Podcasts about VC

Doug Evans is the founder and CEO of The Sprouting Company, an early pioneer in the natural foods industry, former paratrooper in the 82nd Airborne Division, and author of the national bestseller The Sprout Book. From building a multimillion-dollar graphic design firm in his early 20s to exiting Organic Avenue in an eight-figure deal, to raising $120M for Juicero—and losing it all publicly—Doug's entrepreneurial journey has been anything but linear. Now, he's on a mission to revolutionize home food production by teaching people how to grow ultra-nutritious sprouts right on their kitchen counter. On this episode we talk about: Why being willing to do what nobody else wants to do creates opportunity Charging what you're actually worth—and how one $25K invoice changed everything The hard lessons of raising venture capital and losing control of your company Turning public failure (Juicero) into personal reinvention Why sprouts may be the most underrated business (and health) opportunity of the decade The discipline required to override laziness, addiction, and self-sabotage Top 3 Takeaways Value your time—and price accordingly. Doug went from charging $200/hour to confidently asking for $25,000 for a single engagement. That shift in self-perception changed his earning ceiling overnight. VC money comes with strings. Raising $120M for Juicero created scale—but also invited control shifts that ultimately pushed Doug out of his own company. Solve your own problem first. The Sprouting Company was born from Doug asking, “What will I eat in the desert?” The best businesses often start as deeply personal solutions. Notable Quotes “If you're willing to do what nobody else wants to do, you'll get the opportunity.” “You can have anything you want—if you're willing to do the work and be patient.” “Something as small as a seed can grow into a multibillion-dollar company.” “Money is there to be made—but you have to create value first.” Doug's Entrepreneurial Timeline (The Good, The Bad, The Ugly) Built a multimillion-dollar graphic design company in his early 20s Walked away from a bad partnership to protect his freedom Scaled Organic Avenue to 10 NYC stores and achieved an eight-figure exit Founded Juicero, raised $120M+ from top-tier investors—and experienced a high-profile shutdown Reinvented himself in Wonder Valley and launched The Sprouting Company, now generating millions in revenue Connect with Doug Evans: Instagram: @dougevans LinkedIn: Doug Evans Company: The Sprouting Company Book: The Sprout Book  Travis Makes Money is made possible by HighLevel – the all-in-one sales & marketing platform built for agencies.  Capture leads, nurture them, and close more deals—all from one powerful platform.  Get an extended free trial at gohighlevel.com/travis Learn more about your ad choices. Visit megaphone.fm/adchoices

Over the course of a few days, $300 billion in market cap was wiped out from public SaaS companies. Looking at the ten most notable US publicly traded SaaS companies over the last six months, they have lost upwards of $600 billion. The public markets are signaling that the classic VC-funded SaaS model is under massive pressure to show rapid AI integration and tangible revenue growth. This episode examines the fallout of the SaaS market correction and what it means for go-to-market operators. We discuss the shift away from legacy system of record platforms toward agile, AI-native solutions that eat labor budgets. The conversation covers how to adjust your GTM strategy if you are not growing at AI rates, why cash flow is now king over growth at all costs, and how to build a resilient enterprise pipeline generation engine. Finally, we share predictions on which SaaS stocks might bounce back from the dip. Key Takeaways Companies failing to match AI-driven growth expectations are facing severe valuation resets from public markets, as AJ Bruno explains that "The argument you're hearing is AI will replace SaaS... that's the lazy argument... What AI is doing is it's compressing the time value of money." Software businesses unable to achieve hypergrowth must pivot to strict operational efficiency, with Sam Jacobs noting, "If you're generating $50 million growing 25% and you're just breaking even, I need you to either grow faster or be more profitable." Go-to-market professionals at legacy software companies have a limited opportunity to pivot their careers toward emerging technology, as Asad Zaman advises, "Right now the window is open... That window will get smaller and smaller as time grows by. So if you are not confident in your company, this is the time to make a shift and enter the new world." Connect with the Hosts & Guests: Host: Sam Jacobs  Host: AJ Bruno Host: Asad Zaman Topline is more than a YouTube Channel: Subscribe to Topline Newsletter. Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech. Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast!   Chapters: 00:00 Introduction to the SaaS Collapse 07:12 Billions Wiped From SaaS Market Caps 10:44 Compressing the Time Value of Money 14:27 Why Revenue Growth Trumps All 20:56 The Threat of AI Inference Costs 25:17 Shifting Careers to the AI World 28:21 Entering the Slow Growth Movement 35:27 Building Long Term Craft Businesses 38:29 Winning the Long Brand Game 42:03 Founder Burnout and Pivot Challenges 48:24 Managing Investor Board Expectations 52:02 Reengineering for a Platform Shift 60:57 Public SaaS Stock Rebound Picks  

From a back-corner “unofficial” interview at Bitcoin Investor Week, Jordi Visser explains why AI is the real macro driver and why markets can grow even without hiring as profit margins expand. He breaks down the shocking new correlation: Bitcoin tracking software ETFs, driven by liquidity, multiple compression, and the collapse of VC funding as AI becomes the “new shiny toy.” The conversation goes deeper into AI agents transacting, the coming shift in consumer payments, and why NFTs return as proof-of-authenticity in a world where AI makes fakes effortless.

In a world flooded with automation and digital noise, business success comes down to something simple: human connection. That's the core belief of Jon Ferrara, founder of GoldMine and Nimble. In this exclusive interview, Jon shares how building multi-million-dollar companies without VC funding—and surviving a life-changing health scare—reshaped his view of CRM. It's not about tracking sales; it's about nurturing relationships. He explains why traditional CRMs fail modern entrepreneurs, what to look for in your first tech stack, and why you must move from managing customers to managing your entire constituency. If you're a founder, coach, or entrepreneur struggling to stand out, this conversation will reframe how you think about growth—and why CRM matters now more than ever.Love the show? Subscribe, rate, review, and share!Here's How »Join Your First Thousand Clients Community today:mitchrusso.comMitch Russo LinkedIn

Is building data centers in space actually feasible? It may be, thanks to Ariel Ekblaw. The scientist, VC investor and co-founder and CEO of Aurelia Institute has devoted her life to democratizing space and ensuring that humans will one day be a spacefaring species. Ariel sits down with Oz to discuss self-assembling space architecture, how science-fiction influences her inventions, and why she doesn’t think billionaires investing in space is a bad thing.See omnystudio.com/listener for privacy information.

This week, we're back with another weekly roundup where Rob walks us through Dragonfly's most recent $650M raise. We deep dive into the state of crypto VC, what allocators look for when deploying into crypto, whether tokens are investable in 2026, if Base will launch a token, and more. Enjoy. -- Follow Rob: https://x.com/HadickM Follow Santi: https://x.com/santiagoroel Follow Empire:https://x.com/theempirepod -- Join us at DAS (Digital Asset Summit) in New York City this March! Follow the link below to grab your ticket, and use code EMPIRE200 to get $200 off your ticket! https://blockworks.co/event/digital-asset-summit-nyc-2026 -- Coinbase crypto-backed loans, powered by Morpho, enable you to take out loans at competitive rates using crypto as collateral. Rates are typically 4% to 8%. Borrow up to $5M using BTC as collateral and up to $1M using ETH as collateral. Manage crypto-backed loans directly in the Coinbase app with ease. Learn more here: https://www.coinbase.com/onchain/borrow/get-started?utm_campaign=0126_defi-borrow_blockworks_empire&marketId=0x9103c3b4e834476c9a62ea009ba2c884ee42e94e6e314a26f04d312434191836&utm_source=empire -- Timestamps: (00:00) Introduction (00:47) Inside Dragonfly's $650m Raise (10:57) The State of Crypto VC (30:19) Coinbase Ad (31:03) DAS Plug (31:28) Are Tokens Investable? (40:54) Will Base Launch A Token? (45:23) Hyperliquid's Policy Center (48:55) Content of The Week -- Disclaimer: Nothing said on Empire is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Santiago, Jason, Rob and our guests may hold positions in the companies, funds, or projects discussed.

Andrew McConnell built a SaaS company that helped vacation rental managers price homes like airlines using dynamic pricing based on demand. He eventually successfully exited, but not before learning the hard way that building a company and selling one require two entirely different skill sets.  In this episode of Built to Sell Radio, Andrew walks through the pivot that saved his business, why his VC backers stayed on board, and the exact moment he realized that a "short buyer list" is a dangerous trap for founders.  Listen in to discover how to:  Spot the "hidden ceiling" in a business that looks like it's doubling—right up until it isn't.  Move a cap table from a failed bet into a new one without lighting your professional relationships on fire.  Understand liquidation preference in plain English (and why it can erase a founder's take-home pay at exit).  See why a banker's real value isn't just managing the process—it's forcing pressure and widening the field of potential acquirers  Avoid the "I can sell this myself" mindset that often results in a year of free research for buyers and zero leverage for you. 

Robinhood revealed the companies their VC fund invested in… because it's IPOing this month.Stanley's Quencher sales are dropping… so it's pivoting to guys, gym bags, and protein #ManlyHow do you save Colorado's worst ski season?… With one innovative fence. And a trick from Fenway park.Plus, forget Olympic gold… because a Girl Scout just set the record for most cookies ever sold: $700K$HOOD $MTN $BTCBuy tickets to The IPO Tour (our In-Person Offering) TODAYAustin, TX (2/25): SOLD OUTArlington, VA (3/11): https://www.arlingtondrafthouse.com/shows/341317 New York, NY (4/8): https://www.ticketmaster.com/event/0000637AE43ED0C2Los Angeles, CA (6/3): SOLD OUTGet your TBOY Yeti Doll gift here: https://tboypod.com/shop/product/economic-support-yeti-doll NEWSLETTER:https://tboypod.com/newsletter OUR 2ND SHOW:Want more business storytelling from us? Check our weekly deepdive show, The Best Idea Yet: The untold origin story of the products you're obsessed with. Listen for free to The Best Idea Yet: https://wondery.com/links/the-best-idea-yet/NEW LISTENERSFill out our 2 minute survey: https://qualtricsxm88y5r986q.qualtrics.com/jfe/form/SV_dp1FDYiJgt6lHy6GET ON THE POD: Submit a shoutout or fact: https://tboypod.com/shoutouts SOCIALS:Instagram: https://www.instagram.com/tboypod TikTok: https://www.tiktok.com/@tboypodYouTube: https://www.youtube.com/@tboypod Linkedin (Nick): https://www.linkedin.com/in/nicolas-martell/Linkedin (Jack): https://www.linkedin.com/in/jack-crivici-kramer/Anything else: https://tboypod.com/ About Us: The daily pop-biz news show making today's top stories your business. Formerly known as Robinhood Snacks, The Best One Yet is hosted by Jack Crivici-Kramer & Nick Martell. Hosted on Acast. See acast.com/privacy for more information.

In this episode of Scouting for Growth, Sabine VanderLinden welcomes Gil Arazi—a serial entrepreneur, executive, and leading insurtech investor—to explore the urgent transformation taking place in insurance. Gil Arazi argues that the industry's traditional role of simply paying claims post-loss is outdated and that prevention is the new north star for sustainable growth. Their conversation dives into why insurance must shift from risk transfer to risk mitigation, what the future holds as data, AI, and even quantum computing disrupt business models, and how prevention can actually drive profit—not just avoid cost. Gil Arazi introduces The Spark, a not-for-profit initiative designed to help insurers decrease systemic risk and increase societal resilience through practical collaboration, not empty innovation theater. KEY TAKEAWAYS Reflecting on my conversation with Gil Arazi, several themes truly stood out, affirming both the urgency and opportunity for true transformation across insurance.  First, it's clear that insurance cannot remain content with its legacy of paying claims post-loss. We are entering an era where prevention, not just remediation, is imperative—technological advancements, from AI to quantum computing, now offer insurers the tools to anticipate and prevent systemic risks, fundamentally altering their value to customers and society. The model must evolve from chasing losses to proactively reducing risk, and this shift is not just about cost efficiency, but empowering profitable growth through enhanced customer retention and relevance. In building The Spark as a nonprofit prevention lab, Gil Arazi emphasized a collective responsibility: by leveraging data, domain expertise, and increasingly mature technology, we—insurers, partners, and innovators—can bridge the protection gap and act as genuine “protection architects.” This vision requires us to move beyond innovation theater and toward real operational enablement, where execution trumps experimentation. The challenge, however, is not just technological—it is cultural and emotional. Building trust across competitors demands we fall in love with solving the problem, not just owning the solution. Clear boundaries and shared vulnerabilities create the foundation for meaningful collaboration on the risks no single entity can control alone. BEST MOMENTS “The insurance industry needs to move from reacting to the claim ... to proactive prevention of this damage or systemic risk.”  “The only way insurance can be actually successful and sustainably profitable is by being biased.”  “Technology will predict risk, but humans will decide what to do with it. Algorithms are very good at probability, but they're terrible at responsibility.”  “Do something good for humanity and for yourself. If you can't measure your impact by the loss that never happened, you're just optimizing the decline.”  “The real revolution isn't technological anymore. It is emotional, it is behavioral, and it is strategic.”  ABOUT THE GUEST Gil Arazi is recognized as an insurance industry disruptor and visionary. He's the founder and managing partner of Fintlv Venture Capital—a top insurtech VC fund with close to $1 billion invested globally—and the founder of The Spark, a purpose-driven, not-for-profit global prevention lab.  With a career spanning nearly 30 years, including executive leadership, board roles, and serial entrepreneurship in insurance, Gil Arazi has first-hand insight into the industry's pain points and future opportunities. His work focuses on shifting insurance from loss-payout to loss-prevention, leveraging technology and collaboration to build resilience and drive growth. LinkedIn ABOUT THE HOST Sabine VanderLinden is a corporate strategist turned entrepreneur and the CEO of Alchemy Crew Ventures. She leads venture-client labs that help Fortune 500 companies adopt and scale cutting-edge technologies from global tech ventures. A builder of accelerators, investor, and co-editor of the bestseller The INSURTECH Book, Sabine is known for asking the uncomfortable questions—about AI governance, risk, and trust. On Scouting for Growth, she decodes how real growth happens—where capital, collaboration, and courage meet. If this episode sparked your thinking, follow Sabine VanderLinden on LinkedIn, Twitter, and Instagram for more insights. And if you're interested in sponsoring the podcast, reach out to the team at hello@alchemycrew.ventures

OpenClaw's creator makes headlines by joining OpenAI after GitHub fame and a whirlwind of VC and big tech offers, redefining what's possible for independent developers in the AI arms race. Is this the year agentic AI goes mainstream, and are the big players ready for that disruption? OpenClaw, OpenAI and the future | Peter Steinberger OpenAI disbands mission alignment team Opinion | I Left My Job at OpenAI. Putting Ads on ChatGPT Was the Last Straw. - The New York Times Introducing GPT‑5.3‑Codex‑Spark Anthropic releases Sonnet 4.6 Exclusive: Pentagon threatens to cut off Anthropic in AI safeguards dispute Google's Pixel 10a Launches on March 5 for $499 Google's AI drug discovery spinoff Isomorphic Labs claims major leap beyond AlphaFold 3 Gemini 3 Deep Think: AI model update designed for science Radio host David Greene says Google's NotebookLM tool stole his voice A new way to express yourself: Gemini can now create music Why an A.I. Video of Tom Cruise Battling Brad Pitt Spooked Hollywood GPT-5 outperforms federal judges 100% to 52% in legal reasoning experiment An AI project is creating videos to go with Supreme Court justices' real words I used Claude to negotiate $163,000 off a hospital bill. In a complex healthcare system, AI is giving patients power. Sony Tech Can Identify Original Music in AI-Generated Songs AI Pioneer Fei-Fei Li's Startup World Labs Raises $1 Billion Yann v. Yoshua on directed systems Dr. Oz pushes AI avatars as a fix for rural health care. Not so fast, critics say An AI Agent Published a Hit Piece on Me An Ars Technica Reporter Blamed A.I. Tools for Fabricating Quotes in a Bizarre A.I. Story Plain Dealer using AI to write reporters' stories Mediahuis trials use of AI agents to carry out 'first-line' news reporting DJI's first robovac is an autonomous cleaning drone you can't trust Leaked Email Suggests Ring Plans to Expand 'Search Party' Surveillance Beyond Dogs ai;dr I hate my AI pet with every fiber of my being Thanks a lot, AI: Hard drives are sold out for the year, says WD Students Are Being Treated Like Guinea Pigs:' Inside an AI-Powered Private School peon-ping — Stop babysitting your terminal Hugo Barra makes a to-do agent Raspberry Pi soars 40% as CEO buys stock, AI chatter builds Hosts: Leo Laporte, Jeff Jarvis, and Emily Forlini Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: monarch.com with code IM bitwarden.com/twit preview.modulate.ai spaceship.com/twit

OpenClaw's creator makes headlines by joining OpenAI after GitHub fame and a whirlwind of VC and big tech offers, redefining what's possible for independent developers in the AI arms race. Is this the year agentic AI goes mainstream, and are the big players ready for that disruption? OpenClaw, OpenAI and the future | Peter Steinberger OpenAI disbands mission alignment team Opinion | I Left My Job at OpenAI. Putting Ads on ChatGPT Was the Last Straw. - The New York Times Introducing GPT‑5.3‑Codex‑Spark Anthropic releases Sonnet 4.6 Exclusive: Pentagon threatens to cut off Anthropic in AI safeguards dispute Google's Pixel 10a Launches on March 5 for $499 Google's AI drug discovery spinoff Isomorphic Labs claims major leap beyond AlphaFold 3 Gemini 3 Deep Think: AI model update designed for science Radio host David Greene says Google's NotebookLM tool stole his voice A new way to express yourself: Gemini can now create music Why an A.I. Video of Tom Cruise Battling Brad Pitt Spooked Hollywood GPT-5 outperforms federal judges 100% to 52% in legal reasoning experiment An AI project is creating videos to go with Supreme Court justices' real words I used Claude to negotiate $163,000 off a hospital bill. In a complex healthcare system, AI is giving patients power. Sony Tech Can Identify Original Music in AI-Generated Songs AI Pioneer Fei-Fei Li's Startup World Labs Raises $1 Billion Yann v. Yoshua on directed systems Dr. Oz pushes AI avatars as a fix for rural health care. Not so fast, critics say An AI Agent Published a Hit Piece on Me An Ars Technica Reporter Blamed A.I. Tools for Fabricating Quotes in a Bizarre A.I. Story Plain Dealer using AI to write reporters' stories Mediahuis trials use of AI agents to carry out 'first-line' news reporting DJI's first robovac is an autonomous cleaning drone you can't trust Leaked Email Suggests Ring Plans to Expand 'Search Party' Surveillance Beyond Dogs ai;dr I hate my AI pet with every fiber of my being Thanks a lot, AI: Hard drives are sold out for the year, says WD Students Are Being Treated Like Guinea Pigs:' Inside an AI-Powered Private School peon-ping — Stop babysitting your terminal Hugo Barra makes a to-do agent Raspberry Pi soars 40% as CEO buys stock, AI chatter builds Hosts: Leo Laporte, Jeff Jarvis, and Emily Forlini Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: monarch.com with code IM bitwarden.com/twit preview.modulate.ai spaceship.com/twit

OpenClaw's creator makes headlines by joining OpenAI after GitHub fame and a whirlwind of VC and big tech offers, redefining what's possible for independent developers in the AI arms race. Is this the year agentic AI goes mainstream, and are the big players ready for that disruption? OpenClaw, OpenAI and the future | Peter Steinberger OpenAI disbands mission alignment team Opinion | I Left My Job at OpenAI. Putting Ads on ChatGPT Was the Last Straw. - The New York Times Introducing GPT‑5.3‑Codex‑Spark Anthropic releases Sonnet 4.6 Exclusive: Pentagon threatens to cut off Anthropic in AI safeguards dispute Google's Pixel 10a Launches on March 5 for $499 Google's AI drug discovery spinoff Isomorphic Labs claims major leap beyond AlphaFold 3 Gemini 3 Deep Think: AI model update designed for science Radio host David Greene says Google's NotebookLM tool stole his voice A new way to express yourself: Gemini can now create music Why an A.I. Video of Tom Cruise Battling Brad Pitt Spooked Hollywood GPT-5 outperforms federal judges 100% to 52% in legal reasoning experiment An AI project is creating videos to go with Supreme Court justices' real words I used Claude to negotiate $163,000 off a hospital bill. In a complex healthcare system, AI is giving patients power. Sony Tech Can Identify Original Music in AI-Generated Songs AI Pioneer Fei-Fei Li's Startup World Labs Raises $1 Billion Yann v. Yoshua on directed systems Dr. Oz pushes AI avatars as a fix for rural health care. Not so fast, critics say An AI Agent Published a Hit Piece on Me An Ars Technica Reporter Blamed A.I. Tools for Fabricating Quotes in a Bizarre A.I. Story Plain Dealer using AI to write reporters' stories Mediahuis trials use of AI agents to carry out 'first-line' news reporting DJI's first robovac is an autonomous cleaning drone you can't trust Leaked Email Suggests Ring Plans to Expand 'Search Party' Surveillance Beyond Dogs ai;dr I hate my AI pet with every fiber of my being Thanks a lot, AI: Hard drives are sold out for the year, says WD Students Are Being Treated Like Guinea Pigs:' Inside an AI-Powered Private School peon-ping — Stop babysitting your terminal Hugo Barra makes a to-do agent Raspberry Pi soars 40% as CEO buys stock, AI chatter builds Hosts: Leo Laporte, Jeff Jarvis, and Emily Forlini Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: monarch.com with code IM bitwarden.com/twit preview.modulate.ai spaceship.com/twit

In this episode of Excess Returns, Jason Hsu returns for a wide-ranging conversation on China's economy, the global AI race, emerging markets, factor investing, and what the next phase of globalization could mean for U.S. investors. We explore how China's fiercely competitive domestic capitalism contrasts with common Western narratives, why AI could reshape professional services the way globalization reshaped manufacturing, and how investors should think about portfolio allocation in a shifting G2 world.This discussion covers China manufacturing dominance, Chinese EV competition, U.S. vs. China AI strategy, emerging markets investing, factor investing in inefficient markets, and how machine learning is changing quantitative portfolio management.Main topics coveredWhy U.S. investors misunderstand China's economic system and the role of competition inside its domestic marketHow China became the world's manufacturing powerhouse and what that means for tariffs and trade warsThe Chinese government's role as a venture-style capital allocator rather than a central plannerThe real estate reset in China and the shift toward technology, AI, and advanced manufacturingAI as the next wave of globalization and its impact on professional services and labor marketsWhether the U.S. vs. China AI competition is truly winner-take-allCapital expenditure intensity in the U.S. vs. capital efficiency and open-source innovation in ChinaU.S. exceptionalism, G2 geopolitics, and portfolio diversification beyond a U.S.-centric allocationWhy emerging markets ex-China may differ from China tech exposureThe case for separating China from emerging markets in asset allocationThe concept of China as an alpha reservoir due to retail-driven market inefficienciesWhy traditional value and factor strategies have struggled in the U.S. but still work in ChinaHow machine learning and AI are changing quantitative investing and factor constructionThe launch of CNQQ and accessing large-cap China technology exposureTimestamps00:00 China as the world's factory and the role of fierce internal competition01:02 Why U.S. investors misunderstand China's economy03:48 Is China capitalist despite the Communist Party label05:33 The government as a VC-style investor rather than central planner07:45 China EV competition and manufacturing dominance09:23 Tariffs, trade leverage, and manufacturing monopoly dynamics12:18 China's bear market and valuation opportunity13:59 The real estate reset and shift toward productive capital16:00 AI as the next wave of globalization18:01 Labor force participation and economic disruption from AI19:46 Jobs that may survive in an AI-dominated world22:00 Is U.S. vs. China AI a winner-take-all battle24:13 Chip restrictions and long-term innovation incentives26:54 Capital efficiency in China vs. heavy AI capex in the U.S.29:27 Rebalancing away from U.S.-centric portfolios31:18 The end of U.S. exceptionalism and the move toward a G2 world34:00 How endowments approach U.S., developed, and emerging markets36:35 CNQQ and accessing China large-cap technology40:45 China as the great alpha reservoir45:49 The future of factor investing in efficient vs. inefficient markets49:06 Machine learning, factor decay, and next-generation quant strategies55:17 Can AI replace active portfolio managersIf you enjoy deep conversations on global markets, AI investing, China technology, emerging markets, and quantitative strategies, make sure to subscribe to Excess Returns for more interviews with leading investors and thinkers.

OpenClaw's creator makes headlines by joining OpenAI after GitHub fame and a whirlwind of VC and big tech offers, redefining what's possible for independent developers in the AI arms race. Is this the year agentic AI goes mainstream, and are the big players ready for that disruption? OpenClaw, OpenAI and the future | Peter Steinberger OpenAI disbands mission alignment team Opinion | I Left My Job at OpenAI. Putting Ads on ChatGPT Was the Last Straw. - The New York Times Introducing GPT‑5.3‑Codex‑Spark Anthropic releases Sonnet 4.6 Exclusive: Pentagon threatens to cut off Anthropic in AI safeguards dispute Google's Pixel 10a Launches on March 5 for $499 Google's AI drug discovery spinoff Isomorphic Labs claims major leap beyond AlphaFold 3 Gemini 3 Deep Think: AI model update designed for science Radio host David Greene says Google's NotebookLM tool stole his voice A new way to express yourself: Gemini can now create music Why an A.I. Video of Tom Cruise Battling Brad Pitt Spooked Hollywood GPT-5 outperforms federal judges 100% to 52% in legal reasoning experiment An AI project is creating videos to go with Supreme Court justices' real words I used Claude to negotiate $163,000 off a hospital bill. In a complex healthcare system, AI is giving patients power. Sony Tech Can Identify Original Music in AI-Generated Songs AI Pioneer Fei-Fei Li's Startup World Labs Raises $1 Billion Yann v. Yoshua on directed systems Dr. Oz pushes AI avatars as a fix for rural health care. Not so fast, critics say An AI Agent Published a Hit Piece on Me An Ars Technica Reporter Blamed A.I. Tools for Fabricating Quotes in a Bizarre A.I. Story Plain Dealer using AI to write reporters' stories Mediahuis trials use of AI agents to carry out 'first-line' news reporting DJI's first robovac is an autonomous cleaning drone you can't trust Leaked Email Suggests Ring Plans to Expand 'Search Party' Surveillance Beyond Dogs ai;dr I hate my AI pet with every fiber of my being Thanks a lot, AI: Hard drives are sold out for the year, says WD Students Are Being Treated Like Guinea Pigs:' Inside an AI-Powered Private School peon-ping — Stop babysitting your terminal Hugo Barra makes a to-do agent Raspberry Pi soars 40% as CEO buys stock, AI chatter builds Hosts: Leo Laporte, Jeff Jarvis, and Emily Forlini Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: monarch.com with code IM bitwarden.com/twit preview.modulate.ai spaceship.com/twit

Shahar Goldboim is the Founder and CEO of Boom, an AI-enabled property management platform for short-term rental portfolios built by operators. Shahar is an entrepreneur and builder, and he launched Boom with his two sibblings after identifying real-world operational pain points inside a large South Florida property management company as it scaled. Under his leadership, Boom delivers comprehensive software that simplifies workflows, increases revenue, and reduces costs for property managers.(02:15) - Why Short-Term Rentals Are the Hardest Asset Class(02:44) - Fragmentation and the Review-Driven Revenue Trap(04:13) - The Spark: A Miami Airbnb Experiment(05:30) - From Airbnb Host to Property Manager(07:31) - Software Fragmentation in STR Ops(07:55) - From SaaS to Baas (Business-as-Software)(09:09) - Boom, the AI PMS(12:47) - Enabling Proactive Ops(13:51) - The $12M+ Fundraise(14:47) - Winning Investors with Hospitality & Tech Credibility(16:53) - Feature: Blueprint Vegas 2026(17:46) - STR Market Context and the Vacasa Lesson(21:03) - Replacing Point Solutions(23:47) - ROI, AI Moats, Future of STR Ops(32:06) - Collaboration Superpower: Tony Robbins (Wiki)

Review of Marc Spector: Moon Knight #1 (2026) Check out the video version of the episode here! EPISODE 377 The High Priest Rey discusses his thoughts on the brank spankin new series for Moon Knight!  It also heralds the return of Devmalya Pramanik on art, which is always a treat! Teaming up with Jed MacKay, you're sure to get one helluva issue! Marc is drugged and out of his mind - but can an unlikely companion help him escape? Tune in to find out! Marc Spector: Moon Knight Vol. 2  #1 "Agency - Part One" Release Date Febuary 11 2026 Cover Date April 2026   Writer(s) Jed MacKay Penciler(s) Devmalya Pramanik Inker(s) Devmalya Pramanik Colorist(s) Rachelle Rosenberg Letterer(s) VC's Cory Petit Editor(s) Devin Lewis Drew Baumgartner Shine those idols, and dust off the cape....IT'S TIME TO GET YOUR KHONSHU ON! SHOW NOTES: Marc Spector: Moon Knight Vol. 2 #1 WHERE TO HEAR US: Podcast Page Podchaser Apple Podcast Google Play Music Spotify Overcast SoundCloud Stitcher Tunein Podbean Into the Knight RSS Feed YouTube DROP US A LINE: Website: intotheknight.libsyn.com Email: feedback@itkmoonknight.com FB Page: Into the Knight- A Moon Knight Podcast Page FB Group: Into the Knight- A Moon Knight Fan Base Bluesky: Into the Knight - Bluesky X: @ITKmoonknight Instagram: ITK Moon Knight Discord ITK Server: ITK Server   CHECK OUT THESE OTHER SHOWS WE CO-HOST! Sons of the Dragon - An Immortal Iron Fist Podcast DCAU - The DC Animated Universe Podcast  Capes & Lunatics Sidekicks To Know Her Is To Fear Her: The Spider-Woman Podcast Predator & pREY - a Yautja Podcast Rey Plays Games!   OFFICIAL ITK MERCHANDISE @ DASHERY - BUY HERE! Thinking of starting your own podcast? Check out our special offer from Libsyn!   CREDITS: ITK Logo Graphic Design by The High Priests of Khonshu ITK Graphic Design produced and assisted by Randolph Benoit ITK Opening Sequence for video by Chris Kelly Music Written, Performed and generously provided by Deleter Co-Producers Wayne Hunt Josh Johnson Anthony Sytko Matthew Howell Jonathan Sapsed Dan Newland Executive Producers Justin Osgood Derek O'Neill Daniel Doing Mario Di Giacomo Odin Odinsword Produced by Reynaldo Gesmundo The music for this episode contains excerpts from various songs and music copyrighted by Deleter and Brian Warshaw. The music agreed for use on Into the Knight - A Moon Knight Podcast is licensed under an Attribution License;

Many operators launch funds to achieve scale and create diversification for themselves and their investors. Funds also attract lower cost of capital and achieve operational efficiencies that result in improved yield. From an investor standpoint, funds mitigate additional risk because of compliance requirements and third-party auditing. Bridger Pennington, co-founder and CEO of Fund Launch, has helped incubate over 400 funds including Real Estate, VC and Private Equity funds. Bridger recently started his own successful GP Stakes micro fund which has generated above market returns.

Tickets for AIEi Miami and AIE Europe are live, with first wave speakers announced!From pioneering software-defined networking to backing many of the most aggressive AI model companies of this cycle, Martin Casado and Sarah Wang sit at the center of the capital, compute, and talent arms race reshaping the tech industry. As partners at a16z investing across infrastructure and growth, they've watched venture and growth blur, model labs turn dollars into capability at unprecedented speed, and startups raise nine-figure rounds before monetization.Martin and Sarah join us to unpack the new financing playbook for AI: why today's rounds are really compute contracts in disguise, how the “raise → train → ship → raise bigger” flywheel works, and whether foundation model companies can outspend the entire app ecosystem built on top of them. They also share what's underhyped (boring enterprise software), what's overheated (talent wars and compensation spirals), and the two radically different futures they see for AI's market structure.We discuss:* Martin's “two futures” fork: infinite fragmentation and new software categories vs. a small oligopoly of general models that consume everything above them* The capital flywheel: how model labs translate funding directly into capability gains, then into revenue growth measured in weeks, not years* Why venture and growth have merged: $100M–$1B hybrid rounds, strategic investors, compute negotiations, and complex deal structures* The AGI vs. product tension: allocating scarce GPUs between long-term research and near-term revenue flywheels* Whether frontier labs can out-raise and outspend the entire app ecosystem built on top of their APIs* Why today's talent wars ($10M+ comp packages, $B acqui-hires) are breaking early-stage founder math* Cursor as a case study: building up from the app layer while training down into your own models* Why “boring” enterprise software may be the most underinvested opportunity in the AI mania* Hardware and robotics: why the ChatGPT moment hasn't yet arrived for robots and what would need to change* World Labs and generative 3D: bringing the marginal cost of 3D scene creation down by orders of magnitude* Why public AI discourse is often wildly disconnected from boardroom reality and how founders should navigate the noiseShow Notes:* “Where Value Will Accrue in AI: Martin Casado & Sarah Wang” - a16z show* “Jack Altman & Martin Casado on the Future of Venture Capital”* World Labs—Martin Casado• LinkedIn: https://www.linkedin.com/in/martincasado/• X: https://x.com/martin_casadoSarah Wang• LinkedIn: https://www.linkedin.com/in/sarah-wang-59b96a7• X: https://x.com/sarahdingwanga16z• https://a16z.com/Timestamps00:00:00 – Intro: Live from a16z00:01:20 – The New AI Funding Model: Venture + Growth Collide00:03:19 – Circular Funding, Demand & “No Dark GPUs”00:05:24 – Infrastructure vs Apps: The Lines Blur00:06:24 – The Capital Flywheel: Raise → Train → Ship → Raise Bigger00:09:39 – Can Frontier Labs Outspend the Entire App Ecosystem?00:11:24 – Character AI & The AGI vs Product Dilemma00:14:39 – Talent Wars, $10M Engineers & Founder Anxiety00:17:33 – What's Underinvested? The Case for “Boring” Software00:19:29 – Robotics, Hardware & Why It's Hard to Win00:22:42 – Custom ASICs & The $1B Training Run Economics00:24:23 – American Dynamism, Geography & AI Power Centers00:26:48 – How AI Is Changing the Investor Workflow (Claude Cowork)00:29:12 – Two Futures of AI: Infinite Expansion or Oligopoly?00:32:48 – If You Can Raise More Than Your Ecosystem, You Win00:34:27 – Are All Tasks AGI-Complete? Coding as the Test Case00:38:55 – Cursor & The Power of the App Layer00:44:05 – World Labs, Spatial Intelligence & 3D Foundation Models00:47:20 – Thinking Machines, Founder Drama & Media Narratives00:52:30 – Where Long-Term Power Accrues in the AI StackTranscriptLatent.Space - Inside AI's $10B+ Capital Flywheel — Martin Casado & Sarah Wang of a16z[00:00:00] Welcome to Latent Space (Live from a16z) + Meet the Guests[00:00:00] Alessio: Hey everyone. Welcome to the Latent Space podcast, live from a 16 z. Uh, this is Alessio founder Kernel Lance, and I'm joined by Twix, editor of Latent Space.[00:00:08] swyx: Hey, hey, hey. Uh, and we're so glad to be on with you guys. Also a top AI podcast, uh, Martin Cado and Sarah Wang. Welcome, very[00:00:16] Martin Casado: happy to be here and welcome.[00:00:17] swyx: Yes, uh, we love this office. We love what you've done with the place. Uh, the new logo is everywhere now. It's, it's still getting, takes a while to get used to, but it reminds me of like sort of a callback to a more ambitious age, which I think is kind of[00:00:31] Martin Casado: definitely makes a statement.[00:00:33] swyx: Yeah.[00:00:34] Martin Casado: Not quite sure what that statement is, but it makes a statement.[00:00:37] swyx: Uh, Martin, I go back with you to Netlify.[00:00:40] Martin Casado: Yep.[00:00:40] swyx: Uh, and, uh, you know, you create a software defined networking and all, all that stuff people can read up on your background. Yep. Sarah, I'm newer to you. Uh, you, you sort of started working together on AI infrastructure stuff.[00:00:51] Sarah Wang: That's right. Yeah. Seven, seven years ago now.[00:00:53] Martin Casado: Best growth investor in the entire industry.[00:00:55] swyx: Oh, say[00:00:56] Martin Casado: more hands down there is, there is. [00:01:00] I mean, when it comes to AI companies, Sarah, I think has done the most kind of aggressive, um, investment thesis around AI models, right? So, worked for Nom Ja, Mira Ia, FEI Fey, and so just these frontier, kind of like large AI models.[00:01:15] I think, you know, Sarah's been the, the broadest investor. Is that fair?[00:01:20] Venture vs. Growth in the Frontier Model Era[00:01:20] Sarah Wang: No, I, well, I was gonna say, I think it's been a really interesting tag, tag team actually just ‘cause the, a lot of these big C deals, not only are they raising a lot of money, um, it's still a tech founder bet, which obviously is inherently early stage.[00:01:33] But the resources,[00:01:36] Martin Casado: so many, I[00:01:36] Sarah Wang: was gonna say the resources one, they just grow really quickly. But then two, the resources that they need day one are kind of growth scale. So I, the hybrid tag team that we have is. Quite effective, I think,[00:01:46] Martin Casado: what is growth these days? You know, you don't wake up if it's less than a billion or like, it's, it's actually, it's actually very like, like no, it's a very interesting time in investing because like, you know, take like the character around, right?[00:01:59] These tend to [00:02:00] be like pre monetization, but the dollars are large enough that you need to have a larger fund and the analysis. You know, because you've got lots of users. ‘cause this stuff has such high demand requires, you know, more of a number sophistication. And so most of these deals, whether it's US or other firms on these large model companies, are like this hybrid between venture growth.[00:02:18] Sarah Wang: Yeah. Total. And I think, you know, stuff like BD for example, you wouldn't usually need BD when you were seed stage trying to get market biz Devrel. Biz Devrel, exactly. Okay. But like now, sorry, I'm,[00:02:27] swyx: I'm not familiar. What, what, what does biz Devrel mean for a venture fund? Because I know what biz Devrel means for a company.[00:02:31] Sarah Wang: Yeah.[00:02:32] Compute Deals, Strategics, and the ‘Circular Funding' Question[00:02:32] Sarah Wang: You know, so a, a good example is, I mean, we talk about buying compute, but there's a huge negotiation involved there in terms of, okay, do you get equity for the compute? What, what sort of partner are you looking at? Is there a go-to market arm to that? Um, and these are just things on this scale, hundreds of millions, you know, maybe.[00:02:50] Six months into the inception of a company, you just wouldn't have to negotiate these deals before.[00:02:54] Martin Casado: Yeah. These large rounds are very complex now. Like in the past, if you did a series A [00:03:00] or a series B, like whatever, you're writing a 20 to a $60 million check and you call it a day. Now you normally have financial investors and strategic investors, and then the strategic portion always still goes with like these kind of large compute contracts, which can take months to do.[00:03:13] And so it's, it's very different ties. I've been doing this for 10 years. It's the, I've never seen anything like this.[00:03:19] swyx: Yeah. Do you have worries about the circular funding from so disease strategics?[00:03:24] Martin Casado: I mean, listen, as long as the demand is there, like the demand is there. Like the problem with the internet is the demand wasn't there.[00:03:29] swyx: Exactly. All right. This, this is like the, the whole pyramid scheme bubble thing, where like, as long as you mark to market on like the notional value of like, these deals, fine, but like once it starts to chip away, it really Well[00:03:41] Martin Casado: no, like as, as, as, as long as there's demand. I mean, you know, this, this is like a lot of these sound bites have already become kind of cliches, but they're worth saying it.[00:03:47] Right? Like during the internet days, like we were. Um, raising money to put fiber in the ground that wasn't used. And that's a problem, right? Because now you actually have a supply overhang.[00:03:58] swyx: Mm-hmm.[00:03:59] Martin Casado: And even in the, [00:04:00] the time of the, the internet, like the supply and, and bandwidth overhang, even as massive as it was in, as massive as the crash was only lasted about four years.[00:04:09] But we don't have a supply overhang. Like there's no dark GPUs, right? I mean, and so, you know, circular or not, I mean, you know, if, if someone invests in a company that, um. You know, they'll actually use the GPUs. And on the other side of it is the, is the ask for customer. So I I, I think it's a different time.[00:04:25] Sarah Wang: I think the other piece, maybe just to add onto this, and I'm gonna quote Martine in front of him, but this is probably also a unique time in that. For the first time, you can actually trace dollars to outcomes. Yeah, right. Provided that scaling laws are, are holding, um, and capabilities are actually moving forward.[00:04:40] Because if you can put translate dollars into capabilities, uh, a capability improvement, there's demand there to martine's point. But if that somehow breaks, you know, obviously that's an important assumption in this whole thing to make it work. But you know, instead of investing dollars into sales and marketing, you're, you're investing into r and d to get to the capability, um, you know, increase.[00:04:59] And [00:05:00] that's sort of been the demand driver because. Once there's an unlock there, people are willing to pay for it.[00:05:05] Alessio: Yeah.[00:05:06] Blurring Lines: Models as Infra + Apps, and the New Fundraising Flywheel[00:05:06] Alessio: Is there any difference in how you built the portfolio now that some of your growth companies are, like the infrastructure of the early stage companies, like, you know, OpenAI is now the same size as some of the cloud providers were early on.[00:05:16] Like what does that look like? Like how much information can you feed off each other between the, the two?[00:05:24] Martin Casado: There's so many lines that are being crossed right now, or blurred. Right. So we already talked about venture and growth. Another one that's being blurred is between infrastructure and apps, right? So like what is a model company?[00:05:35] Mm-hmm. Like, it's clearly infrastructure, right? Because it's like, you know, it's doing kind of core r and d. It's a horizontal platform, but it's also an app because it's um, uh, touches the users directly. And then of course. You know, the, the, the growth of these is just so high. And so I actually think you're just starting to see a, a, a new financing strategy emerge and, you know, we've had to adapt as a result of that.[00:05:59] And [00:06:00] so there's been a lot of changes. Um, you're right that these companies become platform companies very quickly. You've got ecosystem build out. So none of this is necessarily new, but the timescales of which it's happened is pretty phenomenal. And the way we'd normally cut lines before is blurred a little bit, but.[00:06:16] But that, that, that said, I mean, a lot of it also just does feel like things that we've seen in the past, like cloud build out the internet build out as well.[00:06:24] Sarah Wang: Yeah. Um, yeah, I think it's interesting, uh, I don't know if you guys would agree with this, but it feels like the emerging strategy is, and this builds off of your other question, um.[00:06:33] You raise money for compute, you pour that or you, you pour the money into compute, you get some sort of breakthrough. You funnel the breakthrough into your vertically integrated application. That could be chat GBT, that could be cloud code, you know, whatever it is. You massively gain share and get users.[00:06:49] Maybe you're even subsidizing at that point. Um, depending on your strategy. You raise money at the peak momentum and then you repeat, rinse and repeat. Um, and so. And that wasn't [00:07:00] true even two years ago, I think. Mm-hmm. And so it's sort of to your, just tying it to fundraising strategy, right? There's a, and hiring strategy.[00:07:07] All of these are tied, I think the lines are blurring even more today where everyone is, and they, but of course these companies all have API businesses and so they're these, these frenemy lines that are getting blurred in that a lot of, I mean, they have billions of dollars of API revenue, right? And so there are customers there.[00:07:23] But they're competing on the app layer.[00:07:24] Martin Casado: Yeah. So this is a really, really important point. So I, I would say for sure, venture and growth, that line is blurry app and infrastructure. That line is blurry. Um, but I don't think that that changes our practice so much. But like where the very open questions are like, does this layer in the same way.[00:07:43] Compute traditionally has like during the cloud is like, you know, like whatever, somebody wins one layer, but then another whole set of companies wins another layer. But that might not, might not be the case here. It may be the case that you actually can't verticalize on the token string. Like you can't build an app like it, it necessarily goes down just because there are no [00:08:00] abstractions.[00:08:00] So those are kinda the bigger existential questions we ask. Another thing that is very different this time than in the history of computer sciences is. In the past, if you raised money, then you basically had to wait for engineering to catch up. Which famously doesn't scale like the mythical mammoth. It take a very long time.[00:08:18] But like that's not the case here. Like a model company can raise money and drop a model in a, in a year, and it's better, right? And, and it does it with a team of 20 people or 10 people. So this type of like money entering a company and then producing something that has demand and growth right away and using that to raise more money is a very different capital flywheel than we've ever seen before.[00:08:39] And I think everybody's trying to understand what the consequences are. So I think it's less about like. Big companies and growth and this, and more about these more systemic questions that we actually don't have answers to.[00:08:49] Alessio: Yeah, like at Kernel Labs, one of our ideas is like if you had unlimited money to spend productively to turn tokens into products, like the whole early stage [00:09:00] market is very different because today you're investing X amount of capital to win a deal because of price structure and whatnot, and you're kind of pot committing.[00:09:07] Yeah. To a certain strategy for a certain amount of time. Yeah. But if you could like iteratively spin out companies and products and just throw, I, I wanna spend a million dollar of inference today and get a product out tomorrow.[00:09:18] swyx: Yeah.[00:09:19] Alessio: Like, we should get to the point where like the friction of like token to product is so low that you can do this and then you can change the Right, the early stage venture model to be much more iterative.[00:09:30] And then every round is like either 100 k of inference or like a hundred million from a 16 Z. There's no, there's no like $8 million C round anymore. Right.[00:09:38] When Frontier Labs Outspend the Entire App Ecosystem[00:09:38] Martin Casado: But, but, but, but there's a, there's a, the, an industry structural question that we don't know the answer to, which involves the frontier models, which is, let's take.[00:09:48] Anthropic it. Let's say Anthropic has a state-of-the-art model that has some large percentage of market share. And let's say that, uh, uh, uh, you know, uh, a company's building smaller models [00:10:00] that, you know, use the bigger model in the background, open 4.5, but they add value on top of that. Now, if Anthropic can raise three times more.[00:10:10] Every subsequent round, they probably can raise more money than the entire app ecosystem that's built on top of it. And if that's the case, they can expand beyond everything built on top of it. It's like imagine like a star that's just kind of expanding, so there could be a systemic. There could be a, a systemic situation where the soda models can raise so much money that they can out pay anybody that bills on top of ‘em, which would be something I don't think we've ever seen before just because we were so bottlenecked in engineering, and this is a very open question.[00:10:41] swyx: Yeah. It's, it is almost like bitter lesson applied to the startup industry.[00:10:45] Martin Casado: Yeah, a hundred percent. It literally becomes an issue of like raise capital, turn that directly into growth. Use that to raise three times more. Exactly. And if you can keep doing that, you literally can outspend any company that's built the, not any company.[00:10:57] You can outspend the aggregate of companies on top of [00:11:00] you and therefore you'll necessarily take their share, which is crazy.[00:11:02] swyx: Would you say that kind of happens in character? Is that the, the sort of postmortem on. What happened?[00:11:10] Sarah Wang: Um,[00:11:10] Martin Casado: no.[00:11:12] Sarah Wang: Yeah, because I think so,[00:11:13] swyx: I mean the actual postmortem is, he wanted to go back to Google.[00:11:15] Exactly. But like[00:11:18] Martin Casado: that's another difference that[00:11:19] Sarah Wang: you said[00:11:21] Martin Casado: it. We should talk, we should actually talk about that.[00:11:22] swyx: Yeah,[00:11:22] Sarah Wang: that's[00:11:23] swyx: Go for it. Take it. Take,[00:11:23] Sarah Wang: yeah.[00:11:24] Character.AI, Founder Goals (AGI vs Product), and GPU Allocation Tradeoffs[00:11:24] Sarah Wang: I was gonna say, I think, um. The, the, the character thing raises actually a different issue, which actually the Frontier Labs will face as well. So we'll see how they handle it.[00:11:34] But, um, so we invest in character in January, 2023, which feels like eons ago, I mean, three years ago. Feels like lifetimes ago. But, um, and then they, uh, did the IP licensing deal with Google in August, 2020. Uh, four. And so, um, you know, at the time, no, you know, he's talked publicly about this, right? He wanted to Google wouldn't let him put out products in the world.[00:11:56] That's obviously changed drastically. But, um, he went to go do [00:12:00] that. Um, but he had a product attached. The goal was, I mean, it's Nome Shair, he wanted to get to a GI. That was always his personal goal. But, you know, I think through collecting data, right, and this sort of very human use case, that the character product.[00:12:13] Originally was and still is, um, was one of the vehicles to do that. Um, I think the real reason that, you know. I if you think about the, the stress that any company feels before, um, you ultimately going one way or the other is sort of this a GI versus product. Um, and I think a lot of the big, I think, you know, opening eyes, feeling that, um, anthropic if they haven't started, you know, felt it, certainly given the success of their products, they may start to feel that soon.[00:12:39] And the real. I think there's real trade-offs, right? It's like how many, when you think about GPUs, that's a limited resource. Where do you allocate the GPUs? Is it toward the product? Is it toward new re research? Right? Is it, or long-term research, is it toward, um, n you know, near to midterm research? And so, um, in a case where you're resource constrained, um, [00:13:00] of course there's this fundraising game you can play, right?[00:13:01] But the fund, the market was very different back in 2023 too. Um. I think the best researchers in the world have this dilemma of, okay, I wanna go all in on a GI, but it's the product usage revenue flywheel that keeps the revenue in the house to power all the GPUs to get to a GI. And so it does make, um, you know, I think it sets up an interesting dilemma for any startup that has trouble raising up until that level, right?[00:13:27] And certainly if you don't have that progress, you can't continue this fly, you know, fundraising flywheel.[00:13:32] Martin Casado: I would say that because, ‘cause we're keeping track of all of the things that are different, right? Like, you know, venture growth and uh, app infra and one of the ones is definitely the personalities of the founders.[00:13:45] It's just very different this time I've been. Been doing this for a decade and I've been doing startups for 20 years. And so, um, I mean a lot of people start this to do a GI and we've never had like a unified North star that I recall in the same [00:14:00] way. Like people built companies to start companies in the past.[00:14:02] Like that was what it was. Like I would create an internet company, I would create infrastructure company, like it's kind of more engineering builders and this is kind of a different. You know, mentality. And some companies have harnessed that incredibly well because their direction is so obviously on the path to what somebody would consider a GI, but others have not.[00:14:20] And so like there is always this tension with personnel. And so I think we're seeing more kind of founder movement.[00:14:27] Sarah Wang: Yeah.[00:14:27] Martin Casado: You know, as a fraction of founders than we've ever seen. I mean, maybe since like, I don't know the time of like Shockly and the trade DUR aid or something like that. Way back in the beginning of the industry, I, it's a very, very.[00:14:38] Unusual time of personnel.[00:14:39] Sarah Wang: Totally.[00:14:40] Talent Wars, Mega-Comp, and the Rise of Acquihire M&A[00:14:40] Sarah Wang: And it, I think it's exacerbated by the fact that talent wars, I mean, every industry has talent wars, but not at this magnitude, right? No. Yeah. Very rarely can you see someone get poached for $5 billion. That's hard to compete with. And then secondly, if you're a founder in ai, you could fart and it would be on the front page of, you know, the information these days.[00:14:59] And so there's [00:15:00] sort of this fishbowl effect that I think adds to the deep anxiety that, that these AI founders are feeling.[00:15:06] Martin Casado: Hmm.[00:15:06] swyx: Uh, yes. I mean, just on, uh, briefly comment on the founder, uh, the sort of. Talent wars thing. I feel like 2025 was just like a blip. Like I, I don't know if we'll see that again.[00:15:17] ‘cause meta built the team. Like, I don't know if, I think, I think they're kind of done and like, who's gonna pay more than meta? I, I don't know.[00:15:23] Martin Casado: I, I agree. So it feels so, it feel, it feels this way to me too. It's like, it is like, basically Zuckerberg kind of came out swinging and then now he's kind of back to building.[00:15:30] Yeah,[00:15:31] swyx: yeah. You know, you gotta like pay up to like assemble team to rush the job, whatever. But then now, now you like you, you made your choices and now they got a ship.[00:15:38] Martin Casado: I mean, the, the o other side of that is like, you know, like we're, we're actually in the job hiring market. We've got 600 people here. I hire all the time.[00:15:44] I've got three open recs if anybody's interested, that's listening to this for investor. Yeah, on, on the team, like on the investing side of the team, like, and, um, a lot of the people we talk to have acting, you know, active, um, offers for 10 million a year or something like that. And like, you know, and we pay really, [00:16:00] really well.[00:16:00] And just to see what's out on the market is really, is really remarkable. And so I would just say it's actually, so you're right, like the really flashy one, like I will get someone for, you know, a billion dollars, but like the inflated, um, uh, trickles down. Yeah, it is still very active today. I mean,[00:16:18] Sarah Wang: yeah, you could be an L five and get an offer in the tens of millions.[00:16:22] Okay. Yeah. Easily. Yeah. It's so I think you're right that it felt like a blip. I hope you're right. Um, but I think it's been, the steady state is now, I think got pulled up. Yeah. Yeah. I'll pull up for[00:16:31] Martin Casado: sure. Yeah.[00:16:32] Alessio: Yeah. And I think that's breaking the early stage founder math too. I think before a lot of people would be like, well, maybe I should just go be a founder instead of like getting paid.[00:16:39] Yeah. 800 KA million at Google. But if I'm getting paid. Five, 6 million. That's different but[00:16:45] Martin Casado: on. But on the other hand, there's more strategic money than we've ever seen historically, right? Mm-hmm. And so, yep. The economics, the, the, the, the calculus on the economics is very different in a number of ways. And, uh, it's crazy.[00:16:58] It's cra it's causing like a, [00:17:00] a, a, a ton of change in confusion in the market. Some very positive, sub negative, like, so for example, the other side of the, um. The co-founder, like, um, acquisition, you know, mark Zuckerberg poaching someone for a lot of money is like, we were actually seeing historic amount of m and a for basically acquihires, right?[00:17:20] That you like, you know, really good outcomes from a venture perspective that are effective acquihires, right? So I would say it's probably net positive from the investment standpoint, even though it seems from the headlines to be very disruptive in a negative way.[00:17:33] Alessio: Yeah.[00:17:33] What's Underfunded: Boring Software, Robotics Skepticism, and Custom Silicon Economics[00:17:33] Alessio: Um, let's talk maybe about what's not being invested in, like maybe some interesting ideas that you would see more people build or it, it seems in a way, you know, as ycs getting more popular, it's like access getting more popular.[00:17:47] There's a startup school path that a lot of founders take and they know what's hot in the VC circles and they know what gets funded. Uh, and there's maybe not as much risk appetite for. Things outside of that. Um, I'm curious if you feel [00:18:00] like that's true and what are maybe, uh, some of the areas, uh, that you think are under discussed?[00:18:06] Martin Casado: I mean, I actually think that we've taken our eye off the ball in a lot of like, just traditional, you know, software companies. Um, so like, I mean. You know, I think right now there's almost a barbell, like you're like the hot thing on X, you're deep tech.[00:18:21] swyx: Mm-hmm.[00:18:22] Martin Casado: Right. But I, you know, I feel like there's just kind of a long, you know, list of like good.[00:18:28] Good companies that will be around for a long time in very large markets. Say you're building a database, you know, say you're building, um, you know, kind of monitoring or logging or tooling or whatever. There's some good companies out there right now, but like, they have a really hard time getting, um, the attention of investors.[00:18:43] And it's almost become a meme, right? Which is like, if you're not basically growing from zero to a hundred in a year, you're not interesting, which is just, is the silliest thing to say. I mean, think of yourself as like an introvert person, like, like your personal money, right? Mm-hmm. So. Your personal money, will you put it in the stock market at 7% or you put it in this company growing five x in a very large [00:19:00] market?[00:19:00] Of course you can put it in the company five x. So it's just like we say these stupid things, like if you're not going from zero to a hundred, but like those, like who knows what the margins of those are mean. Clearly these are good investments. True for anybody, right? True. Like our LPs want whatever.[00:19:12] Three x net over, you know, the life cycle of a fund, right? So a, a company in a big market growing five X is a great investment. We'd, everybody would be happy with these returns, but we've got this kind of mania on these, these strong growths. And so I would say that that's probably the most underinvested sector.[00:19:28] Right now.[00:19:29] swyx: Boring software, boring enterprise software.[00:19:31] Martin Casado: Traditional. Really good company.[00:19:33] swyx: No, no AI here.[00:19:34] Martin Casado: No. Like boring. Well, well, the AI of course is pulling them into use cases. Yeah, but that's not what they're, they're not on the token path, right? Yeah. Let's just say that like they're software, but they're not on the token path.[00:19:41] Like these are like they're great investments from any definition except for like random VC on Twitter saying VC on x, saying like, it's not growing fast enough. What do you[00:19:52] Sarah Wang: think? Yeah, maybe I'll answer a slightly different. Question, but adjacent to what you asked, um, which is maybe an area that we're not, uh, investing [00:20:00] right now that I think is a question and we're spending a lot of time in regardless of whether we pull the trigger or not.[00:20:05] Um, and it would probably be on the hardware side, actually. Robotics, right? And the robotics side. Robotics. Right. Which is, it's, I don't wanna say that it's not getting funding ‘cause it's clearly, uh, it's, it's sort of non-consensus to almost not invest in robotics at this point. But, um, we spent a lot of time in that space and I think for us, we just haven't seen the chat GPT moment.[00:20:22] Happen on the hardware side. Um, and the funding going into it feels like it's already. Taking that for granted.[00:20:30] Martin Casado: Yeah. Yeah. But we also went through the drone, you know, um, there's a zip line right, right out there. What's that? Oh yeah, there's a zip line. Yeah. What the drone, what the av And like one of the takeaways is when it comes to hardware, um, most companies will end up verticalizing.[00:20:46] Like if you're. If you're investing in a robot company for an A for agriculture, you're investing in an ag company. ‘cause that's the competition and that's surprising. And that's supply chain. And if you're doing it for mining, that's mining. And so the ad team does a lot of that type of stuff ‘cause they actually set up to [00:21:00] diligence that type of work.[00:21:01] But for like horizontal technology investing, there's very little when it comes to robots just because it's so fit for, for purpose. And so we kinda like to look at software. Solutions or horizontal solutions like applied intuition. Clearly from the AV wave deep map, clearly from the AV wave, I would say scale AI was actually a horizontal one for That's fair, you know, for robotics early on.[00:21:23] And so that sort of thing we're very, very interested. But the actual like robot interacting with the world is probably better for different team. Agree.[00:21:30] Alessio: Yeah, I'm curious who these teams are supposed to be that invest in them. I feel like everybody's like, yeah, robotics, it's important and like people should invest in it.[00:21:38] But then when you look at like the numbers, like the capital requirements early on versus like the moment of, okay, this is actually gonna work. Let's keep investing. That seems really hard to predict in a way that is not,[00:21:49] Martin Casado: I think co, CO two, kla, gc, I mean these are all invested in in Harvard companies. He just, you know, and [00:22:00] listen, I mean, it could work this time for sure.[00:22:01] Right? I mean if Elon's doing it, he's like, right. Just, just the fact that Elon's doing it means that there's gonna be a lot of capital and a lot of attempts for a long period of time. So that alone maybe suggests that we should just be investing in robotics just ‘cause you have this North star who's Elon with a humanoid and that's gonna like basically willing into being an industry.[00:22:17] Um, but we've just historically found like. We're a huge believer that this is gonna happen. We just don't feel like we're in a good position to diligence these things. ‘cause again, robotics companies tend to be vertical. You really have to understand the market they're being sold into. Like that's like that competitive equilibrium with a human being is what's important.[00:22:34] It's not like the core tech and like we're kind of more horizontal core tech type investors. And this is Sarah and I. Yeah, the ad team is different. They can actually do these types of things.[00:22:42] swyx: Uh, just to clarify, AD stands for[00:22:44] Martin Casado: American Dynamism.[00:22:45] swyx: Alright. Okay. Yeah, yeah, yeah. Uh, I actually, I do have a related question that, first of all, I wanna acknowledge also just on the, on the chip side.[00:22:51] Yeah. I, I recall a podcast that where you were on, i, I, I think it was the a CC podcast, uh, about two or three years ago where you, where you suddenly said [00:23:00] something, which really stuck in my head about how at some point, at some point kind of scale it makes sense to. Build a custom aic Yes. For per run.[00:23:07] Martin Casado: Yes.[00:23:07] It's crazy. Yeah.[00:23:09] swyx: We're here and I think you, you estimated 500 billion, uh, something.[00:23:12] Martin Casado: No, no, no. A billion, a billion dollar training run of $1 billion training run. It makes sense to actually do a custom meic if you can do it in time. The question now is timelines. Yeah, but not money because just, just, just rough math.[00:23:22] If it's a billion dollar training. Then the inference for that model has to be over a billion, otherwise it won't be solvent. So let's assume it's, if you could save 20%, which you could save much more than that with an ASIC 20%, that's $200 million. You can tape out a chip for $200 million. Right? So now you can literally like justify economically, not timeline wise.[00:23:41] That's a different issue. An ASIC per model, which[00:23:44] swyx: is because that, that's how much we leave on the table every single time. We, we, we do like generic Nvidia.[00:23:48] Martin Casado: Exactly. Exactly. No, it, it is actually much more than that. You could probably get, you know, a factor of two, which would be 500 million.[00:23:54] swyx: Typical MFU would be like 50.[00:23:55] Yeah, yeah. And that's good.[00:23:57] Martin Casado: Exactly. Yeah. Hundred[00:23:57] swyx: percent. Um, so, so, yeah, and I mean, and I [00:24:00] just wanna acknowledge like, here we are in, in, in 2025 and opening eyes confirming like Broadcom and all the other like custom silicon deals, which is incredible. I, I think that, uh, you know, speaking about ad there's, there's a really like interesting tie in that obviously you guys are hit on, which is like these sort, this sort of like America first movement or like sort of re industrialized here.[00:24:17] Yeah. Uh, move TSMC here, if that's possible. Um, how much overlap is there from ad[00:24:23] Martin Casado: Yeah.[00:24:23] swyx: To, I guess, growth and, uh, investing in particularly like, you know, US AI companies that are strongly bounded by their compute.[00:24:32] Martin Casado: Yeah. Yeah. So I mean, I, I would view, I would view AD as more as a market segmentation than like a mission, right?[00:24:37] So the market segmentation is, it has kind of regulatory compliance issues or government, you know, sale or it deals with like hardware. I mean, they're just set up to, to, to, to, to. To diligence those types of companies. So it's a more of a market segmentation thing. I would say the entire firm. You know, which has been since it is been intercepted, you know, has geographical biases, right?[00:24:58] I mean, for the longest time we're like, you [00:25:00] know, bay Area is gonna be like, great, where the majority of the dollars go. Yeah. And, and listen, there, there's actually a lot of compounding effects for having a geographic bias. Right. You know, everybody's in the same place. You've got an ecosystem, you're there, you've got presence, you've got a network.[00:25:12] Um, and, uh, I mean, I would say the Bay area's very much back. You know, like I, I remember during pre COVID, like it was like almost Crypto had kind of. Pulled startups away. Miami from the Bay Area. Miami, yeah. Yeah. New York was, you know, because it's so close to finance, came up like Los Angeles had a moment ‘cause it was so close to consumer, but now it's kind of come back here.[00:25:29] And so I would say, you know, we tend to be very Bay area focused historically, even though of course we've asked all over the world. And then I would say like, if you take the ring out, you know, one more, it's gonna be the US of course, because we know it very well. And then one more is gonna be getting us and its allies and Yeah.[00:25:44] And it goes from there.[00:25:45] Sarah Wang: Yeah,[00:25:45] Martin Casado: sorry.[00:25:46] Sarah Wang: No, no. I agree. I think from a, but I think from the intern that that's sort of like where the companies are headquartered. Maybe your questions on supply chain and customer base. Uh, I, I would say our customers are, are, our companies are fairly international from that perspective.[00:25:59] Like they're selling [00:26:00] globally, right? They have global supply chains in some cases.[00:26:03] Martin Casado: I would say also the stickiness is very different.[00:26:05] Sarah Wang: Yeah.[00:26:05] Martin Casado: Historically between venture and growth, like there's so much company building in venture, so much so like hiring the next PM. Introducing the customer, like all of that stuff.[00:26:15] Like of course we're just gonna be stronger where we have our network and we've been doing business for 20 years. I've been in the Bay Area for 25 years, so clearly I'm just more effective here than I would be somewhere else. Um, where I think, I think for some of the later stage rounds, the companies don't need that much help.[00:26:30] They're already kind of pretty mature historically, so like they can kind of be everywhere. So there's kind of less of that stickiness. This is different in the AI time. I mean, Sarah is now the, uh, chief of staff of like half the AI companies in, uh, in the Bay Area right now. She's like, ops Ninja Biz, Devrel, BizOps.[00:26:48] swyx: Are, are you, are you finding much AI automation in your work? Like what, what is your stack.[00:26:53] Sarah Wang: Oh my, in my personal stack.[00:26:54] swyx: I mean, because like, uh, by the way, it's the, the, the reason for this is it is triggering, uh, yeah. We, like, I'm hiring [00:27:00] ops, ops people. Um, a lot of ponders I know are also hiring ops people and I'm just, you know, it's opportunity Since you're, you're also like basically helping out with ops with a lot of companies.[00:27:09] What are people doing these days? Because it's still very manual as far as I can tell.[00:27:13] Sarah Wang: Hmm. Yeah. I think the things that we help with are pretty network based, um, in that. It's sort of like, Hey, how do do I shortcut this process? Well, let's connect you to the right person. So there's not quite an AI workflow for that.[00:27:26] I will say as a growth investor, Claude Cowork is pretty interesting. Yeah. Like for the first time, you can actually get one shot data analysis. Right. Which, you know, if you're gonna do a customer database, analyze a cohort retention, right? That's just stuff that you had to do by hand before. And our team, the other, it was like midnight and the three of us were playing with Claude Cowork.[00:27:47] We gave it a raw file. Boom. Perfectly accurate. We checked the numbers. It was amazing. That was my like, aha moment. That sounds so boring. But you know, that's, that's the kind of thing that a growth investor is like, [00:28:00] you know, slaving away on late at night. Um, done in a few seconds.[00:28:03] swyx: Yeah. You gotta wonder what the whole, like, philanthropic labs, which is like their new sort of products studio.[00:28:10] Yeah. What would that be worth as an independent, uh, startup? You know, like a[00:28:14] Martin Casado: lot.[00:28:14] Sarah Wang: Yeah, true.[00:28:16] swyx: Yeah. You[00:28:16] Martin Casado: gotta hand it to them. They've been executing incredibly well.[00:28:19] swyx: Yeah. I, I mean, to me, like, you know, philanthropic, like building on cloud code, I think, uh, it makes sense to me the, the real. Um, pedal to the metal, whatever the, the, the phrase is, is when they start coming after consumer with, uh, against OpenAI and like that is like red alert at Open ai.[00:28:35] Oh, I[00:28:35] Martin Casado: think they've been pretty clear. They're enterprise focused.[00:28:37] swyx: They have been, but like they've been free. Here's[00:28:40] Martin Casado: care publicly,[00:28:40] swyx: it's enterprise focused. It's coding. Right. Yeah.[00:28:43] AI Labs vs Startups: Disruption, Undercutting & the Innovator's Dilemma[00:28:43] swyx: And then, and, but here's cloud, cloud, cowork, and, and here's like, well, we, uh, they, apparently they're running Instagram ads for Claudia.[00:28:50] I, on, you know, for, for people on, I get them all the time. Right. And so, like,[00:28:54] Martin Casado: uh,[00:28:54] swyx: it, it's kind of like this, the disruption thing of, uh, you know. Mo Open has been doing, [00:29:00] consumer been doing the, just pursuing general intelligence in every mo modality, and here's a topic that only focus on this thing, but now they're sort of undercutting and doing the whole innovator's dilemma thing on like everything else.[00:29:11] Martin Casado: It's very[00:29:11] swyx: interesting.[00:29:12] Martin Casado: Yeah, I mean there's, there's a very open que so for me there's like, do you know that meme where there's like the guy in the path and there's like a path this way? There's a path this way. Like one which way Western man. Yeah. Yeah.[00:29:23] Two Futures for AI: Infinite Market vs AGI Oligopoly[00:29:23] Martin Casado: And for me, like, like all the entire industry kind of like hinges on like two potential futures.[00:29:29] So in, in one potential future, um, the market is infinitely large. There's perverse economies of scale. ‘cause as soon as you put a model out there, like it kind of sublimates and all the other models catch up and like, it's just like software's being rewritten and fractured all over the place and there's tons of upside and it just grows.[00:29:48] And then there's another path which is like, well. Maybe these models actually generalize really well, and all you have to do is train them with three times more money. That's all you have to [00:30:00] do, and it'll just consume everything beyond it. And if that's the case, like you end up with basically an oligopoly for everything, like, you know mm-hmm.[00:30:06] Because they're perfectly general and like, so this would be like the, the a GI path would be like, these are perfectly general. They can do everything. And this one is like, this is actually normal software. The universe is complicated. You've got, and nobody knows the answer.[00:30:18] The Economics Reality Check: Gross Margins, Training Costs & Borrowing Against the Future[00:30:18] Martin Casado: My belief is if you actually look at the numbers of these companies, so generally if you look at the numbers of these companies, if you look at like the amount they're making and how much they, they spent training the last model, they're gross margin positive.[00:30:30] You're like, oh, that's really working. But if you look at like. The current training that they're doing for the next model, their gross margin negative. So part of me thinks that a lot of ‘em are kind of borrowing against the future and that's gonna have to slow down. It's gonna catch up to them at some point in time, but we don't really know.[00:30:47] Sarah Wang: Yeah.[00:30:47] Martin Casado: Does that make sense? Like, I mean, it could be, it could be the case that the only reason this is working is ‘cause they can raise that next round and they can train that next model. ‘cause these models have such a short. Life. And so at some point in time, like, you know, they won't be able to [00:31:00] raise that next round for the next model and then things will kind of converge and fragment again.[00:31:03] But right now it's not.[00:31:04] Sarah Wang: Totally. I think the other, by the way, just, um, a meta point. I think the other lesson from the last three years is, and we talk about this all the time ‘cause we're on this. Twitter X bubble. Um, cool. But, you know, if you go back to, let's say March, 2024, that period, it felt like a, I think an open source model with an, like a, you know, benchmark leading capability was sort of launching on a daily basis at that point.[00:31:27] And, um, and so that, you know, that's one period. Suddenly it's sort of like open source takes over the world. There's gonna be a plethora. It's not an oligopoly, you know, if you fast, you know, if you, if you rewind time even before that GPT-4 was number one for. Nine months, 10 months. It's a long time. Right.[00:31:44] Um, and of course now we're in this era where it feels like an oligopoly, um, maybe some very steady state shifts and, and you know, it could look like this in the future too, but it just, it's so hard to call. And I think the thing that keeps, you know, us up at [00:32:00] night in, in a good way and bad way, is that the capability progress is actually not slowing down.[00:32:06] And so until that happens, right, like you don't know what's gonna look like.[00:32:09] Martin Casado: But I, I would, I would say for sure it's not converged, like for sure, like the systemic capital flows have not converged, meaning right now it's still borrowing against the future to subsidize growth currently, which you can do that for a period of time.[00:32:23] But, but you know, at the end, at some point the market will rationalize that and just nobody knows what that will look like.[00:32:29] Alessio: Yeah.[00:32:29] Martin Casado: Or, or like the drop in price of compute will, will, will save them. Who knows?[00:32:34] Alessio: Yeah. Yeah. I think the models need to ask them to, to specific tasks. You know? It's like, okay, now Opus 4.5 might be a GI at some specific task, and now you can like depreciate the model over a longer time.[00:32:45] I think now, now, right now there's like no old model.[00:32:47] Martin Casado: No, but let, but lemme just change that mental, that's, that used to be my mental model. Lemme just change it a little bit.[00:32:53] Capital as a Weapon vs Task Saturation: Where Real Enterprise Value Gets Built[00:32:53] Martin Casado: If you can raise three times, if you can raise more than the aggregate of anybody that uses your models, that doesn't even matter.[00:32:59] It doesn't [00:33:00] even matter. See what I'm saying? Like, yeah. Yeah. So, so I have an API Business. My API business is 60% margin, or 70% margin, or 80% margin is a high margin business. So I know what everybody is using. If I can raise more money than the aggregate of everybody that's using it, I will consume them whether I'm a GI or not.[00:33:14] And I will know if they're using it ‘cause they're using it. And like, unlike in the past where engineering stops me from doing that.[00:33:21] Alessio: Mm-hmm.[00:33:21] Martin Casado: It is very straightforward. You just train. So I also thought it was kind of like, you must ask the code a GI, general, general, general. But I think there's also just a possibility that the, that the capital markets will just give them the, the, the ammunition to just go after everybody on top of ‘em.[00:33:36] Sarah Wang: I, I do wonder though, to your point, um, if there's a certain task that. Getting marginally better isn't actually that much better. Like we've asked them to it, to, you know, we can call it a GI or whatever, you know, actually, Ali Goi talks about this, like we're already at a GI for a lot of functions in the enterprise.[00:33:50] Um. That's probably those for those tasks, you probably could build very specific companies that focus on just getting as much value out of that task that isn't [00:34:00] coming from the model itself. There's probably a rich enterprise business to be built there. I mean, could be wrong on that, but there's a lot of interesting examples.[00:34:08] So, right, if you're looking the legal profession or, or whatnot, and maybe that's not a great one ‘cause the models are getting better on that front too, but just something where it's a bit saturated, then the value comes from. Services. It comes from implementation, right? It comes from all these things that actually make it useful to the end customer.[00:34:24] Martin Casado: Sorry, what am I, one more thing I think is, is underused in all of this is like, to what extent every task is a GI complete.[00:34:31] Sarah Wang: Mm-hmm.[00:34:32] Martin Casado: Yeah. I code every day. It's so fun.[00:34:35] Sarah Wang: That's a core question. Yeah.[00:34:36] Martin Casado: And like. When I'm talking to these models, it's not just code. I mean, it's everything, right? Like I, you know, like it's,[00:34:43] swyx: it's healthcare.[00:34:44] It's,[00:34:44] Martin Casado: I mean, it's[00:34:44] swyx: Mele,[00:34:45] Martin Casado: but it's every, it is exactly that. Like, yeah, that's[00:34:47] Sarah Wang: great support. Yeah.[00:34:48] Martin Casado: It's everything. Like I'm asking these models to, yeah, to understand compliance. I'm asking these models to go search the web. I'm asking these models to talk about things I know in the history, like it's having a full conversation with me while I, I engineer, and so it could be [00:35:00] the case that like, mm-hmm.[00:35:01] The most a, you know, a GI complete, like I'm not an a GI guy. Like I think that's, you know, but like the most a GI complete model will is win independent of the task. And we don't know the answer to that one either.[00:35:11] swyx: Yeah.[00:35:12] Martin Casado: But it seems to me that like, listen, codex in my experience is for sure better than Opus 4.5 for coding.[00:35:18] Like it finds the hardest bugs that I work in with. Like, it is, you know. The smartest developers. I don't work on it. It's great. Um, but I think Opus 4.5 is actually very, it's got a great bedside manner and it really, and it, it really matters if you're building something very complex because like, it really, you know, like you're, you're, you're a partner and a brainstorming partner for somebody.[00:35:38] And I think we don't discuss enough how every task kind of has that quality.[00:35:42] swyx: Mm-hmm.[00:35:43] Martin Casado: And what does that mean to like capital investment and like frontier models and Submodels? Yeah.[00:35:47] Why “Coding Models” Keep Collapsing into Generalists (Reasoning vs Taste)[00:35:47] Martin Casado: Like what happened to all the special coding models? Like, none of ‘em worked right. So[00:35:51] Alessio: some of them, they didn't even get released.[00:35:53] Magical[00:35:54] Martin Casado: Devrel. There's a whole, there's a whole host. We saw a bunch of them and like there's this whole theory that like, there could be, and [00:36:00] I think one of the conclusions is, is like there's no such thing as a coding model,[00:36:04] Alessio: you know?[00:36:04] Martin Casado: Like, that's not a thing. Like you're talking to another human being and it's, it's good at coding, but like it's gotta be good at everything.[00:36:10] swyx: Uh, minor disagree only because I, I'm pretty like, have pretty high confidence that basically open eye will always release a GPT five and a GT five codex. Like that's the code's. Yeah. The way I call it is one for raisin, one for Tiz. Um, and, and then like someone internal open, it was like, yeah, that's a good way to frame it.[00:36:32] Martin Casado: That's so funny.[00:36:33] swyx: Uh, but maybe it, maybe it collapses down to reason and that's it. It's not like a hundred dimensions doesn't life. Yeah. It's two dimensions. Yeah, yeah, yeah, yeah. Like and exactly. Beside manner versus coding. Yeah.[00:36:43] Martin Casado: Yeah.[00:36:44] swyx: It's, yeah.[00:36:46] Martin Casado: I, I think for, for any, it's hilarious. For any, for anybody listening to this for, for, for, I mean, for you, like when, when you're like coding or using these models for something like that.[00:36:52] Like actually just like be aware of how much of the interaction has nothing to do with coding and it just turns out to be a large portion of it. And so like, you're, I [00:37:00] think like, like the best Soto ish model. You know, it is going to remain very important no matter what the task is.[00:37:06] swyx: Yeah.[00:37:07] What He's Actually Coding: Gaussian Splats, Spark.js & 3D Scene Rendering Demos[00:37:07] swyx: Uh, speaking of coding, uh, I, I'm gonna be cheeky and ask like, what actually are you coding?[00:37:11] Because obviously you, you could code anything and you are obviously a busy investor and a manager of the good. Giant team. Um, what are you calling?[00:37:18] Martin Casado: I help, um, uh, FEFA at World Labs. Uh, it's one of the investments and um, and they're building a foundation model that creates 3D scenes.[00:37:27] swyx: Yeah, we had it on the pod.[00:37:28] Yeah. Yeah,[00:37:28] Martin Casado: yeah. And so these 3D scenes are Gaussian splats, just by the way that kind of AI works. And so like, you can reconstruct a scene better with, with, with radiance feels than with meshes. ‘cause like they don't really have topology. So, so they, they, they produce each. Beautiful, you know, 3D rendered scenes that are Gaussian splats, but the actual industry support for Gaussian splats isn't great.[00:37:50] It's just never, you know, it's always been meshes and like, things like unreal use meshes. And so I work on a open source library called Spark js, which is a. Uh, [00:38:00] a JavaScript rendering layer ready for Gaussian splats. And it's just because, you know, um, you, you, you need that support and, and right now there's kind of a three js moment that's all meshes and so like, it's become kind of the default in three Js ecosystem.[00:38:13] As part of that to kind of exercise the library, I just build a whole bunch of cool demos. So if you see me on X, you see like all my demos and all the world building, but all of that is just to exercise this, this library that I work on. ‘cause it's actually a very tough algorithmics problem to actually scale a library that much.[00:38:29] And just so you know, this is ancient history now, but 30 years ago I paid for undergrad, you know, working on game engines in college in the late nineties. So I've got actually a back and it's very old background, but I actually have a background in this and so a lot of it's fun. You know, but, but the, the, the, the whole goal is just for this rendering library to, to,[00:38:47] Sarah Wang: are you one of the most active contributors?[00:38:49] The, their GitHub[00:38:50] Martin Casado: spark? Yes.[00:38:51] Sarah Wang: Yeah, yeah.[00:38:51] Martin Casado: There's only two of us there, so, yes. No, so by the way, so the, the pri The pri, yeah. Yeah. So the primary developer is a [00:39:00] guy named Andres Quist, who's an absolute genius. He and I did our, our PhDs together. And so like, um, we studied for constant Quas together. It was almost like hanging out with an old friend, you know?[00:39:09] And so like. So he, he's the core, core guy. I did mostly kind of, you know, the side I run venture fund.[00:39:14] swyx: It's amazing. Like five years ago you would not have done any of this. And it brought you back[00:39:19] Martin Casado: the act, the Activ energy, you're still back. Energy was so high because you had to learn all the framework b******t.[00:39:23] Man, I f*****g used to hate that. And so like, now I don't have to deal with that. I can like focus on the algorithmics so I can focus on the scaling and I,[00:39:29] swyx: yeah. Yeah.[00:39:29] LLMs vs Spatial Intelligence + How to Value World Labs' 3D Foundation Model[00:39:29] swyx: And then, uh, I'll observe one irony and then I'll ask a serious investor question, uh, which is like, the irony is FFE actually doesn't believe that LMS can lead us to spatial intelligence.[00:39:37] And here you are using LMS to like help like achieve spatial intelligence. I just see, I see some like disconnect in there.[00:39:45] Martin Casado: Yeah. Yeah. So I think, I think, you know, I think, I think what she would say is LLMs are great to help with coding.[00:39:51] swyx: Yes.[00:39:51] Martin Casado: But like, that's very different than a model that actually like provides, they, they'll never have the[00:39:56] swyx: spatial inte[00:39:56] Martin Casado: issues.[00:39:56] And listen, our brains clearly listen, our brains, brains clearly have [00:40:00] both our, our brains clearly have a language reasoning section and they clearly have a spatial reasoning section. I mean, it's just, you know, these are two pretty independent problems.[00:40:07] swyx: Okay. And you, you, like, I, I would say that the, the one data point I recently had, uh, against it is the DeepMind, uh, IMO Gold, where, so, uh, typically the, the typical answer is that this is where you start going down the neuros symbolic path, right?[00:40:21] Like one, uh, sort of very sort of abstract reasoning thing and one form, formal thing. Um, and that's what. DeepMind had in 2024 with alpha proof, alpha geometry, and now they just use deep think and just extended thinking tokens. And it's one model and it's, and it's in LM.[00:40:36] Martin Casado: Yeah, yeah, yeah, yeah, yeah.[00:40:37] swyx: And so that, that was my indication of like, maybe you don't need a separate system.[00:40:42] Martin Casado: Yeah. So, so let me step back. I mean, at the end of the day, at the end of the day, these things are like nodes in a graph with weights on them. Right. You know, like it can be modeled like if you, if you distill it down. But let me just talk about the two different substrates. Let's, let me put you in a dark room.[00:40:56] Like totally black room. And then let me just [00:41:00] describe how you exit it. Like to your left, there's a table like duck below this thing, right? I mean like the chances that you're gonna like not run into something are very low. Now let me like turn on the light and you actually see, and you can do distance and you know how far something away is and like where it is or whatever.[00:41:17] Then you can do it, right? Like language is not the right primitives to describe. The universe because it's not exact enough. So that's all Faye, Faye is talking about. When it comes to like spatial reasoning, it's like you actually have to know that this is three feet far, like that far away. It is curved.[00:41:37] You have to understand, you know, the, like the actual movement through space.[00:41:40] swyx: Yeah.[00:41:40] Martin Casado: So I do, I listen, I do think at the end of these models are definitely converging as far as models, but there's, there's, there's different representations of problems you're solving. One is language. Which, you know, that would be like describing to somebody like what to do.[00:41:51] And the other one is actually just showing them and the space reasoning is just showing them.[00:41:55] swyx: Yeah, yeah, yeah. Right. Got it, got it. Uh, the, in the investor question was on, on, well labs [00:42:00] is, well, like, how do I value something like this? What, what, what work does the, do you do? I'm just like, Fefe is awesome.[00:42:07] Justin's awesome. And you know, the other two co-founder, co-founders, but like the, the, the tech, everyone's building cool tech. But like, what's the value of the tech? And this is the fundamental question[00:42:16] Martin Casado: of, well, let, let, just like these, let me just maybe give you a rough sketch on the diffusion models. I actually love to hear Sarah because I'm a venture for, you know, so like, ventures always, always like kind of wild west type[00:42:24] swyx: stuff.[00:42:24] You, you, you, you paid a dream and she has to like, actually[00:42:28] Martin Casado: I'm gonna say I'm gonna mar to reality, so I'm gonna say the venture for you. And she can be like, okay, you a little kid. Yeah. So like, so, so these diffusion models literally. Create something for, for almost nothing. And something that the, the world has found to be very valuable in the past, in our real markets, right?[00:42:45] Like, like a 2D image. I mean, that's been an entire market. People value them. It takes a human being a long time to create it, right? I mean, to create a, you know, a, to turn me into a whatever, like an image would cost a hundred bucks in an hour. The inference cost [00:43:00] us a hundredth of a penny, right? So we've seen this with speech in very successful companies.[00:43:03] We've seen this with 2D image. We've seen this with movies. Right? Now, think about 3D scene. I mean, I mean, when's Grand Theft Auto coming out? It's been six, what? It's been 10 years. I mean, how, how like, but hasn't been 10 years.[00:43:14] Alessio: Yeah.[00:43:15] Martin Casado: How much would it cost to like, to reproduce this room in 3D? Right. If you, if you, if you hired somebody on fiber, like in, in any sort of quality, probably 4,000 to $10,000.[00:43:24] And then if you had a professional, probably $30,000. So if you could generate the exact same thing from a 2D image, and we know that these are used and they're using Unreal and they're using Blend, or they're using movies and they're using video games and they're using all. So if you could do that for.[00:43:36] You know, less than a dollar, that's four or five orders of magnitude cheaper. So you're bringing the marginal cost of something that's useful down by three orders of magnitude, which historically have created very large companies. So that would be like the venture kind of strategic dreaming map.[00:43:49] swyx: Yeah.[00:43:50] And, and for listeners, uh, you can do this yourself on your, on your own phone with like. Uh, the marble.[00:43:55] Martin Casado: Yeah. Marble.[00:43:55] swyx: Uh, or but also there's many Nerf apps where you just go on your iPhone and, and do this.[00:43:59] Martin Casado: Yeah. Yeah. [00:44:00] Yeah. And, and in the case of marble though, it would, what you do is you literally give it in.[00:44:03] So most Nerf apps you like kind of run around and take a whole bunch of pictures and then you kind of reconstruct it.[00:44:08] swyx: Yeah.[00:44:08] Martin Casado: Um, things like marble, just that the whole generative 3D space will just take a 2D image and it'll reconstruct all the like, like[00:44:16] swyx: meaning it has to fill in. Uh,[00:44:18] Martin Casado: stuff at the back of the table, under the table, the back, like, like the images, it doesn't see.[00:44:22] So the generator stuff is very different than reconstruction that it fills in the things that you can't see.[00:44:26] swyx: Yeah. Okay.[00:44:26] Sarah Wang: So,[00:44:27] Martin Casado: all right. So now the,[00:44:28] Sarah Wang: no, no. I mean I love that[00:44:29] Martin Casado: the adult[00:44:29] Sarah Wang: perspective. Um, well, no, I was gonna say these are very much a tag team. So we, we started this pod with that, um, premise. And I think this is a perfect question to even build on that further.[00:44:36] ‘cause it truly is, I mean, we're tag teaming all of these together.[00:44:39] Investing in Model Labs, Media Rumors, and the Cursor Playbook (Margins & Going Down-Stack)[00:44:39] Sarah Wang: Um, but I think every investment fundamentally starts with the same. Maybe the same two premises. One is, at this point in time, we actually believe that there are. And of one founders for their particular craft, and they have to be demonstrated in their prior careers, right?[00:44:56] So, uh, we're not investing in every, you know, now the term is NEO [00:45:00] lab, but every foundation model, uh, any, any company, any founder trying to build a foundation model, we're not, um, contrary to popular opinion, we're

OpenClaw's creator makes headlines by joining OpenAI after GitHub fame and a whirlwind of VC and big tech offers, redefining what's possible for independent developers in the AI arms race. Is this the year agentic AI goes mainstream, and are the big players ready for that disruption? OpenClaw, OpenAI and the future | Peter Steinberger OpenAI disbands mission alignment team Opinion | I Left My Job at OpenAI. Putting Ads on ChatGPT Was the Last Straw. - The New York Times Introducing GPT‑5.3‑Codex‑Spark Anthropic releases Sonnet 4.6 Exclusive: Pentagon threatens to cut off Anthropic in AI safeguards dispute Google's Pixel 10a Launches on March 5 for $499 Google's AI drug discovery spinoff Isomorphic Labs claims major leap beyond AlphaFold 3 Gemini 3 Deep Think: AI model update designed for science Radio host David Greene says Google's NotebookLM tool stole his voice A new way to express yourself: Gemini can now create music Why an A.I. Video of Tom Cruise Battling Brad Pitt Spooked Hollywood GPT-5 outperforms federal judges 100% to 52% in legal reasoning experiment An AI project is creating videos to go with Supreme Court justices' real words I used Claude to negotiate $163,000 off a hospital bill. In a complex healthcare system, AI is giving patients power. Sony Tech Can Identify Original Music in AI-Generated Songs AI Pioneer Fei-Fei Li's Startup World Labs Raises $1 Billion Yann v. Yoshua on directed systems Dr. Oz pushes AI avatars as a fix for rural health care. Not so fast, critics say An AI Agent Published a Hit Piece on Me An Ars Technica Reporter Blamed A.I. Tools for Fabricating Quotes in a Bizarre A.I. Story Plain Dealer using AI to write reporters' stories Mediahuis trials use of AI agents to carry out 'first-line' news reporting DJI's first robovac is an autonomous cleaning drone you can't trust Leaked Email Suggests Ring Plans to Expand 'Search Party' Surveillance Beyond Dogs ai;dr I hate my AI pet with every fiber of my being Thanks a lot, AI: Hard drives are sold out for the year, says WD Students Are Being Treated Like Guinea Pigs:' Inside an AI-Powered Private School peon-ping — Stop babysitting your terminal Hugo Barra makes a to-do agent Raspberry Pi soars 40% as CEO buys stock, AI chatter builds Hosts: Leo Laporte, Jeff Jarvis, and Emily Forlini Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: monarch.com with code IM bitwarden.com/twit preview.modulate.ai spaceship.com/twit

The daughter of a hospital administrator, Amy Gleason never considered a career in the public sector – she went straight into healthcare. As an emergency room nurse, she started to see the dangers that unfold when healthcare providers don't have access to the information they need to treat patients. Those experiences drove her towards a tech career in the emerging electronic health records space before a very personal experience altered her professional path yet again.Amy's active and healthy 10-year old daughter began suffering unusual healthcare events, from rashes and headaches to broken bones. Eventually, she couldn't walk. It took more than a year from the start of these symptoms for doctors to diagnose her with a rare autoimmune disease. Even then, it was an accidental diagnosis from a dermatologist conducting a skin biopsy.Amy attributes the delayed diagnosis to siloed data, not unsimilar to the challenges she experienced as a nurse and was working to solve in the EHR space. It motivated her to co-found a company focused on helping patients with chronic diseases access their data to share it with the providers and family members helping to navigate complex care journeys.In 2015, Amy's work earned her an award from the White House for Champions of Change in Precision Medicine – her first foray into the public sector. By 2018, she entered civic service full time with a role at the United States Digital Service, which she describes as “DOGE 1.0.”In this episode of Healthcare is Hard, Amy talked to Keith Figlioli about the work she's doing now as Strategic Advisor to CMS and Administrator of the U.S. DOGE Service, where her main mission is modernizing technology across government agencies for the millions of people who rely on federal services every day. This ranges from modernizing FAFSA and the student loan process, to improving the Visa system ahead of the World Cup, and work on various critical healthcare systems. Some of the topics Amy and Keith discussed in this episode, include:Bold plans for a Digital Health Ecosystem. Launched in July 2025, CMS' Health Tech Ecosystem is a public-private partnership designed as a voluntary, fast-moving alternative to slow rulemaking. Rather than years of regulation, the program uses pledges, working groups, and short development cycles to put interoperability building blocks and real patient-facing use cases in place. The goal is to get usable capabilities into the market in months – not years – let the community iterate, and have baseline use cases live by March 31, 2026 with more advanced capabilities rolling out by July.Carrots and sticks before regulation. Recognizing the limitations of regulation, Amy talked about a new philosophy for incentivizing the market to change behaviors on its own first. “Carrots” include the rural health transformation fund and the recently introduced ACCESS model, a 10-year pilot that, for the first time, lets tech-enabled services bill Medicare directly. “Sticks” include stricter enforcement of information-blocking rules.Replacing the 1970s-era Medicare claims system. Amy discussed plans to replace Medicare's decades-old COBOL-based adjudication platform. While it's a stable platform, it can't support real-time processing, AI, or rapid change. To replace it, CMS is looking to commercial, off-the-shelf solutions that operate at scale so claims processing can be modernized, made real-time, and integrated with new interoperability rails. It's a concrete example of bringing modern engineering and product thinking to government technology.To hear Amy and Keith discuss these topics and more, listen to this episode of Healthcare is Hard: A Podcast for Insiders.

On this episode of The SaaS CFO Podcast, host Ben Murray welcomes Luca Cartechini, co-founder and CEO of Shop Circle. With deep roots in equity research and venture capital across the European tech landscape, Luca Cartechini shares how his experiences led to the creation of Shop Circle—an innovative, long-term holding company that acquires and grows mission-critical, profitable SaaS businesses outside the traditional VC and PE model. Listeners will get insider perspectives on the realities of scaling software companies in fragmented European markets, the metrics that matter most when evaluating SaaS acquisitions, and the evolving role of AI in operational excellence. Whether you're a founder considering your next move or simply passionate about SaaS, this episode is packed with actionable wisdom on building, buying, and holding vertical software companies for the long haul. Show Notes: 00:00 "Challenges Scaling European Companies" 03:34 "ShopCircle: AI-Powered Software Platform" 08:51 "AI in Software Acquisitions" 12:06 AI's Role in Business Strategy 14:09 "Pricing, AI, and Value Strategy" 16:58 "Key Metrics for Business Acquisition" 22:28 "Operator-Focused, Long-Term Investment Approach" 25:13 Founder Missteps in Acquisition Process 29:28 Recurring vs. Usage-Based Revenue Analysis 31:51 "SaaS Revenue Analysis for ROI" 36:39 AI-Driven Efficiency and Expansion Links: SaaS Fundraising Stories: https://www.thesaasnews.com/news/shop-circle-raises-60-million-in-series-b https://www.thesaasnews.com/news/shop-circle-extends-series-b-to-100-million Luca Cartechini's LinkedIn: https://www.linkedin.com/in/luca-cartechini/ Shop Circle's LinkedIn: https://www.linkedin.com/company/shop-circle/ Shop Circle's Website: https://shopcircle.co/ To learn more about Ben check out the links below: Subscribe to Ben's daily metrics newsletter: https://saasmetricsschool.beehiiv.com/subscribe Subscribe to Ben's SaaS newsletter: https://mailchi.mp/df1db6bf8bca/the-saas-cfo-sign-up-landing-page SaaS Metrics courses here: https://www.thesaasacademy.com/ Join Ben's SaaS community here: https://www.thesaasacademy.com/offers/ivNjwYDx/checkout Follow Ben on LinkedIn: https://www.linkedin.com/in/benrmurray

In this powerful episode, we dive deep into the realities of entrepreneurship — the stress, the identity crisis, venture capital pressure, and what no one tells you about scaling a company.Our guest shares:• Why she walked away from her startup• The heartbreak of watching it shut down• The hidden stress of venture-backed businesses• Why she'll never raise VC again• How delegation saved her sanity• Designing life instead of being consumed by work• Spiritual habits that ground her daily (gratitude journaling, tarot, reflection)We also discuss founder identity, investor pressure, scaling retail, AI in business, legacy vs exits, and what success really means.If you're a founder, entrepreneur, executive, or someone navigating burnout this conversation will hit home.

Sean Frank, CEO of Ridge, bootstrapped the brand past $100M. Moreover, Ridge has redefined the everyday-carry category. The company has scaled globally without VC dollars, built LTV around products that last a lifetime, and made content the backbone of its growth engine. In this conversation, Sean breaks down the real playbook behind Ridge's rise — from international expansion and localized fulfillment to creator-led marketing, AI adoption, podcasting, and what he sees coming next for modern day eCommerce. Learn more about your ad choices. Visit megaphone.fm/adchoices

From time to time, we'll re-air a previous episode of the show that our newer audience may have missed. During this episode, Santosh is joined by Gary Ong, Founder & CEO at Celadyne Technologies Inc., a company specializing in developing advanced materials and technologies that enhance the durability and efficiency of hydrogen fuel cells and electrolyzers, aiming to decarbonize heavy-duty industries like transportation and manufacturing. Santosh and Gary explore hydrogen's transformative potential in supply chains and energy sectors as Gary shares his journey from battery technology to hydrogen, highlighting its advantages in industrial applications, transportation, and energy storage. The pair addresses public misconceptions about hydrogen, its historical context, and its role in re-industrialization and energy independence in the U.S. The episode underscores hydrogen's critical importance in achieving decarbonization and a sustainable energy future. Don't miss this episode.Highlights from their conversation include:Gary's Background in Hydrogen (0:41)Hydrogen's Potential (2:13)Why Hydrogen Over Batteries? (5:37)Challenges of Energy Storage (8:25)Public Perception of Hydrogen (10:01)Hydrogen's Industrial Applications (12:35)Energy Independence and Global Leverage (16:09)Hydrogen in Transportation and Logistics (19:23)Understanding Fuel Cells (22:02)Collaborations with Major Companies (28:46)Hydrogen Distribution Challenges (31:08)The Importance of a Hydrogen Thesis (36:59)Hydrogen's Multibillion Dollar Potential (39:05)The Future of Fuel (40:43)This or That to Wrap (41:09)Final Thoughts and Takeaways (42:45)Dynamo is a VC firm led by supply chain and mobility specialists that focus on seed-stage, enterprise startups.Find out more at: https://www.dynamo.vc/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ashok Krishnamurthi, Managing Partner at Great Point Ventures, says the biggest mistake in venture capital is confusing prediction with judgment.Early stage investing is not about perfect stories, it is about first principles and picking the founder who can execute when the story breaks.This episode is for startup founders and investors who want a cleaner filter for what matters.“You have to learn to check your ego at the door because it's a partnership.”Ashok shares his path from engineering into building companies, then into venture capital, and explains how he forms an investment thesis when markets are noisy. We talk about founder evaluation, why picking the jockey matters more than the idea, and how first principles thinking shows up in real domains like healthcare data and cancer. We also get practical about artificial intelligence, why AI is not only a compute race, and how AI inference, energy efficiency, and cost shape what wins.00:00 Why legacy matters more than VC metrics02:28 Engineer to founder to venture capital11:16 How to pick the jockey14:21 First principles, cancer data, and AI constraints23:24 AI is here to stay, keep your mind open30:15 How to reach AshokIf this episode helped, subscribe and share it with a builder or investor who will use it.

There's a commonly held belief in manufacturing: big ideas need big money, fast growth, and outside control to survive. But that playbook doesn't work for every business or every industry.Andrew Johnson, co-founder of HeavyTech and CEO of ShelfAware, joins the show from Everywhere Beer Co. in Anaheim, California, to talk through how he and his partners built HeavyTech, a hybrid and electric big machinery manufacturer, on their own terms. He shares the long road behind developing technology for hybrid and electric heavy machinery, and why, when it came time to scale, they made a deliberate decision to crowdfund and not follow the traditional VC path.Along the way, we also get into why diversification within a single industry creates leverage most business owners miss, what it means to be fearless in business, and the struggles of connecting with other entrepreneurs at the same stage of growth.If you've ever questioned whether the “standard” approach to funding actually fits your business, this conversation will make you rethink the rules.In this episode, find out:Why timing is the most important factor in business successHow crowdfunding gives you more control over your business and direct access to future customersWhy diversifying within an industry is one of the smartest entrepreneurial moves you can makeThe importance of connecting with other entrepreneurs in the same position as youHow HeavyTech invented its hybrid and electric machines for construction, farm and ranchWhat it means to be fearless in businessWhere Andrew sees the future of U.S. manufacturing goingEnjoying the show? Please leave us a review here. Even one sentence helps. It's feedback from Manufacturing All-Stars like you that keeps us going!Tweetable Quotes:“I think the inclination today is that you need to go raise a bunch of money with private equity venture capital. I believe that's wrong. Crowdfunding allowed us to raise a bunch of money from individuals. Normal people who believed in the future vision of our company and would eventually become our customers.”“I think that's the beauty of diversification. Each business is in the same industrial space. The products are different, but they complement each other. Sometimes I go into a meeting trying to sell ShelfAware, and I end up selling O-rings or end up talking about HeavyTech and leave with a new investor.”“Timing is everything in business. You have to be at the right place at the right time. You can have a great idea, but if the market is not ready, it won't work.”Links & mentions:HeavyTech, a manufacturing company designing and building hybrid and electric machinery for the construction and agriculture industries. ShelfAware, a manufacturing intelligence company providing real-time production visibility and workflow insights to improve efficiency on the factory floor. Everywhere Beer Co, an independent craft brewery based in Cleaveland, producing small-batch beers.Make sure to visit http://manufacturinghappyhour.com for detailed show notes and a full list of resources mentioned in this episode. Stay Innovative, Stay Thirsty.Mentioned in this episode:Industrial Marketing Summit 2026The Industrial Marketing Summit is the go-to gathering for marketers working in the manufacturing,...

Episode 415 of The VentureFizz #podcast features Parker McKee, Partner at Pillar. “When you work really hard… good things come out on the other side.” - Parker McKee. Parker is a perfect example of this mindset - a mantra that I firmly believe in. When Parker has a goal in his sights, he's going to put in the time to get there. He's proven this time and time again, and the results speak for themselves. In athletics, he spent countless hours in his parents' backyard honing his lacrosse skills, which ultimately led him to the D1 level at the University of Michigan, where he served as a co-captain. Professionally, once he discovered a passion for investing and startups, he set his sights on venture capital. Through relentless networking, he landed an internship at .406 Ventures. Later, after pitching his own startup idea to Jamie Goldstein, he stayed on the radar and eventually joined the team in the early days of Pillar, where he has risen to the role as a Partner in the firm. Pillar is a pre-seed and seed-stage VC firm that invests in technical breakthroughs to overcome the world's greatest challenges. Last year, the firm announced their latest fund that being a $175M Fund IV. In this episode of our podcast, we cover: * The current state of venture investing in the AI era. * Parker's background and what playing D1 lacrosse at Michigan taught him about the rewards of hard work. * How he broke into the industry with an internship at .406 Ventures. * The story of how he pitched an app idea to Jamie Goldstein while still in college, and how that relationship eventually led to his role at Pillar. * An inside look at a "junior-level" role in venture capital and how he learned the ropes by simply "being in the market." * His current investment focus and the details behind his investment in OpenHands, alongside Menlo Ventures. * What he expects out of a first meeting and his best advice for a successful pitch. * The biggest lesson he's learned so far in the world of venture capital. * And so much more! Podcast Sponsor: This podcast is brought to you by one of the strongest longtime supporters of the local startup ecosystem, Silicon Valley Bank, a division of First Citizens Bank. With more than 1,500 bankers and relationship advisors and $44B in loans as of Q4 2025 – SVB delivers expert guidance, specialized products and a team that knows the innovation economy inside and out. Learn more at SVB.com.

What does it take to build a thriving quantum ecosystem from the ground up? Martin Laforest, physicist-turned-venture-capitalist at Quantacet, reveals how Quebec transformed a 1970s academic bet into a $400M quantum powerhouse—and why the industry's biggest misconception is thinking quantum computing is either a science problem or an engineering problem when it's clearly both.SummaryIn this conversation, Sebastian sits down with Martin Laforest, partner at Quantacet, Canada's quantum-only VC fund, to explore the messy realities of building quantum companies and ecosystems. Martin brings a rare perspective: PhD from Waterloo's Institute for Quantum Computing, eight years leading scientific outreach, a stint building a post-quantum cryptography startup with ex-BlackBerry executives, and now investing in the quantum future.This episode is for anyone trying to understand how quantum technology actually gets built—not the hype, but the infrastructure, the collaboration models, the government investment strategies, and the patience required. Whether you're technical or just curious about how transformative technologies emerge, Martin offers a grounded view of what's working, what's not, and why the quantum revolution looks more like slow, deliberate ecosystem building than overnight breakthroughs.What You'll LearnWhy quantum is both a science and engineering challenge and how the vacuum tube-to-transistor transition illuminates today's quantum journeyHow Quebec built a world-class quantum ecosystem starting from a 1970s university bet on condensed matter physics through to today's $400M provincial investmentThe infrastructure that matters: why Sherbrooke's six shared dilution fridges and quantum communication testbed represent a different collaboration modelWhat VCs actually look for in quantum startups beyond the technology—and why Martin believes early-stage investing is about building great companies, not just returnsThe three most dangerous misconceptions plaguing quantum technology (spoiler: it's not just about quantum computers)How regional quantum ecosystems should compete and collaborate with lessons from Netherlands, Chicago, and UK programsWhy fundamental research funding can't stop even as commercialization accelerates—and what happens when governments don't understand this balanceWhat "mutualized infrastructure" means in practice and why no single entity owning critical testbeds might be the secret sauceHow federal and provincial politics shape quantum strategy in Canada and what other countries can learn from itResources & LinksQuantacetInstitute for Quantum Computing (IQC)University of Sherbrooke Institute QuantiqueC2MI semiconductor fabrication facilityQuantumDELTAKey InsightsOn the science vs. engineering debate:"People ask if quantum computing is still a science problem or just engineering. It's both. Look at the vacuum tube to transistor transition—we needed new physics and new engineering. That's exactly where we are now."On ecosystem building:"Sherbrooke made a bet on condensed matter physics in the 1970s. Fifty years later, they have six dilution fridges available for rent and a quantum communication testbed owned by no one. That infrastructure patience is what builds real ecosystems."On VC philosophy:"Early-stage venture capital is about building great companies. The money is a byproduct. If you focus on the returns first, you'll make the wrong decisions every time."On common misconceptions:"The biggest myth is that quantum technology equals quantum computing. We have quantum sensors, quantum communications, post-quantum crypto—this is a multi-faceted industry, not a single magic box."On balancing research and commercialization:"You can't stop funding fundamental research just because commercialization is happening. The vacuum tube didn't kill physics research. We need both engines running or the whole thing stalls."Join the ConversationSubscribe to The New Quantum Era wherever you get your podcasts to hear more conversations with the people building quantum technology's future.

Episode Info Wayne Slavin is the CEO and Co-Founder of Sure, a VC backed insurtech startup. Prior to Sure he was the VP of Product Management at Tapingo, TechCrunch's Most Innovative Company of 2013. His other past projects and companies include NetStumbler, a consumer app with more than 1.5 billion downloads, the Barnes & Noble Nook eBook reader, Buddy Media (now part of salesforce), and BackupRight the enterprise SaaS company he sold in 2012. He has a Masters Degree from Columbia University. You can see Wayne from his appearance on the show in April of 2024 in the final episode of Season 5. Episode Overview: SURE's Role: SURE provides the technology infrastructure and services that enable large brands, including Fortune 500 companies and major auto manufacturers, to launch and manage their own digital insurance businesses. This allows these brands to control the customer experience and build long-term, durable insurance operations. Embedded Insurance: The trend of "embedded insurance" is driven by the fact that insurance is often a necessary component of a core product (like cars or homes) or can be a friction point in a sale. Companies are recognizing the value of offering insurance directly to their customers to enhance the overall experience and capture economic benefits. The "One-Stop-Shop" Vision: Many large consumer brands aim to be a comprehensive provider for their customers, whether it's for car ownership, homeownership, or financial well-being. Insurance is a natural extension of this strategy, allowing them to create a complete ecosystem around their core offerings. Structural Advantage: Brands that already have a customer base have a significant advantage. Acquiring these customers for insurance purposes costs them next to nothing, giving them better economics than external insurance providers. Evolution of SURE: Over the past year, SURE has focused on helping its partners achieve "permanence" in their insurance offerings. This means enabling them to build stable, long-term insurance programs that are not subject to the fluctuating appetites or market conditions of traditional insurers. Challenges for Traditional Insurers: The existing insurance industry has had ample opportunity to improve its technology and customer experience but has largely failed to do so. This has created an opening for new models. The "Build vs. Buy" Dilemma: While some companies attempt to build their own insurance carriers, this is capital-intensive and distracts from their core business. Partnering with a third-party carrier often results in a loss of control over customer experience and technology, leading to suboptimal outcomes. SURE's Sweet Spot: SURE offers a middle ground, enabling brands to have their own differentiated insurance programs with control and economic upside without the need to become full-fledged insurers or rely on inadequate partnerships with traditional carriers. Speed to Market: SURE can bring partners to market with approved insurance products in as little as 90 days, or even faster for simpler offerings, demonstrating a significant advantage over the lengthy internal development times typical for such initiatives. Industry Inertia: The insurance industry often suffers from a lack of incentive for long-term growth and innovation. Decisions are often based on avoiding blame (omission vs. commission) rather than proactively pursuing new opportunities. This makes it difficult for established players to adapt to new models. The Future of Insurance Distribution: The future will likely involve insurance being more deeply integrated into the customer journey, moving away from discrete purchases and towards seamless, embedded solutions. The current models of comparison engines and traditional carrier partnerships are becoming less relevant. Investor Appetite: There is a significant appetite from investors like private equity and sovereign wealth funds for insurance-like returns, especially for well-defined, scalable programs that leverage existing customer bases. This episode is brought to you by The Future of Insurance book series (future-of-insurance.com) from Bryan Falchuk. Follow the podcast at future-of-insurance.com/podcast for more details and other episodes. Music courtesy of Hyperbeat Music, available to stream or download on Spotify, Apple Music, and Amazon Music and more.

In Episode 50 of Chain Reactions, Blake sits down with Nadia Sergujuk, Co-Founder of Lagoon, the permissionless vault management infrastructure that wants to become the State Street of digital assets. With a background spanning Danish law schools, PWC Legal in London, hedge funds managing $10B+ in AUM, and VC investing in deep tech, Nadia brings a rare cross-disciplinary lens to one of the fastest-growing categories in DeFi.We cover:– How Nadia went from law school in Copenhagen to hedge funds in London to co-founding an on-chain vault protocol– What vault management infrastructure actually is and why every stablecoin dollar eventually needs one– Why Lagoon's team put their own capital in first and how word of mouth drove early traction– The stablecoin explosion, neo banks in emerging markets, and why the digital dollar is eating the world– Privacy on-chain, the rise of institutional chains, and what keeps Nadia up at night (hint: quantum computing and the triple bubble)We also get into regulation as a tailwind, why Japan is the most slept-on institutional market in crypto, the innovator's dilemma facing Western Union and Visa, and why founder-led marketing beats KOLs every time.Timestamps00:00 – Going live and Nadia joins from the Swiss Alps04:00 – From law school in Denmark to hedge funds in London06:30 – First exposure to Bitcoin in 2016 (and not buying it)08:20 – COVID, DeFi summer, and going all in on crypto09:30 – Meeting co-founder Remy at a conference in Bogota11:27 – What is Lagoon? Vault management infrastructure explained13:30 – Why permissionless and open source matters for trust16:26 – Business model: 10% of vault fees plus SaaS services18:00 – Go-to-market: putting your own money in the vaults first20:45 – BlackRock, Fidelity, and the TradFi wave coming on-chain faster than expected22:23 – Why regulation is actually a tailwind for Lagoon25:36 – Japan as the most slept-on institutional crypto market28:00 – Neo banks, stablecoin yield, and serving emerging markets30:30 – Why the digital dollar is irresistible in LatAm, Africa, and Southeast Asia37:00 – Conference circuit: DAF London, DAS New York, and founder-led presence40:06 – What keeps Nadia up at night: quantum compute and the triple bubble45:23 – Chain landscape: Solana's DeFi renaissance and BTCFi's comeback48:04 – Privacy on-chain: why institutions need it and how Lagoon will enable it51:35 – Rapid fire: founder-led marketing, KOLs, Merkl, and the power of peopleShow Notes & Mentions

Send a textJesus lived under constant threat of death, but he wasn't shy about speaking the truth anyway.  In this episode the VC points to Jesus' teaching on who the real owner and faithful servants are of his kingdom.

 "BDC is powerful in the sense that it can make or break a fund… And a lot of people are trying to close funds right now." In 2022, the federal government commissioned a report asking Canada's VCs what they thought about Crown corporation BDC. The report was effectively forgotten, and the feedback was never actioned. Why? What did the report have to say about Canada's largest venture investor? And with Canadian VC in a multi-year lull, is BDC's "steady hand" approach preferred or simply necessary? BetaKit reporter Madison McLauchlan joins to discuss. Related Links: The feds asked investors for candid feedback on BDC. It was never actioned BDC head says bank pulled back from life sciences "too early" as it preps new VC fund BDC unveils $4-billion defence technology platform Another fund partner leaves BDC "A perfect storm": 2025 was the worst year for Canadian VC fundraising since 2016  

In dieser Deep-Dive-Folge spricht Markus mit Simona Hübl, Co-Founder & CEO von Nejo, über ihren Weg vom VC-Umfeld in die eigene Gründung und warum der Jobmarkt dringend neu gedacht werden muss. Nach mehreren Jahren im Investing stieg sie bewusst aus operativen VC-Rollen aus, um selbst zu gründen. Nach einem Pivot entstand Nejo, eine KI-gestützte Karriereplattform für den DACH-Raum. Simona erklärt, warum klassische Jobplattformen nur einen Bruchteil der verfügbaren Stellen sichtbar machen, weshalb Keyword-Matching oft ins Leere läuft und wie Nejo mit skills-basiertem, transparentem KI-Matching relevantere Ergebnisse ermöglichen will.Production: Hanna Moser Musik (Intro/Outro): www.sebastianegger.com

New technology is coming soon and here is how to invest in the future! Inventor and investor Pablos Holman shares his journey from early computer hacking to co-founding Blue Origin, leading a prolific deep-tech lab, and now backing "mad scientists" building hard technologies beyond software. He believes Silicon Valley has over-indexed on easy software gains while neglecting transformative advances in hardware, energy, and real-world systems. He explains how breakthroughs in computation now let us model and simulate the physical world, from disease eradication to supply chains, marking a toolkit upgrade on par with the steam engine, while also wrestling with the social, regulatory, and human challenges that slow progress. We talk AI's real potential beyond chatbots, the urgent need to 10x global energy, decentralization vs. centralization in tech, the societal costs of social media, and even more! We discuss... Pablos Holman described his path from early computer hacking to founding deep-tech ventures like Blue Origin and running a VC fund focused on inventors building real-world, non-software technologies. Pablos framed technological progress as periodic "toolkit upgrades," comparing today's advances in computation and simulation to the impact of the steam engine. Modern computational models enable simulations of complex systems like disease spread, cities, and supply chains, dramatically improving decision-making. The conversation highlighted AI's true value as modeling the world while warning of over-centralization and privacy tradeoffs in the near term. Global energy scarcity is the real bottleneck to progress and peace, requiring a massive scale-up in clean, cheap energy. Nuclear power is the only viable path to global energy production and described new reactor designs nearing deployment. The discussion explored how regulatory and political systems, rather than technology itself, are often the biggest obstacles to innovation, especially in healthcare and energy. Pablos criticized social media for societal damage but argued the core issue is human responsibility and misuse rather than the technology itself. AI and crypto represent an open experimental phase where individuals can still influence outcomes before power consolidates. Pablos encouraged people to actively engage with and help build meaningful technologies instead of passively reacting to technological change. Today's Panelists: Kirk Chisholm | Innovative Wealth Barbara Friedberg | Barbara Friedberg Personal Finance Diana Perkins | Trading With Diana Follow on Facebook: https://www.facebook.com/moneytreepodcast Follow LinkedIn: https://www.linkedin.com/showcase/money-tree-investing-podcast Follow on Twitter/X: https://x.com/MTIPodcast For more information, visit the show notes at https://moneytreepodcast.com/how-to-invest-in-the-future-790 

This week, Rebecca Rettig joins the show to discuss the latest happening in Washington and what it means for crypto. We deep dive into the Clarity act, how to regulate prediction markets, who's crypto's enemy now, the state of crypto VC, LayerZero's Zero announcement and more. Enjoy! -- Follow Rebecca: https://x.com/RebeccaRettig1 Follow Rob: https://x.com/HadickM Follow Santi: https://x.com/santiagoroel Follow Empire: https://x.com/theempirepod -- Referenced In The Show: https://open.spotify.com/episode/67w8irQ06j6ZH38FsXSShf?si=5633bb7bb6a248b9&nd=1&dlsi=d7d519562e884e70 -- Coinbase crypto-backed loans, powered by Morpho, enable you to take out loans at competitive rates using crypto as collateral. Rates are typically 4% to 8%. Borrow up to $5M using BTC as collateral and up to $1M using ETH as collateral. Manage crypto-backed loans directly in the Coinbase app with ease. Learn more here: https://www.coinbase.com/onchain/borrow/get-started?utm_campaign=0126_defi-borrow_blockworks_empire&marketId=0x9103c3b4e834476c9a62ea009ba2c884ee42e94e6e314a26f04d312434191836&utm_source=empire -- Timestsamps: (00:00) Introduction (01:57) The State of Crypto Policy In DC (27:24) Coinbase Ad (28:08) Das Plug (28:34) Prediction Markets (36:50) Who's Crypto's Enemy Now? (52:35) The State of Crypto VC (01:01:15) LayerZero's Zero Announcement (01:13:01) Content of The Week -- Disclaimer: Nothing said on Empire is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Santiago, Jason, Rob and our guests may hold positions in the companies, funds, or projects discussed.

Healey Cypher, CEO of BoomPop and COO at Atomic, breaks down what separates founders who win from founders who stall. You will hear a clear way to judge whether an idea is truly worth building, plus the trust mechanics that get investors, customers, and teammates to actually follow you.This conversation is a practical map for tech builders who want to pick smarter problems, execute faster, and earn credibility without the founder theater.Key TakeawaysFounders matter most, but the idea is still a gate, the same great team can get wildly different outcomes depending on the market and timingVC backed is a specific game, it requires not just big potential, but fast scale, and the incentives are not the same as building a profitable lifestyle businessA quick reality check for market size, if you need more than about five to seven percent penetration to hit meaningful revenue, it is usually a brutal pathPainkillers beat vitamins, solve an urgent problem people feel right now, or you risk getting cut the moment budgets tightenTrust is built through authenticity, logic, and empathy, if one wobbles, people feel it fast, and progress slows everywhereTimestamped Highlights00:00:00 Healey's background, why BoomPop, and what the episode is really about00:02:00 The post pandemic spend shift and the why now behind modern events and group travel00:04:30 Founder versus idea, why execution dominates, but the opportunity still decides the ceiling00:06:40 The VC reality, power law returns, speed, and why some good businesses are still a no for venture00:09:15 A simple market math test, penetration levels that become a growth wall00:19:00 Trust as a founder skill, the three ingredients and how to spot when one is missing00:21:30 Vulnerability as a shortcut to real connection, plus the giver mindset that makes people want you to winA line worth stealingIf everyone wants you to win, it is a lot easier to win.Pro Tips for Tech FoundersAsk yourself what you naturally look forward to doing, that is often your zone of strength, hire around the tasks you dreadLearn the financial basics early, especially cash flow, it is the scoreboard that keeps you alive long enough to winWhen trust is lagging, check the three levers, are you showing the real you, can people follow your reasoning, do they feel you care about their outcomesWhat's next:If you build products, lead teams, or are thinking about starting something, follow the show so you do not miss episodes like this. Also connect with me on LinkedIn for short takeaways and clips from each conversation.

Will Caldwell started Snap after his first real estate software startup fizzled, pivoting from agent tools to regulated compliance data. He discovered lenders were required to buy hazard and flood certifications, and realized this was a "painkiller" product. He built Snap as a data and analytics platform for real estate and mortgage underwriting. Snap grew from a single California compliance product into a national flood data business, reaching $5M in revenue and 30 employees. The company charged per-loan transaction fees and embedded via API into mortgage software systems. With double-digit market share, Snap focused on customer experience, automation, and expanding wallet share inside lenders' workflows. In October 2024, Snap sold 51% of the company to Intercontinental Exchange, parent of ICE Mortgage Technology, at a double-digit revenue multiple. Will stayed on to scale the platform inside a much larger ecosystem. His key lesson: dominate a narrow niche, build a required product, and let strategic buyers find you. Key Takeaways Required Beats Optional – Legal compliance products create urgency and retention because customers must buy to complete revenue-generating transactions. Micro-Niche Entry – Starting in a narrow regulated segment let Snap win trust, then expand into much larger adjacent markets. API = Distribution – Embedding inside legacy systems turned Snap into a one-click button that scaled through partners' existing sales teams. Customer Experience Wins – In commodity data markets, faster, cheaper, simpler delivery became Snap's main competitive weapon. Quote from Will Caldwell, CEO and Co-Founder of Snap "You don't need to build a huge business to get a huge, life-changing exit. Just stay laser-focused. Don't chase shiny objects. I see many founders trying to boil the ocean. It is about staying focused on a single niche. "I think vertical SaaS has many great niches, and horizontal software is challenging. You need a lot of money to go after horizontal solutions across industries. However, with vertical SaaS products and niches, there is a lot of overlooked opportunity; the real estate vertical is one prime example." Links Will Caldwell on LinkedIn Snap on LinkedIn Snap website Podcast Sponsor – LaunchBay LaunchBay helps B2B software companies automate client onboarding and implementation so customers activate faster and everyone stays aligned. If your onboarding includes data collection, setup steps, approvals, training, or any level of customization, LaunchBay replaces the messy mix of emails, spreadsheets, and meetings with a clear, all-in-one onboarding system. Teams use LaunchBay to onboard clients faster, stay on top of follow-ups automatically, and deliver a smoother experience, without hiring more people or adding more tools. Visit launchbay.com/practical and get 25% off your first 3 months on any LaunchBay plan. The Practical Founders Podcast Tune into the Practical Founders Podcast for weekly in-depth interviews with founders who have built valuable software companies without big funding. Subscribe to the Practical Founders Podcast using your favorite podcast app or view on our YouTube channel. Get the weekly Practical Founders newsletter and podcast updates at practicalfounders.com. Practical Founders CEO Peer Groups Be part of a committed and confidential group of practical founders creating valuable software companies without big VC funding.  A Practical Founders Peer Group is a committed and confidential group of founders/CEOs who want to help you succeed on your terms. Each Practical Founders Peer Group is personally curated and moderated by Greg Head.

Do startup valuations today make sense?Umesh Padval, an early investor in Cohere, now valued at about $7 billion shares why Cohere stood out at the time of his investment. He shares what he saw early that made him believe this was not just another AI model company.Umesh is the Founding Managing Partner, Seligman Ventures and previously at Thomvest and Bessemer Venture Partners. He brings experience from investing across multiple tech cycles, from chips to cloud to AI. Umesh talks about how deals are really done in venture capital and what he looks for when everything feels noisy and crowded in AI.He also shares why many strong companies are choosing to stay private and what has changed in the IPO market. Public markets now demand cash flow and durability, not just fast growth.Umesh talks about why open source has become a powerful sales funnel for modern AI companies. Developers become the first users, and community adoption turns into long-term enterprise revenue.After four decades in Silicon Valley and 20 years as a VC, Umesh shares what keeps him in building and investing.0:00 – How big is the scope for investing in AI startups?04:04 – Do unit economics justify large AI valuations?06:00 – Thomvest's LLM investment thesis (Cohere case study)09:18 – Are CTO roles changing in AI11:21 – Traits of the best AI founding teams13:40 – Timeline to find the best founders16:52 – Partnership with Jyoti Bansal19:07 – Where is the IPO market headed?23:40 – Salesforce–Clari acquisition25:18 – Is profitability a prerequisite to go public?26:00 – Can the India–US corridor beat US–Israel?28:53 – Umesh's investment philosophy31:08 – Open source as a sales funnel33:38 – IIT → Stanford → Startups41:45 – The only CEO with 60 direct reports43:43 – Why Jensen never does 1-on-1s?48:23 – What ultimately drives Umesh Padval?-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send a text

Miranda Nover is the Co-founder and CEO of Fort Health. Fort builds wearables that automatically track strength training for people who care about longevity.This is a new format I'm experimenting with. It's the first time I've had a Banana portfolio company founder on the show while they're still at the pre-seed stage. When I surveyed my subscribers a few weeks ago, you were most interested in more early stage VC-backed founders, and I'd love your feedback on what you think of this.Miranda is still very much working through the idea maze and iterating on the Fort product. We talk about the megatrends driving consumer health, why she's building a company that helps people get stronger, and everything she's learned getting a hardware company off the ground.She's also in the middle of the current YC batch, and gives an inside look at what it's been like and if she'd recommend it to other founders.Thank you to Numeral and Flex for supporting this episode.Try Numeral, the end-to-end platform for sales tax and compliance: https://www.numeral.comSign-up for Flex Elite with code TURNER, get $1,000: https://form.typeform.com/to/Rx9rTjFzTimestamps:(3:37) Importance of strength training(6:34) Benefits of being strong(10:37) Evolution of Fort's hardware(15:58) Automating workout tracking(19:29) Two types of strength trainers(25:30) Building the strength company(27:26) How healthcare is consumerizing(40:43) Lessons building batteries at Tesla(44:56) Hardest parts about building a hardware startup(51:01) Adventures in vibe coding(57:54) How to use Twitter as a founder(1:02:09) The launch video industrial complex(1:08:03) What it's like doing YC(1:10:19) Selling crayons in 3rd grade, Lemonade stands(1:14:41) Miranda's best vintage finds(1:16:44) How Turner evolved as a VC(1:22:22) Turner's early social media PMF(1:28:53) Inventing shitpostingReferencedTry Fort: https://www.fort.cx/Follow MirandaTwitter: https://x.com/mirandanoverLinkedIn: https://www.linkedin.com/in/mirandanoverFollow TurnerTwitter: https://twitter.com/TurnerNovakLinkedIn: https://www.linkedin.com/in/turnernovakSubscribe to my newsletter to get every episode + the transcript in your inbox every week: https://www.thespl.it/

Will Nitze went from selling Linsanity T-shirts in his college dorm to building IQ Bar into a $125 million brain food empire—with just a team of ten people. No bloated headcount. No burning through VC cash. Just ruthless focus on unit economics and a contrarian approach to funding that let him scale aggressively while maintaining control. In this interview, the founder and CEO of IQ Bar breaks down how he turned a $73,000 Kickstarter into one of the fastest-growing CPG brands in America, why he believes bootstrapping is the worst thing you can do in food and beverage, and the exact moment—five years in—when he knew this could be a massive company. From cracking Costco and Whole Foods to reinventing the business over ten times, this episode is a masterclass in hyper-lean growth, retail strategy, and building a company like a knife fight. What you'll learn in this interview: • Why bootstrapping is the worst thing you can do in CPG • Will's contrarian fundraising strategy: raising less money, more often to maintain control • How he raised just under $10 million while still controlling the company • The exact moment, five years in, when he knew IQ Bar could be a big company • Why IQ Bar has reinvented its fundamental identity over ten times • How to navigate the cash conversion cycle while scaling physical products • Why retail is the "final boss" for CPG brands, even in the e-commerce era • The strategic shift from DTC to cracking Costco, Whole Foods, Walmart, and Target • Why consumers are less loyal every year and how more touchpoints solve that • How building a personal brand creates a network of category experts By the end of this episode, you'll understand how to scale a physical product business without burning cash, maintain control while raising capital strategically, and build the operational discipline required to survive in one of the toughest industries in the world. If you're building a CPG brand, navigating fundraising decisions, or trying to crack retail while staying lean, this conversation will fundamentally change how you think about growth, control, and category-defining execution. SAVE 50% ON OMNISEND FOR 3 MONTHS Get 50% off your first 3 months of email and SMS marketing with Omnisend with the code FOUNDR50. Just head to ⁠⁠⁠⁠⁠⁠⁠https://your.omnisend.com/foundr⁠⁠⁠⁠⁠⁠⁠ to get started. HOW WE CAN HELP YOU SCALE YOUR BUSINESS FASTER Learn directly from 7, 8 & 9-figure founders inside Foundr+ Start your $1 trial → ⁠⁠⁠⁠⁠⁠⁠https://www.foundr.com/startdollartrial⁠⁠⁠⁠⁠⁠⁠ PREFER A CUSTOM ROADMAP AND 1-ON-1 COACHING? → Starting from scratch? Apply here → ⁠⁠⁠⁠⁠⁠⁠https://foundr.com/pages/coaching-start-application⁠⁠⁠⁠⁠⁠⁠ → Already have a store? Apply here → ⁠⁠⁠⁠⁠⁠⁠https://foundr.com/pages/coaching-growth-application⁠⁠⁠⁠⁠⁠⁠ CONNECT WITH NATHAN CHAN Instagram → ⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/nathanchan⁠⁠⁠⁠⁠⁠⁠ LinkedIn → ⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/nathanhchan/⁠⁠⁠⁠⁠⁠⁠ CONNECT WITH WILL NITZE Instagram → https://www.instagram.com//willnitze/ LinkedIn → https://www.linkedin.com/in/will-nitze Website → https://iqbar.com/ FOLLOW FOUNDR FOR MORE BUSINESS GROWTH STRATEGIES YouTube → ⁠⁠⁠⁠⁠⁠⁠https://bit.ly/2uyvzdt⁠⁠⁠⁠⁠⁠⁠ Website → ⁠⁠⁠⁠⁠⁠⁠https://www.foundr.com⁠⁠⁠⁠⁠⁠⁠ Instagram → ⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/foundr/⁠⁠⁠⁠⁠⁠⁠ Facebook → ⁠⁠⁠⁠⁠⁠⁠https://www.facebook.com/foundr⁠⁠⁠⁠⁠⁠⁠ Twitter → ⁠⁠⁠⁠⁠⁠⁠https://www.twitter.com/foundr⁠⁠⁠⁠⁠⁠⁠ LinkedIn → ⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/foundr/⁠⁠⁠⁠⁠⁠⁠ Podcast → ⁠⁠⁠⁠⁠⁠⁠https://www.foundr.com/podcast⁠

Eric Anderson, partner at VC firm Scale, talks about why coding agents changed software forever and why the AI bubble can't be avoided. Eric worked on Spot Instances at AWS and data products at Google before becoming a VC. He explains how companies can still compete against Anthropic and OpenAI by staying laser-focused instead of fighting on every front.Corey and Eric discuss why AWS didn't kill all startups even when they launched competing products, why the AI bubble can't be avoided when companies go from $1 billion to $7 billion in revenue in one year, and why the best AI products don't scream “AI” everywhere in their marketing.Show Highlights:(02:30) Building Spot Instances at AWS(07:41) Why Coding Agents Changed Everything(10:35) Agents Doing Code Review Now(13:53) Competing with Frontier Labs(17:05) Why AWS Didn't Kill All Startups(19:01) Finding the Right Front to Fight On(22:20) Why the Bubble Is Inevitable(23:36) AI Pricing Will Eventually Crash(26:33) Honeycomb's AI Done Right(28:04) Where to Find EricLinks: Scale: https://www.scalevp.com/Eric on LinkedIn: https://www.linkedin.com/in/ericmand/Sponsored by: duckbillhq.com

In this special deep dive episode, Peter is joined by his Carta Insights colleague Hamza Shad to unpack the operational reality of running a venture fund. They leave behind portfolio performance metrics to focus entirely on the business of the fund itself.Peter and Hamza break down the data from Carta's inaugural Fund Economics report. They analyze how much capital GPs are actually committing to their own funds, why anchor LPs are taking larger stakes, and whether the industry standard "2 and 20" fee structure is actually holding up.They also discuss the hidden costs of fund operations, from legal fees to audits, and why the 2022 vintage is deploying capital slower than its predecessors. Plus, they answer audience questions on recycling capital, managing lines of credit, and why marking up SAFEs on SAFEs is a red flag for LPs.Subscribe to Carta's weekly Data Minute newsletter: https://carta.com/subscribe/data-newsletter-sign-up/Explore interactive startup and VC data, with Carta's Data Desk: https://carta.com/data-desk/Chapters:00:00 – Intro: The business of the fund02:30 – GP Commit: How much skin in the game?04:40 – Why PE managers commit more than VCs05:58 – The rise of the Anchor LP10:38 – Capital Calls: Timelines and delays15:30 – Why the 2022 vintage is deploying slowly19:53 – Is "2 and 20" still the standard for fees?23:00 – Carry benchmarks across fund sizes25:40 – The rarity of preferred returns in VC27:00 – Operating Expenses: Legal vs. Tax costs28:58 – Why audits are becoming mandatory31:33 – The danger of marking up SAFEs33:22 – Managing Manco expenses35:24 – Q&A: When to call capital41:35 – Q&A: Valuation methodology and stale marks44:18 – Q&A: Secondaries and recycling capital47:58 – Q&A: Thesis drift49:28 – OutroThis presentation contains general information only and eShares, Inc. dba Carta, Inc. (“Carta”) is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services, and is for informational purposes only.  This presentation is not a substitute for such professional advice or services nor should it be used as a basis for any decision or action that may affect your business or interests. © 2026 eShares, Inc., dba Carta, Inc. All rights reserved.

Tiffany Yeh, MD is the CEO and Co-Founder of Eztia Materials, a climate-tech venture developing energy-efficient cooling materials to protect people from extreme heat. With a mission to advance hard tech solutions at the climate-health nexus, Tiffany draws on her unique background as a physician, engineer, and public health advocate to build technologies that improve global health in a warming world.(01:13) - Dr. Ye's Background & Inspiration (01:52) - The Heat Challenge(05:20) - Singapore and the Power of Cooling(06:32) - Why Construction Has Been Slow to Adapt (07:22) - The Human Factor(08:14) - HydroVolt Technology(09:29) - Business Model, Distribution & Competition(11:19) - Worker Comfort (15:32) - Hidden Productivity Crisis Brewing(18:18) - Feature: Blueprint: The Future of Real Estate 2026 in Vegas on Sep. 22-24 (19:21) - The Secret Sauce Behind HydroVolt (20:31) - Prototyping & Real-World Applications (21:32) - Measuring Impact & ROI (23:34) - Pitching to VCs & Investors(25:31) - Product Roadmap(29:08) - Collaboration Superpower: Lionel Messi

Listen to the episode on Apple Podcasts, Spotify, Fountain, Podcast Addict, Pocket Casts, Amazon Music, or on your favorite podcast platform. Figure is giving away $25,000 in USDC. Deposit into Democratized Prime, earn ~9% APY hourly—and every $1 you keep in for 25 days is 1 entry. Enter here --- Bitcoin slid toward $60,000 on Feb. 5 in a brutal, cross-asset selloff that hit gold, equities, and crypto alike. With leverage unwinding and basis trades breaking, long-time bitcoin holders are distributing to institutional buyers who, by 13F data, are mostly underwater. The mood across digital assets is bleak. Against that backdrop, Nic Carter of Castle Island Ventures argues that key Bitcoin narratives have quietly failed—and warns that developers' inaction on quantum risk could open the door to institutional control. If devs don't act, Carter says ETF giants like BlackRock will. The panel then widens the lens: declaring the token-centric VC model dead, debating whether AI now rivals the industrial revolution, and stress-testing it all across topics ranging from Solana vs. Hyperliquid to Japan's political shift and MrBeast's fintech play. --- If you want your crypto taxes done carefully — not guessed — Crypto Tax Girl is offering $100 off one-on-one crypto tax services. Their team focuses solely on crypto and has been helping investors navigate tax season since 2017. Save $100 here Hosts: Ram Ahluwalia, CFA, CEO and Founder of Lumida Austin Campbell, NYU Stern professor and founder and managing partner of Zero Knowledge Consulting Christopher Perkins, Managing Partner and President of CoinFund Guest: Nic Carter, Founding Partner at Castle Island Ventures Learn more about your ad choices. Visit megaphone.fm/adchoices

Get your tickets here: https://luma.com/83fj2zkcTechish is coming off the timeline and onto the stage.​Join us for a live recording of Techish, the podcast where tech meets culture, money meets meaning, and nothing is off-limits. Hosted by founders and investors Michael Berhane and Abadesi Osunsade, Techish breaks down the biggest stories in tech, business, and culture with insight, humour, and zero corporate fluff.​This isn't a panel.This isn't a keynote.This is a conversation. Live, honest, and interactive.​Expect sharp takes on what's really happening in tech right now, cultural commentary you won't hear on Bloomberg, and the kind of audience energy that turns a podcast into a moment.​What to Expect​A live, unfiltered Techish recordingSmart breakdowns of the biggest tech and culture stories right nowLaughs, hot takes, and side-eyesAudience Q&A and participationAn intimate crowd of people building, investing, and working in tech​Whether you are a founder, operator, investor, creative, or a tech professional or employee looking to better understand the industry you work in, this is your room.The hosts: ​Abadesi Osunsade​CEO of Hustle Crew and an award-winning social entrepreneur and VC scout. A seasoned tech leader, Abadesi previously served as a Global VP and held pivotal roles at Amazon, Product Hunt, and Brandwatch. An author and speaker, she is a leading voice in building inclusive tech ecosystems and mentoring the next generation of founders.​Michael Berhane​Award-winning CEO of POCIT. An MSc Computer Science graduate and founding engineer at Urban Massage, Michael is a former software engineer turned entrepreneur. He is a Venture Scout for Zeal Capital and a Bloomsbury-shortlisted writer currently working on his debut novel.Tickets here: https://luma.com/83fj2zkcSupport the show————————————————————Get tickets to our live show here [Feb 25th London]: https://luma.com/83fj2zkc ———————————————————— Join our Patreon for extra-long episodes and ad-free content: https://www.patreon.com/techish Watch us on YouTube: https://www.youtube.com/@techishpod/Advertise on Techish: https://goo.gl/forms/MY0F79gkRG6Jp8dJ2———————————————————— Stay in touch with the hashtag #Techishhttps://www.instagram.com/techishpod/https://www.instagram.com/abadesi/https://www.instagram.com/michaelberhane_/ https://www.instagram.com/hustlecrewlive/https://www.instagram.com/pocintech/Email us at techishpod@gmail.com

In this Feb 11, 2026 Crypto Town Hall, hosts and guests discuss extreme market fear, dismiss SBF's jailhouse bid for a new trial as futile, and slam big banks' lobbying to kill stablecoin yield via the Clarity Act as pure protectionism. They highlight stablecoins' potential to drive U.S. Treasury demand, BlackRock's DeFi push (including Uniswap), the collapse of hype-driven VC tokens, real-world asset tokenization opportunities, and persistent legal uncertainty for utility tokens without lasting regulatory clarity. The episode closes with AI's rapid coding/automation advances, its disruption of SaaS and DeFi, emerging security/legal risks from AI agents, and why tokenized money (especially stablecoins) will likely power future autonomous systems.

From time to time, we'll re-air a previous episode of the show that our newer audience may have missed. During this episode, Santosh is joined by Andrei Danescu, CEO and Co-Founder of Dexory, a company specializing in AI-powered autonomous robots and a real-time data platform to optimize warehouse operations by providing continuous, accurate insights without disrupting workflows. In this conversation, Andrei and Santosh discuss the transformative role of robotics in supply chain management, focusing on optimizing warehouse operations. Andrei shares his background and the challenges in the supply chain industry, such as visibility and data consistency issues. He explains how Dexory uses autonomous robots and real-time data to address these challenges, improve efficiency, and meet evolving customer expectations. The conversation also covers technological advancements, market trends, a vision for the future of supply chain operations, and more. Highlights from their conversation include:Andrei's Background in Robotics (1:18)The Core Problem in Supply Chain (5:25)Dexory Technology Overview (6:47)Identifying Customer Pain Points (8:04)Case Study of Success (11:27)State of Warehousing Robotics in Europe (13:36)Current Trends in Warehouse Robotics (15:08)Changing ROI Expectations (16:38)Dexter's Vision for the Future (19:31)NVIDIA's Impact on Robotics (21:22)Lessons Learned in Robotics Scaling (24:24)Vision for Product Introduction (25:34)This or That Segment and Final Takeaways (26:22)Dynamo is a VC firm led by supply chain and mobility specialists that focus on seed-stage, enterprise startups.Find out more at: https://www.dynamo.vc/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Infrastructure was passé…uncool. Difficult to get dollars from Private Equity and Growth funds, and almost impossible to get a VC fund interested. Now?! Now, it's cool. Infrastructure seems to be having a Renaissance, a full on Rebirth, not just fueled by commercial interests (e.g. advent of AI), but also by industrial policy and geopolitical considerations. In this episode of Tech Deciphered, we explore what's cool in the infrastructure spaces, including mega trends in semiconductors, energy, networking & connectivity, manufacturing Navigation: Intro We're back to building things Why now: the 5 forces behind the renaissance Semiconductors: compute is the new oil Networking & connectivity: digital highways get rebuilt Energy: rebuilding the power stack (not just renewables) Manufacturing: the return of “atoms + bits” Wrap: what it means for startups, incumbents, and investors Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show: Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Nuno Gonçalves Pedro Introduction Welcome to episode 73 of Tech Deciphered, Infrastructure, the Rebirth or Renaissance. Infrastructure was passé, it wasn’t cool, but all of a sudden now everyone’s talking about network, talking about compute and semiconductors, talking about logistics, talking about energy. What gives? What’s happened? It was impossible in the past to get any funds, venture capital, even, to be honest, some private equity funds or growth funds interested in some of these areas, but now all of a sudden everyone thinks it’s cool. The infrastructure seems to be having a renaissance, a full-on rebirth. In this episode, we will explore in which cool ways the infrastructure spaces are moving and what’s leading to it. We will deep dive into the forces that are leading us to this. We will deep dive into semiconductors, networking and connectivity, energy, manufacturing, and then we’ll wrap up. Bertrand, so infrastructure is cool now. Bertrand Schmitt We're back to building things Yes. I thought software was going to eat the world. I cannot believe it was then, maybe even 15 years ago, from Andreessen, that quote about software eating the world. I guess it’s an eternal balance. Sometimes you go ahead of yourself, you build a lot of software stack, and at some point, you need the hardware to run this software stack, and there is only so much the bits can do in a world of atoms. Nuno Gonçalves Pedro Obviously, we’ve gone through some of this before. I think what we’re going through right now is AI is eating the world, and because AI is eating the world, it’s driving a lot of this infrastructure building that we need. We don’t have enough energy to be consumed by all these big data centers and hyperscalers. We need to be innovative around network as well because of the consumption in terms of network bandwidth that is linked to that consumption as well. In some ways, it’s not software eating the world, AI is eating the world. Because AI is eating the world, we need to rethink everything around infrastructure and infrastructure becoming cool again. Bertrand Schmitt There is something deeper in this. It’s that the past 10, even 15 years were all about SaaS before AI. SaaS, interestingly enough, was very energy-efficient. When I say SaaS, I mean cloud computing at large. What I mean by energy-efficient is that actually cloud computing help make energy use more efficient because instead of companies having their own separate data centers in many locations, sometimes poorly run from an industrial perspective, replace their own privately run data center with data center run by the super scalers, the hyperscalers of the world. These data centers were run much better in terms of how you manage the coolings, the energy efficiency, the rack density, all of this stuff. Actually, the cloud revolution didn’t increase the use of electricity. The cloud revolution was actually a replacement from your private data center to the hyperscaler data center, which was energy efficient. That’s why we didn’t, even if we are always talking about that growth of cloud computing, we were never feeling the pinch in term of electricity. As you say, we say it all changed because with AI, it was not a simple “Replacement” of locally run infrastructure to a hyperscaler run infrastructure. It was truly adding on top of an existing infrastructure, a new computing infrastructure in a way out of nowhere. Not just any computing infrastructure, an energy infrastructure that was really, really voracious in term of energy use. Nuno Gonçalves Pedro There was one other effect. Obviously, we’ve discussed before, we are in a bubble. We won’t go too much into that today. But the previous big bubble in tech, which is in the late ’90s, there was a lot of infrastructure built. We thought the internet was going to take over back then. It didn’t take over immediately, but there was a lot of network connectivity, bandwidth built back in the day. Companies imploded because of that as well, or had to restructure and go in their chapter 11. A lot of the big telco companies had their own issues back then, etc., but a lot of infrastructure was built back then for this advent of the internet, which would then take a long time to come. In some ways, to your point, there was a lot of latent supply that was built that was around that for a while wasn’t used, but then it was. Now it’s been used, and now we need new stuff. That’s why I feel now we’re having the new moment of infrastructure, new moment of moving forward, aligned a little bit with what you just said around cloud computing and the advent of SaaS, but also around the fact that we had a lot of buildup back in the late ’90s, early ’90s, which we’re now still reaping the benefits on in today’s world. Bertrand Schmitt Yeah, that’s actually a great point because what was built in the late ’90s, there was a lot of fibre that was built. Laying out the fibre either across countries, inside countries. This fibre, interestingly enough, you could just change the computing on both sides of the fibre, the routing, the modems, and upgrade the capacity of the fibre. But the fibre was the same in between. The big investment, CapEx investment, was really lying down that fibre, but then you could really upgrade easily. Even if both ends of the fibre were either using very old infrastructure from the ’90s or were actually dark and not being put to use, step by step, it was being put to use, equipment was replaced, and step by step, you could keep using more and more of this fibre. It was a very interesting development, as you say, because it could be expanded over the years, where if we talk about GPUs, use for AI, GPUs, the interesting part is actually it’s totally the opposite. After a few years, it’s useless. Some like Google, will argue that they can depreciate over 5, 6 years, even some GPUs. But at the end of the day, the difference in perf and energy efficiency of the GPUs means that if you are energy constrained, you just want to replace the old one even as young as three-year-old. You have to look at Nvidia increasing spec, generation after generation. It’s pretty insane. It’s usually at least 3X year over year in term of performance. Nuno Gonçalves Pedro At this moment in time, it’s very clear that it’s happening. Why now: the 5 forces behind the renaissance Maybe let’s deep dive into why it’s happening now. What are the key forces around this? We’ve identified, I think, five forces that are particularly vital that lead to the world we’re in right now. One we’ve already talked about, which is AI, the demand shock and everything that’s happened because of AI. Data centers drive power demand, drive grid upgrades, drive innovative ways of getting energy, drive chips, drive networking, drive cooling, drive manufacturing, drive all the things that we’re going to talk in just a bit. One second element that we could probably highlight in terms of the forces that are behind this is obviously where we are in terms of cost curves around technology. Obviously, a lot of things are becoming much cheaper. The simulation of physical behaviours has become a lot more cheap, which in itself, this becomes almost a vicious cycle in of itself, then drives the adoption of more and more AI and stuff. But anyway, the simulation is becoming more and more accessible, so you can do a lot of simulation with digital twins and other things off the real world before you go into the real world. Robotics itself is becoming, obviously, cheaper. Hardware, a lot of the hardware is becoming cheaper. Computer has become cheaper as well. Obviously, there’s a lot of cost curves that have aligned that, and that’s maybe the second force that I would highlight. Obviously, funds are catching up. We’ll leave that a little bit to the end. We’ll do a wrap-up and talk a little bit about the implications to investors. But there’s a lot of capital out there, some capital related to industrial policy, other capital related to private initiative, private equity, growth funds, even venture capital, to be honest, and a few other elements on that. That would be a third force that I would highlight. Bertrand Schmitt Yes. Interestingly enough, in terms of capital use, and we’ll talk more about this, but some firms, if we are talking about energy investment, it was very difficult to invest if you are not investing in green energy. Now I think more and more firms and banks are willing to invest or support different type of energy infrastructure, not just, “Green energy.” That’s an interesting development because at some point it became near impossible to invest more in gas development, in oil development in the US or in most Western countries. At least in the US, this is dramatically changing the framework. Nuno Gonçalves Pedro Maybe to add the two last forces that I think we see behind the renaissance of what’s happening in infrastructure. They go hand in hand. One is the geopolitics of the world right now. Obviously, the world was global flat, and now it’s becoming increasingly siloed, so people are playing it to their own interests. There’s a lot of replication of infrastructure as well because people want to be autonomous, and they want to drive their own ability to serve end consumers, businesses, etc., in terms of data centers and everything else. That ability has led to things like, for example, chips shortage. The fact that there are semiconductors, there are shortages across the board, like memory shortages, where everything is packed up until 2027 of 2028. A lot of the memory that was being produced is already spoken for, which is shocking. There’s obviously generation of supply chain fragilities, obviously, some of it because of policies, for example, in the US with tariffs, etc, security of energy, etc. Then the last force directly linked to the geopolitics is the opposite of it, which is the policy as an accelerant, so to speak, as something that is accelerating development, where because of those silos, individual countries, as part their industrial policy, then want to put capital behind their local ecosystems, their local companies, so that their local companies and their local systems are for sure the winners, or at least, at the very least, serve their own local markets. I think that’s true of a lot of the things we’re seeing, for example, in the US with the Chips Act, for semiconductors, with IGA, IRA, and other elements of what we’ve seen in terms of practices, policies that have been implemented even in Europe, China, and other parts of the world. Bertrand Schmitt Talking about chips shortages, it’s pretty insane what has been happening with memory. Just the past few weeks, I have seen a close to 3X increase in price in memory prices in a matter of weeks. Apparently, it started with a huge order from OpenAI. Apparently, they have tried to corner the memory market. Interestingly enough, it has flat-footed the entire industry, and that includes Google, that includes Microsoft. There are rumours of their teams now having moved to South Korea, so they are closer to the action in terms of memory factories and memory decision-making. There are rumours of execs who got fired because they didn’t prepare for this type of eventuality or didn’t lock in some of the supply chain because that memory was initially for AI, but obviously, it impacts everything because factories making memories, you have to plan years in advance to build memories. You cannot open new lines of manufacturing like this. All factories that are going to open, we know when they are going to open because they’ve been built up for years. There is no extra capacity suddenly. At the very best, you can change a bit your line of production from one type of memory to another type. But that’s probably about it. Nuno Gonçalves Pedro Just to be clear, all these transformations we’re seeing isn’t to say just hardware is back, right? It’s not just hardware. There’s physicality. The buildings are coming back, right? It’s full stack. Software is here. That’s why everything is happening. Policy is here. Finance is here. It’s a little bit like the name of the movie, right? Everything everywhere all at once. Everything’s happening. It was in some ways driven by the upper stacks, by the app layers, by the platform layers. But now we need new infrastructure. We need more infrastructure. We need it very, very quickly. We need it today. We’re already lacking in it. Semiconductors: compute is the new oil Maybe that’s a good segue into the first piece of the whole infrastructure thing that’s driving now the most valuable company in the world, NVIDIA, which is semiconductors. Semiconductors are driving compute. Semis are the foundation of infrastructure as a compute. Everyone needs it for every thing, for every activity, not just for compute, but even for sensors, for actuators, everything else. That’s the beginning of it all. Semiconductor is one of the key pieces around the infrastructure stack that’s being built at scale at this moment in time. Bertrand Schmitt Yes. What’s interesting is that if we look at the market gap of Semis versus software as a service, cloud companies, there has been a widening gap the past year. I forgot the exact numbers, but we were talking about plus 20, 25% for Semis in term of market gap and minus 5, minus 10 for SaaS companies. That’s another trend that’s happening. Why is this happening? One, because semiconductors are core to the AI build-up, you cannot go around without them. But two, it’s also raising a lot of questions about the durability of the SaaS, a software-as-a-service business model. Because if suddenly we have better AI, and that’s all everyone is talking about to justify the investment in AI, that it keeps getting better, and it keeps improving, and it’s going to replace your engineers, your software engineers. Then maybe all of this moat that software companies built up over the years or decades, sometimes, might unravel under the pressure of newly coded, newly built, cheaper alternatives built from the ground up with AI support. It’s not just that, yes, semiconductors are doing great. It’s also as a result of that AI underlying trend that software is doing worse right now. Nuno Gonçalves Pedro At the end of the day, this foundational piece of infrastructure, semiconductor, is obviously getting manifest to many things, fabrication, manufacturing, packaging, materials, equipment. Everything’s being driven, ASML, etc. There are all these different players around the world that are having skyrocket valuations now, it’s because they’re all part of the value chain. Just to be very, very clear, there’s two elements of this that I think are very important for us to remember at this point in time. One, it’s the entire value chains are being shifted. It’s not just the chips that basically lead to computing in the strict sense of it. It’s like chips, for example, that drive, for example, network switching. We’re going to talk about networking a bit, but you need chips to drive better network switching. That’s getting revolutionised as well. For example, we have an investment in that space, a company called the eridu.ai, and they’re revolutionising one of the pieces around that stack. Second part of the puzzle, so obviously, besides the holistic view of the world that’s changing in terms of value change, the second piece of the puzzle is, as we discussed before, there’s industrial policy. We already mentioned the CHIPS Act, which is something, for example, that has been done in the US, which I think is 52 billion in incentives across a variety of things, grants, loans, and other mechanisms to incentivise players to scale capacity quick and to scale capacity locally in the US. One of the effects of that now is obviously we had the TSMC, US expansion with a factory here in the US. We have other levels of expansion going on with Intel, Samsung, and others that are happening as we speak. Again, it’s this two by two. It’s market forces that drive the need for fundamental shifts in the value chain. On the other industrial policy and actual money put forward by states, by governments, by entities that want to revolutionise their own local markets. Bertrand Schmitt Yes. When you talk about networking, it makes me think about what NVIDIA did more than six years ago when they acquired Mellanox. At the time, it was largest acquisition for NVIDIA in 2019, and it was networking for the data center. Not networking across data center, but inside the data center, and basically making sure that your GPUs, the different computers, can talk as fast as possible between each of them. I think that’s one piece of the puzzle that a lot of companies are missing, by the way, about NVIDIA is that they are truly providing full systems. They are not just providing a GPU. Some of their competitors are just providing GPUs. But NVIDIA can provide you the full rack. Now, they move to liquid-cool computing as well. They design their systems with liquid cooling in mind. They have a very different approach in the industry. It’s a systematic system-level approach to how do you optimize your data center. Quite frankly, that’s a bit hard to beat. Nuno Gonçalves Pedro For those listening, you’d be like, this is all very different. Semiconductors, networking, energy, manufacturing, this is all different. Then all of a sudden, as Bertrand is saying, well, there are some players that are acting across the stack. Then you see in the same sentence, you’re talking about nuclear power in Microsoft or nuclear power in Google, and you’re like, what happened? Why are these guys in the same sentence? It’s like they’re tech companies. Why are they talking about energy? It’s the nature of that. These ecosystems need to go hand in hand. The value chains are very deep. For you to actually reap the benefits of more and more, for example, semiconductor availability, you have to have better and better networking connectivity, and you have to have more and more energy at lower and lower costs, and all of that. All these things are intrinsically linked. That’s why you see all these big tech companies working across stack, NVIDIA being a great example of that in trying to create truly a systems approach to the world, as Bertrand was mentioning. Networking & connectivity: digital highways get rebuilt On the networking and connectivity side, as we said, we had a lot of fibre that was put down, etc, but there’s still more build-out needs to be done. 5G in terms of its densification is still happening. We’re now starting to talk, obviously, about 6G. I’m not sure most telcos are very happy about that because they just have been doing all this CapEx and all this deployment into 5G, and now people already started talking about 6G and what’s next. Obviously, data center interconnect is quite important, and all the hubbing that needs to happen around data centers is very, very important. We are seeing a lot movements around connectivity that are particularly important. Network gear and the emergence of players like Broadcom in terms of the semiconductor side of the fence, obviously, Cisco, Juniper, Arista, and others that are very much present in this space. As I said, we made an investment on the semiconductor side of networking as well, realizing that there’s still a lot of bottlenecks happening there. But obviously, the networking and connectivity stack still needs to be built at all levels within the data centers, outside of the data centers in terms of last mile, across the board in terms of fibre. We’re seeing a lot of movements still around the space. It’s what connects everything. At the end of the day, if there’s too much latency in these systems, if the bandwidths are not high enough, then we’re going to have huge bottlenecks that are going to be put at the table by a networking providers. Obviously, that doesn’t help anyone. If there’s a button like anywhere, it doesn’t work. All of this doesn’t work. Bertrand Schmitt Yes. Interestingly enough, I know we said for this episode, we not talk too much about space, but when you talk about 6G, it make me think about, of course, Starlink. That’s really your last mile delivery that’s being built as well. It’s a massive investment. We’re talking about thousands of satellites that are interconnected between each other through laser system. This is changing dramatically how companies can operate, how individuals can operate. For companies, you can have great connectivity from anywhere in the world. For military, it’s the same. For individuals, suddenly, you won’t have dead space, wide zones. This is also a part of changing how we could do things. It’s quite important even in the development of AI because, yes, you can have AI at the edge, but that interconnect to the rest of the system is quite critical. Having that availability of a network link, high-quality network link from anywhere is a great combo. Nuno Gonçalves Pedro Then you start seeing regions of the world that want to differentiate to attract digital nomads by saying, “We have submarine cables that come and hub through us, and therefore, our connectivity is amazing.” I was just in Madeira, and they were talking about that in Portugal. One of the islands of Portugal. We have some Marine cables. You have great connectivity. We’re getting into that discussion where people are like, I don’t care. I mean, I don’t know. I assume I have decent connectivity. People actually care about decent connectivity. This discussion is not just happening at corporate level, at enterprise level? Etc. Even consumers, even people that want to work remotely or be based somewhere else in the world. It’s like, This is important Where is there a great connectivity for me so that I can have access to the services I need? Etc. Everyone becomes aware of everything. We had a cloud flare mishap more recently that the CEO had to jump online and explain deeply, technically and deeply, what happened. Because we’re in their heads. If Cloudflare goes down, there’s a lot of websites that don’t work. All of this, I think, is now becoming du jour rather than just an afterthought. Maybe we’ll think about that in the future. Bertrand Schmitt Totally. I think your life is being changed for network connectivity, so life of individuals, companies. I mean, everything. Look at airlines and ships and cruise ships. Now is the advent of satellite connectivity. It’s dramatically changing our experience. Nuno Gonçalves Pedro Indeed. Energy: rebuilding the power stack (not just renewables) Moving maybe to energy. We’ve talked about energy quite a bit in the past. Maybe we start with the one that we didn’t talk as much, although we did mention it, which was, let’s call it the fossil infrastructure, what’s happening around there. Everyone was saying, it’s all going to be renewables and green. We’ve had a shift of power, geopolitics. Honestly, I the writing was on the wall that we needed a lot more energy creation. It wasn’t either or. We needed other sources to be as efficient as possible. Obviously, we see a lot of work happening around there that many would have thought, Well, all this infrastructure doesn’t matter anymore. Now we’re seeing LNG terminals, pipelines, petrochemical capacity being pushed up, a lot of stuff happening around markets in terms of export, and not only around export, but also around overall distribution and increases and improvements so that there’s less leakage, distribution of energy, etc. In some ways, people say, it’s controversial, but it’s like we don’t have enough energy to spare. We’re already behind, so we need as much as we can. We need to figure out the way to really extract as much as we can from even natural resources, which In many people’s mind, it’s almost like blasphemous to talk about, but it is where we are. Obviously, there’s a lot of renaissance also happening on the fossil infrastructure basis, so to speak. Bertrand Schmitt Personally, I’m ecstatic that there is a renaissance going regarding what is called fossil infrastructure. Oil and gas, it’s critical to humanity well-being. You never had growth of countries without energy growth and nothing else can come close. Nuclear could come close, but it takes decades to deploy. I think it’s great. It’s great for developed economies so that they do better, they can expand faster. It’s great for third-world countries who have no realistic other choice. I really don’t know what happened the past 10, 15 years and why this was suddenly blasphemous. But I’m glad that, strangely, thanks to AI, we are back to a more rational mindset about energy and making sure we get efficient energy where we can. Obviously, nuclear is getting a second act. Nuno Gonçalves Pedro I know you would be. We’ve been talking about for a long time, and you’ve been talking about it in particular for a very long time. Bertrand Schmitt Yes, definitely. It’s been one area of interest of mine for 25 years. I don’t know. I’ve been shocked about what happened in Europe, that willingness destruction of energy infrastructure, especially in Germany. Just a few months ago, they keep destroying on live TV some nuclear station in perfect working condition and replacing them with coal. I’m not sure there is a better definition of insanity at this stage. It looks like it’s only the Germans going that hardcore for some reason, but at least the French have stopped their program of decommissioning. America, it seems to be doing the same, so it’s great. On top of it, there are new generations that could be put to use. The Chinese are building up a very large nuclear reactor program, more than 100 reactors in construction for the next 10 years. I think everybody has to catch up because at some point, this is the most efficient energy solution. Especially if you don’t build crazy constraints around the construction of these nuclear reactors. If we are rational about permits, about energy, about safety, there are great things we could be doing with nuclear. That might be one of the only solution if we want to be competitive, because when energy prices go down like crazy, like in China, they will do once they have reach delivery of their significant build-up of nuclear reactors, we better be ready to have similar options from a cost perspective. Nuno Gonçalves Pedro From the outside, at the very least, nuclear seems to be probably in the energy one of the areas that’s more being innovated at this moment in time. You have startups in the space, you have a lot really money going into it, not just your classic industrial development. That’s very exciting. Moving maybe to the carbonization and what’s happening. The CCUS, and for those who don’t know what it is, carbon capture, utilization, and storage. There’s a lot of stuff happening around that space. That’s the area that deals with the ability to capture CO₂ emissions from industrial sources and/or the atmosphere and preventing their release. There’s a lot of things happening in that space. There’s also a lot of things happening around hydrogen and geothermal and really creating the ability to storage or to store, rather, energy that then can be put back into the grids at the right time. There’s a lot of interesting pieces happening around this. There’s some startup movement in the space. It’s been a long time coming, the reuse of a lot of these industrial sources. Not sure it’s as much on the news as nuclear, and oil and gas, but certainly there’s a lot of exciting things happening there. Bertrand Schmitt I’m a bit more dubious here, but I think geothermal makes sense if it’s available at reasonable price. I don’t think hydrogen technology has proven its value. Concerning carbon capture, I’m not sure how much it’s really going to provide in terms of energy needs, but why not? Nuno Gonçalves Pedro Fuels niche, again, from the outside, we’re not energy experts, but certainly, there are movements in the space. We’ll see what’s happening. One area where there’s definitely a lot of movement is this notion of grid and storage. On the one hand, that transmission needs to be built out. It needs to be better. We’ve had issues of blackouts in the US. We’ve had issues of blackouts all around the world, almost. Portugal as well, for a significant part of the time. The ability to work around transmission lines, transformers, substations, the modernization of some of this infrastructure, and the move forward of it is pretty critical. But at the other end, there’s the edge. Then, on the edge, you have the ability to store. We should have, better mechanisms to store energy that are less leaky in terms of energy storage. Obviously, there’s a lot of movement around that. Some of it driven just by commercial stuff, like Tesla a lot with their storage stuff, etc. Some of it really driven at scale by energy players that have the interest that, for example, some of the storage starts happening closer to the consumption as well. But there’s a lot of exciting things happening in that space, and that is a transformative space. In some ways, the bottleneck of energy is also around transmission and then ultimately the access to energy by homes, by businesses, by industries, etc. Bertrand Schmitt I would say some of the blackout are truly man-made. If I pick on California, for instance. That’s the logical conclusion of the regulatory system in place in California. On one side, you limit price that energy supplier can sell. The utility company can sell, too. On the other side, you force them to decommission the most energy-efficient and least expensive energy source. That means you cap the revenues, you make the cost increase. What is the result? The result is you cannot invest anymore to support a grid and to support transmission. That’s 100% obvious. That’s what happened, at least in many places. The solution is stop crazy regulations that makes no economic sense whatsoever. Then, strangely enough, you can invest again in transmission, in maintenance, and all I love this stuff. Maybe another piece, if we pick in California, if you authorize building construction in areas where fires are easy, that’s also a very costly to support from utility perspective, because then you are creating more risk. You are forced buy the state to connect these new constructions to the grid. You have more maintenance. If it fails, you can create fire. If you create fire, you have to pay billions of fees. I just want to highlight that some of this is not a technological issue, is not per se an investment issue, but it’s simply the result of very bad regulations. I hope that some will learn, and some change will be made so that utilities can do their job better. Nuno Gonçalves Pedro Then last, but not the least, on the energy side, energy is becoming more and more digitally defined in some ways. It’s like the analogy to networks that they’ve become more, and more software defined, where you have, at the edge is things like smart meters. There’s a lot of things you can do around the key elements of the business model, like dynamic pricing and other elements. Demand response, one of the areas that I invested in, I invest in a company called Omconnect that’s now merged with what used to be Google Nest. Where to deploy that ability to do demand response and also pass it to consumers so that consumers can reduce their consumption at times where is the least price effective or the less green or the less good for the energy companies to produce energy. We have other things that are happening, which are interesting. Obviously, we have a lot more electric vehicles in cars, etc. These are also elements of storage. They don’t look like elements of storage, but the car has electricity in it once you charge it. Once it’s charged, what do you do with it? Could you do something else? Like the whole reverse charging piece that we also see now today in mobile devices and other edge devices, so to speak. That also changes the architecture of what we’re seeing around the space. With AI, there’s a lot of elements that change around the value chain. The ability to do forecasting, the ability to have, for example, virtual power plans because of just designated storage out there, etc. Interesting times happening. Not sure all utilities around the world, all energy providers around the world are innovating at the same pace and in the same way. But certainly just looking at the industry and talking to a lot of players that are CEOs of some of these companies. That are leading innovation for some of these companies, there’s definitely a lot more happening now in the last few years than maybe over the last few decades. Very exciting times. Bertrand Schmitt I think there are two interesting points in what you say. Talking about EVs, for instance, a Cybertruck is able to send electricity back to your home if your home is able to receive electricity from that source. Usually, you have some changes to make to the meter system, to your panel. That’s one great way to potentially use your car battery. Another piece of the puzzle is that, strangely enough, most strangely enough, there has been a big push to EV, but at the same time, there has not been a push to provide more electricity. But if you replace cars that use gasoline by electric vehicles that use electricity, you need to deliver more electricity. It doesn’t require a PhD to get that. But, strangely enough, nothing was done. Nuno Gonçalves Pedro Apparently, it does. Bertrand Schmitt I remember that study in France where they say that, if people were all to switch to EV, we will need 10 more nuclear reactors just on the way from Paris to Nice to the Côte d’Azur, the French Rivière, in order to provide electricity to the cars going there during the summer vacation. But I mean, guess what? No nuclear plant is being built along the way. Good luck charging your vehicles. I think that’s another limit that has been happening to the grid is more electric vehicles that require charging when the related infrastructure has not been upgraded to support more. Actually, it has quite the opposite. In many cases, we had situation of nuclear reactors closing down, so other facilities closing down. Obviously, the end result is an increase in price of electricity, at least in some states and countries that have not sold that fully out. Nuno Gonçalves Pedro Manufacturing: the return of “atoms + bits” Moving to manufacturing and what’s happening around manufacturing, manufacturing technology. There’s maybe the case to be made that manufacturing is getting replatformed, right? It’s getting redefined. Some of it is very obvious, and it’s already been ongoing for a couple of decades, which is the advent of and more and more either robotic augmented factories or just fully roboticized factories, where there’s very little presence of human beings. There’s elements of that. There’s the element of software definition on top of it, like simulation. A lot of automation is going on. A lot of AI has been applied to some lines in terms of vision, safety. We have an investment in a company called Sauter Analytics that is very focused on that from the perspective of employees and when they’re still humans in the loop, so to speak, and the ability to really figure out when people are at risk and other elements of what’s happening occurring from that. But there’s more than that. There’s a little bit of a renaissance in and of itself. Factories are, initially, if we go back a couple of decades ago, factories were, and manufacturing was very much defined from the setup. Now it’s difficult to innovate, it’s difficult to shift the line, it’s difficult to change how things are done in the line. With the advent of new factories that have less legacy, that have more flexible systems, not only in terms of software, but also in terms of hardware and robotics, it allows us to, for example, change and shift lines much more easily to different functions, which will hopefully, over time, not only reduce dramatically the cost of production. But also increase dramatically the yield, it increases dramatically the production itself. A lot of cool stuff happening in that space. Bertrand Schmitt It’s exciting to see that. One thing this current administration in the US has been betting on is not just hoping for construction renaissance. Especially on the factory side, up of factories, but their mindset was two things. One, should I force more companies to build locally because it would be cheaper? Two, increase output and supply of energy so that running factories here in the US would be cheaper than anywhere else. Maybe not cheaper than China, but certainly we get is cheaper than Europe. But three, it’s also the belief that thanks to AI, we will be able to have more efficient factories. There is always that question, do Americans to still keep making clothes, for instance, in factories. That used to be the case maybe 50 years ago, but this move to China, this move to Bangladesh, this move to different places. That’s not the goal. But it can make sense that indeed there is ability, thanks to robots and AI, to have more automated factories, and these factories could be run more efficiently, and as a result, it would be priced-competitive, even if run in the US. When you want to think about it, that has been, for instance, the South Korean playbook. More automated factories, robotics, all of this, because that was the only way to compete against China, which has a near infinite or used to have a near infinite supply of cheaper labour. I think that all of this combined can make a lot of sense. In a way, it’s probably creating a perfect storm. Maybe another piece of the puzzle this administration has been working on pretty hard is simplifying all the permitting process. Because a big chunk of the problem is that if your permitting is very complex, very expensive, what take two years to build become four years, five years, 10 years. The investment mass is not the same in that situation. I think that’s a very important part of the puzzle. It’s use this opportunity to reduce regulatory state, make sure that things are more efficient. Also, things are less at risk of bribery and fraud because all these regulations, there might be ways around. I think it’s quite critical to really be careful about this. Maybe last piece of the puzzle is the way accounting works. There are new rules now in 2026 in the US where you can fully depreciate your CapEx much faster than before. That’s a big win for manufacturing in the US. Suddenly, you can depreciate much faster some of your CapEx investment in manufacturing. Nuno Gonçalves Pedro Just going back to a point you made and then moving it forward, even China, with being now probably the country in the world with the highest rate of innovation and take up of industrial robots. Because of demographic issues a little bit what led Japan the first place to be one of the real big innovators around robots in general. The fact that demographics, you’re having an aging population, less and less children. How are you going to replace all these people? Moving that into big winners, who becomes a big winner in a space where manufacturing is fundamentally changing? Obviously, there’s the big four of robots, which is ABB, FANUC, KUKA, and Yaskawa. Epson, I think, is now in there, although it’s not considered one of the big four. Kawasaki, Denso, Universal Robots. There’s a really big robotics, industrial robotic companies in the space from different origins, FANUC and Yaskawa, and Epson from Japan, KUKA from Germany, ABB from Switzerland, Sweden. A lot of now emerging companies from China, and what’s happening in that space is quite interesting. On the other hand, also, other winners will include players that will be integrators that will build some of the rest of the infrastructure that goes into manufacturing, the Siemens of the world, the Schneider’s, the Rockwell’s that will lead to fundamental industrial automation. Some big winners in there that whose names are well known, so probably not a huge amount of surprises there. There’s movements. As I said, we’re still going to see the big Chinese players emerging in the world. There are startups that are innovating around a lot of the edges that are significant in this space. We’ll see if this is a space that will just be continued to be dominated by the big foreign robotics and by a couple of others and by the big integrators or not. Bertrand Schmitt I think you are right to remind about China because China has been moving very fast in robotics. Some Chinese companies are world-class in their use of robotics. You have this strange mix of some older industries where robotics might not be so much put to use and typically state-owned, versus some private companies, typically some tech companies that are reconverting into hardware in some situation. That went all in terms of robotics use and their demonstrations, an example of what’s happening in China. Definitely, the Chinese are not resting. Everyone smart enough is playing that game from the Americans, the Chinese, Japanese, the South Koreans. Nuno Gonçalves Pedro Exciting things are manufacturing, and maybe to bring it all together, what does it mean for all the big players out there? If we talk with startups and talk about startups, we didn’t mention a ton of startups today, right? Maybe incumbent wind across the board. But on a more serious note, we did mention a few. For example, in nuclear energy, there’s a lot of startups that have been, some of them, incredibly well-funded at this moment in time. Wrap: what it means for startups, incumbents, and investors There might be some big disruptions that will come out of startups, for example, in that space. On the chipset side, we talked about the big gorillas, the NVIDIAs, AMDs, Intel, etc., of the world. But we didn’t quite talk about the fact that there’s a lot of innovation, again, happening on the edges with new players going after very large niches, be it in networking and switching. Be it in compute and other areas that will need different, more specialized solutions. Potentially in terms of compute or in terms of semiconductor deployments. I think there’s still some opportunities there, maybe not to be the winner takes all thing, but certainly around a lot of very significant niches that might grow very fast. Manufacturing, we mentioned the same. Some of the incumbents seem to be in the driving seat. We’ll see what happens if some startups will come in and take some of the momentum there, probably less likely. There are spaces where the value chains are very tightly built around the OEMs and then the suppliers overall, classically the tier one suppliers across value chains. Maybe there is some startup investment play. We certainly have played in the couple of the spaces. I mentioned already some of them today, but this is maybe where the incumbents have it all to lose. It’s more for them to lose rather than for the startups to win just because of the scale of what needs to be done and what needs to be deployed. Bertrand Schmitt I know. That’s interesting point. I think some players in energy production, for instance, are moving very fast and behaving not only like startups. Usually, it’s independent energy suppliers who are not kept by too much regulations that get moved faster. Utility companies, as we just discussed, have more constraints. I would like to say that if you take semiconductor space, there has been quite a lot of startup activities way more than usual, and there have been some incredible success. Just a few weeks ago, Rock got more or less acquired. Now, you have to play games. It’s not an outright acquisition, but $20 billion for an IP licensing agreement that’s close to an acquisition. That’s an incredible success for a company. Started maybe 10 years ago. You have another Cerebras, one of the competitor valued, I believe, quite a lot in similar range. I think there is definitely some activity. It’s definitely a different game compared to your software startup in terms of investment. But as we have seen with AI in general, the need for investment might be larger these days. Yes, it might be either traditional players if they can move fast enough, to be frank, because some of them, when you have decades of being run as a slow-moving company, it’s hard to change things. At the same time, it looks like VCs are getting bigger. Wall Street is getting more ready to finance some of these companies. I think there will be opportunities for startups, but definitely different types of startups in terms of profile. Nuno Gonçalves Pedro Exactly. From an investor standpoint, I think on the VC side, at least our core belief is that it’s more niche. It’s more around big niches that need to be fundamentally disrupted or solutions that require fundamental interoperability and integration where the incumbents have no motivation to do it. Things that are a little bit more either packaging on the semiconductor side or other elements of actual interoperability. Even at the software layer side that feeds into infrastructure. If you’re a growth investor, a private equity investor, there’s other plays that are available to you. A lot of these projects need to be funded and need to be scaled. Now we’re seeing projects being funded even for a very large, we mentioned it in one of the previous episodes, for a very large tech companies. When Meta, for example, is going to the market to get funding for data centers, etc. There’s projects to be funded there because just the quantum and scale of some of these projects, either because of financial interest for specifically the tech companies or for other reasons, but they need to be funded by the market. There’s other place right now, certainly if you’re a larger private equity growth investor, and you want to come into the market and do projects. Even public-private financing is now available for a lot of things. Definitely, there’s a lot of things emanating that require a lot of funding, even for large-scale projects. Which means the advent of some of these projects and where realization is hopefully more of a given than in other circumstances, because there’s actual commercial capital behind it and private capital behind it to fuel it as well, not just industrial policy and money from governments. Bertrand Schmitt There was this quite incredible stat. I guess everyone heard about that incredible growth in GDP in Q3 in the US at 4.4%. Apparently, half of that growth, so around 2.2% point, has been coming from AI and related infrastructure investment. That’s pretty massive. Half of your GDP growth coming from something that was not there three years ago or there, but not at this intensity of investment. That’s the numbers we are talking about. I’m hearing that there is a good chance that in 2026, we’re talking about five, even potentially 6% GDP growth. Again, half of it potentially coming from AI and all the related infrastructure growth that’s coming with AI. As a conclusion for this episode on infrastructure, as we just said, it’s not just AI, it’s a whole stack, and it’s manufacturing in general as well. Definitely in the US, in China, there is a lot going on. As we have seen, computing needs connectivity, networks, need power, energy and grid, and all of this needs production capacity and manufacturing. Manufacturing can benefit from AI as well. That way the loop is fully going back on itself. Infrastructure is the next big thing. It’s an opportunity, probably more for incumbents, but certainly, as usual, with such big growth opportunities for startups as well. Thank you, Nuno. Nuno Gonçalves Pedro Thank you, Bertrand.

I interviewed Play Ventures General Partner Phylicia Koh to explore what founders outside of gaming can learn from two decades of game design. Play Ventures began as a gaming-focused VC fund. Today, it also invests in what Phylicia calls “playable apps,” consumer products that combine utility with the engagement mechanics of games. That doesn't mean slapping on points and badges. It means understanding motivation, social dynamics, retention loops, and in-app economies. We talk about: What actually makes an app “playable” — and why most gamification fails The difference between vanity retention and real engagement Why founders should get comfortable with paid user acquisition  What she wants to see at pre-seed (hint: can you ship?) How to design for habit in categories like fintech, wellness, and spirituality If you're a domain expert building a consumer product and you've never seriously considered how game design might increase engagement and lifetime value, this conversation will give you a new lens. RUNTIME 37:20   EPISODE BREAKDOWN (2:33) “Play identifies as a gaming and also a consumer VC fund.” (7:53) How she determines if gaming skills/practices will add value. (11:19) How to pitch Play Ventures  (14:50) "Can you ship? Because shipping is hard." (18:05) Phylicia's top success metrics for playable apps (21:39) “You're going to need to use paid user acquisition." (28:07) “If somebody has a good idea, I guarantee you somebody else around the world has that idea too.” (32:46) An idea she'd like to back that doesn't exist yet LINKS Phylicia Koh Play Ventures SUBSCRIBE

“And I’m here to remind you Of the mess you left when you went away It’s not fair to deny me Of the cross I bear that you gave to me You, you, you oughta know…” In this review episode, Mark and Dan discuss Amazing Spider-Man (vol. 7) #20, which is legacy issue #984. This issue was written by Joe Kelly. The cover features artwork by John Romita Jr., Scott Hanna, and Dean White. The interiors feature pencils by John Romita Jr., Paco Diaz, and Todd Nauck, inks by Scott Hanna, Paco Diaz, and Todd Nauck, colors by Marcio Menyz, Erick Arciniega, and Marte Gracia, and, of course, letters by VC's Joe Caramagna. This issue was first released on January 21st, 2025. Rick Coste edited this episode. Alex Galucki edited the video version of this podcast. Our artwork is handcrafted by artists Ron Frenz, Sal Buscema, and Nick Cagnetti. Our theme songs were produced by Ryland Bojack, Tony Thaxton, and Spider-Maj. Our animated introduction to the show is by Josh Sutton of Panels to Pixels. Watch the show on YouTube: https://www.youtube.com/channel/UCOPCnjzQZNViyEnoOuckaVQ We would also love to see you join our Amazing Spider-Slack community board. If you'd like to join in on our amazing conversations, click this link to get started: https://join.slack.com/t/amazingspider/shared_invite/zt-42tsfhs2-yBaH6KkRmOWiW_8gCf9SmQ This week's Patreon podcasts include a review of Amazing Spider-Man (vol. 7) #21, our interview with Ron Frenz and Tom DeFalco about Venom #252, and two episodes of the Whatever a Spider Can Diaries, which documents Dan’s process of writing a book about Spider-Man. If you'd like to follow along with our reviews as they are released, please check out our Patreon page: https://www.patreon.com/superiorspidertalk Read our B-Title reviews, collecting memories, and more in the Amazing Spider-Talk Substack! http://www.amazingspider.substack.com You can email questions to our show at amazingspidertalk@gmail.com or by clicking here. You can also BUY MARK'S BOOK, 100 Things Spider-Man Fans Should Know & Do Before They Die. The post The Amazing Spider-Man (vol. 7) #20 / LGY #984 – REVIEW appeared first on Amazing Spider-Talk.