, okay, this is the onboarding call we had. This was the use case. Look at the questions. How do I make Lindy slower? How do I add delays to make Lindy slower? And I was able, in the Slack thread, to ask follow-up questions like, oh, what did we answer to these questions? And it's really handy because I know I can have this sort of interactive Q&A with these meetings. It means that very often now, I don't go to meetings anymore. I just send my Lindy. And instead of going to like a 60-minute meeting, I have like a five-minute chat with my Lindy afterwards. And she just replied. She was like, well, this is what we replied to this customer. And I can just be like, okay, good job, Jack. Like, no notes about your answers. So that's the kind of use cases people have with Lindy. It's a lot of like, there's a lot of sales automations, customer support automations, and a lot of this, which is basically personal assistance automations, like meeting scheduling and so forth.Alessio [00:13:21]: Yeah, and I think the question that people might have is memory. So as you get coaching, how does it track whether or not you're improving? You know, if these are like mistakes you made in the past, like, how do you think about that?Flo [00:13:31]: Yeah, we have a memory module. So I'll show you my meeting scheduler, Lindy, which has a lot of memories because by now I've used her for so long. And so every time I talk to her, she saves a memory. If I tell her, you screwed up, please don't do this. So you can see here, oh, it's got a double memory here. This is the meeting link I have, or this is the address of the office. If I tell someone to meet me at home, this is the address of my place. This is the code. I guess we'll have to edit that out. This is not the code of my place. No dogs. Yeah, so Lindy can just manage her own memory and decide when she's remembering things between executions. Okay.Swyx [00:14:11]: I mean, I'm just going to take the opportunity to ask you, since you are the creator of this thing, how come there's so few memories, right? Like, if you've been using this for two years, there should be thousands of thousands of things. That is a good question.Flo [00:14:22]: Agents still get confused if they have too many memories, to my point earlier about that. So I just am out of a call with a member of the Lama team at Meta, and we were chatting about Lindy, and we were going into the system prompt that we sent to Lindy, and all of that stuff. And he was amazed, and he was like, it's a miracle that it's working, guys. He was like, this kind of system prompt, this does not exist, either pre-training or post-training. These models were never trained to do this kind of stuff. It's a miracle that they can be agents at all. And so what I do, I actually prune the memories. You know, it's actually something I've gotten into the habit of doing from back when we had GPT 3.5, being Lindy agents. I suspect it's probably not as necessary in the Cloud 3.5 Sunette days, but I prune the memories. Yeah, okay.Swyx [00:15:05]: The reason is because I have another assistant that also is recording and trying to come up with facts about me. It comes up with a lot of trivial, useless facts that I... So I spend most of my time pruning. Actually, it's not super useful. I'd much rather have high-quality facts that it accepts. Or maybe I was even thinking, were you ever tempted to add a wake word to only memorize this when I say memorize this? And otherwise, don't even bother.Flo [00:15:30]: I have a Lindy that does this. So this is my inbox processor, Lindy. It's kind of beefy because there's a lot of different emails. But somewhere in here,Swyx [00:15:38]: there is a rule where I'm like,Flo [00:15:39]: aha, I can email my inbox processor, Lindy. It's really handy. So she has her own email address. And so when I process my email inbox, I sometimes forward an email to her. And it's a newsletter, or it's like a cold outreach from a recruiter that I don't care about, or anything like that. And I can give her a rule. And I can be like, hey, this email I want you to archive, moving forward. Or I want you to alert me on Slack when I have this kind of email. It's really important. And so you can see here, the prompt is, if I give you a rule about a kind of email, like archive emails from X, save it as a new memory. And I give it to the memory saving skill. And yeah.Swyx [00:16:13]: One thing that just occurred to me, so I'm a big fan of virtual mailboxes. I recommend that everybody have a virtual mailbox. You could set up a physical mail receive thing for Lindy. And so then Lindy can process your physical mail.Flo [00:16:26]: That's actually a good idea. I actually already have something like that. I use like health class mail. Yeah. So yeah, most likely, I can process my physical mail. Yeah.Swyx [00:16:35]: And then the other product's idea I have, looking at this thing, is people want to brag about the complexity of their Lindys. So this would be like a 65 point Lindy, right?Flo [00:16:43]: What's a 65 point?Swyx [00:16:44]: Complexity counting. Like how many nodes, how many things, how many conditions, right? Yeah.Flo [00:16:49]: This is not the most complex one. I have another one. This designer recruiter here is kind of beefy as well. Right, right, right. So I'm just saying,Swyx [00:16:56]: let people brag. Let people be super users. Oh, right.Flo [00:16:59]: Give them a score. Give them a score.Swyx [00:17:01]: Then they'll just be like, okay, how high can you make this score?Flo [00:17:04]: Yeah, that's a good point. And I think that's, again, the beauty of this on-rails phenomenon. It's like, think of the equivalent, the prompt equivalent of this Lindy here, for example, that we're looking at. It'd be monstrous. And the odds that it gets it right are so low. But here, because we're really holding the agent's hand step by step by step, it's actually super reliable. Yeah.Swyx [00:17:22]: And is it all structured output-based? Yeah. As far as possible? Basically. Like, there's no non-structured output?Flo [00:17:27]: There is. So, for example, here, this AI agent step, right, or this send message step, sometimes it gets to... That's just plain text.Swyx [00:17:35]: That's right.Flo [00:17:36]: Yeah. So I'll give you an example. Maybe it's TMI. I'm having blood pressure issues these days. And so this Lindy here, I give it my blood pressure readings, and it updates a log that I have of my blood pressure that it sends to my doctor.Swyx [00:17:49]: Oh, so every Lindy comes with a to-do list?Flo [00:17:52]: Yeah. Every Lindy has its own task history. Huh. Yeah. And so you can see here, this is my main Lindy, my personal assistant, and I've told it, where is this? There is a point where I'm like, if I am giving you a health-related fact, right here, I'm giving you health information, so then you update this log that I have in this Google Doc, and then you send me a message. And you can see, I've actually not configured this send message node. I haven't told it what to send me a message for. Right? And you can see, it's actually lecturing me. It's like, I'm giving it my blood pressure ratings. It's like, hey, it's a bit high. Here are some lifestyle changes you may want to consider.Alessio [00:18:27]: I think maybe this is the most confusing or new thing for people. So even I use Lindy and I didn't even know you could have multiple workflows in one Lindy. I think the mental model is kind of like the Zapier workflows. It starts and it ends. It doesn't choose between. How do you think about what's a Lindy versus what's a sub-function of a Lindy? Like, what's the hierarchy?Flo [00:18:48]: Yeah. Frankly, I think the line is a little arbitrary. It's kind of like when you code, like when do you start to create a new class versus when do you overload your current class. I think of it in terms of like jobs to be done and I think of it in terms of who is the Lindy serving. This Lindy is serving me personally. It's really my day-to-day Lindy. I give it a bunch of stuff, like very easy tasks. And so this is just the Lindy I go to. Sometimes when a task is really more specialized, so for example, I have this like summarizer Lindy or this designer recruiter Lindy. These tasks are really beefy. I wouldn't want to add this to my main Lindy, so I just created a separate Lindy for it. Or when it's a Lindy that serves another constituency, like our customer support Lindy, I don't want to add that to my personal assistant Lindy. These are two very different Lindys.Alessio [00:19:31]: And you can call a Lindy from within another Lindy. That's right. You can kind of chain them together.Flo [00:19:36]: Lindys can work together, absolutely.Swyx [00:19:38]: A couple more things for the video portion. I noticed you have a podcast follower. We have to ask about that. What is that?Flo [00:19:46]: So this one wakes me up every... So wakes herself up every week. And she sends me... So she woke up yesterday, actually. And she searches for Lenny's podcast. And she looks for like the latest episode on YouTube. And once she finds it, she transcribes the video and then she sends me the summary by email. I don't listen to podcasts as much anymore. I just like read these summaries. Yeah.Alessio [00:20:09]: We should make a latent space Lindy. Marketplace.Swyx [00:20:12]: Yeah. And then you have a whole bunch of connectors. I saw the list briefly. Any interesting one? Complicated one that you're proud of? Anything that you want to just share? Connector stories.Flo [00:20:23]: So many of our workflows are about meeting scheduling. So we had to build some very open unity tools around meeting scheduling. So for example, one that is surprisingly hard is this find available times action. You would not believe... This is like a thousand lines of code or something. It's just a very beefy action. And you can pass it a bunch of parameters about how long is the meeting? When does it start? When does it end? What are the meetings? The weekdays in which I meet? How many time slots do you return? What's the buffer between my meetings? It's just a very, very, very complex action. I really like our GitHub action. So we have a Lindy PR reviewer. And it's really handy because anytime any bug happens... So the Lindy reads our guidelines on Google Docs. By now, the guidelines are like 40 pages long or something. And so every time any new kind of bug happens, we just go to the guideline and we add the lines. Like, hey, this has happened before. Please watch out for this category of bugs. And it's saving us so much time every day.Alessio [00:21:19]: There's companies doing PR reviews. Where does a Lindy start? When does a company start? Or maybe how do you think about the complexity of these tasks when it's going to be worth having kind of like a vertical standalone company versus just like, hey, a Lindy is going to do a good job 99% of the time?Flo [00:21:34]: That's a good question. We think about this one all the time. I can't say that we've really come up with a very crisp articulation of when do you want to use a vertical tool versus when do you want to use a horizontal tool. I think of it as very similar to the internet. I find it surprising the extent to which a horizontal search engine has won. But I think that Google, right? But I think the even more surprising fact is that the horizontal search engine has won in almost every vertical, right? You go through Google to search Reddit. You go through Google to search Wikipedia. I think maybe the biggest exception is e-commerce. Like you go to Amazon to search e-commerce, but otherwise you go through Google. And I think that the reason for that is because search in each vertical has more in common with search than it does with each vertical. And search is so expensive to get right. Like Google is a big company that it makes a lot of sense to aggregate all of these different use cases and to spread your R&D budget across all of these different use cases. I have a thesis, which is, it's a really cool thesis for Lindy, is that the same thing is true for agents. I think that by and large, in a lot of verticals, agents in each vertical have more in common with agents than they do with each vertical. I also think there are benefits in having a single agent platform because that way your agents can work together. They're all like under one roof. That way you only learn one platform and so you can create agents for everything that you want. And you don't have to like pay for like a bunch of different platforms and so forth. So I think ultimately, it is actually going to shake out in a way that is similar to search in that search is everywhere on the internet. Every website has a search box, right? So there's going to be a lot of vertical agents for everything. I think AI is going to completely penetrate every category of software. But then I also think there are going to be a few very, very, very big horizontal agents that serve a lot of functions for people.Swyx [00:23:14]: That is actually one of the questions that we had about the agent stuff. So I guess we can transition away from the screen and I'll just ask the follow-up, which is, that is a hot topic. You're basically saying that the current VC obsession of the day, which is vertical AI enabled SaaS, is mostly not going to work out. And then there are going to be some super giant horizontal SaaS.Flo [00:23:34]: Oh, no, I'm not saying it's either or. Like SaaS today, vertical SaaS is huge and there's also a lot of horizontal platforms. If you look at like Airtable or Notion, basically the entire no-code space is very horizontal. I mean, Loom and Zoom and Slack, there's a lot of very horizontal tools out there. Okay.Swyx [00:23:49]: I was just trying to get a reaction out of you for hot takes. Trying to get a hot take.Flo [00:23:54]: No, I also think it is natural for the vertical solutions to emerge first because it's just easier to build. It's just much, much, much harder to build something horizontal. Cool.Swyx [00:24:03]: Some more Lindy-specific questions. So we covered most of the top use cases and you have an academy. That was nice to see. I also see some other people doing it for you for free. So like Ben Spites is doing it and then there's some other guy who's also doing like lessons. Yeah. Which is kind of nice, right? Yeah, absolutely. You don't have to do any of that.Flo [00:24:20]: Oh, we've been seeing it more and more on like LinkedIn and Twitter, like people posting their Lindys and so forth.Swyx [00:24:24]: I think that's the flywheel that you built the platform where creators see value in allying themselves to you. And so then, you know, your incentive is to make them successful so that they can make other people successful and then it just drives more and more engagement. Like it's earned media. Like you don't have to do anything.Flo [00:24:39]: Yeah, yeah. I mean, community is everything.Swyx [00:24:41]: Are you doing anything special there? Any big wins?Flo [00:24:44]: We have a Slack community that's pretty active. I can't say we've invested much more than that so far.Swyx [00:24:49]: I would say from having, so I have some involvement in the no-code community. I would say that Webflow going very hard after no-code as a category got them a lot more allies than just the people using Webflow. So it helps you to grow the community beyond just Lindy. And I don't know what this is called. Maybe it's just no-code again. Maybe you want to call it something different. But there's definitely an appetite for this and you are one of a broad category, right? Like just before you, we had Dust and, you know, they're also kind of going after a similar market. Zapier obviously is not going to try to also compete with you. Yeah. There's no question there. It's just like a reaction about community. Like I think a lot about community. Lanespace is growing the community of AI engineers. And I think you have a slightly different audience of, I don't know what.Flo [00:25:33]: Yeah. I think the no-code tinkerers is the community. Yeah. It is going to be the same sort of community as what Webflow, Zapier, Airtable, Notion to some extent.Swyx [00:25:43]: Yeah. The framing can be different if you were, so I think tinkerers has this connotation of not serious or like small. And if you framed it to like no-code EA, we're exclusively only for CEOs with a certain budget, then you just have, you tap into a different budget.Flo [00:25:58]: That's true. The problem with EA is like, the CEO has no willingness to actually tinker and play with the platform.Swyx [00:26:05]: Maybe Andrew's doing that. Like a lot of your biggest advocates are CEOs, right?Flo [00:26:09]: A solopreneur, you know, small business owners, I think Andrew is an exception. Yeah. Yeah, yeah, he is.Swyx [00:26:14]: He's an exception in many ways. Yep.Alessio [00:26:16]: Just before we wrap on the use cases, is Rick rolling your customers? Like a officially supported use case or maybe tell that story?Flo [00:26:24]: It's one of the main jobs to be done, really. Yeah, we woke up recently, so we have a Lindy obviously doing our customer support and we do check after the Lindy. And so we caught this email exchange where someone was asking Lindy for video tutorials. And at the time, actually, we did not have video tutorials. We do now on the Lindy Academy. And Lindy responded to the email. It's like, oh, absolutely, here's a link. And we were like, what? Like, what kind of link did you send? And so we clicked on the link and it was a recall. We actually reacted fast enough that the customer had not yet opened the email. And so we reacted immediately. Like, oh, hey, actually, sorry, this is the right link. And so the customer never reacted to the first link. And so, yeah, I tweeted about that. It went surprisingly viral. And I checked afterwards in the logs. We did like a database query and we found, I think, like three or four other instances of it having happened before.Swyx [00:27:12]: That's surprisingly low.Flo [00:27:13]: It is low. And we fixed it across the board by just adding a line to the system prompt that's like, hey, don't recall people, please don't recall.Swyx [00:27:21]: Yeah, yeah, yeah. I mean, so, you know, you can explain it retroactively, right? Like, that YouTube slug has been pasted in so many different corpuses that obviously it learned to hallucinate that.Alessio [00:27:31]: And it pretended to be so many things. That's the thing.Swyx [00:27:34]: I wouldn't be surprised if that takes one token. Like, there's this one slug in the tokenizer and it's just one token.Flo [00:27:41]: That's the idea of a YouTube video.Swyx [00:27:43]: Because it's used so much, right? And you have to basically get it exactly correct. It's probably not. That's a long speech.Flo [00:27:52]: It would have been so good.Alessio [00:27:55]: So this is just a jump maybe into evals from here. How could you possibly come up for an eval that says, make sure my AI does not recall my customer? I feel like when people are writing evals, that's not something that they come up with. So how do you think about evals when it's such like an open-ended problem space?Flo [00:28:12]: Yeah, it is tough. We built quite a bit of infrastructure for us to create evals in one click from any conversation history. So we can point to a conversation and we can be like, in one click we can turn it into effectively a unit test. It's like, this is a good conversation. This is how you're supposed to handle things like this. Or if it's a negative example, then we modify a little bit the conversation after generating the eval. So it's very easy for us to spin up this kind of eval.Alessio [00:28:36]: Do you use an off-the-shelf tool which is like Brain Trust on the podcast? Or did you just build your own?Flo [00:28:41]: We unfortunately built our own. We're most likely going to switch to Brain Trust. Well, when we built it, there was nothing. Like there was no eval tool, frankly. I mean, we started this project at the end of 2022. It was like, it was very, very, very early. I wouldn't recommend it to build your own eval tool. There's better solutions out there and our eval tool breaks all the time and it's a nightmare to maintain. And that's not something we want to be spending our time on.Swyx [00:29:04]: I was going to ask that basically because I think my first conversations with you about Lindy was that you had a strong opinion that everyone should build their own tools. And you were very proud of your evals. You're kind of showing off to me like how many evals you were running, right?Flo [00:29:16]: Yeah, I think that was before all of these tools came around. I think the ecosystem has matured a fair bit.Swyx [00:29:21]: What is one thing that Brain Trust has nailed that you always struggled to do?Flo [00:29:25]: We're not using them yet, so I couldn't tell. But from what I've gathered from the conversations I've had, like they're doing what we do with our eval tool, but better.Swyx [00:29:33]: And like they do it, but also like 60 other companies do it, right? So I don't know how to shop apart from brand. Word of mouth.Flo [00:29:41]: Same here.Swyx [00:29:42]: Yeah, like evals or Lindys, there's two kinds of evals, right? Like in some way, you don't have to eval your system as much because you've constrained the language model so much. And you can rely on open AI to guarantee that the structured outputs are going to be good, right? We had Michelle sit where you sit and she explained exactly how they do constraint grammar sampling and all that good stuff. So actually, I think it's more important for your customers to eval their Lindys than you evaling your Lindy platform because you just built the platform. You don't actually need to eval that much.Flo [00:30:14]: Yeah. In an ideal world, our customers don't need to care about this. And I think the bar is not like, look, it needs to be at 100%. I think the bar is it needs to be better than a human. And for most use cases we serve today, it is better than a human, especially if you put it on Rails.Swyx [00:30:30]: Is there a limiting factor of Lindy at the business? Like, is it adding new connectors? Is it adding new node types? Like how do you prioritize what is the most impactful to your company?Flo [00:30:41]: Yeah. The raw capabilities for sure are a big limit. It is actually shocking the extent to which the model is no longer the limit. It was the limit a year ago. It was too expensive. The context window was too small. It's kind of insane that we started building this when the context windows were like 4,000 tokens. Like today, our system prompt is more than 4,000 tokens. So yeah, the model is actually very much not a limit anymore. It almost gives me pause because I'm like, I want the model to be a limit. And so no, the integrations are ones, the core capabilities are ones. So for example, we are investing in a system that's basically, I call it like the, it's a J hack. Give me these names, like the poor man's RLHF. So you can turn on a toggle on any step of your Lindy workflow to be like, ask me for confirmation before you actually execute this step. So it's like, hey, I receive an email, you send a reply, ask me for confirmation before actually sending it. And so today you see the email that's about to get sent and you can either approve, deny, or change it and then approve. And we are making it so that when you make a change, we are then saving this change that you're making or embedding it in the vector database. And then we are retrieving these examples for future tasks and injecting them into the context window. So that's the kind of capability that makes a huge difference for users. That's the bottleneck today. It's really like good old engineering and product work.Swyx [00:31:52]: I assume you're hiring. We'll do a call for hiring at the end.Alessio [00:31:54]: Any other comments on the model side? When did you start feeling like the model was not a bottleneck anymore? Was it 4.0? Was it 3.5? 3.5.Flo [00:32:04]: 3.5 Sonnet, definitely. I think 4.0 is overhyped, frankly. We don't use 4.0. I don't think it's good for agentic behavior. Yeah, 3.5 Sonnet is when I started feeling that. And then with prompt caching with 3.5 Sonnet, like that fills the cost, cut the cost again. Just cut it in half. Yeah.Swyx [00:32:21]: Your prompts are... Some of the problems with agentic uses is that your prompts are kind of dynamic, right? Like from caching to work, you need the front prefix portion to be stable.Flo [00:32:32]: Yes, but we have this append-only ledger paradigm. So every node keeps appending to that ledger and every filled node inherits all the context built up by all the previous nodes. And so we can just decide, like, hey, every X thousand nodes, we trigger prompt caching again.Swyx [00:32:47]: Oh, so you do it like programmatically, not all the time.Flo [00:32:50]: No, sorry. Anthropic manages that for us. But basically, it's like, because we keep appending to the prompt, the prompt caching works pretty well.Alessio [00:32:57]: We have this small podcaster tool that I built for the podcast and I rewrote all of our prompts because I noticed, you know, I was inputting stuff early on. I wonder how much more money OpenAN and Anthropic are making just because people don't rewrite their prompts to be like static at the top and like dynamic at the bottom.Flo [00:33:13]: I think that's the remarkable thing about what we're having right now. It's insane that these companies are routinely cutting their costs by two, four, five. Like, they basically just apply constraints. They want people to take advantage of these innovations. Very good.Swyx [00:33:25]: Do you have any other competitive commentary? Commentary? Dust, WordWare, Gumloop, Zapier? If not, we can move on.Flo [00:33:31]: No comment.Alessio [00:33:32]: I think the market is,Flo [00:33:33]: look, I mean, AGI is coming. All right, that's what I'm talking about.Swyx [00:33:38]: I think you're helping. Like, you're paving the road to AGI.Flo [00:33:41]: I'm playing my small role. I'm adding my small brick to this giant, giant, giant castle. Yeah, look, when it's here, we are going to, this entire category of software is going to create, it's going to sound like an exaggeration, but it is a fact it is going to create trillions of dollars of value in a few years, right? It's going to, for the first time, we're actually having software directly replace human labor. I see it every day in sales calls. It's like, Lindy is today replacing, like, we talk to even small teams. It's like, oh, like, stop, this is a 12-people team here. I guess we'll set up this Lindy for one or two days, and then we'll have to decide what to do with this 12-people team. And so, yeah. To me, there's this immense uncapped market opportunity. It's just such a huge ocean, and there's like three sharks in the ocean. I'm focused on the ocean more than on the sharks.Swyx [00:34:25]: So we're moving on to hot topics, like, kind of broadening out from Lindy, but obviously informed by Lindy. What are the high-order bits of good agent design?Flo [00:34:31]: The model, the model, the model, the model. I think people fail to truly, and me included, they fail to truly internalize the bitter lesson. So for the listeners out there who don't know about it, it's basically like, you just scale the model. Like, GPUs go brr, it's all that matters. I think it also holds for the cognitive architecture. I used to be very cognitive architecture-filled, and I was like, ah, and I was like a critic, and I was like a generator, and all this, and then it's just like, GPUs go brr, like, just like let the model do its job. I think we're seeing it a little bit right now with O1. I'm seeing some tweets that say that the new 3.5 SONNET is as good as O1, but with none of all the crazy...Swyx [00:35:09]: It beats O1 on some measures. On some reasoning tasks. On AIME, it's still a lot lower. Like, it's like 14 on AIME versus O1, it's like 83.Flo [00:35:17]: Got it. Right. But even O1 is still the model. Yeah.Swyx [00:35:22]: Like, there's no cognitive architecture on top of it.Flo [00:35:23]: You can just wait for O1 to get better.Alessio [00:35:25]: And so, as a founder, how do you think about that, right? Because now, knowing this, wouldn't you just wait to start Lindy? You know, you start Lindy, it's like 4K context, the models are not that good. It's like, but you're still kind of like going along and building and just like waiting for the models to get better. How do you today decide, again, what to build next, knowing that, hey, the models are going to get better, so maybe we just shouldn't focus on improving our prompt design and all that stuff and just build the connectors instead or whatever? Yeah.Flo [00:35:51]: I mean, that's exactly what we do. Like, all day, we always ask ourselves, oh, when we have a feature idea or a feature request, we ask ourselves, like, is this the kind of thing that just gets better while we sleep because models get better? I'm reminded, again, when we started this in 2022, we spent a lot of time because we had to around context pruning because 4,000 tokens is really nothing. You really can't do anything with 4,000 tokens. All that work was throwaway work. Like, now it's like it was for nothing, right? Now we just assume that infinite context windows are going to be here in a year or something, a year and a half, and infinitely cheap as well, and dynamic compute is going to be here. Like, we just assume all of these things are going to happen, and so we really focus, our job to be done in the industry is to provide the input and output to the model. I really compare it all the time to the PC and the CPU, right? Apple is busy all day. They're not like a CPU wrapper. They have a lot to build, but they don't, well, now actually they do build the CPU as well, but leaving that aside, they're busy building a laptop. It's just a lot of work to build these things. It's interesting because, like,Swyx [00:36:45]: for example, another person that we're close to, Mihaly from Repl.it, he often says that the biggest jump for him was having a multi-agent approach, like the critique thing that you just said that you don't need, and I wonder when, in what situations you do need that and what situations you don't. Obviously, the simple answer is for coding, it helps, and you're not coding, except for, are you still generating code? In Indy? Yeah.Flo [00:37:09]: No, we do. Oh, right. No, no, no, the cognitive architecture changed. We don't, yeah.Swyx [00:37:13]: Yeah, okay. For you, you're one shot, and you chain tools together, and that's it. And if the user really wantsFlo [00:37:18]: to have this kind of critique thing, you can also edit the prompt, you're welcome to. I have some of my Lindys, I've told them, like, hey, be careful, think step by step about what you're about to do, but that gives you a little bump for some use cases, but, yeah.Alessio [00:37:30]: What about unexpected model releases? So, Anthropic released computer use today. Yeah. I don't know if many people were expecting computer use to come out today. Do these things make you rethink how to design, like, your roadmap and things like that, or are you just like, hey, look, whatever, that's just, like, a small thing in their, like, AGI pursuit, that, like, maybe they're not even going to support, and, like, it's still better for us to build our own integrations into systems and things like that. Because maybe people will say, hey, look, why am I building all these API integrationsFlo [00:38:02]: when I can just do computer use and never go to the product? Yeah. No, I mean, we did take into account computer use. We were talking about this a year ago or something, like, we've been talking about it as part of our roadmap. It's been clear to us that it was coming, My philosophy about it is anything that can be done with an API must be done by an API or should be done by an API for a very long time. I think it is dangerous to be overly cavalier about improvements of model capabilities. I'm reminded of iOS versus Android. Android was built on the JVM. There was a garbage collector, and I can only assume that the conversation that went down in the engineering meeting room was, oh, who cares about the garbage collector? Anyway, Moore's law is here, and so that's all going to go to zero eventually. Sure, but in the meantime, you are operating on a 400 MHz CPU. It was like the first CPU on the iPhone 1, and it's really slow, and the garbage collector is introducing a tremendous overhead on top of that, especially a memory overhead. For the longest time, and it's really only been recently that Android caught up to iOS in terms of how smooth the interactions were, but for the longest time, Android phones were significantly slowerSwyx [00:39:07]: and laggierFlo [00:39:08]: and just not feeling as good as iOS devices. Look, when you're talking about modules and magnitude of differences in terms of performance and reliability, which is what we are talking about when we're talking about API use versus computer use, then you can't ignore that, right? And so I think we're going to be in an API use world for a while.Swyx [00:39:27]: O1 doesn't have API use today. It will have it at some point, and it's on the roadmap. There is a future in which OpenAI goes much harder after your business, your market, than it is today. Like, ChatGPT, it's its own business. All they need to do is add tools to the ChatGPT, and now they're suddenly competing with you. And by the way, they have a GPT store where a bunch of people have already configured their tools to fit with them. Is that a concern?Flo [00:39:56]: I think even the GPT store, in a way, like the way they architect it, for example, their plug-in systems are actually grateful because we can also use the plug-ins. It's very open. Now, again, I think it's going to be such a huge market. I think there's going to be a lot of different jobs to be done. I know they have a huge enterprise offering and stuff, but today, ChatGPT is a consumer app. And so, the sort of flow detail I showed you, this sort of workflow, this sort of use cases that we're going after, which is like, we're doing a lot of lead generation and lead outreach and all of that stuff. That's not something like meeting recording, like Lindy Today right now joins your Zoom meetings and takes notes, all of that stuff.Swyx [00:40:34]: I don't see that so farFlo [00:40:35]: on the OpenAI roadmap.Swyx [00:40:36]: Yeah, but they do have an enterprise team that we talk to You're hiring GMs?Flo [00:40:42]: We did.Swyx [00:40:43]: It's a fascinating way to build a business, right? Like, what should you, as CEO, be in charge of? And what should you basically hireFlo [00:40:52]: a mini CEO to do? Yeah, that's a good question. I think that's also something we're figuring out. The GM thing was inspired from my days at Uber, where we hired one GM per city or per major geo area. We had like all GMs, regional GMs and so forth. And yeah, Lindy is so horizontal that we thought it made sense to hire GMs to own each vertical and the go-to market of the vertical and the customization of the Lindy templates for these verticals and so forth. What should I own as a CEO? I mean, the canonical reply here is always going to be, you know, you own the fundraising, you own the culture, you own the... What's the rest of the canonical reply? The culture, the fundraising.Swyx [00:41:29]: I don't know,Flo [00:41:30]: products. Even that, eventually, you do have to hand out. Yes, the vision, the culture, and the foundation. Well, you've done your job as a CEO. In practice, obviously, yeah, I mean, all day, I do a lot of product work still and I want to keep doing product work for as long as possible.Swyx [00:41:48]: Obviously, like you're recording and managing the team. Yeah.Flo [00:41:52]: That one feels like the most automatable part of the job, the recruiting stuff.Swyx [00:41:56]: Well, yeah. You saw myFlo [00:41:59]: design your recruiter here. Relationship between Factorio and building Lindy. We actually very often talk about how the business of the future is like a game of Factorio. Yeah. So, in the instance, it's like Slack and you've got like 5,000 Lindys in the sidebar and your job is to somehow manage your 5,000 Lindys. And it's going to be very similar to company building because you're going to look for like the highest leverage way to understand what's going on in your AI company and understand what levels do you have to make impact in that company. So, I think it's going to be very similar to like a human company except it's going to go infinitely faster. Today, in a human company, you could have a meeting with your team and you're like, oh, I'm going to build a facility and, you know, now it's like, okay,Swyx [00:42:40]: boom, I'm going to spin up 50 designers. Yeah. Like, actually, it's more important that you can clone an existing designer that you know works because the hiring process, you cannot clone someone because every new person you bring in is going to have their own tweaksFlo [00:42:54]: and you don't want that. Yeah.Swyx [00:42:56]: That's true. You want an army of mindless dronesFlo [00:42:59]: that all work the same way.Swyx [00:43:00]: The reason I bring this, bring Factorio up as well is one, Factorio Space just came out. Apparently, a whole bunch of people stopped working. I tried out Factorio. I never really got that much into it. But the other thing was, you had a tweet recently about how the sort of intentional top-down design was not as effective as just build. Yeah. Just ship.Flo [00:43:21]: I think people read a little bit too much into that tweet. It went weirdly viral. I was like, I did not intend it as a giant statement online.Swyx [00:43:28]: I mean, you notice you have a pattern with this, right? Like, you've done this for eight years now.Flo [00:43:33]: You should know. I legit was just hearing an interesting story about the Factorio game I had. And everybody was like, oh my God, so deep. I guess this explains everything about life and companies. There is something to be said, certainly, about focusing on the constraint. And I think it is Patrick Collison who said, people underestimate the extent to which moonshots are just one pragmatic step taken after the other. And I think as long as you have some inductive bias about, like, some loose idea about where you want to go, I think it makes sense to follow a sort of greedy search along that path. I think planning and organizing is important. And having older is important.Swyx [00:44:05]: I'm wrestling with that. There's two ways I encountered it recently. One with Lindy. When I tried out one of your automation templates and one of them was quite big and I just didn't understand it, right? So, like, it was not as useful to me as a small one that I can just plug in and see all of. And then the other one was me using Cursor. I was very excited about O1 and I just up frontFlo [00:44:27]: stuffed everythingSwyx [00:44:28]: I wanted to do into my prompt and expected O1 to do everything. And it got itself into a huge jumbled mess and it was stuck. It was really... There was no amount... I wasted, like, two hours on just, like, trying to get out of that hole. So I threw away the code base, started small, switched to Clouds on it and build up something working and just add it over time and it just worked. And to me, that was the factorial sentiment, right? Maybe I'm one of those fanboys that's just, like, obsessing over the depth of something that you just randomly tweeted out. But I think it's true for company building, for Lindy building, for coding.Flo [00:45:02]: I don't know. I think it's fair and I think, like, you and I talked about there's the Tuft & Metal principle and there's this other... Yes, I love that. There's the... I forgot the name of this other blog post but it's basically about this book Seeing Like a State that talks about the need for legibility and people who optimize the system for its legibility and anytime you make a system... So legible is basically more understandable. Anytime you make a system more understandable from the top down, it performs less well from the bottom up. And it's fine but you should at least make this trade-off with your eyes wide open. You should know, I am sacrificing performance for understandability, for legibility. And in this case, for you, it makes sense. It's like you are actually optimizing for legibility. You do want to understand your code base but in some other cases it may not make sense. Sometimes it's better to leave the system alone and let it be its glorious, chaotic, organic self and just trust that it's going to perform well even though you don't understand it completely.Swyx [00:45:55]: It does remind me of a common managerial issue or dilemma which you experienced in the small scale of Lindy where, you know, do you want to organize your company by functional sections or by products or, you know, whatever the opposite of functional is. And you tried it one way and it was more legible to you as CEO but actually it stopped working at the small level. Yeah.Flo [00:46:17]: I mean, one very small example, again, at a small scale is we used to have everything on Notion. And for me, as founder, it was awesome because everything was there. The roadmap was there. The tasks were there. The postmortems were there. And so, the postmortem was linkedSwyx [00:46:31]: to its task.Flo [00:46:32]: It was optimized for you. Exactly. And so, I had this, like, one pane of glass and everything was on Notion. And then the team, one day,Swyx [00:46:39]: came to me with pitchforksFlo [00:46:40]: and they really wanted to implement Linear. And I had to bite my fist so hard. I was like, fine, do it. Implement Linear. Because I was like, at the end of the day, the team needs to be able to self-organize and pick their own tools.Alessio [00:46:51]: Yeah. But it did make the company slightly less legible for me. Another big change you had was going away from remote work, every other month. The discussion comes up again. What was that discussion like? How did your feelings change? Was there kind of like a threshold of employees and team size where you felt like, okay, maybe that worked. Now it doesn't work anymore. And how are you thinking about the futureFlo [00:47:12]: as you scale the team? Yeah. So, for context, I used to have a business called TeamFlow. The business was about building a virtual office for remote teams. And so, being remote was not merely something we did. It was, I was banging the remote drum super hard and helping companies to go remote. And so, frankly, in a way, it's a bit embarrassing for me to do a 180 like that. But I guess, when the facts changed, I changed my mind. What happened? Well, I think at first, like everyone else, we went remote by necessity. It was like COVID and you've got to go remote. And on paper, the gains of remote are enormous. In particular, from a founder's standpoint, being able to hire from anywhere is huge. Saving on rent is huge. Saving on commute is huge for everyone and so forth. But then, look, we're all here. It's like, it is really making it much harder to work together. And I spent three years of my youth trying to build a solution for this. And my conclusion is, at least we couldn't figure it out and no one else could. Zoom didn't figure it out. We had like a bunch of competitors. Like, Gathertown was one of the bigger ones. We had dozens and dozens of competitors. No one figured it out. I don't know that software can actually solve this problem. The reality of it is, everyone just wants to get off the darn Zoom call. And it's not a good feeling to be in your home office if you're even going to have a home office all day. It's harder to build culture. It's harder to get in sync. I think software is peculiar because it's like an iceberg. It's like the vast majority of it is submerged underwater. And so, the quality of the software that you ship is a function of the alignment of your mental models about what is below that waterline. Can you actually get in sync about what it is exactly fundamentally that we're building? What is the soul of our product? And it is so much harder to get in sync about that when you're remote. And then you waste time in a thousand ways because people are offline and you can't get a hold of them or you can't share your screen. It's just like you feel like you're walking in molasses all day. And eventually, I was like, okay, this is it. We're not going to do this anymore.Swyx [00:49:03]: Yeah. I think that is the current builder San Francisco consensus here. Yeah. But I still have a big... One of my big heroes as a CEO is Sid Subban from GitLab.Flo [00:49:14]: Mm-hmm.Swyx [00:49:15]: Matt MullenwegFlo [00:49:16]: used to be a hero.Swyx [00:49:17]: But these people run thousand-person remote businesses. The main idea is that at some company

Tyler Cowen is an economics professor and blogger at Marginal Revolution. Patrick Collison is the billionaire founder of the online payments company Stripe. In 2019, they wrote an article calling for a discipline of Progress Studies, which would figure out what progress was and how to increase it. Later that year, tech entrepreneur Jason Crawford stepped up to spearhead the effort. The immediate reaction was mostly negative. There were the usual gripes that “progress” was problematic because it could imply that some cultures/times/places/ideas were better than others. But there were also more specific objections: weren't historians already studying progress? Wasn't business academia already studying innovation? Are you really allowed to just invent a new field every time you think of something it would be cool to study? It seems like you are. Five years later, Progress Studies has grown enough to hold its first conference. I got to attend, and it was great. https://www.astralcodexten.com/p/notes-from-the-progress-studies-conference 

When I think of digital biology, I think of Patrick Hsu—he's the prototype, a rarified talent in both life and computer science, who recently led the team that discovered bridge RNAs, what may be considered CRISPR 3.0 for genome editing, and is building new generative A.I. models for life science. You might call them LLLMs-large language of life models. He is Co-Founder and a Core Investigator of the Arc Institute and Assistant Professor of Bioengineering and Deb Faculty Fellow at the University of California, Berkeley.Above is a brief snippet of our conversation. Full videos of all Ground Truths podcasts can be seen on YouTube here. The audios are also available on Apple and Spotify.Here's the transcript with links to the audio and external links to relevant papers and things we discussed.Eric Topol (00:06):Well hello, it's Eric Topol with Ground Truths and I'm really delighted to have with me today Patrick Hsu. Patrick is a co-founder and core investigator at the Arc Institute and he is also on the faculty at the University of California Berkeley. And he has been lighting things up in the world of genome editing and AI and we have a lot to talk about. So welcome, Patrick.Patrick Hsu (00:29):Thanks so much. I'm looking forward to it. Appreciate you having me on, Eric.The Arc InstituteEric Topol (00:33):Well, the first thing I'd like to get into, because you're into so many important things, but one that stands out of course is this Arc Institute with Patrick Collison who I guess if you can tell us a bit about how you two young guys got to meet and developed something that's really quite unique that I think brings together investigators at Stanford, UCSF, and Berkeley. Is that right? So maybe you can give us the skinny about you and Patrick and how all this got going.Patrick Hsu (01:05):Yeah, sure. That sounds great. So we started Arc with Patrick C and with Silvana Konermann, a longtime colleague and chemistry faculty at Stanford about three years ago now, though we've been physically operational just over two years and we're an independent research institute working at the interface of biomedical science and machine learning. And we have a few different aspects of our model, but our overall mission is to understand and treat complex human diseases. And we have three pillars to our model. We have this PI driven side of the house where we centrally fund our investigators so that they don't have to write grants and work on their very best ideas. We have a technical staff side of the house more like you'd see in a frontier AI lab or in biotech industry where we have professional teams of R&D scientists working cross-functionally on higher level organizational wide goals that we call our institute initiatives.(02:05):One focused on Alzheimer's disease experimentally and one that we call a virtual cell initiative to simulate human biology with AI foundation models. And our third pillar over time is to have things not just end up as academic papers, but really get things out into the real world as products or as medicines that can actually help patients on the translational side. And so, we thought that some really important scientific programs could be unlocked by enabling new organizational models and we are experimenting at the institutional scale with how we can better organize and incentivize and support scientists to reach these long-term capability breakthroughs.Patrick, Patrick and SilvanaEric Topol (02:52):So the two Patrick's. How did you, one Patrick I guess is a multi-billionaire from Stripe and then there's you who I suspect maybe not quite as wealthy as the other Patrick, how did you guys come together to do this extraordinary thing?Patrick Hsu (03:08):Yeah, no, science is certainly expensive. I met Patrick originally through Silvana actually. They actually met, so funny trivia, all three Arc founders did high school science together. Patrick and Silvana originally met in the European version of the European Young Scientist competition in high school. And Silvana and I met during our PhDs in her case at MIT and I was at Harvard, but we met at the Broad Institute sort of also a collaborative Harvard, MIT and Harvard hospitals Institute based in Kendall Square. And so, we sort of in various pairwise combinations known each other for decades and worked together for decades and have all collectively been really excited about science and technology and its potential to accelerate societal progress. Yet we also felt in our own ways that despite a lot of the tremendous progress, the structures in which we do this work, fund it, incentivize it and roll it out into the real world, seems like it's really possible that we'll undershoot that potential. And if you take 15 years ago, we didn't have the modern transformer that launched the current AI revolution, CRISPR technology, single-cell, mRNA technology or broadly addressable LNPs. That's a tremendous amount of technologies have developed in the next 15 years. We think there's a real unique opportunity for new institutes in the 2020s to take advantage of all of these breakthroughs and the new ones that are coming to continue to accelerate biological progress but do so in a way that's fast and flexible and really focused.Eric Topol (04:58):Yeah, I did want to talk with you a bit. First of all before I get to the next related topic, I get a kick out of you saying you've worked or known each other for decades because I think you're only in your early thirties. Is that right?Patrick Hsu (05:14):I was lucky to get an early start. I first started doing research at the local university when I was 14 actually, and I was homeschooled actually until college. And so, one of the funny things that you got to do when you're homeschooled is well, you could do whatever you want. And in my case that was work in the lab. And so, I actually worked basically full time as an intern volunteer, cut my teeth in single cell patch clamp, molecular biology, protein biochemistry, two photon and focal imaging and kind of spiraled from there. I loved the lab, I loved doing bench work. It was much more exciting to me than programming computers, which was what I was doing at the time. And I think these sort of two loves have kind of brought me and us to where we are today.Eric Topol (06:07):Before you got to Berkeley and Arc, I know you were at Broad Institute, but did you also pick up formal training in computer science and AI or is that something that was just part of the flow?Patrick Hsu (06:24):So I grew up coding. I used to work through problems sets before dinner growing up. And so, it's just something that you kind of learn natively just like learning French or Mandarin.New Models of Funding Life ScienceEric Topol (06:42):That's what I figured. Okay. Now this model of Arc Institute came along in a kind of similar timeframe as the Arena BioWorks in Boston, where some of the faculty left to go to Arena like my friend Stuart Schreiber and many others. And then of course Priscilla and Mark formed the Chan Zuckerberg Institute and its biohub and its support. So can you contrast for one, these three different models because they're both very different than of course the traditional NIH pathway, how Arc is similar or different to the others, and obviously the goal here is accelerating things that are going to really make a difference.Patrick Hsu (07:26):Yeah, the first thing I would say is zooming out. There have been lots of efforts to experiment with how we do science, the practice of science itself. And in fact, I've recently been reading this book, the Demon Under the Microscope about the history of infectious disease, and it talks about how in the 1910s through the 1930s, these German industrial dye manufacturing companies like Bayer and BASF actually launched what became essentially an early model for industrial scale science, where they were trying to develop Prontosil, Salvarsan and some of these early anti-infectives that targeted streptococcus. And these were some of the major breakthroughs that led to huge medical advances on tackling infectious disease compared to the more academic university bound model. So these trends of industrial versus academic labs and different structures to optimize breakthroughs and applications has been a through current throughout international science for the last century.(08:38):And so, the way that we do research today, and that's some of our core tenets at Arc is basically it hasn't always been this way. It doesn't need to necessarily be this way. And so, I think organizational experiments should really matter. And so, there's CZI, Altos, Arena, Calico, a variety of other organizational experiments and similarly we had MRC and Bell Labs and Xerox PARCS, NIBRT, GNF, Google Research, and so on. And so, I think there are lots of different ways that you can organize folks. I think at a high level you can think about ways that you can play with for-profit versus nonprofit structures. Whether you want to be a completely independent organization or if you want to be partnered with universities. If you want to be doing application driven science or really blue sky curiosity driven work. And I think also thinking through internally the types of expertise that you bring together.(09:42):You can think of it like a cancer institute maybe as a very vertically integrated model. You have folks working on all kinds of different areas surrounding oncology or immunotherapy and you might call that the Tower of Babel model. The other way that folks have built institutes, you might call the lily pad model where you have coverage of as many areas of biomedical research as possible. Places like the Whitehead or Salk, it will be very broad. You'll have planned epigenetics, folks looking at RNA structural biology, people studying yeast cell cycle, folks doing in vivo melanoma models. It's very broad and I think what we try to do at Arc is think about a model that you might liken more to overlapping Viking shields where there's sort of five core areas that we're deeply investing in, in genetics and genomics, computation, neuroscience, immunology and chemical biology. Now we really think of these as five areas that are maybe the minimal critical mass that you would need to make a dent on something as complicated as complex human diseases. It's certainly not the only thing that you need, but we needed a critical mass of investigators working at least in these areas.Eric Topol (11:05):Well, yeah, and they really converge on where the hottest advances are being made these days. Now can you work at Arc Institute without being one of these three universities or is it really that you maintain your faculty and your part of this other entity?Patrick Hsu (11:24):So we have a few elements to even just the academic side of the house. We have our core investigators. I'm one of them, where we have dually appointed faculty who retain their latter rank or tenured appointment in their home department, but their labs are physically cited at the Arc headquarters where we built out a lab in Stanford Research Park in Palo Alto. And so, folks move their labs there. They continue to train graduate students based on whatever graduate programs they're formally affiliated with through their university affiliation. And so, we have nearly 40 PhD students across our labs that are training on site every day.(12:03):So in addition to our core investigators, we also have what we call our innovation investigators, which is more of a grant program to faculty at our partner universities. They receive unrestricted funding from us to seed a new project or accelerate an existing area in their group and their labs stay at their home campus and they just get that funding to augment their work. The third way is our technical staff model where folks basically just come work at Arc and many of them also are establishing their own research groups focusing on technology R&D areas. And so, we have five of those technology centers working in molecular engineering, multi-omics, complex cellular models, in vivo models, and in machine learning.Discovery of Bridge RNAsEric Topol (12:54):Yeah, that's a great structure. In fact, just a few months ago, Patrick Collison, the other Patrick came to Stanford HAI where I'm on the board and you've summarized it really well and it's very different than the other models and other entities, companies included that you mentioned. It's really very impressive. Now speaking of impressive on June 26, this past few months ago, which incidentally is coincident with the draft genome in the year 2000, the human sequence. You and your colleagues, perhaps the most impressive jump in terms of an Arc Institute contribution published two papers back-to-back in Nature about bridge RNA: [Bridge RNAs direct programmable recombination of target and donor DNA] and [Structural mechanism of bridge RNA-guided recombination.] And before I get you to describe this breakthrough in genome editing, some would call it genome editing 3.0 or CRISPR 3.0, whatever. But what we have today in the clinic with the approval of CRISPR 1.0 for sickle cell and thalassemia is actually quite crude. I think most people will know it's just a double stranded DNA cleavage with all sorts of issues about repair and it's not very precise. And so, CRISPR 2.0 is supposed to be represented by David Liu's contributions and his efforts at Broad like prime and base editing and then comes yours. So maybe you can tell us about it and how it is has to be viewed as quite an important advance.Patrick Hsu (14:39):The first thing I would say before CRISPR, is that we had RNA interference. And so, even before this modern genome editing revolution with programmable CRISPRs, we had this technology that had a lot of the core selling points as well. Any target will now become druggable to us. We simply need to reprogram a guide RNA and we can get genetic access to things that are intracellular. And I think both the discovery of RNA interference by Craig Mello and Andy Fire or the invention or discovery of programmable CRISPR technologies, both depend on the same fundamental biological mechanism. These non-coding guide RNAs that are essentially a short RNA search string that you can easily reprogram to retarget a desired enzyme function, and natively both RNAi and CRISPR are molecular scissors. Their RNA or DNA nucleases that can be reprogrammed to different regions of the genome or the transcriptome to make a cut.(15:48):And as bioengineers, we have come up with all kinds of creative ways to leverage the ability to make site specific cuts to do all kinds of incredible things including genome editing or beyond transcriptional up or down regulation, molecular imaging and so on and so forth. And so, the first thing that we started thinking about in our lab was, why would mother nature have stopped only RNAi and CRISPR? There probably are lots of other non-coding RNAs out there that might be able to be programmable and if they did exist, they probably also do more complicated and interesting things than just guide a molecular scissors. So that was sort of the first core kind of intuition that we had. The second intuition that we had on the technology side, I was just wearing my biology hat, I'll put on my technology hat, is the thing that we call genome editing today hardly involves the genome.(16:50):It's really you're making a cut to change an individual base or an individual gene or locus. So really you're doing small scale single locus editing, so you might call it gene level or locus level cuts. And what you really want to be able to do is do things at the genome scale at 100 kb, a megabase at the chromosome scale. And I think that's where I think the field will inevitably go if you follow the technology curves of longer and longer range gene sequencing, longer and longer range gene synthesis, and then longer and longer range gene editing. And so, what would that look like? And we started thinking, could there be essentially recombination technologies that allow you to do cut and paste in a single step. Now, the reason for that is the way that we do gene editing today involves a cut and then a multi-step process of cellular DNA repair that resolves the cut to make the exertion or the error prone deletion or the modification that ends up happening.(17:59):And so, it's very complicated and whether that's nucleases or base or prime editing, you're all generally limited to the small-scale single locus changes. However, there are natural mechanisms that have solved this cut and paste problem, right? There are these viruses or bacterial versions of viruses known as phage that have generally been trying to exert their multi kilobase genomes into bacterial hosts and specialize throughout billions of years. So our core thought was, well, if there are these new non-coding RNAs, what kind of functions would we be excited about? Can we look in these mobile genetic elements, these so-called jumping genes for new mechanisms? They're incredibly widespread. Transposons are thought to be some of the most diverse enzyme mechanisms found in nature. And so, we started computationally by asking ourselves a very simple question. If a mobile element inserts itself into foreign DNA and it's able to somehow be programmable, presumably the inside or something encoded in the inside of the element is predictive of some sequence on the outside of the element.(19:15):And so, that was the core insight we took, and we thought let's look across the boundaries of many different mobile genetic elements and we zoomed in on a particular sub family of these MGE known as insertion sequence (IS) elements which are the most autonomous minimal transposons. Normally transposons have all kinds of genes that they use to hitchhike around the genomic galaxy and endow the bacterial host with some fitness advantage like some ability to metabolize some copper and some host or some metal. And these IS elements have only the enzymes that they need to jump around. And if you identify the boundaries of these using modern computational methods, this is actually a really non-trivial problem. But if you solve that problem to figure out with nucleotide resolution where the element boundaries end and then you look for the open reading frame of the transposases enzyme inside of this element, you'll find that it's not just that coding sequence.(20:19):There are also these non-coding flanks inside of the element boundaries. And when we looked across the non-coding, the entire IS family tree, there are hundreds of these different types of elements. We found that this particular family IS110, had the longest non-coding ends of all IS elements. And we started doing experiments in the lab to try to figure out how these work. And what we found was that these elements are cut and paste elements, so they excise themselves into a circular form and paste themselves back in into a target site linearly. But the circularization of this element brings together two distal ends together, which brings together a -35 and a -10 box that create and reconstitute a canonical bacterial transcriptional promoter. This essentially is like plugging a plug into an electrical socket in the wall and it jacks up transcription. Now you would think this transcription would turn on the transposase enzyme so it can jump around more but it transcribes a non-coding RNA out of this non-coding end.(21:30):We're like, holy crap, are these RNAs actually involved in regulating the transposon? Now the boring answer would be, oh, it regulates the expression. It's like an antisense regulate or something. The exciting answer would be, oh, it's a new type of guide RNA and you found an RNA guided integrase. So we started zooming in bound dramatically on this and we undertook a covariation analysis where we were able to show that this cryptic non-coding RNA has a totally novel guide RNA structure, totally distinct from RNAi or CRISPR guide RNAs. And it had a target site that covaried with the target site of the element. And so we're like, oh wow, this could be a programmable transposase. The second thing that we found was even more surprising, there was a second region of complementarity in that same RNA that recognized the donor sequence, which is the circularized element itself. And so, this was the first example of a bispecific guide RNA, and also the first example of RNA guided self-recognition by a mobile genetic element.Eric Topol (22:39):It's pretty extraordinary because basically you did a systematic assessment of jumping genes or transposons and you found that they contain things that previously were not at all recognized. And then you have a way to program these to edit, change the genome without having to do any cuts or nicks, right?Patrick Hsu (23:05):Yeah. So what we showed in a test tube is when we took this, so-called bridge RNA, which we named because it bridges the target and donor together along with the recombinase enzyme. So the two component system, those are the only two things that you need. They're able to cut and paste DNA and recombine them in a test tube without any DNA repair, meaning that it's independent of cellular DNA repair and it does strand nicking, exchange, junction resolution and religation all in a single mechanism. So that's when we got super excited about its potential applications as bioengineering tool.Eric Topol (23:46):Yeah, it's pretty extraordinary. And have you already gone into in vivo assessment?Patrick Hsu (23:54):Yes, in our initial set of papers, what we showed is that these are programmable and functional or recombinases in a test tube and in bacterial cells. And by reprogramming the target and donor the right way, you can use these enzymes not just for insertion, but also for flipping and cutting out DNA. And so, we actually have in a single mechanism the ability to do bridge editing, if you will, for universal DNA recombination, insertion, excision or inversion, similar to what folks have been doing for decades with Cre recombinase, but with fully programmable recognition sequences. The work that we're doing now in the lab as you can imagine is to adapt these into robust tools for mammalian genome editing, including of course, human genomes. We're excited about this, we're making good progress. The CRISPR has had thousands of labs over the last 10, 15 years working on it to make these therapeutic level potency and selectivity. We're going to work and follow that same blueprint for getting bridge systems to get to that level of performance, but we're on the path and we're very optimistic for the future.Exemplar of Digital BiologyEric Topol (25:13):Yeah, I think it's quite extraordinary and it's a whole different look to what we've been seeing in the CRISPR era for over the past decade and how that's been advancing and getting more specific and less need for repair and being able to be more versatile. But this takes it to yet another dimension. Now, this brings me to the field that when I think of this term digital biology, I think of you and now our mutual acquaintance, Jensen Huang, who everybody knows now. Back some months ago, he wrote and said at a conference, “Where do I think the next amazing revolution is going to come? And this is going to be flat out one of the biggest ones ever. There's no question that digital biology is going to be it. For the first time in human history, biology has the opportunity to be engineering, not science.” So can you critique Jensen? Is he right? And tell us how you conceive the field of digital biology.Patrick Hsu (26:20):If you look at gene therapy today, the core concepts are actually remarkably simple. They're elegant. Of course, you're missing a broken gene, you need to put it back. And that can be curative. Very simple, powerful concept. However, for complex diseases where you don't have just a single gene that goes wrong, in many cases we actually have no idea what to do. And in fact, when you're trying to put in DNA, that's over more than a gene scale. We kind of very quickly run out of ideas. Is it a CAR and a cytokine, a CAR and a cytokine and another thing? And then we're kind of out of ideas. And so, we started thinking in the lab, how can we actually design genomes where it's not just let's reduce the genome into individual Lego blocks, iGem style with promoters and different genes that we just sort of shuffle the Lego blocks around, but actually use AI to design genome sequences.(27:29):So to do that, we thought we would have to first of all, train a model that can learn and decode the foreign language of biology and use that in order to design sequences. And so, we sort of have been training DNA foundation models and virtual cell models at Arc, sort of a major effort of ours where the first thing that we tried was to take a variance of transformer architecture that's used to train ChatGPT from OpenAI, but instead apply this to study the next DNA token, right? Now, the interesting thing about next token prediction in English is that you can actually learn a surprising amount of information by just predicting the next word. You can learn world knowledge is the capital of Azerbaijan, is it Baku or is it London, right? Or if you're walking around in the kitchen, then the next text is, I then left the kitchen or the bathroom, right?(28:33):Now you're learning about spatial reasoning, and so you can also learn translation obviously. And so similarly, I think predicting the next token or the next base and DNA can lead you to learn about molecular biochemistry, is the next amino acid residue, hydrophobic or hydrophilic. And it can teach you about the mechanics of some catalytic binding pocket or something. You can learn about a disease mutation. Is the next base, the sick linked base or the wild type base and so on and so forth. And what we found was that at massive scale, DNA foundation models learn about molecular function, not just at the DNA level, but also at the RNA and the protein. And indeed, we could use these to design molecular systems like CRISPR-Cas systems, where you have a protein and the guide RNA. It could also design new DNA transposons, and we could design sequences that look plausibly like real genomes, where we generate a megabase a million bases of continuous genome sequence. And it really looks and feels like it could be a blurry picture of something that you would actually sequence. This has been a wonderful collaboration with Brian Hie, a PI at Stanford and an Arc investigator, and we're really excited about what we've seen in this work because it promises the better performance with even more scale. And so, simply by scaling up these models, by adding in more compute, more training data or more powerful models, they're going to get sharper and sharper.New A.I. Models in Life ScienceEric Topol (30:25):Yeah. Well, this whole use of large language models for the language of life, whether it's the genome proteins and on and on, actually RNA and even cells has really taken root. And of course, this is really one of the foundations of that field of digital biology, which brings together generative AI, AI tools and trying to push forward our understanding in biology. And also, obviously what's been emphasized in drug discovery, perhaps it's been emphasized even too much because we still have a lot to learn about biology, but that gets me to these models. Like today, AlphaProteo was announced by DeepMind, as we all know, AlphaFold 1, 2, now 3. They were kind of precursors of being able to predict proteins from amino acid 3D structure. And that kind of took the field by a little bit like ChatGPT for life science, but now it's a new model all the time. So you've been working on various models and Arc Institute, how do you see this unfolding? Are we just going to have every aspect of the language of life being approached in all the different interactions? And this is going to help us get to a much more deep level of understanding.Patrick Hsu (31:56):I'll say two things. The first is a lot of models that you just described are what I would call task specific models. A model for de novo design of a binder, a model for protein structure prediction. And there are other models for protein fitness or for RNA structure prediction, et cetera, et cetera. And I think what we're going to move towards are more unifying models where there's different classes of models at different levels of scale. So we will have these atomic level models for looking at generative chemistry or ligand docking. We have models that can unify genomes and their molecules, and then we have models that can unify cells and tissues. And so, for example, if you took an H&E stain of some liver, there are folks building models where you can then predict what the single cell spatial transcriptome will look like of that model. And that's obviously operating at a very different level of abstraction than a de novo protein binder. But in the long run, all of these are going to get, I think unified. I think the reason why this is possible is that biology, unlike physics, actually has this unifying theory of evolution that runs across all of its length scales from atomic, molecular, cellular, organismal to entire ecosystem. And the promise of these models is no short then to make biology a predictive discipline.Patrick Hsu (33:37):In physics, the experimentalists win the big prizes for the theorists when they measure gravitational waves or whatever. But in biology, we're very practical people. You do something three times and do a T-test. And I think my prediction is we can actually gauge the success of these LLMs or whatever in biology by how much we respect theory in this field.The A.I. ScientistEric Topol (34:05):Yeah. Well, that's a really interesting perspective, an important perspective because the proliferation of models, which we're going to get into not just doing the things that you described, but also being able to be “pseudo” scientists, the so-called AI scientist. Maybe you could comment about that concept because that's been the idea that everything from the question that could be asked to the hypothesis and the experiment design and the analysis of data and then the feedback. So what is the role of the scientists, that seems to have been overplayed? And maybe you can put that in context.Patrick Hsu (34:48):So yeah, right now there's a lot of excitement that we can use AI agents not just to do software enterprise workflows, but to be a research assistant. And then over time, itself an autonomous research scientist that can read the literature, come up with an idea, maybe run a bunch of robots in the lab or do a bunch of computational analyses and then potentially even analyze data, conclude what is going on and actually write an entire paper. Now, I think the vision of this is compelling in the long term. I think the question is really about timescale. If you break down the scientific method into its constituent parts, like hypothesis generation, doing an experiment, analyzing experiment and iterating, we're clearly going to use AI of some kind at every single step of this cycle. I think different steps will require different levels of maturity. The way that I would liken this is just wet lab automation, folks have dreamed about having pipetting robots that just do their western blots and do their cell culture for them for generations.(36:01):But of course, today they don't actually really feel fundamentally different from the same ones that we had in the 90s, let's say. Right? And so, obviously they're getting better, but it seems to me one of the trends I'm very bullish about is the explosion of humanoid robots and robot foundation models that have a world model and a sense of physics and proportionate space loaded onto them. Within five years, we're going to have home robots that can fold your clothes, that can organize your kitchen and do all of this while you're sleeping, so you wake up to a clean home every day.Eric Topol (36:40):It's not going to be just Roomba anymore. There's going to be a lot more, but it isn't just the hardware, it's also the agents playing in software, right?Patrick Hsu (36:50):It's the integrated loop of the hardware and the software where the ability to make the same machine generally intelligent will make it adaptable to a broad array of tasks. Now, what I'm excited about is those generally intelligent humanoid robots coming into the lab, where instead of creating a centrifuge or a new type of pipetter that's optimized for your Beckman or Hamilton device, instead you just have robot arms that you snap onto the edge of the bench and then they just work alongside you. And I do think that's coming, although it'll take a lot of hardware and software and computer vision engineering to make that possible.A Sense of HumorEric Topol (37:32):Yeah, and I think also going back to originating the question, there still is quite a debate about the creativity and the lack of any simulation of AGI, whatever that means anymore. And so, the human in the loop part of this is obviously I think it's still of critical nature. Now, the other thing I learned about you is you have a great sense of humor, which is really important by the way. And recently, which is great that you're active on X or Twitter because that's one way we get to see what you're thinking on a day-to-day basis. But I think you put out a poll which was really quite provocative , and it was about, here's what it said, “do more people in the world *truly* understand transformers or health insurance?” And interestingly, you got 49% for transformers at 51% for health insurance. Can you tell us what you're thinking when you put that poll together? Because obviously a lot of people don't understand either of these.Patrick Hsu (38:44):I think the core question is, there are different ways of looking at the world, some of which are very bottom up and some of which are very top down. And one of the very surprising things about transformers is they're taking something that is in principle, an incredibly simple task, which is if you have a string of text, what is the next letter? And somehow at massive, massive scale, you can unlock something that looks an awful lot like reasoning, and you've got these emergent behaviors. Now the bottoms up theory of just the linear algebra that's going on in these models couldn't possibly really help us predict that we have these emerging capabilities. And I think similarly in healthcare, there's a literal set of parts that are operating in some complex way that at massive scale becomes this incredibly confusing and dynamic system for how we can actually incentivize how we make medicines, how we actually take care of people, and how we actually pay for any of this from an economic point of view. And so, I think it was, in some sense if transformers can actually be an explainable by just linear algebra equations, maybe there will be a way to decompose the seemingly incredibly confusing world of healthcare in order to actually build a better way forward.Computing Power and the GPU Arms RaceEric Topol (40:12):Yeah. Well that's great. Now the other thing I wanted to ask you about, we open source and the arms race of GPUs and this whole kind of idea is you touched on the need for coalescing a lot of these tools to exploit the synergy. But we have an issue because many academic labs like here at Scripps Research and so many others, including as I learned even at Stanford, have limited access to GPUs. So computing power of large language models is a problem. And then the models that exist today that can be adopted like Llama or others, and they're somewhat limited. And then we also have a movement towards trying to make things more open source, like for example, recently OpenCRISPR with Profluent Bio that is basically trying to use AI for CRISPR guides. And so, how do you deal with this arms race, computing power, open source, proprietary models that are not easily accessible without a lot of resources?Patrick Hsu (41:30):So the first thing I would say is, we are in the academic science sphere really unprepared for the level of resources that are required for doing this type of cutting edge computational work. There are top Stanford computer science professors or computational researchers who have a single GPU in their office, and that's actually what their whole lab runs off of.(41:58):The UC Berkeley campus, the grid runs on something like 12 megawatts of power and how are they going to build an on-premises GPU clusters, like a central question that can scale across the entire needs? And these are two of the top computer science universities in the world. And so, I think one of our kind of core beliefs at Arc is, as science both experimentally and computationally has gotten incredibly complex, not just in terms of conceptually, but also just the actual infrastructure and machines and know-how that you need to do things. We actually need to essentially support this. So we have a private GPU cloud that we use to train our models, and we have access to significantly large clusters for large burst kind of train outs as necessary. And I think infrastructurally for running genomics experiments or doing scalable brain organoid screens, right, we're also building out the infrastructure to support that experimentally.Eric Topol (43:01):Yeah, no, I think this is one of the advantages of the new model like the Arc Institute because not many centers have that type of plasticity with access to computing power when needed. So that's where a brilliant mind you and the Arc Institute together makes for a formidable recipe for future advances and of course building on the ones you've already accomplished.The Primacy of Human TalentPatrick Hsu (43:35):I would just say, my main skill, if I have one, is to recruit really, really smart people. And so, everything that you're seeing and hearing about is the work of unbelievable colleagues who are curious, passionate, and incredible scientists.Eric Topol (43:53):But it also takes the person who can judge those who are in that category set as a role model. And you're certainly doing that. I guess just in closing, I mean, it's just such a delight to get to meet you here and kind of get your thoughts on what is the hottest thing in life science without question, which brings together the fields of AI and what's going on, not just obviously in genome editing, but this digital biology era that we're still in the early phases of, I mean, I think you could say that it's just going to continue to accelerate the exponential curve. We're still kind of on the bottom of that, I would imagine where we're headed. Any other things that you want to bring up that I haven't touched on that will round out this conversation?Patrick Hsu (44:50):I mean, I think it's very early days here at Arc.Patrick Hsu (44:53):When we founded Arc, we asked ourselves, how do we measure success? We don't have customers or revenue in the way that a typical startup does. And we felt sort of three things. The first was research institutes live and die by their talent. Can we actually hire incredible people when we make offers to people we want to come, do they come? The second was, when those folks do come to Arc, do they feel like they're able to work on important research programs that they couldn't do sort of at their prior university or company? And then longer term, the third thing was, and there's just no shortcut around this, you need to do important work. And I think we've been really excited that there are early signs that we're able to do all three of these things, and we're still, again, just following the same scaling laws that we're seeing in natural language and vision, but for the domain of biology. And so, we're excited about what's ahead and think if there are folks who are interested in learning more about Arc, just shoot me an email or DM.Eric Topol (46:07):Yeah, well I would just say, congratulations on what you've already achieved. I know you're going to keep rocking it because you already have in a short time. And for anybody who doesn't know about Arc Institute and your work and your team, I hope this is going to be putting them on notice actually what can be accomplished outside of the usual NIH funded model, which is kind of a risk-free zone where you basically have to have your results nailed down before you send in your proposal frequently, and it doesn't do great things for young people. Really, I think you actually qualify in that demographic where it's hard for them to break in for getting NIH grants and also for this type of work that you're doing. So we'll look for the next bridge beyond bridge RNAs of your just fantastic efforts. So Patrick, thanks so much for joining us today, and we'll be checking back with you and following all the great work that you'll be doing in the times ahead.Patrick Hsu (47:14):Thanks so much, Eric. It was such a pleasure to be here today. Appreciate the opportunity.*******************Thanks for listening, reading or watching!The Ground Truths newsletters and podcasts are all free, open-access, without ads.Please share this post/podcast with your friends and network if you found it informative!Voluntary paid subscriptions all go to support Scripps Research. Many thanks for that—they greatly help fund our summer internship programs.Thanks to my producer Jessica Nguyen and Sinjun Balabanoff for audio and video support at Scripps Research.Note: you can select preferences to receive emails about newsletters, podcasts, or all I don't want to bother you with an email for content that you're not interested in. Get full access to Ground Truths at erictopol.substack.com/subscribe

When Y Combinator's Paul Graham released his viral essay "Founder Mode," it sparked a firestorm in the tech world. Based on a private talk by Airbnb's Brian Chesky and endorsed by the likes of Elon Musk and Patrick Collison, the piece garnered over 20 million views. Enter Jim Cook, legendary Silicon Valley CFO (Netflix, Intuit, Mozilla) who just wrote a counterargument to set the record straight. Cook challenges the simplistic notion of founder supremacy — where only 10% succeed — and offers a different Leadership Mode framework for building high-performance, generational companies.

In this episode, I'm joined by product and leadership expert Shreyas Doshi to dissect Founder Mode, why it's appealing, and how to activate it. We dive deep into Paul Graham's recent essay which struck a chord in the tech community and resonated strongly with many founders and leaders.We also discuss:Why founder mode is a mindset, not a titleWhether founder mode is good or badBalancing detail and delegationThe importance of product sense and good judgmentMastering founder mode as a product leaderOperational insights from Meta and StripeReferenced:Crafting a compelling career story: https://www.youtube.com/watch?v=0Reh9wTUIYc&t=928sPaul Graham's "Founder Mode": https://paulgraham.com/foundermode.htmlShreyas' Tweet on founder mode': https://x.com/shreyas/status/1830767630917214318Six superpowers of product managers: https://www.youtube.com/watch?v=OnsSwHP3d-cShreyas' previous appearance on the podcast: https://www.youtube.com/watch?v=y_TnXtnY3QM&t=23sThe 3 types of product leaders: https://x.com/shreyas/status/1375491623308550144Where to find Shreyas:Twitter/XLinkedInYouTubeWhere to find Nikhyl:Twitter/XLinkedInFind The Skip:WebsiteSubstackYouTubeSpotifyApple PodcastsTikTokDon't forget to subscribe to The Skip to hear me coach you through timely career lessons. If you're interested in joining me on a future call, send me a note on LinkedIn, Threads, or Twitter. You can also email me at nikhyl@skip.communityTimestamps(00:00) Teaser: Unpacking founder mode(02:47) What Shreyas has been up to(04:04) Shreyas' take on founder mode(08:59) Why judgment and product sense is critical(13:04) Don't confuse founder mode with micromanagement(20:57) The key question for founders about ownership(23:01) Not every company needs a CPO or Head of Product(28:07) When product people should prioritize detail(31:32) What everyone gets wrong about Steve Jobs(34:22) Shreyas' observation about John and Patrick Collison(38:17) Nikhyl's observation about Mark Zuckerberg(40:05) Founder vs manager mode(43:40) Should leaders avoid manager mode?(48:17) Chase impact, not optics(57:00) The 3 types of product leaders(60:46) Aligning your environment, opinion, and superpower(63:10) Shreyas' non-consensus view on building product(67:52) Mastering founder mode as a PM(72:58) Getting in touch with Shreyas(74:49) How to find Nikhyl

Lenny's Podcast: Product | Growth | Career ✓ Claim Key Takeaways Check out the episode pageRead the full notes @ podcastnotes.orgMike Maples, Jr. is a legendary early-stage startup investor and a co-founder and partner at Floodgate. He's made early bets on transformative companies like Twitter, Lyft, Twitch, Okta, Rappi, and Applied Intuition and is one of the pioneers of seed-stage investing as a category. He's been on the Forbes Midas List eight times and enjoys sharing the lessons he's learned from his years studying iconic companies. In his new book, Pattern Breakers: Why Some Start-Ups Change the Future, co-authored with Peter Ziebelman, he discusses what he's found separates startups and founders that break through and change the world from those that don't. After spending years reviewing the notes and decks from the thousands of startups he's known over the past two decades, he's uncovered three ways that breakthrough founders think and act differently. In our conversation, Mike talks about:• The three elements of breakthrough startup ideas• Why you need to both think and act differently• How to avoid the “comparison trap” and “conformity trap”• The importance of movements, storytelling, and healthy disagreeableness in startup success• How to apply pattern-breaking principles within large companies• Mike's one piece of advice for founders• Much morePre-order Mike's book here and get a second signed copy for free. Limited copies are available, so order ASAP: patternbreakers.com/lenny.—Brought to you by:• Enterpret—Transform customer feedback into product growth• Anvil—The fastest way to build software for documents• Webflow—The web experience platform—Find the transcript at: https://www.lennysnewsletter.com/p/how-to-find-a-great-startup-idea-mike-maples-jr—Where to find Mike Maples, Jr.:• X: https://x.com/m2jr• LinkedIn: https://www.linkedin.com/in/maples/• Substack: https://greatness.substack.com/• Website: https://www.floodgate.com/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Mike's background(03:10) The inspiration behind Pattern Breakers(08:09) Uncovering startup insights(11:37) A quick summary of Pattern Breakers(13:52) Coming up with an idea(15:30) Inflections(17:09) Examples of inflections(28:10) Insights(36:58) The power of surprises(47:36) Founder-future fit(55:33) Advice for aspiring founders(56:41) Living in the future: valid opinions(55:34) Case study: Maddie Hall and Living Carbon(58:40) Identifying lighthouse customers(01:00:53) The importance of desperation in customer needs(01:03:57) Creating movements and storytelling(01:24:22) The role of disagreeableness in startups(01:34:42) Applying these principles within a company(01:40:43) Lightning round—Referenced:• Pattern Breakers: Why Some Start-Ups Change the Future: https://www.amazon.com/Pattern-Breakers-Start-Ups-Change-Future/dp/1541704355• Justin.tv: https://en.wikipedia.org/wiki/Justin.tv• Airbnb's CEO says a $40 cereal box changed the course of the multibillion-dollar company: https://fortune.com/2023/04/19/airbnb-ceo-cereal-box-investors-changed-everything-billion-dollar-company/• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• The Unconventional Exit: How Justin Kan Sold His First Startup on eBay: https://medium.datadriveninvestor.com/the-unconventional-exit-how-justin-kan-sold-his-first-startup-on-ebay-4d705afe1354• Kyle Vogt on LinkedIn: https://www.linkedin.com/in/kylevogt/• The State of Telehealth Before and After the COVID-19 Pandemic: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035352/• The Craigslist Killers: https://www.gq.com/story/craigslist-killers• The social radar: Y Combinator's secret weapon | Jessica Livingston (co-founder of Y Combinator, author, podcast host): https://www.lennysnewsletter.com/p/the-social-radar-jessica-livingston• Michael Seibel on LinkedIn: https://www.linkedin.com/in/mwseibel/• The Airbnb Story: How Three Ordinary Guys Disrupted an Industry, Made Billions ... and Created Plenty of Controversy: https://www.amazon.com/Airbnb-Story-Ordinary-Disrupted-Controversy/dp/0544952669• Scott Cook: https://www.forbes.com/profile/scott-cook/• Chegg: https://www.chegg.com/• Aayush Phumbhra on LinkedIn: https://www.linkedin.com/in/aayush/• Osman Rashid on LinkedIn: https://www.linkedin.com/in/osmanrashid/• Okta: https://www.okta.com/• The Man Who Makes the Future: Wired Icon Marc Andreessen: https://www.wired.com/2012/04/ff-andreessen/• Peter Ludwig on LinkedIn: https://www.linkedin.com/in/peterwludwig/• Qasar Younis on LinkedIn: https://www.linkedin.com/in/qasar/• Paul Allen's website: https://paulallen.com/• Louis Pasteur quote: https://www.forbes.com/quotes/6145/• What was Atrium and why did it fail? https://www.failory.com/cemetery/atrium• Patrick Collison on LinkedIn: https://www.linkedin.com/in/patrickcollison/• Drew Houston on LinkedIn: https://www.linkedin.com/in/drewhouston/• William Gibson's quote: https://www.goodreads.com/quotes/681-the-future-is-already-here-it-s-just-not-evenly• Maddie Hall on LinkedIn: https://www.linkedin.com/in/maddie-hall-76293135/• Living Carbon: https://www.livingcarbon.com• Zenefits (now Trinet): https://connect.trinet.com/• Sam Altman on X: https://x.com/sama• Steve Wozniak on LinkedIn: https://www.linkedin.com/in/wozniaksteve/• Horsley Bridge Partners: https://www.horsleybridge.com/• David Swensen: https://en.wikipedia.org/wiki/David_F._Swensen• Judith Elsea on LinkedIn: https://www.linkedin.com/in/judithelsea/• 7 Powers: The Foundations of Business Strategy: https://www.amazon.com/7-Powers-Foundations-Business-Strategy/dp/0998116319• Business strategy with Hamilton Helmer (author of 7 Powers): https://www.lennysnewsletter.com/p/business-strategy-with-hamilton-helmer• Lyft's Focus on Community and the Story Behind the Pink Mustache: https://techcrunch.com/2012/09/17/lyfts-focus-on-community-and-the-story-behind-the-pink-mustache/• Logan Green on LinkedIn: https://www.linkedin.com/in/logangreen/• John Zimmer on LinkedIn: https://www.linkedin.com/in/johnzimmer11/• Storytelling with Nancy Duarte: How to craft compelling presentations and tell a story that sticks: https://www.lennysnewsletter.com/p/storytelling-with-nancy-duarte-how• Steve Jobs Introducing the iPhone at MacWorld 2007: https://www.youtube.com/watch?v=x7qPAY9JqE4• Jonathan Livingston Seagull: https://www.amazon.com/Jonathan-Livingston-Seagull-Richard-Bach/dp/0743278909• The paths to power: How to grow your influence and advance your career | Jeffrey Pfeffer (author of 7 Rules of Power, professor at Stanford GSB): https://www.lennysnewsletter.com/p/the-paths-to-power-jeffrey-pfeffer• Robin Roberts on LinkedIn: https://www.linkedin.com/in/robin-roberts-393a934b/• Skunkworks: https://www.lockheedmartin.com/en-us/who-we-are/business-areas/aeronautics/skunkworks.html• Vision, conviction, and hype: How to build 0 to 1 inside a company | Mihika Kapoor (Product at Figma): https://www.lennysnewsletter.com/p/vision-conviction-hype-mihika-kapoor• Hard-won lessons building 0 to 1 inside Atlassian | Tanguy Crusson (Head of Jira Product Discovery): https://www.lennysnewsletter.com/p/building-0-to-1-inside-atlassian-tanguy-crusson• Figma: https://www.figma.com/• Atlassian: https://www.atlassian.com/• Vinod Khosla: https://www.khoslaventures.com/team/vinod-khosla/• Top Five Regrets of the Dying: A Life Transformed by the Dearly Departing: https://www.amazon.com/Top-Five-Regrets-Dying-Transformed-ebook/dp/B07KNRLY1L• Chase, Chance, and Creativity: The Lucky Art of Novelty: https://www.amazon.com/Chase-Chance-Creativity-Lucky-Novelty/dp/0262511355• Clay Christensen's books: https://www.amazon.com/stores/Clayton-M.-Christensen/author/B000APPD3Y• Resonate: Present Visual Stories That Transform: https://www.amazon.com/Resonate-Present-Stories-Transform-Audiences/dp/0470632011• Ferrari on Prime: https://www.amazon.com/Ferrari-Adam-Driver/dp/B0CNDBN672• Montblanc fountain pens: https://www.montblanc.com/en-us—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Lenny's Podcast: Product | Growth | Career ✓ Claim Key Takeaways Check out the episode pageRead the full notes @ podcastnotes.orgMike Maples, Jr. is a legendary early-stage startup investor and a co-founder and partner at Floodgate. He's made early bets on transformative companies like Twitter, Lyft, Twitch, Okta, Rappi, and Applied Intuition and is one of the pioneers of seed-stage investing as a category. He's been on the Forbes Midas List eight times and enjoys sharing the lessons he's learned from his years studying iconic companies. In his new book, Pattern Breakers: Why Some Start-Ups Change the Future, co-authored with Peter Ziebelman, he discusses what he's found separates startups and founders that break through and change the world from those that don't. After spending years reviewing the notes and decks from the thousands of startups he's known over the past two decades, he's uncovered three ways that breakthrough founders think and act differently. In our conversation, Mike talks about:• The three elements of breakthrough startup ideas• Why you need to both think and act differently• How to avoid the “comparison trap” and “conformity trap”• The importance of movements, storytelling, and healthy disagreeableness in startup success• How to apply pattern-breaking principles within large companies• Mike's one piece of advice for founders• Much morePre-order Mike's book here and get a second signed copy for free. Limited copies are available, so order ASAP: patternbreakers.com/lenny.—Brought to you by:• Enterpret—Transform customer feedback into product growth• Anvil—The fastest way to build software for documents• Webflow—The web experience platform—Find the transcript at: https://www.lennysnewsletter.com/p/how-to-find-a-great-startup-idea-mike-maples-jr—Where to find Mike Maples, Jr.:• X: https://x.com/m2jr• LinkedIn: https://www.linkedin.com/in/maples/• Substack: https://greatness.substack.com/• Website: https://www.floodgate.com/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Mike's background(03:10) The inspiration behind Pattern Breakers(08:09) Uncovering startup insights(11:37) A quick summary of Pattern Breakers(13:52) Coming up with an idea(15:30) Inflections(17:09) Examples of inflections(28:10) Insights(36:58) The power of surprises(47:36) Founder-future fit(55:33) Advice for aspiring founders(56:41) Living in the future: valid opinions(55:34) Case study: Maddie Hall and Living Carbon(58:40) Identifying lighthouse customers(01:00:53) The importance of desperation in customer needs(01:03:57) Creating movements and storytelling(01:24:22) The role of disagreeableness in startups(01:34:42) Applying these principles within a company(01:40:43) Lightning round—Referenced:• Pattern Breakers: Why Some Start-Ups Change the Future: https://www.amazon.com/Pattern-Breakers-Start-Ups-Change-Future/dp/1541704355• Justin.tv: https://en.wikipedia.org/wiki/Justin.tv• Airbnb's CEO says a $40 cereal box changed the course of the multibillion-dollar company: https://fortune.com/2023/04/19/airbnb-ceo-cereal-box-investors-changed-everything-billion-dollar-company/• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• The Unconventional Exit: How Justin Kan Sold His First Startup on eBay: https://medium.datadriveninvestor.com/the-unconventional-exit-how-justin-kan-sold-his-first-startup-on-ebay-4d705afe1354• Kyle Vogt on LinkedIn: https://www.linkedin.com/in/kylevogt/• The State of Telehealth Before and After the COVID-19 Pandemic: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035352/• The Craigslist Killers: https://www.gq.com/story/craigslist-killers• The social radar: Y Combinator's secret weapon | Jessica Livingston (co-founder of Y Combinator, author, podcast host): https://www.lennysnewsletter.com/p/the-social-radar-jessica-livingston• Michael Seibel on LinkedIn: https://www.linkedin.com/in/mwseibel/• The Airbnb Story: How Three Ordinary Guys Disrupted an Industry, Made Billions ... and Created Plenty of Controversy: https://www.amazon.com/Airbnb-Story-Ordinary-Disrupted-Controversy/dp/0544952669• Scott Cook: https://www.forbes.com/profile/scott-cook/• Chegg: https://www.chegg.com/• Aayush Phumbhra on LinkedIn: https://www.linkedin.com/in/aayush/• Osman Rashid on LinkedIn: https://www.linkedin.com/in/osmanrashid/• Okta: https://www.okta.com/• The Man Who Makes the Future: Wired Icon Marc Andreessen: https://www.wired.com/2012/04/ff-andreessen/• Peter Ludwig on LinkedIn: https://www.linkedin.com/in/peterwludwig/• Qasar Younis on LinkedIn: https://www.linkedin.com/in/qasar/• Paul Allen's website: https://paulallen.com/• Louis Pasteur quote: https://www.forbes.com/quotes/6145/• What was Atrium and why did it fail? https://www.failory.com/cemetery/atrium• Patrick Collison on LinkedIn: https://www.linkedin.com/in/patrickcollison/• Drew Houston on LinkedIn: https://www.linkedin.com/in/drewhouston/• William Gibson's quote: https://www.goodreads.com/quotes/681-the-future-is-already-here-it-s-just-not-evenly• Maddie Hall on LinkedIn: https://www.linkedin.com/in/maddie-hall-76293135/• Living Carbon: https://www.livingcarbon.com• Zenefits (now Trinet): https://connect.trinet.com/• Sam Altman on X: https://x.com/sama• Steve Wozniak on LinkedIn: https://www.linkedin.com/in/wozniaksteve/• Horsley Bridge Partners: https://www.horsleybridge.com/• David Swensen: https://en.wikipedia.org/wiki/David_F._Swensen• Judith Elsea on LinkedIn: https://www.linkedin.com/in/judithelsea/• 7 Powers: The Foundations of Business Strategy: https://www.amazon.com/7-Powers-Foundations-Business-Strategy/dp/0998116319• Business strategy with Hamilton Helmer (author of 7 Powers): https://www.lennysnewsletter.com/p/business-strategy-with-hamilton-helmer• Lyft's Focus on Community and the Story Behind the Pink Mustache: https://techcrunch.com/2012/09/17/lyfts-focus-on-community-and-the-story-behind-the-pink-mustache/• Logan Green on LinkedIn: https://www.linkedin.com/in/logangreen/• John Zimmer on LinkedIn: https://www.linkedin.com/in/johnzimmer11/• Storytelling with Nancy Duarte: How to craft compelling presentations and tell a story that sticks: https://www.lennysnewsletter.com/p/storytelling-with-nancy-duarte-how• Steve Jobs Introducing the iPhone at MacWorld 2007: https://www.youtube.com/watch?v=x7qPAY9JqE4• Jonathan Livingston Seagull: https://www.amazon.com/Jonathan-Livingston-Seagull-Richard-Bach/dp/0743278909• The paths to power: How to grow your influence and advance your career | Jeffrey Pfeffer (author of 7 Rules of Power, professor at Stanford GSB): https://www.lennysnewsletter.com/p/the-paths-to-power-jeffrey-pfeffer• Robin Roberts on LinkedIn: https://www.linkedin.com/in/robin-roberts-393a934b/• Skunkworks: https://www.lockheedmartin.com/en-us/who-we-are/business-areas/aeronautics/skunkworks.html• Vision, conviction, and hype: How to build 0 to 1 inside a company | Mihika Kapoor (Product at Figma): https://www.lennysnewsletter.com/p/vision-conviction-hype-mihika-kapoor• Hard-won lessons building 0 to 1 inside Atlassian | Tanguy Crusson (Head of Jira Product Discovery): https://www.lennysnewsletter.com/p/building-0-to-1-inside-atlassian-tanguy-crusson• Figma: https://www.figma.com/• Atlassian: https://www.atlassian.com/• Vinod Khosla: https://www.khoslaventures.com/team/vinod-khosla/• Top Five Regrets of the Dying: A Life Transformed by the Dearly Departing: https://www.amazon.com/Top-Five-Regrets-Dying-Transformed-ebook/dp/B07KNRLY1L• Chase, Chance, and Creativity: The Lucky Art of Novelty: https://www.amazon.com/Chase-Chance-Creativity-Lucky-Novelty/dp/0262511355• Clay Christensen's books: https://www.amazon.com/stores/Clayton-M.-Christensen/author/B000APPD3Y• Resonate: Present Visual Stories That Transform: https://www.amazon.com/Resonate-Present-Stories-Transform-Audiences/dp/0470632011• Ferrari on Prime: https://www.amazon.com/Ferrari-Adam-Driver/dp/B0CNDBN672• Montblanc fountain pens: https://www.montblanc.com/en-us—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Jeff Weinstein is a product lead at Stripe, where he helped grow their payment APIs to hundreds of billions in volume and transformed the way founders start companies into a few simple clicks with Atlas. Prior to Stripe, Jeff led several startups and sold companies to Groupon and Box. He's known for his customer obsession, craft, quality, and building beloved products businesses rely on. In our conversation, we discuss:• The power of customer obsession and how to operationalize it in the product development process• How to pick the right metrics and use them to drive impact• Techniques for getting things done at big companies• A group practice Jeff started to uplevel product craft, called Study Group• The story behind Stripe Atlas and its mission to increase entrepreneurship globally• Lessons from working with the founders of Stripe—Brought to you by:• Pendo—The all-in-one platform for product-led companies building breakthrough digital experiences• Cycle—Your feedback hub, on autopilot• Anvil—The fastest way to build software for documents—Find the transcript at: https://www.lennysnewsletter.com/p/creating-a-culture-of-excellence—Where to find Jeff Weinstein:• X: https://x.com/jeff_weinstein• LinkedIn: https://www.linkedin.com/in/jeffwweinstein/• Email: jweinstein@gmail.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Jeff's background (10:16)  The “go, go, go ASAP + optimistic, long-term compounding” approach(15:38) The importance of craft and quality(24:15) Effective customer communication strategies(28:57) The importance of speed in customer interactions (33:19) Narrowing your focus(36:53) Why you should pay attention only to paying-customer feedback(40:24) Practicing silence when communicating (45:33) The role of metrics in product success(54:08) Empowering teams with a single metric(58:23) Picking the right metric for your audience(01:05:10) The importance of metric hygiene(01:11:33) How Stripe uses “study groups” for product improvement(01:37:20) Stripe's Atlas: simplifying company formation(01:50:38) Automation and operational efficiency(01:55:13) Diversity and team building(02:03:09) Building new products within a large company(02:21:10) Lightning round—Referenced:• Atlas: https://stripe.com/atlas• Stripe: https://stripe.com/• SQL: https://en.wikipedia.org/wiki/SQL• GitHub: https://github.com/• Linear: https://linear.app/• Figma: https://www.figma.com/• Jeff's tweet about Stripe's bug-finder program: https://x.com/jeff_weinstein/status/1777487507934040300• The “Collison installation”: https://news.ycombinator.com/item?id=18400504• How we use friction logs to improve products at Stripe: https://dev.to/stripe/how-we-use-friction-logs-to-improve-products-at-stripe-i6p• Fidelity: https://www.fidelity.com/• 83(b) election: https://docs.stripe.com/atlas/83b-election• Jeff's tweet about Atlas's NPS score: https://x.com/jeff_weinstein/status/1788644576330469638• What is a Delaware corporation? Here's what makes this state so attractive to businesses: https://stripe.com/resources/more/what-is-a-delaware-corporation• Incorporating in Delaware explained: Why it's such a popular option for businesses: https://stripe.com/resources/more/incorporating-in-delaware-explained• 7 of Pixar's Best Storyboard Examples and the Stories Behind Them: https://boords.com/blog/7-of-pixars-best-storyboard-examples-and-the-stories-behind-them• Alex Kehayias on LinkedIn: https://www.linkedin.com/in/alexkehayias/• Patrick McKenzie on LinkedIn: https://www.linkedin.com/in/patrickmckenzie/• AngelList: https://www.angellist.com/• Dan Hightower on LinkedIn: https://www.linkedin.com/in/danhighto/• Stripe Atlas perks partners: https://support.stripe.com/questions/stripe-atlas-perks-partners• Vision, conviction, and hype: How to build 0 to 1 inside a company | Mihika Kapoor (Product at Figma): https://www.lennysnewsletter.com/p/vision-conviction-hype-mihika-kapoor• High Output Management: https://www.amazon.com/High-Output-Management-Andrew-Grove/dp/0679762884• Orbiting the Giant Hairball: A Corporate Fool's Guide to Surviving with Grace: https://www.amazon.com/Orbiting-Giant-Hairball-Corporate-Surviving/dp/0670879835• 7 Powers: The Foundations of Business Strategy: https://www.amazon.com/7-Powers-Foundations-Business-Strategy/dp/0998116319• Business strategy with Hamilton Helmer (author of 7 Powers): https://www.lennysnewsletter.com/p/business-strategy-with-hamilton-helmer• Box: https://www.box.com/• Patrick Collison on X: https://x.com/patrickc• How to with John Wilson on HBO: https://www.hbo.com/how-to-with-john-wilson• The Quiet Girl on Hulu: https://www.hulu.com/movie/the-quiet-girl-b50a4b8e-d3ff-4635-b806-5e7dbd292ca4• Raycast: https://www.raycast.com/• Quicksilver: https://qsapp.com/• Alfred: https://www.alfredapp.com/help/workflows/automations/• CleanShot: https://cleanshot.com/• John Collison on X: https://x.com/collision—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Written version: https://www.justgogrind.com/p/larry-ellison More about the Just Go Grind newsletter: Learn the tactics, strategies, and stories of world-class founders. I spend 20+ hours each week researching founders like Sam Altman, Melanie Perkins, and Patrick Collison, sharing the best insights with you every Sunday. Subscribe to the Just Go Grind newsletter: https://www.justgogrind.com/subscribe

Mike Maples, Jr. is a legendary early-stage startup investor and a co-founder and partner at Floodgate. He's made early bets on transformative companies like Twitter, Lyft, Twitch, Okta, Rappi, and Applied Intuition and is one of the pioneers of seed-stage investing as a category. He's been on the Forbes Midas List eight times and enjoys sharing the lessons he's learned from his years studying iconic companies. In his new book, Pattern Breakers: Why Some Start-Ups Change the Future, co-authored with Peter Ziebelman, he discusses what he's found separates startups and founders that break through and change the world from those that don't. After spending years reviewing the notes and decks from the thousands of startups he's known over the past two decades, he's uncovered three ways that breakthrough founders think and act differently. In our conversation, Mike talks about:• The three elements of breakthrough startup ideas• Why you need to both think and act differently• How to avoid the “comparison trap” and “conformity trap”• The importance of movements, storytelling, and healthy disagreeableness in startup success• How to apply pattern-breaking principles within large companies• Mike's one piece of advice for founders• Much morePre-order Mike's book here and get a second signed copy for free. Limited copies are available, so order ASAP: patternbreakers.com/lenny.—Brought to you by:• Enterpret—Transform customer feedback into product growth• Anvil—The fastest way to build software for documents• Webflow—The web experience platform—Find the transcript at: https://www.lennysnewsletter.com/p/how-to-find-a-great-startup-idea-mike-maples-jr—Where to find Mike Maples, Jr.:• X: https://x.com/m2jr• LinkedIn: https://www.linkedin.com/in/maples/• Substack: https://greatness.substack.com/• Website: https://www.floodgate.com/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Mike's background(03:10) The inspiration behind Pattern Breakers(08:09) Uncovering startup insights(11:37) A quick summary of Pattern Breakers(13:52) Coming up with an idea(15:30) Inflections(17:09) Examples of inflections(28:10) Insights(36:58) The power of surprises(47:36) Founder-future fit(55:33) Advice for aspiring founders(56:41) Living in the future: valid opinions(55:34) Case study: Maddie Hall and Living Carbon(58:40) Identifying lighthouse customers(01:00:53) The importance of desperation in customer needs(01:03:57) Creating movements and storytelling(01:24:22) The role of disagreeableness in startups(01:34:42) Applying these principles within a company(01:40:43) Lightning round—Referenced:• Pattern Breakers: Why Some Start-Ups Change the Future: https://www.amazon.com/Pattern-Breakers-Start-Ups-Change-Future/dp/1541704355• Justin.tv: https://en.wikipedia.org/wiki/Justin.tv• Airbnb's CEO says a $40 cereal box changed the course of the multibillion-dollar company: https://fortune.com/2023/04/19/airbnb-ceo-cereal-box-investors-changed-everything-billion-dollar-company/• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• The Unconventional Exit: How Justin Kan Sold His First Startup on eBay: https://medium.datadriveninvestor.com/the-unconventional-exit-how-justin-kan-sold-his-first-startup-on-ebay-4d705afe1354• Kyle Vogt on LinkedIn: https://www.linkedin.com/in/kylevogt/• The State of Telehealth Before and After the COVID-19 Pandemic: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035352/• The Craigslist Killers: https://www.gq.com/story/craigslist-killers• The social radar: Y Combinator's secret weapon | Jessica Livingston (co-founder of Y Combinator, author, podcast host): https://www.lennysnewsletter.com/p/the-social-radar-jessica-livingston• Michael Seibel on LinkedIn: https://www.linkedin.com/in/mwseibel/• The Airbnb Story: How Three Ordinary Guys Disrupted an Industry, Made Billions ... and Created Plenty of Controversy: https://www.amazon.com/Airbnb-Story-Ordinary-Disrupted-Controversy/dp/0544952669• Scott Cook: https://www.forbes.com/profile/scott-cook/• Chegg: https://www.chegg.com/• Aayush Phumbhra on LinkedIn: https://www.linkedin.com/in/aayush/• Osman Rashid on LinkedIn: https://www.linkedin.com/in/osmanrashid/• Okta: https://www.okta.com/• The Man Who Makes the Future: Wired Icon Marc Andreessen: https://www.wired.com/2012/04/ff-andreessen/• Peter Ludwig on LinkedIn: https://www.linkedin.com/in/peterwludwig/• Qasar Younis on LinkedIn: https://www.linkedin.com/in/qasar/• Paul Allen's website: https://paulallen.com/• Louis Pasteur quote: https://www.forbes.com/quotes/6145/• What was Atrium and why did it fail? https://www.failory.com/cemetery/atrium• Patrick Collison on LinkedIn: https://www.linkedin.com/in/patrickcollison/• Drew Houston on LinkedIn: https://www.linkedin.com/in/drewhouston/• William Gibson's quote: https://www.goodreads.com/quotes/681-the-future-is-already-here-it-s-just-not-evenly• Maddie Hall on LinkedIn: https://www.linkedin.com/in/maddie-hall-76293135/• Living Carbon: https://www.livingcarbon.com• Zenefits (now Trinet): https://connect.trinet.com/• Sam Altman on X: https://x.com/sama• Steve Wozniak on LinkedIn: https://www.linkedin.com/in/wozniaksteve/• Horsley Bridge Partners: https://www.horsleybridge.com/• David Swensen: https://en.wikipedia.org/wiki/David_F._Swensen• Judith Elsea on LinkedIn: https://www.linkedin.com/in/judithelsea/• 7 Powers: The Foundations of Business Strategy: https://www.amazon.com/7-Powers-Foundations-Business-Strategy/dp/0998116319• Business strategy with Hamilton Helmer (author of 7 Powers): https://www.lennysnewsletter.com/p/business-strategy-with-hamilton-helmer• Lyft's Focus on Community and the Story Behind the Pink Mustache: https://techcrunch.com/2012/09/17/lyfts-focus-on-community-and-the-story-behind-the-pink-mustache/• Logan Green on LinkedIn: https://www.linkedin.com/in/logangreen/• John Zimmer on LinkedIn: https://www.linkedin.com/in/johnzimmer11/• Storytelling with Nancy Duarte: How to craft compelling presentations and tell a story that sticks: https://www.lennysnewsletter.com/p/storytelling-with-nancy-duarte-how• Steve Jobs Introducing the iPhone at MacWorld 2007: https://www.youtube.com/watch?v=x7qPAY9JqE4• Jonathan Livingston Seagull: https://www.amazon.com/Jonathan-Livingston-Seagull-Richard-Bach/dp/0743278909• The paths to power: How to grow your influence and advance your career | Jeffrey Pfeffer (author of 7 Rules of Power, professor at Stanford GSB): https://www.lennysnewsletter.com/p/the-paths-to-power-jeffrey-pfeffer• Robin Roberts on LinkedIn: https://www.linkedin.com/in/robin-roberts-393a934b/• Skunkworks: https://www.lockheedmartin.com/en-us/who-we-are/business-areas/aeronautics/skunkworks.html• Vision, conviction, and hype: How to build 0 to 1 inside a company | Mihika Kapoor (Product at Figma): https://www.lennysnewsletter.com/p/vision-conviction-hype-mihika-kapoor• Hard-won lessons building 0 to 1 inside Atlassian | Tanguy Crusson (Head of Jira Product Discovery): https://www.lennysnewsletter.com/p/building-0-to-1-inside-atlassian-tanguy-crusson• Figma: https://www.figma.com/• Atlassian: https://www.atlassian.com/• Vinod Khosla: https://www.khoslaventures.com/team/vinod-khosla/• Top Five Regrets of the Dying: A Life Transformed by the Dearly Departing: https://www.amazon.com/Top-Five-Regrets-Dying-Transformed-ebook/dp/B07KNRLY1L• Chase, Chance, and Creativity: The Lucky Art of Novelty: https://www.amazon.com/Chase-Chance-Creativity-Lucky-Novelty/dp/0262511355• Clay Christensen's books: https://www.amazon.com/stores/Clayton-M.-Christensen/author/B000APPD3Y• Resonate: Present Visual Stories That Transform: https://www.amazon.com/Resonate-Present-Stories-Transform-Audiences/dp/0470632011• Ferrari on Prime: https://www.amazon.com/Ferrari-Adam-Driver/dp/B0CNDBN672• Montblanc fountain pens: https://www.montblanc.com/en-us—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Jessica Livingston is a co-founder of Y Combinator, the first and most successful startup accelerator. Y Combinator has funded over 5,000 companies, 200 of which are now unicorns, including Airbnb, Dropbox, DoorDash, Stripe, Coinbase, and Reddit. Jessica played a crucial role in YC's early success, when she was nicknamed the “social radar” because of her uncanny ability to quickly evaluate people—an essential skill when investing in early-stage startups. She's also the host of the popular podcast The Social Radars, where she interviews billion-dollar-startup founders, and the author of the acclaimed book Founders at Work, which captures the origin stories of some of today's most interesting companies. In our conversation, we discuss:• How Jessica gained the affectionate title of the “social radar”• Why defensive founders are a red flag• How to develop your social radar• What she looks for in founders during YC interviews• How YC's early inexperience in angel investing led to the batch model• Her favorite stories from interviews with Airbnb, Rippling, and more• Lessons learned from hosting her own podcast• Much more—Brought to you by:• Enterpret—Transform customer feedback into product growth• Anvil—The fastest way to build software for documents• Vanta—Automate compliance. Simplify security—Find the transcript at: https://www.lennysnewsletter.com/p/the-social-radar-jessica-livingston—Where to find Jessica Livingston:• X: https://x.com/jesslivingston• LinkedIn: https://www.linkedin.com/in/jessicalivingston1/• Podcast: https://www.thesocialradars.com/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Jessica's background(02:42) Thoughts on being under-recognized(07:52) Jessica's superpower: the social radar(15:11) Evaluating founders: key traits and red flags(21:00) The Airbnb story: a lesson in hustle and determination(25:57) A YC success story(28:26) The importance of earnestness(32:45) Confidence vs. defensiveness(34:43) Commitment and co-founder disputes(37:46) Relentless resourcefulness(40:00) Jessica's social radar: origins and insights(43:24) Honing her social radar skills(45:44) Conviction and scams: a Y Combinator story(46:50) The interview process: challenges and insights(48:20) Operationalizing founder evaluation(49:38) Advice for building social radar skills(52:08) The “Reading the Mind in the Eyes” quiz(55:19) Jessica's podcast: The Social Radars(01:00:34) Lessons from podcasting and interviewing(01:09:58) Lightning round—Referenced:• Paul Graham's post about Jessica: https://paulgraham.com/jessica.html• Paul Graham on X: https://x.com/paulg• Robert Tappan Morris: https://en.wikipedia.org/wiki/Robert_Tappan_Morris• Trevor Blackwell on X: https://x.com/tlbtlbtlb• Y Combinator: https://www.ycombinator.com/• “The Founders” examines the rise and legend of PayPal: https://www.economist.com/culture/2022/02/19/the-founders-examines-the-rise-and-legend-of-paypal• Patrick Collison on X: https://x.com/patrickc• John Collison on X: https://x.com/collision• Brian Chesky on LinkedIn: https://www.linkedin.com/in/brianchesky/• Nate Blecharczyk on LinkedIn: https://www.linkedin.com/in/blecharczyk/• Joe Gebbia on LinkedIn: https://www.linkedin.com/in/jgebbia/• Airbnb's CEO says a $40 cereal box changed the course of the multibillion-dollar company: https://fortune.com/2023/04/19/airbnb-ceo-cereal-box-investors-changed-everything-billion-dollar-company/• Parker Conrad on LinkedIn: https://www.linkedin.com/in/parkerconrad/• Zenefits: https://connect.trinet.com/hr-platform• Goat: https://www.goat.com/• Eddy Lu on LinkedIn: https://www.linkedin.com/in/eddylu/• Drew Houston on LinkedIn: https://www.linkedin.com/in/drewhouston/• Arash Ferdowsi on LinkedIn: https://www.linkedin.com/in/arashferdowsi/• Lessons from 1,000+ YC startups: Resilience, tar pit ideas, pivoting, more | Dalton Caldwell (Y Combinator, Managing Director): https://www.lennysnewsletter.com/p/lessons-from-1000-yc-startups•Bitcoin launderer pleads guilty, admits to massive Bitfinex hack: https://www.cnbc.com/2023/08/03/new-york-man-admits-being-original-bitfinex-hacker-during-guilty-plea-in-dc-to-bitcoin-money-laundering.html• Paul Graham's tweet with the facial recognition test: https://x.com/paulg/status/1782875262855663691• SmartLess podcast: https://www.smartless.com• Jason Bateman on X: https://x.com/batemanjason• Will Arnett on X: https://x.com/arnettwill• Sean Hayes on X: https://x.com/seanhayes• The Social Radars with Tony Xu, Co-Founder & CEO of DoorDash: https://www.ycombinator.com/library/Ja-tony-xu-co-founder-ceo-of-doordash• The Social Radars with Brian Chesky: https://www.ycombinator.com/library/JW-brian-chesky-co-founder-ceo-of-airbnb• The Social Radars with Patrick and John Collison: https://www.ycombinator.com/library/Kx-patrick-john-collison-co-founders-of-stripe• The Social Radars with Brian Armstrong: https://www.ycombinator.com/library/K3-brian-armstrong-co-founder-and-ceo-of-coinbase• The Social Radars with Emmett Shear: https://www.ycombinator.com/library/KM-emmett-shear-co-founder-of-twitch• The Social Radars with Paul Graham: https://www.ycombinator.com/library/JV-paul-graham-co-founder-of-y-combinator-and-viaweb• The Social Radars with Adora Cheung: https://www.ycombinator.com/library/L0-adora-cheung-co-founder-of-homejoy-instalab• Founders at Work: Stories of Startups' Early Days: https://www.amazon.com/Founders-Work-Stories-Startups-Early/dp/1430210788• Startup School: https://www.startupschool.org/• The Social Radars with Parker Conrad: https://www.ycombinator.com/library/Ky-parker-conrad-founder-of-zenefits-rippling• Rippling: https://www.rippling.com/• Carry on, Jeeves: https://www.amazon.com/Carry-Jeeves-Dover-Thrift-Editions/dp/0486848957• Very Good, Jeeves: https://www.amazon.com/Very-Good-Jeeves-Wooster-Book-ebook/dp/B0051GST06• Right Ho, Jeeves: https://www.amazon.com/Right-Ho-Jeeves-P-Wodehouse-ebook/dp/B083FFDNHN/• Life: https://www.amazon.com/Life-Keith-Richards-ebook/dp/B003UBTX72/• My Name Is Barbra: https://www.amazon.com/My-Name-Barbra-Streisand/dp/0525429522• Clarkson's Farm on Prime: https://www.amazon.com/Clarksons-Farm-Season-1/dp/B095RHJ52R• Schitt's Creek on Hulu: https://www.hulu.com/series/schitts-creek-a2e7a946-9652-48a8-884b-3ea7ea4de273• Yellowstone on Peacock: https://www.peacocktv.com/stream-tv/yellowstone• Sam Altman on X: https://x.com/sama• Justin Kan on LinkedIn: https://www.linkedin.com/in/justinkan/• Alexis Ohanian on X: https://x.com/alexisohanian• Steve Huffman on LinkedIn: https://www.linkedin.com/in/shuffman56/• Breaking News: Condé Nast/Wired Acquires Reddit: https://techcrunch.com/2006/10/31/breaking-news-conde-nastwired-acquires-reddit/• Charles River Venture: https://www.crv.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Progress Conference 2024: Toward Abundant Futures, published by jasoncrawford on June 26, 2024 on LessWrong. The progress movement has grown a lot in the last few years. We now have progress journals, think tanks, and fellowships. The progress idea has spread and evolved into the "abundance agenda", "techno-optimism", "supply-side progressivism", "American dynamism". All of us want to see more scientific, technological, and economic progress for the good of humanity, and envision a bold, ambitious, flourishing future. What we haven't had so far is a regular gathering of the community. Announcing Progress Conference 2024, a two-day event to connect people in the progress movement. Meet great people, share ideas in deep conversations, catalyze new projects, get energized and inspired. Hosted by: the Roots of Progress Institute, together with the Foresight Institute, HumanProgress.org, the Institute for Humane Studies, the Institute for Progress, and Works in Progress magazine When: October 18-19, 2024 Where: Berkeley, CA - at the Lighthaven campus, an inviting space perfect for mingling Speakers: Keynotes include Patrick Collison, Tyler Cowen, Jason Crawford, and Steven Pinker. Around 20 additional speakers will share ideas on four tracks: the big idea of human progress, policy for progress, tech for progress, and storytelling/media for progress. Full speaker list Attendees: We expect 200+ intellectuals, builders, policy makers, storytellers, and students. This is an invitation-only event, but anyone can apply for an invitation. Complete the open application by July 15th. Program: Two days of intellectual exploration, inspiration and interaction that will help shape the progress movement into a cultural force. Attend talks on topics from tech to policy to culture, build relationships with new people as you hang out on cozy sofas or enjoy the sun in the garden, sign up to run an unconference session and find others who share your interests and passions, or pitch your ideas to those who could help make your dreams a reality. Special thanks to our early sponsors: Cato Institute, Astera Institute, and Freethink Media! We have more sponsorships open, view sponsorship opportunities here. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org

Written version: https://www.justgogrind.com/p/shonda-rhimes More about the Just Go Grind newsletter: Learn the tactics, strategies, and stories of world-class founders. I spend 20+ hours each week researching founders like Sam Altman, Melanie Perkins, and Patrick Collison, sharing the best insights with you every Sunday. Subscribe to the Just Go Grind newsletter: https://www.justgogrind.com/subscribe

Alex Wang is the Founder and CEO @ Scale.ai, the company that allows you to make the best models with the best data. To date, Alex has raised $1.6BN for the company with a last reported valuation of $14BN earlier this year. Scale tripled their ARR in 2023 and is expected to hit $1.4BN in ARR by the end of 2024. Their investors include Accel, Index, Thrive, Founders Fund, Meta and Nvidia to name a few. In Today's Show with Alex Wang We Discuss: 1. Foundation Models: Diminishing Returns: What are the three core pillars that can meaningfully improve foundation models performance? Why is data the single largest bottleneck to the performance of models today? What data do we need to capture that we do not currently, that will have the biggest impact on model performance moving forward? Will we see the largest companies in the world revert back to on-prem with the increasing security challenges of migrating all customer data to foundation models? 2. AI: A Military Asset in Global Conflict: China + Russia Why does Alex believe that AI has the potential to be an even more powerful military asset than nuclear weapons? If this is the case, should we have open systems? Do we not have to have closed systems? Why does Alex believe that the CCP's approach to industrial policy is better than anyone else's? How does Alex evaluate the rise of Chinese EV car manufacturers in the last few years? Does Alex really believe that China is two years behind the US in the AI race? 3. "I Get Fairer Treatment in Congress than in the Press": Why does Alex believe that the best PR is no PR? Why does Alex believe that he got fairer treatment in congress than he does in the media? Why does Alex believe that all founders should look to own their own distribution channels today? 4. Alex Wang: AMA: What are some of Alex's biggest lessons from Patrick Collison on the impact that a hot company brand has on the ability for that company to hire the best? Does Alex think Trump is going to win? What would be the impact if he were to? Why does Alex believe that enterprise software will be changed forever in the next few years? What question is Alex never asked that he thinks he should be asked?  

Written version: https://www.justgogrind.com/p/daniel-ek More about the Just Go Grind newsletter: Learn the tactics, strategies, and stories of world-class founders. I spend 20+ hours each week researching founders like Sam Altman, Melanie Perkins, and Patrick Collison, sharing the best insights with you every Sunday. Subscribe to the Just Go Grind newsletter: https://www.justgogrind.com/subscribe

Written version: https://www.justgogrind.com/p/estee-lauder More about the Just Go Grind newsletter: Learn the tactics, strategies, and stories of world-class founders. I spend 20+ hours each week researching founders like Sam Altman, Melanie Perkins, and Patrick Collison, sharing the best insights with you every Sunday. Subscribe to the Just Go Grind newsletter: https://www.justgogrind.com/subscribe

Take our Listener Survey Michael Nielsen is scientist who helped pioneer quantum computing and the modern open science movement. He's worked at Y Combinator, co-authored on scientific progress with Patrick Collison, and is a prolific writer, reader, commentator, and mentor.  He joined Tyler to discuss why the universe is so beautiful to human eyes (but not ears), how to find good collaborators, the influence of Simone Weil, where Olaf Stapledon's understand of the social word went wrong, potential applications of quantum computing, the (rising) status of linear algebra, what makes for physicists who age well, finding young mentors, why some scientific fields have pre-print platforms and others don't, how so many crummy journals survive, the threat of cheap nukes, the many unknowns of Mars colonization, techniques for paying closer attention, what you learn when visiting the USS Midway, why he changed his mind about Emergent Ventures, why he didn't join OpenAI in 2015, what he'll learn next, and more.  Read a full transcript enhanced with helpful links, or watch the full video. Recorded March 24th, 2024. Other ways to connect Follow us on X and Instagram Follow Tyler on X Follow Michael on X Sign up for our newsletter Join our Discord Email us: cowenconvos@mercatus.gmu.edu Learn more about Conversations with Tyler and other Mercatus Center podcasts here.

Written version: https://www.justgogrind.com/p/cesar-ritz More about the Just Go Grind newsletter: Learn the tactics, strategies, and stories of world-class founders. I spend 20+ hours each week researching founders like Sam Altman, Melanie Perkins, and Patrick Collison, sharing the best insights with you every Sunday. Subscribe to the Just Go Grind newsletter: https://www.justgogrind.com/subscribe

In episode #2738, we discuss takeaways from an interview with Patrick Collison, the CEO of Stripe, and Jensen Huang from NVIDIA. We cover the use of group feedback instead of private criticism, the potential impact of AI on industries and jobs, the challenges of implementing AI in large corporations, and the varying adoption rates.      Don't forget to help us grow by subscribing and liking on YouTube!   Check out more of Eric's content (Leveling UP YT) and Neil's videos (Neil Patel YT)    TIME-STAMPED SHOW NOTES: (00:00) Today's topic: NVIDIA's Jenson Huang's unorthodox leadership style, and How AI agents will change marketing (01:15) NVIDIA's Jenson Huang's unorthodox leadership style (07:43) How AI agents will change marketing (24:13) That's it for today! Don't forget to rate, review, and subscribe!   Go to https://www.marketingschool.io to learn more!   Leave Some Feedback: What should we talk about next? Please let us know in the comments below Did you enjoy this episode? If so, please leave a short review.   Connect with Us:    Single Grain

Matteo Franceschetti is the Co-Founder and CEO of Eight Sleep, the sleep fitness company.Eight Sleep developed a proprietary technology which is redesigning sleep by developing cutting-edge AI and machine learning models to track bio signals during the night and optimizing body recovery and rest while asleep. The end goal of the Pod is to compress sleep and scan your body while asleep to monitor your health.Eight Sleep is currently used by pro athletes and top performers across multiple industries and was recognized as one of TIME's “Best Inventions” in 2018 and 2019, was named one of Fast Company's “Most Innovative Companies” in 2018, and has raised over $150M in funding from leading investors, including Founders Fund, Softbank, Khosla Ventures, Y Combinator, Valor Equity Partners, General Catalyst, Naval Ravikant, and Patrick Collison.Prior to Eight, Matteo co-founded and led GIR (acquired in 2014) and Global Investment (acquired 2011). Both companies were in cleantech.Matteo holds multiple patents in tech and health, is a Member of the Forbes Technology Council, has been Co-Chair at FWD.us and Mentor at Techstars, Microsoft Bizpark and the NYU Summer Launchpad Program.He graduated magna cum laude with a Law degree from University of Ferrara, and was a member of the Italian Bar Association while working as a lawyer in the finance practice of Freshfields Bruckhaus Deringer and Allen & Overy, both part of the Magic Circle of British's elite law firms.

Guest: Taylor Francis, co-founder of WatershedOne day when he was 13, Taylor Francis walked out of the movie theater, and he was pissed off. He had just seen Al Gore's documentary An Inconvenient Truth and internalized a “generational call to arms, that my parents had screwed our generation” by causing the climate crisis, he says. 14 years later, he was working at Stripe and felt another call to arms: The 2020s would be a crucial decade for slashing carbon emissions and combating global warming. So, he and his co-founders Avi Itskovich and Christian Anderson all left Stripe to start Watershed, which helps companies measure and reduce their emissions.In this episode, Taylor and Joubin discuss Patrick Collison, Dan Miller-Smith, hiring challenges, Jonathan Neman, “golden age syndrome,” John Doerr and Mike Moritz, the Climate Reality Project, steady partnerships, DRI cultures, shared context, social distancing, information sprawl, and the founders' “woe is me” narrative.Chapters:(01:02) - Magnetic missions (06:40) - How enterprise sustainability works (08:40) - Watershed's first client, Sweetgreen (11:04) - Reflecting on the early days (16:36) - Al Gore and An Inconvenient Truth (18:53) - Mobilizing teenagers (22:16) - The origins of Watershed (27:04) - Leaving Stripe and raising money (31:41) - Interchangeable co-founders (33:33) - The ground truth (35:52) - The Dunbar Number (38:49) - Watershed's operating principles (42:23) - Intensity, priorities, and sacrifice (48:04) - Moving faster (50:53) - Sustainability is a part of business (52:48) - The topology of emissions (58:35) - Who Watershed is hiring Links:Connect with TaylorTwitterLinkedInConnect with JoubinTwitterLinkedInEmail: grit@kleinerperkins.com Learn more about Kleiner PerkinsThis episode was edited by Eric Johnson from LightningPod.fm

Written version: https://www.justgogrind.com/p/arianna-huffington More about the Just Go Grind newsletter: Learn the tactics, strategies, and stories of world-class founders. I spend 20+ hours each week researching founders like Sam Altman, Melanie Perkins, and Patrick Collison, sharing the best insights with you every Sunday. Subscribe to the Just Go Grind newsletter: https://www.justgogrind.com/subscribe

Written version: https://www.justgogrind.com/p/tobi-lutke More about the Just Go Grind newsletter: Learn the tactics, strategies, and stories of world-class founders. I spend 20+ hours each week researching founders like Sam Altman, Melanie Perkins, and Patrick Collison, sharing the best insights with you every Sunday. Subscribe to the Just Go Grind newsletter: https://www.justgogrind.com/subscribe

Dalton Caldwell is Managing Director and Group Partner at Y Combinator. Prior to YC, he was the co-founder and CEO of imeem (acquired by MySpace in 2009) and the co-founder and CEO of App.net. During his time at YC, he's advised more than 35 YC unicorns, including DoorDash, Amplitude, Webflow, and Retool, and has worked across 21 different YC batches. He's also racked up more than 6,500 office hours with founders. In our conversation, we discuss:• Why founders need to adopt the mindset “Just don't die”• The most common reason startups fail• When to pivot, and characteristics of a good pivot• The concept of “tar pit ideas” and examples of bad startup ideas• Why investors say no to startups• The importance of market size in investment decisions• The pitfalls of founders over-delegating• Effective ways to talk to customers• 20 ideas Dalton is looking to fund—Brought to you by:• Eppo—Run reliable, impactful experiments• Vanta—Automate compliance. Simplify security• Coda—The all-in-one collaborative workspace—Find the transcript at: https://www.lennysnewsletter.com/p/lessons-from-1000-yc-startups—Where to find Dalton Caldwell:• X: https://twitter.com/daltonc• LinkedIn: https://www.linkedin.com/in/daltoncaldwell/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Dalton's background(04:41) The value of simple advice(07:04) Dalton's advice: “Just don't die”(08:39) Knowing when to stop(11:45) Deciding to pivot(14:26) Characteristics of a good pivot(17:53) Knowing when to pivot(19:03) Zip's journey and finding a market(21:22) Why Dalton says to “Move towards the mountains and the desert”(23:45) Tar pit ideas(26:49) Understanding why investors say no(29:14) The importance of market size(32:16) Avoiding over-delegation and hiring senior people too early(36:43) Why startups fail(40:30) Effectively talking to customers(45:17) Examples of startups hustling to talk to customers(48:01) Patterns of successful startups(52:05) YC's Request for Startups(55:37) Early days of Silicon Valley(01:05:33) Contrarian corner: growth hacking for early startups(01:09:28) Failure corner(01:11:15) Closing thoughts(01:12:22) Lightning round—Referenced:• Y Combinator: https://www.ycombinator.com/• Tiger Woods's website: https://tigerwoods.com/• Co-Founder Mistakes That Kill Companies & How to Avoid Them: https://www.youtube.com/watch?v=dlfjs_eEEzs• Daniel Alberson's LinkedIn post about Y Combinator: https://www.linkedin.com/posts/alberson_i-left-my-dream-job-as-a-product-manager-activity-7089677882431533056-jJ9H• Companies in Y Combinator W17 Batch: https://www.ycdb.co/batch/w17• Brex: https://www.brex.com/• Retool: https://retool.com/• Segment: https://segment.com/• Mixpanel: https://mixpanel.com/• Whatnot: https://www.whatnot.com/• Andreessen Horowitz: https://a16z.com/• Airbnb's CEO says a $40 cereal box changed the course of the multibillion-dollar company: https://fortune.com/2023/04/19/airbnb-ceo-cereal-box-investors-changed-everything-billion-dollar-company/• Rujul Zaparde on LinkedIn: https://www.linkedin.com/in/rujulz/• Zip: https://ziphq.com/• Lu Cheng on LinkedIn: https://www.linkedin.com/in/lu-cheng-973b7830/• Avoid these tempting startup tar pit ideas: https://www.ycombinator.com/library/Ij-avoid-these-tempting-startup-tarpit-ideas• Airbnb acquires Localmind to create crowdsourced advice about neighborhoods: https://skift.com/2012/12/13/airbnb-acquires-localmind-to-create-crowdsourced-advice-about-neighborhoods/• Foursquare: https://foursquare.com/• Razorpay: https://razorpay.com/• Total Addressable Market: https://www.productplan.com/glossary/total-addressable-market/• Lenny Bogdonoff on LinkedIn: https://www.linkedin.com/in/rememberlenny/• Milk Video: https://milkvideo.com/• Lessons from working with 600+ YC startups | Gustaf Alströmer (Y Combinator, Airbnb): https://www.lennyspodcast.com/lessons-from-working-with-600-yc-startups-gustaf-alstromer-y-combinator-airbnb/• How the most successful B2B startups came up with their original idea: https://www.lennysnewsletter.com/p/how-the-most-successful-b2b-startups• Collison installation: https://news.ycombinator.com/item?id=18400504• Stripe: https://stripe.com/• Patrick Collison on LinkedIn: https://www.linkedin.com/in/patrickcollison/• John Collison on LinkedIn: https://www.linkedin.com/in/johnbcollison/• Tony Xu on LinkedIn: https://www.linkedin.com/in/xutony/• Grant LaFontaine on LinkedIn: https://www.linkedin.com/in/grantlafontaine/• Ryan Petersen on LinkedIn: https://www.linkedin.com/in/rpetersen/• Lessons on building product sense, navigating AI, optimizing the first mile, and making it through the messy middle | Scott Belsky (Adobe, Behance): https://www.lennyspodcast.com/lessons-on-building-product-sense-navigating-ai-optimizing-the-first-mile-and-making-it-through-t/• YC's latest Request for Startups: https://www.ycombinator.com/blog/ycs-latest-request-for-startups• ERPs: https://www.ycombinator.com/rfs#new-enterprise-resource-planning-software• Commercial open source companies: https://www.ycombinator.com/rfs#commercial-open-source-companies• New space companies: https://www.ycombinator.com/rfs#new-space-companies• A way to end cancer: https://www.ycombinator.com/rfs#a-way-to-end-cancer• Spatial computing: https://www.ycombinator.com/rfs#spatial-computing• New defense technology: https://www.ycombinator.com/rfs#new-defense-technology• Bringing manufacturing back to America: https://www.ycombinator.com/rfs#bring-manufacturing-back-to-america• Better enterprise glue: https://www.ycombinator.com/rfs#better-enterprise-glue• Small fine-tuned models, as an alternative to giant generic ones: https://www.ycombinator.com/rfs#small-finetuned-models-as-an-alternative-to-giant-generic-ones• Reid Hoffman on LinkedIn: https://www.linkedin.com/in/reidhoffman/• Sam Altman on X: https://twitter.com/sama• Sean Parker on LinkedIn: https://www.linkedin.com/in/parkersean/• Owen Van Natta on LinkedIn: https://www.linkedin.com/in/owen-van-natta-444a7/• iMeme: https://apps.apple.com/us/app/imeme-generator/id1560021364• Marc Andreessen on X: https://twitter.com/pmarca• Picplz 1, Instagram 0 as VC firm Andreessen Horowitz chooses photo app rival: https://www.reuters.com/article/idUS2587232395/• Gustaf Alstromer—How to Get Users and Grow: https://www.youtube.com/watch?v=T9ikpoF2GH0• Getting to Yes: Negotiating Agreement Without Giving In: https://www.amazon.com/Getting-Yes-Negotiating-Agreement-Without/dp/0143118757• Founding Sales: The Early Stage Go-to-Market Handbook: https://www.amazon.com/Founding-Sales-Go-Market-Handbook-ebook/dp/B08PMK17Z1• Founder-led sales | Pete Kazanjy (Founding Sales, Atrium): https://www.lennyspodcast.com/founder-led-sales-pete-kazanjy-founding-sales-atrium/• The Sopranos on HBO: https://www.hbo.com/the-sopranos• The Wire on HBO: https://www.hbo.com/the-wire• Columbo on Prime Video: https://www.amazon.com/Columbo-Season-1/dp/B008SA89HA• Oura ring: https://ouraring.com/• Apple watch: https://www.apple.com/watch/• SiPhox: https://siphoxhealth.com/• Dalton & Michael on YouTube: https://www.youtube.com/playlist?list=PLQ-uHSnFig5Nd98Sc9I-kkc0ZWe8peRMC• How Future Billionaires Get Sh*t Done: https://www.youtube.com/watch?v=ephzgxgOjR0• The Student's Guide to Becoming a Successful Startup Founder: https://www.youtube.com/watch?v=O5KCB2p6SB8—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

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Guest: Jason Kelly, CEO and co-founder of Gingko BioworksAlmost everyone in the second generation of biotechnology entrepreneurs, says Gingko Bioworks CEO Jason Kelly, works in that field because of one thing: Jurassic Park. The Michael Crichton novel-turned-Steven Spielberg movie captured both the wonder and beauty of bioengineering, and the challenges of bending DNA to your own ends. “You didn't invent biology,” Jason says. “You need to have humility in the face of it ... because life will find a way. It will do things you don't expect. It's not a computer.” In this episode, Jason and Joubin discuss the Wall Street rollercoaster, designer cells, the history of biotech, Herbert Boyer and Genentech, ChatGPT, extinct flowers, Sam Altman and YCombinator, first principles thinking, compounding risk, Patrick Collison, super-voting shares, capital intensive businesses, Pets.com, and why biology is like “freakishly powerful alien technology.”In this episode, we cover:Being private vs. being public (00:58)How bioengineering works (04:27)Jurassic Park (08:51)Biotech breakthroughs (12:15)Why this field is not well-known yet (16:57)“The ChatGPT moment for biotech” (22:05)Meaningful stuff takes forever (26:23)Gingko's first five years (29:02)Why the company went public (36:20)Short sellers, Warren Buffett, and Elon Musk (42:08)Applying AI to DNA engineering (47:57)The long-term future (55:57)Who Gingko is hiring (58:39)Links:Connect with JasonTwitterLinkedInConnect with JoubinTwitterLinkedInEmail: grit@kleinerperkins.com Learn more about Kleiner PerkinsThis episode was edited by Eric Johnson from LightningPod.fm

Judd Antin has spent 15 years leading research and design teams at companies like Yahoo, Meta, and Airbnb. His direct reports have gone on to lead user research at Figma, Notion, Slack, Robinhood, Duolingo, AllTrails, and more. In our conversation, we unpack the transformation that the user-research field is experiencing. Specifically:• Where user research went wrong over the past decade• The three types of research—macro, middle-range, and micro—and the purpose of each• How to effectively integrate researchers into the product development process• The “user-centered performance” phenomenon and why it's a waste of time• Common tropes about PMs, from researchers• The ideal ratio of researchers in a company• Why Judd says NPS is useless, and what to use instead—Brought to you by Teal—Your personal career growth platform | Vanta—Automate compliance. Simplify security | Ahrefs—Improve your website's SEO for free—Find the transcript for this episode and all past episodes at: https://www.lennyspodcast.com/episodes/. Today's transcript will be live by 8 a.m. PT.—Where to find Judd Antin:• LinkedIn: https://www.linkedin.com/in/juddantin/• Website: https://juddantin.com/• Blog: https://medium.com/onebigthought—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Judd's background(04:16) Critiques and responses to Judd's post “The UX Research Reckoning Is Here”(07:33) The state of user research(08:53) Macro, middle-range, and micro research(14:05) What teams get wrong when it comes to research(15:46) The importance of integrating research from the beginning(17:30) Traits of great researchers(19:53) Advice for evaluating user researchers(21:10) Balancing business and product focus(23:55) User-centered performance(26:42) The role of intuition in product development(30:15) Checking your gut instincts(32:54) Common tropes about PMs, from researchers(41:02) A/B testing vs. user research(43:15) Hindsight bias and narrative fallacy(44:55) Making recommendations based on research(47:26) Advice for teams on how to leverage researchers(51:18) How product managers can be better partners to user researchers(56:53) The ideal ratio of researchers in a company(59:43) Empowering user researchers to drive impact(01:03:39) The limitations of NPS as a metric(01:06:48) The risks of dogfooding(01:08:51) Lightning round—Referenced:• Matt Gallivan on LinkedIn: https://www.linkedin.com/in/mattgallivan/• Janna Bray on LinkedIn: https://www.linkedin.com/in/janna-bray-a4046a25/• Celeste Ridlen on LinkedIn: https://www.linkedin.com/in/celesteridlen/• Rebecca Gray on LinkedIn: https://www.linkedin.com/in/rebeccagray2/• Hannah Pileggi on LinkedIn: https://www.linkedin.com/in/hannah-pileggi-43169314/• Louise Beryl on LinkedIn: https://www.linkedin.com/in/louise-beryl-13225833/• The UX Research Reckoning Is Here: https://medium.com/onebigthought/the-ux-research-reckoning-is-here-c63710ea4084• The end of the “free money” era: https://www.theguardian.com/technology/2023/apr/11/techscape-zirp-tech-boom• Cognitive biases: https://en.wikipedia.org/wiki/List_of_cognitive_biases• IDEO design thinking: https://designthinking.ideo.com/• Everything Is Obvious: How Common Sense Fails Us: https://www.amazon.com/Everything-Obvious-Common-Sense-Fails/dp/0307951790• Patrick Collison's tweet: https://twitter.com/patrickc/status/1443215022029619200?lang=en• Brian Chesky on LinkedIn: https://www.linkedin.com/in/brianchesky/• Brian Chesky on Lenny's Podcast: https://www.lennyspodcast.com/brian-cheskys-new-playbook/• NPS: https://en.wikipedia.org/wiki/Net_promoter_score• What is CSAT and how do you measure it?: https://www.qualtrics.com/experience-management/customer/what-is-csat/• Michael Murakami on LinkedIn: https://www.linkedin.com/in/michaelhmurakami/• Bad Leadership: What It Is, How It Happens, Why It Matters: https://www.amazon.com/Bad-Leadership-Happens-Matters-Common/dp/1591391660• Demon Copperhead: https://www.amazon.com/Demon-Copperhead-Novel-Barbara-Kingsolver/dp/0063251922• All Systems Red: The Murderbot Diaries: https://www.amazon.com/All-Systems-Red-Murderbot-Diaries/dp/0765397536• The Last of Us on HBO: https://www.hbo.com/the-last-of-us• Belay glasses: https://www.amazon.com/Belay-Glasses-Climbing-Comfortable-Sturdy/dp/B08GSBYDKQ/• Epictetus: Control What You Can—Especially Yourself: https://www.shortform.com/blog/epictetus-control/• The 7 Habits of Highly Effective People: Powerful Lessons in Personal Change: https://www.amazon.com/Habits-Highly-Effective-People-Powerful/dp/0743269519—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Ebi Atawodi is Director of Product Management for the Creator Experience at YouTube, former Head of Product at Uber, and a former Director of Product (Payments and EMEA) at Netflix. Known for crafting a strong, unified vision, Ebi empowers her teams to achieve outsized outcomes. In today's episode, we go deep into vision and strategy, including:• The four key elements of a good vision statement• Three ways to determine your mission• The four pillars of great product management• How writing helps you gain clarity• How culture influences product• Tips on how to structure a strategy session• Advice on building team culture and improving work relationships• What's coming soon at YouTube—Brought to you by Sidebar—Accelerate your career by surrounding yourself with extraordinary peers | Jira Product Discovery—Atlassian's new prioritization and roadmapping tool built for product teams | Wix Studio—The web creation platform built for agencies—Find the transcript for this episode and all past episodes at: https://www.lennyspodcast.com/episodes/. Today's transcript will be live by 8 a.m. PT.—Where to find Ebi Atawodi:• X: https://twitter.com/ebiatawodi• LinkedIn: https://www.linkedin.com/in/ebiatawodi• YouTube mixes: https://www.youtube.com/@EbiAtawodi/videos—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Ebi's background(04:31) Four key elements of a product vision(08:14) Examples of lofty but attainable visions(11:43) Vision vs. mission (13:23) Examples of visions and missions from notable companies(15:00) A simple framework for outlining a vision (20:51) Other methods for outlining a vision (23:29) The impact of writing clear headlines(26:41) Using mockups to frame your vision(28:24) A step-by-step approach to developing a vision(32:58) Ebi's “10 Things” document(37:47) A quick summary of Ebi's tips(40:56) How to use the “10 Things” doc in a strategy session(43:11) The three concentric circles of evangelizing (47:48) The cadence of developing a vision and bringing it to life(49:26) Visions vs. micro visions(52:58) First steps in developing a vision(55:12) Infrastructure is the product(56:39) Clarity and conviction, the main jobs of PMs(59:58) Ebi's narrative doc(1:04:59) Conviction, its role in the job, and how to build it(1:08:20) How to build company culture(1:17:06) The monolithic culture at Uber(1:19:09) The culture Ebi embeds in her teams(1:23:58) How to evaluate your relationship with your engineering manager (1:26:02) What's new at YouTube(1:29:22) Ebi's closing thoughts(1:30:45) Lightning round—Referenced:• Andre Albuquerque on LinkedIn: https://www.linkedin.com/in/andre-albuquerque• TED's mission: https://www.ted.com/about/our-organization#:~:text=Our%20mission%3A%20Spread%20ideas%2C%20foster,and%20create%20impact%20%7C%20About%20%7C%20TED• Stripe's operating principles: https://stripe.com/jobs/culture• Microsoft's vision and mission: https://www.microsoft.com/en-us/about• Tesla's mission statement: https://www.tesla.com/blog/mission-tesla• Lyft's mission on Comparably: https://www.comparably.com/companies/lyft/mission• Ebi's playbooks and templates: https://docs.google.com/presentation/d/1tU3jpbq_xHcF4x1bdANCVBsO6rbQ8h1HqvdQfwGW4MA/edit• Working Backwards Press Release Template and Example: https://www.linkedin.com/pulse/working-backwards-press-release-template-example-ian-mcallister/• Patrick Collison on X: https://twitter.com/patrickc• Seinfeld meme: https://seinfeldmemes.com/you-know-how-to-take-the-reservation/• Travis Kalanick on LinkedIn: https://www.linkedin.com/in/traviskalanick/• Wimdu: https://www.wimdu.com/• Leaving big tech to build the #1 technology newsletter | Gergely Orosz (The Pragmatic Engineer): https://www.lennyspodcast.com/leaving-big-tech-to-build-the-1-technology-newsletter-gergely-orosz-the-pragmatic-engineer/• The 48 Laws of Power: https://www.amazon.com/48-Laws-Power-Robert-Greene/dp/0140280197• The God of Small Things: https://www.amazon.com/God-Small-Things-Novel/dp/0812979656/• Outliers: The Story of Success: https://www.amazon.com/Outliers-Story-Success-Malcolm-Gladwell/dp/0316017930• All About Love: https://www.amazon.com/All-About-Love-New-Visions/dp/0060959479• The Bear on Hulu: https://www.hulu.com/series/the-bear-05eb6a8e-90ed-4947-8c0b-e6536cbddd5f• Scavengers Reign on Max: https://www.max.com/shows/scavengers-reign/50c8ce6d-088c-42d9-9147-d1b19b1289d4• Sleep Cycle: https://www.sleepcycle.com/• Nanit: https://www.nanit.com/• “Invictus” by William Ernest Henley: https://www.poetryfoundation.org/poems/51642/invictus• Burning Man: https://burningman.org/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

My guests this week are the co-founders of Stripe, Patrick and John Collison. My conversation with John in 2020 is still one of our most popular. A key theme that emerged from that first discussion was John's boundless curiosity for all things business and this conversation continues that thread. We talk about setting a strategy and culture that attracts ambition, why the returns to sweating the details are high, and how they view Stripe's progress against their mission to increase the GDP of the internet. Please enjoy this great and wide-ranging discussion with John and Patrick Collison. Buy a ticket to Patrick and David Senra's live show this Thursday in NYC. Listen to Founders Podcast Founders Episode 311: James Cameron Subscribe to Colossus's New Show: Art of Investing For the full show notes, transcript, and links to mentioned content, check out the episode page here. ----- This episode is brought to you by Tegus. Tegus is the modern research platform for leading investors, and provider of Canalyst. Tired of calculating fully-diluted shares outstanding? Access every publicly-reported datapoint and industry-specific KPI through their database of over 4,000 drivable global models hand-built by a team of sector-focused analysts, 35+ industry comp sheets, and Excel add-ins that let you use their industry-leading data in your own spreadsheets. Tegus' models automatically update each quarter, including hard to calculate KPIs like stock-based compensation and organic growth rates, empowering investors to bypass the friction of sourcing, building and updating models. Make efficiency your competitive advantage and take back your time today. As a listener, you can trial Canalyst by Tegus for free by visiting tegus.co/patrick. ----- Invest Like the Best is a property of Colossus, LLC. For more episodes of Invest Like the Best, visit joincolossus.com/episodes.  Past guests include Tobi Lutke, Kevin Systrom, Mike Krieger, John Collison, Kat Cole, Marc Andreessen, Matthew Ball, Bill Gurley, Anu Hariharan, Ben Thompson, and many more. Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here. Follow us on Twitter: @patrick_oshag | @JoinColossus Show Notes (00:03:16) - (First question) - Stripe's curiosity-driven growth fuels enduring success and expansion (00:08:34) - Why companies should resonate with founders' ideas but also have strong enduring cultures (00:012:27) - Stripe aims to reduce friction and expand global commerce by solving practical barriers (00:25:59) - Simplifying processes for startups and large companies to drive growth efficiently (00:29:11) - Analyzing the enduring stories of ancient companies (00:35:44) - Success in Hollywood and academia depends on unmeasurable vision and knowledge (00:40:11) - Stripe's ubiquity, self-serve nature, and collective care drive its unique status (00:43:16) - Success in tech is grounded in user-centricity, care, and connecting with customers (00:48:17) - Parental influence on becoming entrepreneurs is complex (00:50:21) - Adult perspective on parents, admiration for their work, and ongoing philanthropy (00:52:30) - Stripe's challenges include complexity due to diverse payment methods and global programmable accessibility (00:57:27) - Aiming for long-term durability, Stripe prioritizes beauty and craftsmanship in its pursuit (01:02:50) - The most memorable conversation they had between them (01:05:30) - Why the launch of Atlas was a defining moment in Stripe's history (01:06:35) - How their 25-year-old selves would react to what they are doing now (01:10:19) - The various ways in which they feel proud of each other (01:14:35) - The kindest thing anyone has ever done for them