Podcast Notes Playlist: Startup

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. 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(00:06:08) 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

Shawn Ryan Show Intro Advice for future innovators: Work on something that you would be proud to fail at“There’s a whole generation or two that did not go into aviation because the door was closed to innovation.” – Blake Scholl Great people do not want to work for bosses who do not know what they are doing: There is no substitute for actually knowing what you are talking about and doing the work The world does not need more of what it has already got; the world needs more of what you can uniquely bring The incentives of government regulation agencies create an asymmetric bias towards conservatism, a reality that ultimately stifles progress and innovation; this centralizes and monopolizes risk decisions into the hands of government regulators The smaller the team, the easier it is to keep the talent bar high; the number one thing great people want is to work with other great people Using AI to create a talent engine: Have the AI handle the boring and rudimentary tasks so that human talent can work on the most interesting problems; this creates a flywheel of talent retention and magnetismBe unafraid to deploy inexperienced, high-aptitude talent – but phone somebody who has some gray hair The Speed Dividend from supersonic: If the flight is twice as fast, then you need half the number of pilots, half as many airplanes, and can get twice as many flights from the same number of airplanes and crewWork on what you love because you will learn so much about: You will learn 99% new stuff along the way, so why not learn 99.5% new stuff while working on something you really love?Go work on the thing that your five-year-old self would have been dazzled by Read the full notes @ podcastnotes.orgBlake Scholl is the Founder and CEO of Boom Supersonic, a company he started in 2014 to revive commercial supersonic flight with the Overture airliner, designed to fly at Mach 1.7 and carry 64–80 passengers. A Carnegie Mellon University computer science graduate (BS, 2001), Scholl began his career as a software engineer at Amazon, later owning a $300 million P&L at age 24, and co-founded Kima Labs, acquired by Groupon in 2012. Inspired by seeing Concorde in a museum, he self-taught aerospace engineering to launch Boom, which achieved the first privately developed supersonic flight with the XB-1 demonstrator in January 2025. With orders from United, American, and Japan Airlines, Scholl aims to make sustainable supersonic travel mainstream using 100% sustainable aviation fuel, targeting passenger flights by 2030. Shawn Ryan Show Sponsors: https://americanfinancing.net/srs NMLS 182334, nmlsconsumeraccess.org https://tryarmra.com/srs https://betterhelp.com/srs This episode is sponsored. Give online therapy a try at betterhelp.com/srs and get on your way to being your best self. https://meetfabric.com/shawn https://shawnlikesgold.com https://hexclad.com/srs https://hillsdale.edu/srs https://ketone.com/srs Visit https://ketone.com/srs for 30% OFF your subscription order https://ROKA.com – USE CODE SRS https://trueclassic.com/srs https://USCCA.com/srs https://blackbuffalo.com Learn more about your ad choices. Visit podcastchoices.com/adchoices

Crazy Wisdom Key Takeaways FarmBot is a robotic farmer for your garden, designed to take care of your garden by performing functions such as planting seeds, watering, weeding, and monitoringSimply being open source is not enough. For a project to be genuinely useful, it must also have extensive, clear documentation and use open, affordable file formatsToday, the vast majority of food that people eat is grown very far away and in ways that is not great for the food or environment We have very little control over the food production system, which is vital to our existence Let us get back to the smaller scale, more diverse polycrop system of food production; many follow-on benefits will result Building a resilient alternative to industrial food systems (which often rely on single-crop farming) reduces single points of failure along vulnerable supply chains The more that we can distribute the food system and bring it closer to the end-eater, the more robust our overall food system becomes Read the full notes @ podcastnotes.orgOn this episode of Crazy Wisdom, Stewart Alsop speaks with Rory Aronson, CEO of FarmBot, about how his open-source hardware project is transforming home gardening into a more automated and accessible practice. Rory explains how FarmBot works—essentially as a CNC machine for your garden—covering its evolution from Arduino-based electronics to custom boards, the challenges of integrating hardware and software, and the role of closed-loop feedback systems to prevent errors. They explore solarpunk visions of distributed food systems, discuss the importance of “useful source” documentation in open-source hardware, and imagine a future where growing food is as easy as running a dishwasher. For more on Rory and FarmBot, check out farm.bot and the open-source resources at docs.farm.bot.Check out this GPT we trained on the conversationTimestamps00:00 Rory explains FarmBot as a CNC machine for gardens, using Arduino and Raspberry Pi, automating planting, watering, and weeding.05:00 Discussion on the hardware stack evolution, open-source electronics roots, and moving to custom boards for better integration.10:00 Stewart shares his Raspberry Pi experiments, Rory breaks down the software layers from cloud apps to firmware, emphasizing complexity.15:00 Conversation shifts to closed-loop feedback with rotary encoders, avoiding 3D printer-style “spaghetti” errors in outdoor environments.20:00 Rory explores open-source challenges, highlighting “useful source” documentation and hardware accessibility for modifications.25:00 Solarpunk vision emerges: distributed food systems, automation enabling home-grown fresh food without expert knowledge.30:00 Raised bed setup, energy efficiency, and FarmBot as a home appliance concept for urban and suburban gardens.35:00 Small-scale versus industrial farming, niche commercial uses like seedling automation, and user creativity with custom tools.40:00 AI potential with vision systems, LLMs for garden planning, and enhancing FarmBot intelligence for real-time adaptation.45:00 Sensors, soil monitoring, image analysis for plant health, and empowering users to integrate FarmBot into smart homes.50:00 Rory describes community innovations, auxiliary hardware, and open documentation supporting experimentation.55:00 Final reflections on solarpunk futures, automation as empowerment, and how to access FarmBot’s resources online.Key InsightsRory Aronson shares how FarmBot began as a DIY project built on Arduino and Raspberry Pi, leveraging the open-source 3D printing ecosystem to prototype quickly. Over time, they transitioned to custom circuit boards to meet the specific demands of automating gardening tasks like seed planting, watering, and weeding, highlighting the tradeoffs between speed to market and long-term hardware optimization.The conversation unpacks the complexity of FarmBot’s “stack,” which integrates cloud-based software, a web app, a message broker, a Raspberry Pi running a custom OS, and firmware on both Arduino and auxiliary chips for real-time feedback. This layered approach is crucial for precision in an unpredictable outdoor environment where mechanical errors could damage growing plants.Aronson emphasizes that being open source isn’t enough; to be genuinely useful, projects must provide extensive, accessible documentation and export files in open, affordable formats. Without this, open source risks being a hollow promise for most users, especially in hardware where barriers to modification are higher.They explore the solarpunk potential of FarmBot, imagining a future where growing food at home is as effortless as using a washing machine. By turning gardening into an automated process, FarmBot enables people to produce fresh vegetables without needing expertise, offering resilience against industrial food systems reliant on monoculture and long supply chains.Aronson points out that while FarmBot isn’t designed for industrial agriculture, its modularity allows it to support niche commercial use cases, like automating seedling production in cleanroom environments. This adaptability reflects the broader vision of empowering both individuals and small operations with accessible automation tools.The episode highlights user creativity enabled by FarmBot’s open hardware, including custom tools like side-mounted mirrors for alternative camera angles and pneumatic grippers for harvesting. These community-driven innovations showcase the platform’s flexibility and the value of encouraging experimentation.Finally, Aronson sees great potential for integrating AI, particularly vision systems and multimodal LLMs, to make FarmBot smarter—detecting pests, diagnosing plant health, and even planning gardens tailored to user goals like nutrient needs or event timelines, moving closer to a truly intelligent gardening companion.