Podcast Notes Playlist: Startup

David Senra Key Takeaways Check out the episode page and show notesRead the full notes @ podcastnotes.orgTravis Kalanick is best known for co-founding Uber and building it into one of the world’s largest transportation platforms. Before Uber, he spent years building Red Swoosh under extreme financial pressure. He says he took no salary for its first four years, repeatedly ran out of money and lost much of his social life to the company before eventually selling it. He later invested much of the proceeds in friends’ startups, becoming the first investor in Expensify. Kalanick started Uber at 33 and carried the intensity of those earlier years into the company. He describes operating with “precision, perfection and obsession” and continued running Uber with the mentality of someone worried about making the next grocery bill even after the company had reached a valuation of roughly $70 billion. Under his leadership, Uber expanded rapidly across cities and countries, creating a new category of app-based transportation and challenging the entrenched taxi systems that controlled many local markets. Uber’s growth depended on empowering young operators to build markets from scratch while maintaining tight control over the decisions that mattered most. Kalanick personally participated in the pricing process for the company’s first 20 to 30 cities, using each launch to refine a playbook that could eventually operate without him. He describes this management philosophy as finding the line between order and chaos: using the fewest possible rules while preserving the structure required to move quickly at scale. After leaving Uber, he returned to company building within months. His current company, Atoms, is developing artificial intelligence and specialized robotics for industries including food, mining and transportation. Kalanick describes his role as “problem solver in chief,” focusing on the most consequential problems that are not already being solved and pursuing what he considers his broader calling: digitizing the physical world. Show notes: https://www.davidsenra.com/episode/travis-kalanick Made possible by Ramp: https://ramp.com AppLovin: https://applovin.com/senra Deel: https://deel.com/senra Chapters (00:00:00) Building Atoms & the Meta Problem of Management (00:03:51) The Appeal of Impossible Problems: Starting Over in China (00:12:19) Uber vs. Didi: Copycats, Hypergrowth & China's Rules (00:21:02) How Network Effects Become an Efficiency Fortress (00:31:48) Capitalism vs. the Taxi Cartel (00:44:05) The China War Goes Global & the Entrepreneur's Capacity for Pain (00:54:04) Life After Uber: Lawfare, Media Narratives & Reputation (00:58:21) What Founders Get Wrong About Venture Capital (01:08:35) The Fundraising Playbook: QED Storytelling & a Five-Room Auction (01:18:38) The Uber Coup, Radical Accountability & Outgrowing Fear (01:26:42) Why Specialized Robots Beat Humanoids at Industrial Scale (01:31:30) Finding Your Sport: Food, Mining & the Physical AI Stack (01:40:14) How to Build Many Companies Inside One Company (01:46:33) Entropy, Civilization & the Meaning of Progress Learn more about your ad choices. Visit megaphone.fm/adchoices

Knowledge Project Key Takeaways The dating site story is systems thinking in one anecdote: a large dating site hypothesized longer profiles would drive more engagement They tested it. It was true. They rolled it outMany, many months later they discovered it was negative for conversion — when people knew that much about each other, they converted lessThat is a second-derivative effect, and you only find it way after the factThe combination is the whole point: know the really old stuff (the history of your field, which signals passion) and really understand the new edge. Do both and you’re a power playerApplying for a marketing job at P&G or Pepsi? Know the legends of marketing and genuinely get TikTok. That’s a wildly differentiated candidateThe built-in filter: if learning the history of your field sounds tedious, you’re in the wrong lane. Tedium is the signal that the passion isn’t thereWall Street is the buyer of the product venture capitalists create, since liquidity is either M&A or an IPO and that’s where the price gets set — so even at two people on a PowerPoint, you’re asking whether this thing grown up is something that buyer gets excited aboutChina has roughly 10 good open source models and the farmer metaphor explains why that matters: two agricultural societies, in one the farmers come to market, sell goods, go home. In the other, they’re forced to share best practices with every other farmer. Which one evolves faster? They’re open sourcing weights and publishing the new techniques. Meanwhile a lot of US startups are quietly forking those modelsThe chart that tells the AI funding story: losses of the category-leading company before going cash flow positive. Amazon was two or three billion. Uber was around 15 billion. These AI companies will be way bigger than thatBurn rate used to be the risk metric: ten years ago a million a month was terrifying. Now companies burn five billion a year, over a hundred million a month, and at that speed it’s genuinely hard to know what your unit economics even areStablecoins are functionally a workaround for regulation the banks lobbied into existence. ACH takes three days, a same-day wire costs $25 and a page of forms, and credit cards charge 2 to 2.5% — “there’s zero reason why it should cost two or three percent, just zero” UK Faster Payments did instant bank-to-bank 20 years ago, Pix hit 60-70% of transactions within six years, and the US built FedNow but it went nowhereBill once asked Jeff Bezos how his angel portfolio was so successful given he has zero free time. The answer: when he meets an entrepreneur there is only one question he asks himself, is this person going to do this no matter what, come hell or high water?Benchmark made the partnership flat — no lead partner, no king, no president, just five equal partners, which makes recruiting easy, actually develops new partners, and eliminates all the annual comp politics. The one huge negative: with no CEO, nobody owns anything firm-wide, which is why the site is still a single splash page 15 years laterRead the full notes @ podcastnotes.orgBill Gurley spent years on Wall Street, built his career as a partner at Benchmark, worked through Uber’s hypergrowth era, and now serves on the board of the Santa Fe Institute, where he studies complexity and systems thinking. In this episode, Bill shares the mental models he returns to most, including systems thinking, second- and third-order effects, and the importance of understanding both the bedrock of your field and the bleeding edge. He explains what separates great founders, why storytelling and product instincts matter, how he uses AI across different models, and what he sees coming in open source, China, stablecoins, tokenization, payments, and venture capital.  ------ Timestamps: (00:00) Key Mental Models (02:02) Investing Journey and Key Players (05:21) Knowing the Bedrock of the Industry (08:50) Obsessive Learning in Founders (10:04) The Silent Edge (11:44) Surprising AI Use (13:13) The Future of AI Models (14:17) Global AI Regulation (18:12) Impacts of AI on Investing (19:53) Are There Limitations on Training AI Models? (23:04) Would You Sit in the Back Seat While Your Tesla Drives? (24:15) Non-Consensus Opinions (24:53) Are We Overfunding this Buildout? (29:40) The Role of Retail Investors and Tokenization (34:26) What is a Stablecoin? (37:58) Competitive Mode: Visa and Mastercard (39:55) AI and Debt Analysis (45:05) The Craft of Storytelling and Writing (48:07) Founder Advantage: Product Instinct (50:12) Real World Lessons from Working With Uber (52:10) Inside Benchmark’s Success (59:42) What is Success for You? ------ Newsletter: The Brain Food newsletter delivers actionable insights and thoughtful ideas every Sunday. It takes 5 minutes to read, and it’s completely free. Learn more and sign up at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠fs.blog/newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ------ Follow Shane Parrish: X: ⁠⁠⁠⁠⁠⁠https://x.com/shaneparrish⁠ Insta: ⁠https://www.instagram.com/farnamstreet/⁠ LinkedIn: ⁠https://www.linkedin.com/in/shane-parrish-050a2183/⁠ Follow Bill Gurley LinkedIn: https://www.linkedin.com/in/billgurley/ X: https://x.com/bgurley?lang=en Check out Runnin’ Down a Dream: How to Thrive in a Career You Actually Love ------ Thank you to the sponsors for this episode: +CoinShares: Delivering Reason to Digital Asset Investing. ⁠https://coinshares.com/⁠ +Granola AI, The AI notepad for people in back-to-back meetings: https://www.granola.ai/shane Check out the Granola Notes +HeyGen is a message-first AI video platform that helps people and AI agents turn ideas into professional video in minutes. Try for free at https://www.heygen.com/tkp +LMNT: My go-to zero sugar electrolytes — get a free LMNT Sample Pack here: DrinkLMNT.com/TKP Learn more about your ad choices. 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My First Million Key Takeaways Tesla as AI’s Largest Play: Tesla represents the world’s largest AI project, combining robotaxis ($8-10T opportunity, 50% platform capture) and humanoid robots ($26T opportunity in 7-15 years) Embodied AI (physical + digital) is severely underappreciated by marketsElon’s recent FSD breakthrough, solving “the last mile” problem, positions Tesla to dominate autonomous mobilityWright’s Law Investment Framework: Cost per unit falls by a constant percentage with every cumulative doubling of productionThis mathematical certainty drives exponential adoption in AI compute, EV batteries, robotics, and DNA sequencingEVs have unlimited doublings ahead; internal combustion engines have none—making legacy automotive “no shot” to compete long-termPortfolio Management Beyond Headlines: Selling Nvidia from early entry at $0.20 per share was not necessarily a mistake if proceeds were used to buy another stock that 10x’d in price Opportunity cost matters more than hindsight narrativesARK trades volatility thresholds around conviction holdings without thesis changesBull Market Discipline and Rebalancing: Top-performing stocks go crazy in bull runs; this requires active diversification and profit-taking End-point sensitivity in performance criticism ignores the fund timeframeHer future strategy: aggressive rebalancing guidance to counter fear/greed cycles inherent to retail investor behaviorRead the full notes @ podcastnotes.orgGet the free investing playbook to invest like Warren Buffet: https://clickhubspot.com/rme Episode 760: Shaan Puri ( ⁠https://x.com/ShaanVP⁠ ) talks to Cathie Wood ( https://x.com/CathieDWood ) about her fund’s performance, her biggest bets on AI, and the most misunderstood stock on earth. — Show Notes: (0:00) McDonald’s to Managing Billions (8:54) A day in the life of Cathie Wood (17:29) ARK’s Performance Review (30:00) Cathie’s #1 stock pick — Links: • ARK - https://www.ark-funds.com/ • The MFM Newsletter Challenge - https://www.beehiiv.com/application/mfm — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Need a bank for your company? Go check out Mercury (mercury.com). Shaan uses it for all of his companies! Mercury is a financial technology company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., and Evolve Bank & Trust, Members FDIC — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth • Sam’s List - http://samslist.co/ My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano

A16z Podcast Key Takeaways In any domain of human effort in which there is a verifiable answer, AI will drive extremely rapid progress; it is about the concreteness of the problem, not the difficulty In fields with concrete true/false answers (math, coding, physics, genomics), AI will drive extremely rapid advancementThe difficulty matters less than the concreteness of the problemAI agents can now code autonomously for hoursUsing platforms like Replit, anyone can describe an app in plain English, and AI will build itAgents maintain coherence through verification loops that allow them to check their work and course-correct in real-timeThe definition of AI is always the next thing that the machine can’t do; AI scientists are always being judged against the next thing, as opposed to all the things they have already accomplished We may be hitting diminishing returns with frontier modelsGPT-5 showed improvements in verifiable domains, but didn’t advance much elsewhereTop models excel at synthesizing information but struggle with nuanced, abstract problems and original discovery“Functional AGI” may block true AGI: AI that’s “good enough” to automate most economically useful tasks could reduce incentives to pursue actual general intelligenceThe real AGI benchmark should be efficient continual learning and generalized reasoning acquisitionRead the full notes @ podcastnotes.orgAmjad Masad, founder and CEO of Replit, joins a16z’s Marc Andreessen and Erik Torenberg to discuss the new world of AI agents, the future of programming, and how software itself is beginning to build software.They trace the history of computing to the rise of AI agents that can now plan, reason, and code for hours without breaking, and explore how Replit is making it possible for anyone to create complex applications in natural language. Amjad explains how RL unlocked reasoning for modern models, why verification loops changed everything, whether LLMs are hitting diminishing returns — and if “good enough” AI might actually block progress toward true general intelligence. Resources:Follow Amjad on X: https://x.com/amasadFollow Marc on X: https://x.com/pmarcaFollow Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

My First Million Key Takeaways The Eric Ryan Entrepreneurial Playbook: Find categories drowning in a sea of sameness, spot the macro trend incumbents are missing, then build the solution in that gap.Relentlessly look for a cultural shift that a category has missed: The future is here, it is just not evenly distributed If a category appears to take itself too seriously, then it is probably hiding something, and likely an opportunity to take advantage of in that space The goal is to create an object of desire; take something that people have to buy and turn it into something that people want to buy The entrepreneurial sweet spot lives at the intersection of familiarity and novelty; finding these intersections is the art formThe Power of Consumer Auditions: When you sit down with buyers, instead of trying to prove yourself, try to improve yourself and invite their feedback into your creative process When building off a successful product, change one thing at a time – throw consumers one egg and they’ll catch it; throw three and they’ll drop them allThe Art of Simplification is the biggest hack in entrepreneurship: The best entrepreneurs take complex ideas and simplify them down; this makes it easy for the consumer to understand and for the team to execute against If what you are working on is giving you energy back, then you are probably working on the right thing Read the full notes @ podcastnotes.orgWant the guide to spot $100M+ Product Ideas? Get it here: https://clickhubspot.com/hre Episode 754: Sam Parr ( https://x.com/theSamParr ) and Shaan Puri ( https://x.com/ShaanVP ) brainstorm $100M ideas with Eric Ryan ( https://x.com/ericthomasryan ). — Show Notes: (0:00) My $1B product playbook (3:32) Look for a sea of sameness (9:31) Trend trips (15:27) Remix opposing ideas (22:46) Case Study: Olly (32:14) The State of Make (37:54) IDEA: A better Metamucil (44:34) IDEA: The SoulCycle of diners (55:57) IDEA: White label chicken (1:03:28) Holy Grail of Naming (1:06:23) IDEA: Gourmet Babybels (1:10:28) IDEA: fun shaped cheese (1:14:26) Commit and then figure ou — Links: • Method - https://methodhome.com/ • Olly - https://www.olly.com/ • Welly - https://www.getwelly.com/ — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Need a bank for your company? Go check out Mercury (mercury.com). Shaan uses it for all of his companies! Mercury is a financial technology company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., and Evolve Bank & Trust, Members FDIC — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth • Sam’s List - http://samslist.co/ My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano

Invest Like the Best Key Takeaways Today, the challenge is not to make the model bigger; the problem is knowing how best to generate and create data in useful domains so that the model gets better at them AIs do not have to get to digital god mode for AI to have an enormous impact on productivity and society: Even if AI does not become smarter than humans in the short term, the economic value creation boom will still be enormous“If we didn’t have the AI boom, the US probably would be behind China and no longer the world hegemon by the end of the decade, if not sooner.” – Dylan Patel The US is doing what China has done historically: dumping tons of capital into something, and then the market becomes If there is a sustained lag in model improvement, the US economy will go into a recession; this is the case for Korea and Taiwan, too On the AI talent wars: If these companies are willing to spend billions on training runs, it makes sense to spend a lot on talent to optimize those runs and potentially mitigate errors We actually are not dedicating that much power to AI yet; only 3-4% of total power is going to data centers He is more optimistic on Anthropic than OpenAI; their revenue is accelerating much faster because of their focus on the $2 trillion software market, whereas OpenAI’s focus is split between many thingsWhile Meta “has the cards to potentially own it all”, Google is better positioned to dominate the consumer and professional markets Read the full notes @ podcastnotes.orgMy guest today is Dylan Patel. Dylan is the founder and CEO of SemiAnalysis. At SemiAnalysis Dylan tracks the semiconductor supply chain and AI infrastructure buildout with unmatched granularity—literally watching data centers get built through satellite imagery and mapping hundreds of billions in capital flows. Our conversation explores the massive industrial buildout powering AI, from the strategic chess game between OpenAI, Nvidia, and Oracle to why we're still in the first innings of post-training and reinforcement learning. Dylan explains infrastructure realities like electrician wages doubling and companies using diesel truck engines for emergency power, while making a sobering case about US-China competition and why America needs AI to succeed. We discuss his framework for where value will accrue in the stack, why traditional SaaS economics are breaking down under AI's high cost of goods sold, and which hardware bottlenecks matter most. This is one of the most comprehensive views of the physical reality underlying the AI revolution you'll hear anywhere. Please enjoy my conversation with Dylan Patel. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠ ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ramp’s mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp.com/invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to sign up for free and get a $250 welcome bonus. – This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Head to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ridgelineapps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about the platform. – This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ AlphaSense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. AlphaSense has completely transformed the research process with cutting-edge AI technology and a vast collection of top-tier, reliable business content. Invest Like the Best listeners can get a free trial now at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Alpha-Sense.com/Invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and experience firsthand how AlphaSense and Tegus help you make smarter decisions faster. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Show Notes: (00:00:00) Welcome to Invest Like the Best (00:05:12) The AI Infrastructure Buildout (00:08:25) Scaling AI Models and Compute Needs (00:11:44) Reinforcement Learning and AI Training (00:14:07) The Future of AI and Compute (00:17:47) AI in Practical Applications (00:22:29) The Importance of Data and Environments in AI Training (00:29:45) Human Analogies in AI Development (00:40:34) The Challenge of Infinite Context in AI Models (00:44:08) The Bullish and Bearish Perspectives on AI (00:48:25) The Talent Wars in AI Research (00:56:54) The Power Dynamics in AI and Tech (01:13:29) The Future of AI and Its Economic Impact (01:18:55) The Gigawatt Data Center Boom (01:21:12) Supply Chain and Workforce Dynamics (01:24:23) US vs. China: AI and Power Dynamics (01:37:16) AI Startups and Innovations (01:52:44) The Changing Economics of Software (01:58:12) The Kindest Thing

Knowledge Project Key Takeaways Ignorance can be a superpower; sometimes knowing too much kills action As an entrepreneur, the moment that you think you have it figured out, that is when your business starts to die The best insights often come not from getting what you want, but from watching closely when you don’tNever put yourself in a position to need the kindness of strangers The day you stop fearing competition is the day that competition stops fearing you Know who the decision-maker is; if you are in a big meeting and someone is sitting off in the corner in a suit, that’s probably the person you have to convince The most profitable decision on a spreadsheet can be the worst decision for a business: when the data point and anecdote differ, the anecdote is often right Every business that you see is the result of someone’s irrational dedication The outliers know every detail of their company; they do not make decisions nor operate from the spreadsheet Become someone people want to root for: Understand what you must do and how you approach life so that other people want you to succeed; having people rooting for your success is a powerful tailwind Most people explain away failure; the best dissect it like surgeons – the precision of your diagnosis proves the depth of your understanding What you get out of any effort is directly proportional to the effort that you put into it Read the full notes @ podcastnotes.orgEd Stack built Dick’s Sporting Goods from a struggling family store into an empire of more than 800 stores and billions in sales. Along the way he nearly lost everything. Multiple times. This episode is the story of what he did, how he did it, and the lessons you can learn. ----- Some of the things you'll learn in this episode: Never rely on the kindness of strangers. Your name is your biggest asset. The person who talks the least is usually the decision maker. Sometimes the most profitable decision on a spreadsheet is the worst decision for a business. Good businesses don’t need debt and bad ones can’t handle it. When the data and the anecdotes differ, you’re measuring the wrong thing. Trust isn’t earned in the easy times; it’s earned in the fire. People are rarely buying just your product. Give the underdog a chance. They want it more. Not knowing what you’re doing can be an asset. All money comes with strings. Your competition always has something to teach you. Always bet on yourself. Learn from mistakes, but don’t over-learn them. “The moment a business stops evolving, the moment its leaders sit back and think, ‘Everything’s good,’ that’s when it starts to fail.” Problems are opportunities to add value. Play the game to win. Become someone people want to help. Investment bankers are not your friends. Manically focus on the numbers. The recipe is boldness mixed with caution. What you get out of anything is directly proportional to what you put in. The spreadsheet is not the customer. Arguing teaches you how to think. If you go into a deal with a win-win mindset, it almost always works out. Clever excuses don’t make anything better. Every business is someone’s irrational dedication. The most important element of success is perseverance. Always let people keep their dignity. The cost of making others happy is losing yourself. Do right for the company. Do right for society. You can’t prosper unless the community around you prospers. Believing in someone before they believe in themselves changes everything. Learn more at: https://fs.blog/knowledge-project-podcast/outliers-ed-stack/ ----- Upgrade: Get a hand edited transcripts and ad free experiences along with my thoughts and reflections at the end of every conversation. Learn more @ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠fs.blog/membership⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ----- Newsletter: The Brain Food newsletter delivers actionable insights and thoughtful ideas every Sunday. It takes 5 minutes to read, and it’s completely free. Learn more and sign up at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠fs.blog/newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ----- Follow Shane Parrish X @ShaneAParrish Insta ⁠@farnamstreet⁠ LinkedIn ⁠Shane Parrish ----- This episode is for informational purposes only. Learn more about your ad choices. Visit megaphone.fm/adchoices

Invest Like the Best Key Takeaways Personalized, mastery-based learning (driven by AI) can enable students to learn 10x faster, mastering material in just two hours a day and freeing up time for real-world skills, entrepreneurship, and personal interestsMotivation is essential: Kids must love school for it to be effective. The greatest motivator is giving students time back in their day, achieved by efficient mastery learning.Time-based, lecture-driven models leave knowledge gaps: Most U.S. students plateau in middle school, as traditional education pushes content too fast, resulting in a fragile “swiss-cheese” learning foundationAI’s transformational role: With generative AI, obsolete textbooks and one-size-fits-all instruction are replaced by continuous, adaptive, and personalized feedback, tailored to each learner’s interests and needs.Feedback and growth mindset are superpowers: Receiving and seeking feedback in school builds resilience, accelerates learning, and prepares students to thrive beyond the classroomHigh standards + high support = success and happiness: Kids grow most when challenged and held to ambitious goals with strong mentoring, even if the process is uncomfortable.Gamification and engagement: Applying video game design and motivation mechanics to education can make learning irresistible, turning hard tasks into meaningful and fun challengesNo one-size-fits-all: Multiple school types, customized daily schedules, and teaching entrepreneurship, leadership, and teamwork ensure education aligns with each child’s unique strengths and ambitions.“I think this is one of the coolest projects happening in America that people are just starting to learn about.” – Patrick O’Shaughnessy on Alpha School Read the full notes @ podcastnotes.orgMy guest today is Joe Liemandt. Joe is the Principal at Alpha School and the founder of Triliogy Software and ESW Capital. He became the youngest member of the Forbes 400 in the 1990s before vanishing from public view for two decades—only to emerge with a $1 billion bet that he can make kids learn 10x faster using AI. Joe has built an AI tutoring system so effective that students at his Alpha School literally beg not to take summer breaks, achieving 2x learning outcomes in just 2 hours with standardized test results that compete with the best of them. We dive deep into why this could be the most valuable product he's ever built, his contrarian thesis that traditional SaaS is facing AI-driven obsolescence, and how his experience buying 100+ software companies prepared him for this moonshot in a trillion-dollar market that hasn't innovated in 200 years. For investors, this is a masterclass in deploying patient capital to rebuild broken systems from first principles, with insights on everything from regulatory moats to the intersection of AI and human psychology. As your excited skeptic, I push hard on the technology readiness, parental adoption hurdles, and whether this audacious vision can actually scale to a billion kids. Additionally, in a Colossus Profile released last week, our editor-in-chief Jeremy Stern reported, for the first time, Joe as the product guy behind Alpha School in a can’t miss piece of writing. And now please enjoy my conversation with Joe Liemandt. Joe Liemandt’s Colossus Profile by Jeremy Stern. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠ ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ramp’s mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp.com/invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to sign up for free and get a $250 welcome bonus. – This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Head to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ridgelineapps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about the platform. – This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ AlphaSense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. AlphaSense has completely transformed the research process with cutting-edge AI technology and a vast collection of top-tier, reliable business content. 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Show Notes: (00:00:00) Welcome to Invest Like the Best(00:06:08) How Alpha School Is Revolutionizing Learning(00:12:47) Personalized Tutoring with AI(00:19:59) Measuring the Impossible: 2x Learning Outcomes(00:25:39) All Educational Content Is Obsolete(00:35:51) Motivating Students: The Key to Success(00:42:06) Life Skills Workshops: Real-World Lessons(00:47:47) The Key to Happiness: High Standards(00:52:33) The Role of Guides and Coaches(00:58:22) Feedback Loops and AI in Education(01:04:20) The AI-Powered Classroom Experience(01:18:06) From Self-Doubt to Limitless Learning(01:28:20) Challenges in Public School Systems(01:41:56) Gamified Learning and Technology(01:49:46) From Trilogy to Trillion-Dollar Markets(01:55:05) Why Software Companies Fail(02:01:21) Trilogy University(02:10:39) Lessons from Mentors(02:17:25) Pushing Limits and Finding Passion(02:27:12) Joe's Kindest Thing