Podcasts about Andreessen Horowitz

“We are all in the gutter, but some of us are looking at the stars,” Oscar Wilde wrote in his 1892 play Lady Windermere's Fan. This week, Elon Musk managed — not for the first time — to be simultaneously in the stars and the gutter. SpaceX's IPO valued his rocket company at $2 trillion — making Musk, officially, a trillionaire, the richest person in the world by a very large margin. The space Musk — the defiant genius who bet everything on a reusable rocket and the promise of a cosmic monopoly — is astonishing. The Wall Street Journal called the IPO a Goldilocks debut with Musk starring as the three bears. But there is another Musk — the one in the gutter, promoting white nationalist violence from his platform on X. This week Musk not only stoked the anti-immigrant riots in Belfast but reiterated his support for the English white supremacist gangster Tommy Robinson. So is this another Strange Case of Dr Jekyll and Mr Hyde, Robert Louis Stevenson's 1886 novella? Keith Teare, publisher of That Was the Week, certainly thinks so. While Keith is in awe of Musk's entrepreneurial genius at SpaceX, he seems to excuse Musk's support for Tommy Robinson's paramilitarism. “I'm not even sure I like him,” Keith confesses in his musings on “civilisation.” Nor do the rest of us. But I wonder if this good/bad Elon narrative is too convenient. There is an uncomfortable symbiosis between Musk's journey to SpaceX and to white nationalist violence. For all the utopian cornucopia of space, our earthly reality is one of scarce land and fear of immigrants — Trump, Tommy Robinson, and this weekend's Swiss referendum on capping its population at 10 million. For all the Muskian promise of cosmic abundance, today's Muskian politics is paranoid and exclusionary. So maybe it's not just Elon. Everyone these days is simultaneously in the gutter and looking up at the stars. Five Takeaways •       SpaceX: From El Segundo Warehouse to $2 Trillion Juggernaut: SpaceX is 25 years old. It started in a warehouse near Los Angeles, in an area with a concentration of rocket scientists. Musk bet almost all of his Tesla gains on the idea of a reusable rocket — and nearly lost everything. Then a rocket worked. Since then: iterative improvement, the rockets getting bigger and more reliable, a virtual global monopoly on delivering payloads to space, Starlink (satellite internet that actually works at gigabit speeds), and NASA subcontracting its launches. Now: $2 trillion at IPO, Musk a trillionaire. Wall-to-wall applause from the startup world. Wall-to-wall pylon on social media. Both simultaneously true. •       The Grimace vs the Applause: Andrew vs Keith's Media Diet: Keith says most commentators are grimacing at the valuation and Musk's net worth. Andrew says the serious press — the Wall Street Journal, even the New York Times — is largely applauding. The exchange reveals the media bifurcation: mainstream outlets cover the achievement; social media — X, Facebook, LinkedIn — is wall-to-wall outrage about a trillionaire in a world of growing inequality. Keith's verdict on Musk: he doesn't care whether people like him. Neither, in Keith's view, should we. You judge him not on likability but on criteria: civilization or net worth. Different criteria, different judgment. •       California and Europe: The Failure of Government: Fareed Zakaria in the Washington Post: California is a case study in failed government. Andrew had Jonathan Weber on the show this week — City on the Edge, the historic dysfunctionality of San Francisco city government. Fukuyama is trying to be optimistic about Europe's liberal future. Keith's counter: Fukuyama ignores the structural problem — top-heavy EU bureaucracy that overrides countries, producing dislike of the EU in every European nation, even France, which built it. Populism, Keith argues, is not the disease. It's the symptom. The disease is twenty years of bad policy. •       Bernie Sanders Finally Had an Insight: The Sovereign Wealth Fund: Sanders has proposed a sovereign wealth fund owning 50% of all high-growth AI companies, giving every citizen ownership shares. Keith, who last week said 50% wasn't enough, this week credits it as the first genuine insight Sanders has had. The kicker: David Sacks — arch right-winger, former PayPal Mafia, Andreessen Horowitz — agreed on his podcast and said it should be 75%. Keith's observation: when David Sacks and Bernie Sanders can agree on the direction, left-right labels stop helping. The question is just how to make capitalism's gains flow to everyone. •       Planning Beats Complaint: Keith's editorial closer. The choice is not between liking Musk and hating Musk, not between celebrating SpaceX and resenting its valuation. The choice is between complaining and planning. John O'Farrell, former general partner at Andreessen Horowitz, resigned and wrote an op-ed in the New York Times: “We can't let my former venture capital colleagues buy off democracy.” Gary Tan organised an Asian-American reaction against San Francisco's school board and won. Citizens who act beat citizens who complain. That's the week's lesson. That's Keith's lesson. Andrew is away next week. About the Guest Keith Teare is a British-American entrepreneur, investor, and publisher of the That Was the Week newsletter. He is a co-founder of TechCrunch and Andrew's regular TWTW co-host. References: •       That Was the Week by Keith Teare. •       Fareed Zakaria, “How California Became a Case Study in Failed Government,” Washington Post — referenced in the conversation. •       John O'Farrell, “We Can't Let My Former Venture Capital Colleagues Buy Off Democracy,” New York Times — referenced in the conversation. •       Francis Fukuyama on the liberal vision of Europe — referenced in the conversation. •       Episode 2938: Jonathan Weber on City on the Edge — referenced at the opening. About Keen On America Nobody asks more awkward questions than the Anglo-American writer and filmmaker Andrew Keen. In Keen On America, Andrew brings his pointed Transatlantic wit to making sense of the United States — hosting daily interviews about the history and future of this now venerable Republic. With nearly 2,900 episodes since the show launched on TechCrunch in 2010, Keen On America is the most prolific intellectual interview show in the history of podcasting. WebsiteSubstackYouTubeApple PodcastsSpotify Chapters: (00:31) - Introduction: SpaceX IPO, ...

Primer fallecimiento por golpe de calor en TabascoTlalpan invita al Festival Fogones de MéxicoHonduras confirma primer caso de sarampión en 30 añosMás información en nuestro Podcast#grc

SpaceX startet mit einem ordentlichen Pop in den Handel. Tausende Mitarbeiter werden zu Millionären, Founders Fund und Andreessen Horowitz vermelden Rekord-Returns. Anthropic launcht Fable 5 und das Mythos-Modell für Testpartner. OpenAI plant laut Wall Street Journal drastische Preissenkungen für den User-Krieg mit Anthropic. China plant $300 Mrd. für nationalen KI-Ausbau über fünf Jahre. Xiaomi MiMo Code schlägt Claude Code in den gängigen Benchmarks. OpenAI übernimmt das Kieler Startup ONA, Mistral kauft das Linzer Emmi AI für eine Industrie-KI-Plattform und verhandelt selbst eine $20-Mrd.-Bewertung. Dario Amodei mit neuem Essay zur AI-Exponential-Politik. Oracle Earnings, Prometheus von Jeff Bezos bei $41 Mrd. Die Trump-Familie hat $2,3 Mrd. mit Krypto eingestrichen. Palantir verliert vor dem Zürcher Handelsgericht gegen die Zeitschrift Republik. Neura Robotics raised $1,4 Mrd. mit Tether als Lead. Landgericht München: Google haftet für seine AI-Overviews.  Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) SpaceX-IPO (00:08:04) Mitarbeiter-Millionäre (00:11:51) OpenAI/Anthropic-IPO-Outlook (00:15:31) Elon-Puppe vor der Nasdaq (00:16:13) Anthropic Fable 5 & Mythos 5 (00:19:54) OpenAI Preiskrieg (00:27:27) Token-Wert pro Abo (00:30:30) Messi für ChatGPT (00:34:48) China $300 Mrd. KI-Plan (00:37:31) Xiaomi MiMo Code (00:39:46) OpenAI kauft ONA (00:42:54) Anthropic: AI Exponential Policy (00:46:53) Oracle Earnings (00:48:07) Mistral kauft Emmi AI (00:49:08) Prometheus von Bezos (00:50:48) Trump Phone (00:51:22) Waymo Premier (00:55:40) Google Trade-Worker (00:57:08) Anthropic Claude Corps (00:58:37) Trump-Krypto-Scam (00:59:35) The Platform Group (01:03:48) Palantir vs. Republik (01:05:48) Mistral $20 Mrd. Runde (01:07:07) Neura Robotics Series C (01:10:47) NYT: China und Robotik (01:13:19) Google haftet für AI-Overviews Shownotes SpaceX-IPO zieht $70 Mrd. an Retail-Orders - bloomberg.com Founders Fund + Andreessen: Rekord-Returns aus SpaceX-IPO - bloomberg.com SpaceX Proteste - xcancel.com Anthropic launcht Claude Fable 5 & Mythos 5 - wired.com OpenAI plant drastische Preissenkungen für User-Krieg mit Anthropic - wsj.com Bitte manuell prüfen (petergostev-Post) - xcancel.com SemiAnalysis - xcancel.com China plant $295 Mrd. für nationalen KI-Ausbau - bloomberg.com ONA: Kieler KI-Startup raised - linkedin.com Anthropic: Policy on the AI Exponential - anthropic.com Oracle Q4 Earnings - cnbc.com Mistral übernimmt Emmi AI für Industrie-KI-Plattform - handelsblatt.com Prometheus: Bezos' Industrial-AI-Startup - axios.com Teardown: Trump Phone ist HTC U24 Pro in Gold - de.ifixit.com Waymo launcht Loyalty-Programm mit 10% Cashback - techcrunch.com Google launcht Trade-Worker-Initiative für KI - axios.com Daniela Amodei startet Anthropics Claude Corps - apnews.com Xiaomi MiMo Code schlägt Claude Code bei 200-Step-Tasks - venturebeat.com Trump-Crypto-Playbook: Family wins, Investors don't - reuters.com The Platform Group - manager-magazin.de Einstweilige Verfügung: The Platform Group vs. Manager Magazin - lhr-law.de Palantir - ft.com Mistral verhandelt $20 Mrd. Bewertung - bloomberg.com Bitte manuell prüfen (dreger-Post) - linkedin.com Neura Robotics schließt Rekord-Series-C - neura-robotics.com Chinas Humanoid-Robot-Schub - nytimes.com Deutsches Gericht: Google haftbar für AI-Overviews - thenextweb.com

Exposing The Dark Money Machine Behind AI PropagandaSUPPORT MY WORK: Buy a paid subscription to my newsletter at usermag.co     Support my work on Patreon: http://patreon.com/taylorlorenz I break down my investigation into a network of pro-AI and anti-AI meme accounts that I found were secretly being run and funded by OpenAI, Palantir, and Andreessen Horowitz's big $125M super PAC and dark money group. I reveal how these accounts operated, who is connected to them, why they promoted both sides of the AI debate, and how the organization at the center of the story confirmed key aspects of the reporting after publication.I talk about how a self-described “Meme Lord” named Jason Levin,  founder of Memelord Technologies was hired by the super PAC, Leading the Future, to create and run sock puppet accounts like “DoomersAreDumb” and “Jonathan Doomer” to attack AI critics, mock disabled people, post violent threats, and even pretend to be an anti-AI activist.OpenAI's president Greg Brockman donated millions to this campaign. OpenAI's head of strategy follows these meme accounts. And when confronted, Build American AI confirmed it all.Topics covered:AI propaganda and influence campaignsOpenAI and AI policy politicsDark money groups and Super PACsFake activist accountsAI-generated content networksMeme pages and online manipulationPolitical lobbying and artificial intelligenceSocial media influence operationsTech industry power and public opinion#AI #ArtificialIntelligence #TechNews #OpenAI #SiliconValley #MemeCulture #InvestigativeJournalism #InfluenceCampaign #AIDebate #TechPolicy #PowerUser

Hoy conversé con Ian Lee, fundador de Nexor, una startup de inteligencia artificial respaldada por Andreessen Horowitz, una de las firmas de Venture Capital más influyentes del mundo.Antes de Nexor, Ian fundó Examedi en 2021. Participó en Y Combinator y fue el primer chileno en recibir la prestigiosa beca Thiel Fellowship, creada por Peter Thiel.

"$75M in 13 months. a16z just led their Series A."We sat down with Niklas Lindgren, Co-Founder & CEO of Endra, fresh off their $50M Series A led by Andreessen Horowitz, taking total funding to $75M in 13 months.Endra is building the purpose-built workspace for MEP engineering, already partnering with AtkinsRéalis, Buro Happold, WSP, Hoare Lea, Ramboll and AFRY.Tune in to find out about:✅ Why a16z led at Series A instead of waiting for later traction✅ The Stripe vs PayPal analogy behind Endra's category play (and why they're not replacing Revit)✅ The honest answer to the billable-hours paradox✅ What this means for the next generation of MEP graduatesWatch now on Spotify and YouTube

If it feels like investors everywhere have some curiosity about the defense tech landscape, then it's because more of them both want to increase their knowledge and sometimes involvement in the ecosystem. Steve Brotman, founder and managing partner of the growth equity investment firm Alpha Partners, fits into that category as an observer and participant that works with venture capital firms to be involved in promising tech companies. Steve joins our Ross Wilkers for this episode to answer the questions laid out in the title, namely how it became cool again for investors to get involved with defense tech companies and markers that indicate how long this boom of interest could last. SpaceX's initial public offering and corporate VC funds feature in the chat too. Also listen out for Steve's tips and suggested homework for business leaders to do before venturing out into VC networks. US investors warm to Ukrainian defense startups—but export laws slow cooperation Budget would cut Pentagon research by one-third. Can industry compensate? Meet the startups trying to build military-specific AI Venture investing is part of the M&A conversation too The defense tech ecosystem gives investors many opportunities Public offerings put GovCon in a new spotlight as SpaceX's listing looms SpaceX's S-1 lays out its government work and market ambitions SpaceX's governance structure is built for one person: Elon Musk SpaceX's biggest risk factor might be Elon Musk Lockheed boosts its venture investment fund to $1B Booz Allen commits $400M to Andreessen Horowitz's late-stage fund Booz Allen gives big boost to its venture arm WT 360: For Lockheed's ventures team, its investments are merely step one WT 360: RTX Ventures casts its net wide and far across an expanding tech ecosystem WT 360: Booz Allen's roadmap for collaborating with startups after an investment WT 360: SAIC Ventures' methods for investing in and working with tech startups

Benedict Evans is an independent analyst and former partner at Andreessen Horowitz, where he spent years as their in-house “thinker” tracking the most important technology trends. For the past six years, he's been publishing deeply researched presentations on where tech is heading, most recently focused on AI's transformation of the economy. His work is read by founders, investors, and operators trying to make sense of a noisy field. His most controversial opinion: AI is as big a deal as the internet or mobile—and only as big.In our in-depth conversation, we discuss:1. Why we're in “1997” for AI—early, exciting, and deeply uncertain about what comes next2. Where value will actually accrue in the AI stack3. The anti-AI backlash, and where it may lead4. The surprising boom in consulting and professional services at AI companies5. Why distribution is becoming the ultimate moat as software gets easier to build6. Why the right question about your job isn't “What percent can AI do?” but “Is this a task or a job?”7. Why things will probably be okay—and what you need to do to prepare—Brought to you by:WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more: https://workos.com/lennyVanta—Automate compliance, manage risk, and accelerate trust with AI: https://vanta.com/lenny—Episode transcript: https://www.lennysnewsletter.com/p/a-rational-conversation-on-where—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Benedict Evans:• LinkedIn: https://www.linkedin.com/in/benedictevans• Newsletter: https://www.ben-evans.com/newsletter• Website: https://www.ben-evans.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Benedict Evans(02:19) What people aren't pricing in about AI's impact(06:24) Why we're in the 1997 moment of AI(09:44) The unexpected boom in professional services and consultants(17:44) Why distribution is becoming the ultimate moat(23:17) The coming job transformation: what's real vs. panic(27:33) Why AGI definitions keep shifting(38:11) Where value will accrue: models vs. applications(42:55) Distribution wars: Google, Meta, Apple, and OpenAI(48:12) The anti-AI sentiment and backlash(53:11) How to raise kids in an AI future(58:27) What jobs to steer toward or away from(59:20) The question nobody's asking about AI(1:06:25) How to be successful in this coming future(1:08:43) AI corner(1:11:43) Lightning round—Referenced: https://www.lennysnewsletter.com/p/a-rational-conversation-on-where—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Brad Carson was the Army's General Counsel, served two terms in Congress and was Acting Under Secretary of Defense for Personnel and Readiness. He now heads Americans for Responsible Innovation, the AI-policy advocacy group he co-founded. Keith Duggar spends roughly eighty minutes pushing back.SPONSOR:---Cyber Fund built the Monastery to help founders ship products that were impossible a year ago. Applications for Batch 1 are now open.Apply now: https://cyber.fund---Carson's whole case rests on one line: the genie is not out of the bottle. We have pulled dangerous tech back before. Asilomar halted recombinant DNA in 1975, and the West still controls the chips AI runs on. Calling it unstoppable, he says, is the most dangerous idea in the room.Then Keith drags him somewhere darker. A Palantir heat map scores you 0.73 on whether you are a combatant, and a strike follows. The model is wrong some accepted share of the time, and when it is, nobody answers for it. You cannot court-martial a model, and not even the interpretability researchers can say why it picked you.—Note: after recording, we learned that Americans for Responsible Innovation is backed by EA-aligned philanthropy (not sponsored)---TIMESTAMPS:00:00:00 From the Pentagon to AI governance00:04:52 Regulatory capture vs Silicon Valley networks00:07:56 Transparency and the Claude tier changes00:09:40 Tort liability when AI tools cause harm00:13:40 AI is a product, not a person00:16:01 Children, suicide, and the suicide business00:19:59 Opaque neural nets and the law of war00:25:54 Probabilistic targeting and the death of accountability00:28:47 The arms race fallacy: Asilomar and restraint00:34:02 Talking to China: track 2 talks and chip leverage00:39:45 Air power never wins: capital for labour00:43:29 Anthropic vs the Department of War00:51:29 Concentration, open source, and brain drain01:00:18 DeepSeek, Chinese culture, and AI as diplomacy01:12:25 Upskilling Congress and why public trust matters---REFERENCES:organization:[00:02:45] ICRC position on autonomous weaponshttps://www.icrc.org/en/law-and-policy/autonomous-weapons[00:05:22] Americans for Responsible Innovation (ARI)https://ari.us[00:07:20] Andreessen Horowitz (a16z)https://a16z.com/[01:16:05] Office of Technology Assessmenthttps://en.wikipedia.org/wiki/Office_of_Technology_Assessmentother:[00:03:35] Beneficial AGI 2019 Conference (Future of Life Institute, Puerto Rico)https://futureoflife.org/event/beneficial-agi-2019/[00:18:30] Section 230 of the Communications Decency Acthttps://en.wikipedia.org/wiki/Section_230[00:19:59] Lethal Autonomous Weapons (LAWS)https://en.wikipedia.org/wiki/Lethal_autonomous_weapon[00:31:35] Strategic Arms Limitation Talks (SALT)https://en.wikipedia.org/wiki/Strategic_Arms_Limitation_Talks[00:32:28] Asilomar Conference on Recombinant DNA (1975)https://en.wikipedia.org/wiki/Asilomar_Conference_on_Recombinant_DNA[00:39:45] The New Iron Triangle (ARI policy byte)https://ari.us/policy-bytes/the-new-iron-triangle/[00:48:05] Defense Production Acthttps://en.wikipedia.org/wiki/Defense_Production_Actperson:[00:03:35] Anthony Aguirrehttps://en.wikipedia.org/wiki/Anthony_Aguirre[00:06:48] Dean Ball — Hyperdimensionalhttps://www.hyperdimensional.co/[00:23:13] Neel Nanda — mechanistic interpretabilityhttps://www.neelnanda.io/[00:36:02] Jack Clark (Anthropic) on Conversations with Tylerhttps://conversationswithtyler.com/episodes/jack-clark/[00:39:15] Robert Trager — Centre for the Governance of AIhttps://www.governance.ai/team/robert-trager[00:41:55] Giulio Douhethttps://en.wikipedia.org/wiki/Giulio_Douhet[01:15:05] Don Beyer (US Congress)https://en.wikipedia.org/wiki/Don_Beyertool:[00:22:19] Phalanx CIWShttps://en.wikipedia.org/wiki/Phalanx_CIWS---ReScript:https://app.rescript.info/public/share/9405ff35c0215b7cdae6402d41284171https://app.rescript.info/api/public/sessions/0a6c081b8e5fe413/pdf

In episode 303 of Remarkable Retail, Steve Dennis and Michael LeBlanc deliver a sharp, fast-moving episode built around a single conviction from one of retail's most influential retailers: the future is people-led and tech-enabled. Chris Nicholas, former President & CEO of Sam's Club and now President & CEO of Walmart International — a global operation spanning 18 countries, 5,700 stores, and over 500,000 employees shares how humanity and technology are intertwined to drive growth. In this encore interview, Chris makes the case that retail innovation isn't about replacing people with technology. It's about using AI and digital tools to strip out friction, empower associates, and build better member experiences. Technology serves the human, not the other way around. Chris unpacks Sam's Club's nearly $90 billion membership-driven model and explains why the warehouse club sector keeps gaining momentum worldwide. He goes deep on the "club of the future" strategy — including the closely watched Grapevine, Texas location with computer vision-powered exits, Scan & Go checkout, AI-enabled shopping, and a radically redesigned store built around convenience, inspiration, and engagement. His core belief: consumers everywhere want the same things — value, convenience, innovation, and experiences that genuinely improve their lives. Before the interview, the hosts break down a blockbuster earnings week. Walmart posts another massive quarter, adding a staggering $18 billion in quarterly revenue while investing aggressively in price to hold share against inflation. Target delivers one of its strongest quarters in years, a sign its turnaround may finally be gaining traction. TJX proves resilient yet again as off-price rides the consumer "stampede to value." Home Depot and Lowe's, meanwhile, keep struggling in a sluggish housing and renovation market as higher rates squeeze big-ticket spending. The episode closes with Shein's surprising acquisition of Everlane — which Steve calls "where irony goes to die," given Everlane's brand built on radical transparency. Steve and Michael also dig into rising bond yields and the broader implications of AI legislation and the growing political clout of major technology investors like Andreessen Horowitz. Join us at the CommerceNext Growth Show in New York June 23rd and 24th with this exclusive discount code for 10% off general admission tickets and FREE retail tickets: Your code is "REMARKABLE" . See you in the Big Apple! About UsSteve Dennis is a strategic advisor and keynote speaker focused on growth and innovation, who has also been named one of the world's top retail influencers. He is the bestselling author of two books: Leaders Leap: Transforming Your Company at the Speed of Disruption and Remarkable Retail: How To Win & Keep Customers in the Age of Disruption. Steve regularly shares his insights in his role as a Forbes senior retail contributor and on social media.Michael LeBlanc is a senior retail advisor, keynote speaker and media entrepreneur. Michael has delivered keynotes, hosted fire-side discussions hosted senior retail executive on-stage in 1:1 interviews worldwide. Michael produces and hosts a network of leading retail trade podcasts, including The Remarkable Retail Podcast, The Voice of Retail The Food Professor, The FEED powered by Loblaw and the Global eCommerce Leaders podcast. He has been recognized by the NRF as a global Top Retail Voice for 2025 and 2025 and continues to be a ReThink Retail Top Retail Expert for the fifth year in a row.

Interactive social media site Status announced Tuesday $17 million in combined seed and Series A funding, with investors including General Catalyst, YC, LightShed Ventures, and Abstract. Also, Stilta announced Tuesday a $10 million seed round led by Andreessen Horowitz. Other investors in the round include YC and operators from companies like OpenAI, Legora, and Lovable. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Marc Andreessen is a co-founder and general partner at the venture capital firm Andreessen Horowitz, co-creator of the Mosaic internet browser and co-founder of Netscape, and author of “The Techno-Optimist Manifesto.”www.youtube.com/@a16zhttps://pmarca.substack.comhttps://a16z.com/the-techno-optimist-manifesto/www.a16z.com Perplexity: Download the app or ask Perplexity anything at https://pplx.ai/rogan. Great Coffee, Great Mission – Black Rifle Coffee is America's Coffee. Visit https://blackriflecoffee.com/joerogan today to get 30% off your next order. Learn more about your ad choices. Visit podcastchoices.com/adchoices

The AI narrative shifting… Jobs apocalypse? What jobs apocalypse!? Who said that was coming? There's been a noticeable shift from the AI titans recently. Turns out (shocker!) the world isn't responding well to being told we'll all be out of a job soon. And Silicon Valley is waking up to the fact that they need more popular support — both for the data centers they hope to build quickly and also for their upcoming IPOs. Meanwhile, the AI outrage is building. This week in AI anxiety: Students boo a commencement speaker who mentioned AIGallup reports that 71% of Americans are opposed to new data centers (with 48% “strongly opposed”)Meta employees are miserable as another round of (AI-driven, so they say) layoffs approachThis week in trying to change the narrative: Andreessen Horowitz publishes “The ‘AI Job Apocalypse' Is a Complete Fantasy” and explains why the “the claim that AI will produce economy-wide, permanent unemployment is unhelpful marketing, bad economics, and worse history.” And I find it very instructive that this list (and every list is an ordered list whether you admit it or not) begins with the concern that this is “unhelpful marketing.” (To the piece's credit, it gets pretty wonky with charts and graphs from there.)Meanwhile, you know what's helpful to marketing? Spending a gazillion dollars to get your message out. To wit: The New York Times reports that Andreessen Horowitz is the biggest spender so far in this midterm election cycle, spending $115M to promote AI, crypto, and other founder-friendly initiatives. OK, so these pieces of data and “anecdata” are the jumping off point for this week's “FAFO Friday.” Enjoy! Support Future Around & Find OutFollow Dan on LinkedInGet the free newsletterBecome a paid subscriber and help future proof FAFO!---Music by Jonathan Zalben

Kara and Scott unpack what AI obsession is doing to relationships and young men. Then, they break down Trump's China summit, the crew of business executives he brought along, and ominous warnings from Xi Jinping about Taiwan. Plus, Sam Altman testifies in the Elon Musk–OpenAI trial, inflation surges, and Andreessen Horowitz becomes the biggest donor of the midterms. Also, Anthropic eyes a valuation higher than OpenAI's, and Google explores orbital data centers with SpaceX. Watch this episode on the ⁠⁠Pivot YouTube channel⁠⁠.Follow us on Instagram and Threads at ⁠⁠@pivotpodcastofficial⁠⁠.Follow us on Bluesky at ⁠⁠@pivotpod.bsky.social⁠⁠Follow us on TikTok at ⁠⁠@pivotpodcast⁠⁠.Send us your questions by calling us at 855-51-PIVOT, or email pivot@voxmedia.com Learn more about your ad choices. Visit podcastchoices.com/adchoices

Grab your favorite beverage for a special, highly opinionated "just us girls" episode of the podcast, featuring Joel Cheesman and Maureen “Moe” Clough taking the mic without the rest of the usual crew. This week, the duo delivers a light-hearted yet deeply substantive look into the massive worker backlash against artificial intelligence and the brutal realities of today's hiring market. The hosts kick things off with quick hits covering a disastrous, heavily booed commencement speech at the University of Central Florida and a surprising take on the narrative depth of The Devil Wears Prada 2. From there, the conversation tackles major industry shifts as massive job platforms like Upwork and ZipRecruiter face severe financial softening, sparking a debate on whether automation is permanently consuming traditional contractor roles. The gloves come off as they dissect a bold claim from Andreessen Horowitz labeling legacy HR software giants like Workday a "cartel," while analyzing how defensive tech acquisitions—such as Ashby buying Talent Llama—signal a broader software-as-a-service apocalypse. Moe offers her expertise on age discrimination, discussing a lawsuit against Bloomberg Industry Group. The discussion moves to the backlash against automated hiring tools and LinkedIn's new paid consultation feature. Finally, there is a disagreement over Google's new Gemini-powered smart glasses. Chapters 00:00 - Introduction to the Podcast and Hosts 01:35 - Current Events and AI's Impact 05:30 - AI and the Youth Perspective 10:01 - Data Centers and Community Impact16:31Industry News: Upwork, ZipRecruiter, and Workday 19:59 - The Future of Work and AI's Role 22:00 - The SaaS Cartel and Its Challenges 25:02 - Age Discrimination in the Workplace 34:56 - AI's Role in Hiring and Recruitment 42:21 - The Rapid Evolution of AI in Hiring 45:04 - LinkedIn's New Monetization Features 52:51 - The Controversy of Smart Glasses 01:03:01 - The Inevitable Rise of Smart Technology

In this episode, we unpack Cerebras Systems' blockbuster IPO and how it may reignite momentum across the AI infrastructure trade. We also discuss the macro backdrop shaping risk assets, including speculation around the new Federal Reserve chair, hotter-than-expected inflation data, alongside resilient labor markets, and what it could mean for digital assets and broader growth markets. Further, we cover growing legislative momentum behind the Digital Asset Market Clarity Act, the sharp rise of privacy-focused token Xcoin, and renewed venture appetite as firms including Haun Ventures and Andreessen Horowitz raise billions in fresh digital asset-focused capital. Remember to Stay Current! To learn more, visit us on the web at https://www.morgancreekcap.com/morgan-creek-digital/. To speak to a team member or sign up for additional content, please email mcdigital@morgancreekcap.com Legal Disclaimer This podcast is for informational purposes only and should not be construed as investment advice or a solicitation for the sale of any security, advisory, or other service. Investments related to the themes and ideas discussed may be owned by funds managed by the host and podcast guests. Any conflicts mentioned by the host are subject to change. Listeners should consult their personal financial advisors before making any investment decisions.

Special discounts up for AIE Melbourne (LS discount) and AIE World's Fair (group discounts up to 25% - CFPs still open for Autoresearch and Vertical AI) Cya there!Abridge did not start as an “GPT wrapper”. It was founded in 2018, years before the Cambrian explosion of AI application layer companies. OpenAI launched ChatGPT publicly on November 30, 2022 and by then, Abridge had already spent years doing the unglamorous work of building trust for one of the highest context, most important workflows in healthcare: the conversation between a patient and a clinician.Abridge's original wedge was clinical documentation. Listen to the visit, generate the note, reduce the clerical burden, and let clinicians spend more time with patients instead of the EHR. By focusing on how doctors actually document, how health systems actually buy, how EHR integration actually works, how clinicians verify outputs, and how missing context during a visit turns into downstream friction across billing, prior authorization, quality, and follow-up, the adoption of LLMs became a force multiplier on a workflow already optimized for sensitive context gathering.The company has scaled fast: Abridge says it is projected to support 80M+ patient-clinician conversations this year across 250 large and complex U.S. health systems, with support for 28+ languages and 50+ specialties. It raised $300M at a $5.3B valuation in June 2025, after a $250M round earlier that year.Today, Janie Lee and Chaitanya “Chai” Asawa of Abridge join us for another crossover pod with Redpoint's Jacob Effron (who is on the board of Abridge) to dive into how Abridge is building the clinical intelligence layer for healthcare starting with ambient documentation, then expanding into clinical decision support, prior authorization, payer/provider/pharma workflows, and eventually real-time agents that act before, during, and after the patient conversation. We go inside the product, data, infra, evals, workflow, privacy, and org design choices behind bringing AI into one of the highest-stakes enterprise environments from 100M+ medical conversations and specialty-specific evals to real-time alerts, EHR integration, de-identification, clinician-scientist teams, and why healthcare may solve some of the hardest AI problems first.We discuss:* Why Abridge started with clinical documentation, “pajama time,” and saving clinicians 10–20 hours a week* The transition from ambient scribe to clinical intelligence layer: save time, save money, and save lives* Why conversations between patients and clinicians may be the most important workflow in healthcare (patient visit summary feature)* Chai's “healthcare-coded Glean” framing: context is king, but healthcare raises the stakes on safety, evals, and rollout* Why Abridge wants AI to feel like “air conditioning”: always in the background, but only interrupting when it truly matters* The prior authorization example: turning a denied MRI weeks later into real-time guidance while the patient is still in the room* Why payer policies, EHR data, medical literature, and hospital-specific guidelines make the problem hard, and also create the moat* How Abridge thinks about ambient form factors: mobile, desktop, in-room devices, nursing workflows, multimodality, and future AR* The multi-sided healthcare customer: CMIOs, CFOs, CIOs, clinicians, patients, payers, and pharma* The hardest AI problem at Abridge: high-quality, low-latency, low-cost real-time support in a high-stakes clinical setting* When Abridge uses frontier models vs proprietary models, and why its unique data from medical conversations matters* Why “every agent is a coding agent underneath,” and how the EHR can be thought of as a filesystem for healthcare agents* How Abridge approaches personalization across individual doctors, specialties, and health systems* Why “AI slop” is AI without context, and how edits, memories, and clinician preferences create a data flywheel* Abridge's eval stack: LFDs, LLM judges, in-house clinicians, third-party evaluators, specialty-specific evals, and progressive rollout* HIPAA, PHI, de-identification, one-way anonymization, customer contracts, and learning from healthcare data safely* What changes when you operate at 100M+ conversations: reliability, cost, post-training, model routing, and infrastructure optimization* Why the same clinical conversation can serve doctors, patients, payers, pharma, and future clinical-trial workflows* How Abridge works with EHRs, and why deep interoperability is table stakes for clinician adoption* Why healthcare AI has regulatory tailwinds, why 80/20 does not work here, and why high-stakes domains may drive AI forward* Why Abridge embeds “clinician scientists” into product and eval teams* What Chai learned from Glean about search, quality, and durable AI infrastructure* Why the future of AI infra may look like context layers, event-driven systems, Kafka, Temporal, sockets, CRDTs, and tools built for humans* Why Janie changed her mind on “PRDs are dead,” and why crisp written clarity matters more in complex AI products* How Abridge uses Claude Code, Cursor, and coding agents internallyAbridge:* Website: https://www.abridge.com/* X: https://x.com/AbridgeHQJanie Lee:* LinkedIn: https://www.linkedin.com/in/janiejleeChaitanya “Chai” Asawa:* LinkedIn: https://www.linkedin.com/in/casawaTimestamps00:00:00 Introduction and what Abridge does00:02:05 From ambient documentation to clinical intelligence00:04:04 Clinical decision support and context as king00:06:57 Alert fatigue, proactive intelligence, and prior authorization00:12:36 Ambient AI form factors and healthcare customers00:16:59 The hardest AI problems in healthcare00:18:26 Frontier models, proprietary data, and model strategy00:21:07 The EHR as a filesystem for agents00:24:03 Personalization, memory, and clinician preferences00:30:40 Evals, LLM judges, and progressive rollout00:36:47 HIPAA, de-identification, and privacy00:39:21 100M conversations and operating at scale00:44:10 EHR integration and the clinical intelligence layer00:46:39 Healthcare regulation, latency, and high-stakes AI00:50:11 Clinician scientists and long-tail quality00:53:04 Lessons from Glean and durable AI infrastructure00:57:03 The future of agentic healthcare workflows00:57:34 PRDs, product clarity, and building serious AI products01:03:11 AI coding tools at Abridge01:04:06 OutroTranscriptIntroduction: Abridge, Clinical Intelligence, and the Latent Space x Unsupervised Learning CrossoverSwyx [00:00:00]: Okay. This is a special crossover Latent Space Unsupervised Learning pod.Jacob [00:00:07]: Very excited to do this.Jacob [00:00:08]: At this point, we get together once a year.Swyx [00:00:10]: Once a yearJacob [00:00:11]: And this is a fun occasion to get to do it on.Swyx [00:00:13]: I really wanted to talk to Abridge but I felt very underqualified because healthcare is not something we cover very intensely. It just so happens that Redpoint's our big investors and supporters of Abridge.Jacob [00:00:27]: Anytime you want to have a portfolio company on your podcastJacob [00:00:29]: Please, by all means.Swyx [00:00:31]: So we'll introduce our guests. Chai and Janie, welcome to the pod.Janie [00:00:34]: Thanks for having us.Chai [00:00:35]: Thank you.Janie [00:00:35]: We're excited to be here.Chai [00:00:36]: Thank you.Swyx [00:00:36]: So for listeners, what do you guys do, just to situate you guys in the company?Janie [00:00:42]: Abridge is a clinical intelligence layer for health systems. We really started with documentation and building for clinicians and as we think about reducing the burden that clinicians have, they're spending 10 to 20 hours a week on documentation. There's a massive doctor shortage in the country. We also think that conversations between patients and clinicians are probably the most important workflow in healthcare. It's where care is given and received but if you think about the 20% of our GDP that goes towards healthcare, almost everything is a derivative of that conversation, whether it's the claim, the payment, the actual diagnosis given, the treatment. And we've started with a conversation to reduce the burden for doctors on documentation but we're really excited about the path ahead as we become this broader clinical intelligence layer.Chai [00:01:34]: I'm Chai. I work on clinical decision support at Abridge.Swyx [00:01:37]: Yes.Chai [00:01:37]: And so as Janie said, we're uniquely situated where we started off with the clinical note. What I'm really excited about and where we're expanding towards is what are all the things you can do before the conversation, during the conversation and after the conversation if you did have access to all the context about patients, payer guidelines, medical literature and put that together and to serve, how healthcare could look fundamentally different.Swyx [00:02:01]: And that's the context engine that you guys have?Chai [00:02:04]: Yes.Swyx [00:02:04]: Is that what it's called? Okay.Swyx [00:02:05]: So historically, as I understand it, the company started in 2018. A lot of people would be familiar with the AI voice notes form factor that doctors would be “Well, do you consent to being recorded?” It replaces handwriting and what have you. But it sounds like more recently there's been a big transition in the company. Tell me about the broader transition.From Documentation to Clinical Intelligence: Save Time, Save Money, Save LivesJanie [00:02:26]: So from a transition perspective, we really think about our journey as The first act was: how do we help save time? And that's where a lot of that original product was.Swyx [00:02:37]: By the way, one of those interesting statsSwyx [00:02:39]: On your landing page was, doctors spend time after hours.Janie [00:02:43]: They call it pajama time.Swyx [00:02:44]: Why is that pajama time?Janie [00:02:46]: Doctors after work in their pajamasSwyx [00:02:48]: In their pajamas. OhJanie [00:02:49]: At home are just writing and catching up on their notes every day.Janie [00:02:53]: Some of our favorite customer love stories, we have a Slack channel called Love Stories. We have clinicians telling us, “Abridge has helped us, from retiring early or we're now finally able toJanie [00:03:06]: go home and eat dinner with our kids for the first time.”Chai [00:03:08]: Save the marriage in some cases.Swyx [00:03:10]: One of the quotes was “We're not divorcing anymore.”Swyx [00:03:12]: I'm asking, “Why?”Swyx [00:03:14]: Because they're working too much.Janie [00:03:16]: But, in terms of where we're going and where we're expanding, we really think about our second and third acts around how do we help health systems save and make more money. Health systems are operating with record-low operating margins. It's getting harder and harder to serve patients and they have regulatory, some tailwinds but also a lot of headwinds coming their way and AI is ripe for helping on the saving and make-more-money piece. And then ultimately, how do we help save lives? The fact that our software and our product is open millions of times a week before, during and after a patient walks in the room, gives us massive opportunity with products like clinical decision support, which Chai is building but so many others to improve patient outcomes and probably one of the most important workflows and problems to be going after right now.From Glean to Healthcare: Context Is KingJacob [00:04:04]: One thing that's interesting, Chai, is you came over to Abridge from Glean and clinical decision support, which for our listeners is, in the context of a visit, helping a doctor figure out the right type of care. It's really a search problem in many ways, going through lots of different data sources. Very analogous to your previous role as one of the earliest engineers over at Glean. I'm sure a lot of our listeners are curious what's similar about the problems that you're going after now and what feels different, now that you're in healthcare.Chai [00:04:33]: Very similar. Taking a step back, with every wave, there's a lot of very similar patterns that happen across different products. A lot of social networking products look the same. A lot of credit-based products look the same. And we're seeing that very similar in the agent era with many companies, of course, in Redpoint's portfolio and so forth. And the key insight between both companies is that you have amazing models but context is king. Context is what puts them to work. So I see it in a lot of ways, a lot of similarities in this is a healthcare-coded version of Glean but the differences are really interesting. A couple things that come to mind. First and foremost, the rigor of the setting we're in. The downside risk is extremely high here in healthcare. It can be fatal in some cases. You prescribe something that the patient is allergic to for example. Whereas at Glean, it's “Oh, you got the question wrong.” It wasn't the end of the world in most cases. And so what does that mean? That shapes our evaluation strategy, both offline evaluation, progressive rollout and there's a lot more we could go into there. Second thing that comes to mind is, vertical versus horizontal. In both cases, there's a large variance but when Glean is, it's a much more horizontal company, there's a variance of personas, companies that you're working with. We also have a variance of personas, different types of specialties, different hospital systems. But the variance is a little more narrow. So from a product perspective, you're able to focus far more, especially when you have a maturing technology and you're building new products that never existed before. It lets you go after them much more easily and especially in healthcare where so many problems were solved with labor and process, that it's extremely ripe for AI to keep helping augment and enable. And the final thing that's really interesting, Abridge specifically compared to many other companies in the AI area, is the modality we started with where we're ambient and we're always listening in the background. And many more AI products will go that way but it's how we started. And that's the greatest form of AI we can create, AI that's seamless. You're not looking at your screen. It's always there. It's always helping you out and being proactive. The Jarvis vision that, every hackathon I went to over the past decade, there was always a Jarvis competitor. But Abridge very much started from the opportunity and continues to go that way.Ambient AI and Alert Fatigue: When Should the Product Interrupt?Jacob [00:06:57]: One thing that is super interesting then from a product perspective is you have this always-on seamless in the background and then you have to decide when you break the wall almost and say, “Hey, clinician, you might not have thought about X,” or whatever it is that you want to do. And in healthcare traditionally there's been this idea of alert fatigue and a million pop-ups and then a doctor just ignores all of them. It's probably a pattern that a lot of builders are thinking through now. How do you think about the right way to intervene or to pop up in a doctor visit?Janie [00:07:26]: It's such a good question. Alerts are notorious in healthcare specifically. Over 90% of alerts are ignored. The first and most important thing is context is everything, as Chai alluded to and I also think about how do we go from being reactive alerting to really proactive intelligence at the point at which it matters most. One thing we like to say is we want our product to feel like air conditioning. It should be in the background just making things better and if there is something that has great clinical risk and we're acutely aware that intervening now and not later is incredibly important, we should decide to act. But if you think about proactive versus reactive, instead of alerting a clinician during a visit when they're with their patient having a pretty serious and sensitive conversation, how do we prep a clinician before they walk into the room with that patient? And so historically, clinicians might have to manually go through charts with a patient that they've had over the course of months or years and they'll try to suss out what are the things they should be doing. You can imagine a world with Abridge. We'll summarize all of the most recent context for you, tell you based on the reason for a visit the patient is coming in for the types of things you should be discussing. And so you're going into that conversation prepped rather than walking in cold to that patient visit and then having this product interrupt you five or 10 times throughout the visit. And there might be times where it's really important to interrupt. We have a product called Prior Authorization and so this is when you may go into a doctor's office with knee pain. They'll prescribe you an MRI and so many of us have had this experience before, where in four weeks you'll get a call saying, “Hey, Sean, that MRI that you were prescribed wasn't approved and why don't you come back in? We'll figure it out.” In a world with Abridge, we might choose to quietly but still alert a doctor in that visit. And alert is probably not even the word we would want to use. Before a patient leaves, we would want to tell the doctor, “Hey, Doctor, before Sean leaves, you should ask him, has he had physical therapy and has his pain lasted for more than six weeks? Because the Aetna plan that he's on in California requires six things. We've already confirmed four of them have been met ‘cause we have all the context. But these two last criteria, if you can address with Sean before he leaves the room, we could guarantee that your MRI is approved before you leave.” And so when you think about clinical usefulness, impact to the patient, there are instances in which if we can catch a doctor while the patient is still in the room, as we think about save time, save money, save lives, we get to check all of those boxes. But when doctors have 15 minutes between visits, we have to be really thoughtful about when it matters.Prior Authorization: Reducing Latency in CareChai [00:10:23]: There's this interesting product opportunity AI has is reducing latency in the world. For example, prior authorization is an example of where care gets delayed and so great AI can reduce that. And the problem with alerts before partially is a technical problem: the quality of your alerts really matters. They're going to get ignored if you get alerts that... Similarly in engineering, where they're noisy alerts that you can't act on. But if you can make really high-quality alerts with both the context, as Janie said, and really high-quality models, then you can create a whole other game.Janie [00:10:53]: And I really like that experience because it starts to tease apart, what makes this so hard and unique. One, to make that prior authorization example possible, think about all the data that you need to have. You need to integrate with the electronic health record to know all of the patient context. Do we have access to your previous labs, previous imaging? And then to match you and to know that you're on Aetna, we have to collect all of the different payer policies and they vary by state. Some of these payer policies live on websites. Some of them live in unstructured 50-page PDF files.Jacob [00:11:31]: I thought this episode wasJacob [00:11:31]: To make sure we didn't scare people from healthcare.Janie [00:11:34]: But when you think about the things that make it hard, it also gives you the moat.Janie [00:11:39]: And then the second is the AI and the model quality we need to be able to hang our hat on. And so the bar, similarly when I worked at Opendoor, I worked on pricing models. Every outlier wiped out the margins of 30 and so similarly here in healthcare, the bar for accuracy is so high. And then I'd say the last is workflow is everything. If insurance companies deploy AI, it typically happens too late and this is when you have the notorious comical examples of AI just fighting each other when it's too late. But if we can pull forward the use of both the AI but also the ability to solve problems when the patient's in the room, you can start to collapse what typically takes weeks or months after your visit, ideally down to minutes or real-time. And it's where healthcare is both very difficult but also extremely rewarding if you can crack it.Product Form Factors: Mobile, Desktop, In-Room Devices, and ARSwyx [00:12:36]: Just to get some baseline on the form factors, because I've seen some videos on your website and stuff. You guys talk a lot about ambient AI. Is it primarily on the phone? Is there any other form factor that people get Abridge in? Is there an Abridge room setup where it's always on? I don't know.Jacob [00:12:55]: An Abridge podcast studio.Janie [00:12:58]: Primary form factor is mobile and desktop. UsuallyJanie [00:13:00]: Clinicians are walking in and out of rooms with mobile but at the end of the day, when they're closing out their notes or wanting to prep for the day ahead, they might use desktop. We have been having a lot of really interesting partnership conversations with a lot of these in-room device companies as you think about the power of multimodality and even more data, as you think about all of what is not captured today. It is fascinating to think about, especially even as we go into building and scaling our nursing product. It's one where nurses constantly, as they're walking in to check in on a patient for two minutes or maybe even 30 seconds,Janie [00:13:43]: Starting an Abridge experience is probably going to take longer than the visit. And so what can we do with in-room devices that are always on starts to raise really interesting and fun product questions.Swyx [00:13:54]: I was thinking, the way in tech companies we have all these Google MeetSwyx [00:13:58]: And other things, we might as well set up entire rooms with just Abridge tech.Chai [00:14:02]: Very much. AR glasses and related form factors are also relevant: how do we bring the information to the clinician in real-time without a screen, while still letting them focus on the patient?Swyx [00:14:18]: Do you think they want that? I'm skeptical of AR, but I'm curious what you've tried.Chai [00:14:26]: Admittedly, it's not a near-term product roadmapChai [00:14:29]: By any means. I'm being far-fetched.Jacob [00:14:31]: There's some sick AR stuff for surgeries.Swyx [00:14:33]: Really?Jacob [00:14:33]: When people are trying to visualize, you're about to make an incision but you want to see, what the cut might look or what the body might look like inside and they can layer in imaging.Swyx [00:14:43]: That's cool.Chai [00:14:45]: At some point in the future.Janie [00:14:46]: But there are a lot of our largest customers and at the largest health systems integrating already and so even as we think about building into it, unlocks a lot of product capabilities.Swyx [00:14:57]: And just to establish the terminology. Sorry, and I know I'm asking basic questions somewhat for myself but also for the audience who might beHealth Systems, Buyers, Clinicians, Patients, and PayersSwyx [00:15:05]: Less integrated. When you say health systems, it's like the Johns Hopkins, the Kaiser Permanentes.Janie [00:15:09]: Mayos, the Kaisers of the world.Swyx [00:15:10]: These are your customers, right? And the outcome that you deliver for them is happier doctors, reduced cost of processing, reduced mistakes. It's weird in a sense that I feel like there's also, a secondary customer, the customer of the customer and I don't know if you — do you think about it that way?Janie [00:15:28]: The other interesting and complex part of building product is we have our buyers, who are the chief medical information officersJanie [00:15:39]: The chief financial officers, the CIOs of these large health systems. Our users today are clinicians but if you think about who downstream is impacted, it's patients. And so as we build, with every product in mind, we think about who we're building for, who the secondary user is and what does that mean either in terms of experience, security compliance, ROI that we have to make tangible. And so like you said, time savings is one of them. But for CFOs, they care a lot more than just time savings. We have to show for every dollar you put into Abridge, because you have more compliant documentation or because you have fewer queries coming from your billing team, we save or add real dollars to your bottom line or top line, are things that we're constantly thinking about because of the dynamic across all three sets of users.Chai [00:16:32]: There's a whole other axis too with the payers and pharmaChai [00:16:35]: as well. Connecting all these three big stakeholders in healthcare isSwyx [00:16:39]: Do the payers ever see your data? Sorry, the payers meaning the insurers, right?Chai [00:16:44]: Yes.Swyx [00:16:44]: They also see Abridge data?Chai [00:16:47]: NoSwyx [00:16:47]: Like the direct integration to you guysChai [00:16:48]: They wouldn't see the raw Abridge data but when you're working together on something like prior authorization, whatever information they need, we'd communicate to them.Jacob [00:16:59]: That's cool. I would love to dig into the AI side. You still have a lot of problems on the AI side. And so maybe to start at the highest level, what's one of the hardest problems you have to solve in AI at Abridge today?The Hardest AI Problems: Quality, Latency, and CostChai [00:17:11]: To make things simple, let's take, building off the prior auth example. So one thing Janie talked about is okay, this data is all over the place and there's this combinatorial explosion of procedures, payer policies and even sometimes different health systems. There can be some cross-product of all of these different considerations you have to take into account. But what's really hard about this problem is doing it real-time in the conversation. So, in any AI product, usually the three KPIs you care about are quality, latency and cost. Now, what we're saying is we want you to do this real-time in the conversation, guiding the clinician. How do we do it in a way that does not break the bank? But we're using — But we also need very intelligent models because you're working with this cross-product of data and this, all this context layer as well. So you need high intelligence and high-quality because you don't want the alert fatigue but you also need to be fast and cost-effective. And so that's where a lot of clever engineering goes. It's okay, without getting into all the details here, can you model these policies in some intermediate representation or other things that you can do that can make this problem tractable? And of course, the Pareto frontier is always changing but we are also trying to do this now.Model Strategy: Third-Party Models, Proprietary Data, and Medical ConversationsJacob [00:18:26]: What implications has that had for what you take off-the-shelf and say, “ what? We don't need to be world-class at X. We'll just take this from the model providers or from some infrastructure player,” and what you're “No, this is where we spend most of our time focused on”?Chai [00:18:38]: This is, the fun challenge in AI?Jacob [00:18:42]: It changes every three months? SoChai [00:18:42]: Of course, with the shifting landscape, we try to be extremely thoughtful on predicting the trends of where third-party models are going and where we can uniquely go. And, sometimes when you talk about AI models, we're the models are just going to get infinitely better. But I don't think... It may be in the grandness of time you could say that but, within every month, every quarter, there's specific ways they're getting better. They're training on a lot more, coding data to be better coding agents, for example. And soChai [00:19:14]: We have to think about where are the things that won't — unique data that we're uniquely training on or to step back a little, where is a proprietary model bringing advantage to us is if it can give higher quality or lower cost and latency for similar quality, very similar to many other companies. And when we can do that is when we have proprietary data. So, for example, we have on the order of eighty million or hundreds of millions now getting close to of medical conversations.Jacob [00:19:44]: It's insane.Chai [00:19:45]: This is a unique data set. And this data set, it's very interesting because this data set is effectively a large part of the trace between the patient and the provider. That's where the quote-unquote debugging happens in healthcare. We have these traces at scale, as in as, our CEOs even called it, an exhaust that comes out of our product. And so when you have these traces, that's how you can train better agents on certain use cases, whether it's your transcription diarization use cases or so on or like note generation models and we can do that much cheaper and faster. But we're always also working with these third-party model providers. We closely collaborate with them and that's how we predict where the trends are going. The thing that I think about a lot is that, I know that the model providers are going to train much more on agentic workflows and so forth, so that's great, so that you have a better agentic harness. But the other thing that's interesting is that the model providers, because a large class of the consumer model providers is healthcare queries, that they might, optimize to train a lot of healthcare data to encode the knowledge in its weights. And this is just a great thing for us as well, where the off-the-shelf models can keep bett-getting better at general healthcare information, such that what our strategy is, we have a constellation of models, we can use something for this, that and, we only care about, at the end of the day, the best product experience.EHR as File System: Agentic Workflows and Real-Time InterfacesJacob [00:21:07]: And, you have, overall capabilities improving. I'm curious, as these models get better, is there something you look at and you're “, three months ago, we really couldn't do that but God, the the latest models really allow us to do it”?Chai [00:21:19]: So here's something interesting that I've, been toying with. So all models are... This wasn't super obvious a year ago but now it's become clear and clear that almost every agent is a coding agent underneath the hood? So you give it whatever file system, it can write its own code and so forth. So when you think about within healthcare and the use case that we have, you can think of the EHR effectively like a file system. It's just — it's a storage of all this information. It's a lot of information there that cannot fit into the context window, at least of today's models and you want to use that context effectively for all these product use cases we're talking about. And so if you have better agents that can, manipulate data, read that data, treat it as a file system as we see they're going and we know model companies are investing this way, then that very directly benefits us.Swyx [00:22:09]: Yeah. Okay, cool. Again, just establishing basic things. But we're going back to the model stuff. I'm really interested in double-clicking more on the real-time, element, which is pretty important for both of you. Is it — Is real-time just batches of every one minute, every five minutes? Is that how we do it? Or is there some more native, genuinely real-time in the sense that OpenAI has a real-time API or Gemini has a real-time API?Chai [00:22:35]: Yeah. Yeah. So today it is more on the on the batch basis but there's interestingChai [00:22:41]: Prototypes that we have that we're still not fully, full time, voice in text out or in that sense. But, can you trigger your models, your agents or agentic workflows, depending on the right times in the conversation?Chai [00:22:58]: And so you can imagine, different techniques to bring this latency down and, you want to bring the feedback loop down as much as you can. And so a lot of clever engineering there without fully... Maybe one day we'll do full voice in and text out, train a model to do something like that.Swyx [00:23:15]: You do — People don't want voice in voice out?Chai [00:23:18]: Now we aren't creating experiences that are, during the conversation, inter — It's almost likeSwyx [00:23:25]: Might be too disruptiveChai [00:23:26]: Too disruptive until, who knows, maybe eventually you could have full voice agents once we — the quality and we improve the comfort of the technology. But right now gra — that change is much more gradual and it's more text focus, text out.Janie [00:23:42]: And so much of currently what our product is trying to do is allow a clinician to focus on their patient and maybe at some point but right now patients, clinicians don't want a third voice, at least in a literal voice in that room. And so how do we be there with all the contacts and information ready at hand when there's the right moment?Personalization: Individual Doctors, Specialties, and Health SystemsJacob [00:24:03]: Jenny, one thing I'm curious about is how you think about, personalization in the product. I imagine, every doctor is a special snowflake in their own way, has their own way they like to do things. There are probably a bunch of different approaches you could take to doing that, both within the model layer itself but then also just with clever prompting or engineering. How do youJacob [00:24:20]: Deliver on that?Janie [00:24:21]: It's such a good question. Personalization is massive for us. We think about personalization at three levels. The first is at the individual, the second is at the specialty level and then the third is at the health system or the organization level. To your point, there are a lot of individual preferences. You-When a note is produced, it almost is a reflection that is so deeply personal of a doctor's work and how they give care. And so do they have preferences on things like style? They might want bullets versus paragraphs, really concise versus comprehensive. They also might have phrases that they really like to use or the templates that they want every note to be structured. And, we see it in our feedback all the time. We want two spaces in between sentences or I refuse to use this tool. And so that's something that we've had to build in. And the tricky part is how do you make sure that stylistic preferences don't interrupt accuracy and quality and that's something that we've really had to refine and hone over time. Second is at the specialty level. A cardiologist note or workflow is going to look very different from a dermatologist workflow.Jacob [00:25:32]: I assume cardiology notes are the highest stakes for you guys, given your CEO is a cardiologist.Jacob [00:25:36]: It's “Oh my God, make sure we get this one.”Janie [00:25:37]: Shiv, our CEO, is still a practicing cardiologist. He rounds once a month. And so, first call when we want just quick and easy user feedback too.Janie [00:25:46]: But, specialties require a lot of personalization, both in terms of what does the product look and so we make sure that as new users onboard, we catch that and the product proportionally reflects that. But also on the back end, evals at the specialty level, they are hard-earned to calibrate and get. What does a really great dermatology note look like? What makes it complete? What makes it compliant and billable is very different than a primary care doctor. And so it's not just about what does the product experience look but on the back end tuning and really deepening our understanding for the specialists. What does great output look like? And that's, a problem that we need to calibrate internally, externally, online, offline but, takes lots of cycles but is necessary in a high-stakes environment. And then at the health system level, for products like clinical decision support, you have health systems who've spent years or decades refining their best practices and they want to know, “Hey, we love your clinical decision support product but how do we embed our own hospital guidelines into them to inform clinicians before, during or after a visit what brest — best practices should look like?” And as you think about, deepening moats as well, when health systems, trust us with that data, allow us to productize it and directly into the clinical workflow, makes us a really great partner to health systems who want to build something that truly meets their needs, their practicing guidelines.AI Slop, Memory, and Product Data FlywheelsChai [00:27:23]: And I want to add onto that. The for the clinical documentation problem, it's very similar to AI writing that doesn't feel like your own and then we call that slop. But the way I describe one framing of slop is like AI without context. But we have all that context and both the clinicians, can have it and can guide it. And so part of the other interesting exhaust for us is, memory is, one of these new systems recordsChai [00:27:49]: Almost.Janie [00:27:50]: And we also have all the edits people make on our product and when you think about a data flywheel and how we get better over time becomes really powerful as a mechanism to just going deeper in personalization.Jacob [00:28:04]: It's interesting. I love this idea of working with systems on the guidelines they built up over a long time. I feel like so many of the best AI app companies today are... The question is: How do you take the expertise that a law firm or a bank has built up over many years and then add that as context and also a special sauce over, a an AI tool? And so seems like y'all are really doing that very effectively.Janie [00:28:24]: We're now starting to have our customers ask, “What are other customers doing?”Janie [00:28:28]: “And how are they doing it?”Janie [00:28:30]: And as we think about having visibility across such a large set of care being delivered right now, a really interesting place we could also partner.Swyx [00:28:40]: I'm just curious. I — This may be a nothing question but, how different are health system guidelines from each other? Don't they all converge to the same thing? And if not, where do they differ?Chai [00:28:52]: At a really high level, they're going to talk about very similar things but the difference is probably in some more of the details. “Oh, you should refer to specialists only when XYZ conditions are met,” or so forth and maybe different organizations have different practices and guidelines around that. But high level, talking about similar things but the details are what, of course, that shapes the context and the decisions you make.Swyx [00:29:15]: And this all goes into the context engine and it might affect the notes but maybe not.Chai [00:29:21]: The — For these local pathways, we're definitely thinking about it a little more for our clinical decision support product.Chai [00:29:26]: So yeah.Swyx [00:29:27]: Which is your stuff, yeah.Swyx [00:29:28]: And then the memory which you raised, let's just tell us more about that. What have you tried in memory? What's the structure of the memory? What works? What doesn't work?Chai [00:29:38]: There's, of course, many different ways you could do memory, where it's okay, can you bake it into the model weights or can you do it in some external store? For us, what's interesting is, of course, when you think the models are rapidly changing, whether it's in-house or third-party, baking into the model weights, sometimes you worry that it could be a little throwaway. And so, how do you... You need to find a way that you decompose the problem, the preferences from the underlying models and so forth. The thing we're right now most both that's easiest to start with and we're excited about is having, a separate store for memory, where you have, for example, a memory sub-agent that's, working in the background, figuring out what are the important parts of the clinician's actions that we want to remember for the long term. And then you can also imagine, other things where in the — you have background jobs that are running that are collating these, memories similar to Sleep, of course and what other pattern, patterns products do as well. Learning over all these action, all the action data we have, again, note edits, the conversations they did and the actual transcripts.Evals: LFD, LLM Judges, and Clinical SafetyJacob [00:30:40]: What about evals? How in the world do you... It is such a complex product surface area. We would love to hear you riff on that and also how has that evolved? I'm sure you've gotten better at it, so any learnings along the way.Janie [00:30:50]: From an evals perspective, we, from day one when we build any new product or feature, we think about, what does good look like? And there are table stakes things like clinical safety but then you start to get deeper into what does good quality look like. And when you go into something like our core product, there's stuff like style and completeness and there's things like does this note become something that can be billable, which is very high stakes for a health system. We have a number of ways in which we get confidence for this. We have, internal in-house clinicians who do what we call an LFD process to give us our very first pass at is this or isn't this a good enough output, look at the effing data.Jacob [00:31:41]: LFD?Chai [00:31:42]: That's why I was smiling. I was “Is Janie going to mention what it stands for?”Jacob [00:31:46]: I was not... There's like a million acronyms.Jacob [00:31:48]: How am I supposed to know that I don't? So “Oh yeah, of course, an LFD.”Swyx [00:31:51]: I've never heard of LFDs.Chai [00:31:53]: It's a bridge for sure.Janie [00:31:55]: I got through three days and then I had to ask someone.Janie [00:31:58]: I thought it was just me that didn't knowJanie [00:32:01]: It's our internal process.Swyx [00:32:02]: But look at the data as a meme in ML, ‘cause you tend to not look at it. You just want to look at number go up.Chai [00:32:06]: Exactly.Swyx [00:32:07]: But yes.Janie [00:32:08]: But so, we make sure we look at the data and then as we think about all of the components of good output, we, one, create LLM judges across all of these and we make sure with annotated data and either internal or external evaluators, we feel like these judges are calibrated. And then depending on the stakes, we also work with in-house and third-party evaluators across all of these before we ship any big change. And the goal is, in terms of evolution, how do you go from this process taking months, down to weeks, down to days? Some of it is, a true science and ML problem. A lot of it's also just, hard operational work. Have you planned ahead in terms of what you need? Have you really optimized the capacity that you need across all of the different specialties you need? Have you gotten a really good sense of which third parties are great to work with for what use cases? This takes a lot of domain, expertise and, lots of mistakes and errors in figuring that out. And so as much of it is an ML problem, so much of it has also been operational gains that are hugely important, where domain-specific expertise is everything.Specialty-Level Evaluation and Progressive RolloutsJacob [00:33:23]: But it's funny, ‘cause I feel like people talk about healthcare like it's one giant market and the reality isJacob [00:33:26]: It's, dozens and dozens of sub-markets. And so it feels like in your evals you have to build that up across the board, probably.Swyx [00:33:34]: And is specialization the primary cardinality at... That's the word that comes to mind.Janie [00:33:40]: Sometimes, depending on the product or the use case. And so if we're making a note improvement or feature for a particular specialty, definitely but we have products that are for nurses. We have products that, are really aimed at making the document or the output a lot more billable. And so we'll want to work with coding teams and not necessary clinicians. And so likeJacob [00:34:05]: Coding meaning healthcare coding.Janie [00:34:06]: Yes. Yes.Jacob [00:34:07]: NotChai [00:34:07]: Yes. I see you.Swyx [00:34:07]: Other kinds.Janie [00:34:09]: But is this output proportional to the work that was delivered? Is there sufficient documentation to justify the amount that a health system may end up charging? And so, specialty sometimes but also domain, very different across all of the different products that we're working for. And building out that network is, not easy and is where a lot of our operational investments have gone into.Chai [00:34:35]: And I view a lot of analogies to self-driving cars here, where, part of it is we really want progressive rollout of features to test in the real world is this useful? Is this going to work? One big difference compared to past lives is before I'd build a product, maybe I'd alpha it and then I'd like GA it the next week, ‘cause I'm “Go, move fast, ship,” and whatnot. But the mentality is like you... I want to make contact with the reality as quick as possible but I want a progressive rollout. Because as much as I get as large of an offline eval set, I want the distribution of that to match real-life distribution. And over time, by rolling out early, similar to Waymo has a tagline, “The world's most experienced driver,” another thing that can, at least linearly increase for us is, both the size of our evaluation offline and online, that and it all feeds back.Janie [00:35:25]: Something that's been earned over time, speaking of evolution, is just the trust we've gotten with customers. Historically, a lot of these health systems, when they bring on new vendors, their release cycles are quarters, sometimes twice a year. We've gotten our customers onto monthly release cycles, which is pretty fast for health systems but what is more exciting over the last, call it, few quarters, has been, a subset of our customers have said, “We want to innovate with you. We trust you,” and we have a pretty, decent chunk of our customers who say, “We'll develop with you outside of these monthly release cycles. We have a higher tolerance. We know that the stakes are very high but we want to be the first ones using these products, giving you feedback.” And so for a pretty substantial set of our customers, we've been able to convince them to be able to ship, in this gradual way before GA. Something we talk about a lot internally is, trust is earned in drops, earned in buckets and so we still can't do what I used to do when I worked at Loom. We had 30 million users. I'd just be, rolling out experiments left and. The bar is still quite high for iterative rollout but because of the trust we've earned, we're able to learn at pretty high volume very quickly.Privacy, HIPAA, and De-IdentificationSwyx [00:36:45]: Your scale is still pretty huge.Swyx [00:36:47]: One thing I want to... We were going to go into scale? In a sec. One thing I wanted to call up, follow up on evals, which, again, just coming from a generalist engineer point of view, just thinking through what would people be scared of in doing this, the privacy and HIPAAJacob [00:37:00]: Elements of this. I have zero experience in that. What do you have to do? What is surprisingly not that bad?Chai [00:37:06]: So one thing that's really important here from a compliance perspective is very much that any of the data we use needs to be de-identified, any real-world data we use as a basis of online eval sets we're learning from. And so you have to — And there's, very clear, government guidelines, what counts as PHI. And so we've even have built models that can take, for example, a clinical transcript and remove all the key PHI indicators and so you have a scrubbed/de-identified version. And then once you... And so one thing that's important is first you've got to get confidence in that model in the first place? And prove that out. Because, now you have, multiple probabilistic systems on top of each other.Chai [00:37:46]: But once you have that, then you can train on it use it for evaluation and so forth, provided one of the cool things also that you can do from a business side is the right data contracting as well with your partners.Jacob [00:37:57]: Is the anonymization one way? Once it's done, you cannot undo it? Or is there someoneChai [00:38:01]: YesJacob [00:38:02]: Who holds the master key that can... Yeah, okay. So it's one way.Chai [00:38:05]: It's one way. Yeah.Jacob [00:38:06]: That's how it works. I just wanted to... Because, there's a lot of this, learning from feedback and everything that, you would want to debug more but you can't because you just physically don't allow yourself to.Janie [00:38:17]: Some of it's also written in our customer contracts in terms of who can or can't access PHI data, how long do we retain it,Jacob [00:38:27]: Very goodJanie [00:38:27]: Before it gets de-identified. And so we have a pretty high bar for who can access that PHI data, just to make sure that we always respect our customer data and privacy. But that's something that we partner with our customers on too, to make sure that as we want full, as close to precision as possible in that qualityJanie [00:38:48]: We can still use it.Jacob [00:38:50]: But it'll be fascinating to see how that space evolves? Because you think about, I used to work at a company that, did a lot of healthcare data in the cancer space and if you asked, the average cancer patient, “Hey, do you want people, do you want other patients to be able to learn-”Chai [00:39:03]: Take it.Jacob [00:39:03]: “... Learn from your experience?”Chai [00:39:04]: Take it all.Jacob [00:39:05]: They're “Please.”Jacob [00:39:06]: “I'd love, nothing more than for other people to be able to learn fromJacob [00:39:10]: The experience that I had.” And so in the past it was a lot harder to do that learning. But with this technology, that might really be practical and so it'll be fascinating to see how that continues to evolve.Chai [00:39:21]: There's so much in our data set of 100 million conversations.Chai [00:39:26]: You can imagine things like insights that you can give to the clinician. How could you, oh, how could you have reacted to this? In coaching or insights around, which treatments are effective or, like... Because you have this, again, this data source that was never captured before but that's, where, intuition or experience is created from, going back to this idea that the conversation is the agent of truth.Operating at Scale: Reliability, Cost, and Token EfficiencyJacob [00:39:46]: Back to the 100 million conversations, I feel like you have this insane scale that maybe only a few other AI app companies have and everyone else dreams of. So not everyone has had to confront this yet but maybe just talk about some of the challenges of operating at that scale and what, our listeners have to look forward to if they ever get to this level of scale.Chai [00:40:05]: At large and larger in scale, so of course there's a general, infrastructure reliability. When you... In any given startup, you're building the plane while it's flying. So there's some notion of that. But what gets interesting on the AI and ML side for sure is this, as you get at more and more scale, so one, you have the data to first and foremost do this. But, you start thinking about costs or infrastructure in a whole different way at scale versus, a prototype.Chai [00:40:34]: You can use the most expensive model, you can burn as many tokens as you want but when you're doing 100 million conversationsJacob [00:40:41]: Token max on leaderboards are less upsetting than that context.Chai [00:40:45]: . When you're doing that and so that comes for we have the data and we also have the team that's able to post-train based on this and you can optimize for efficiency, especially in areas where you believe that maybe a lot of the quality headroom is less so and you don't expect the other off-the-shelf models to go that way, such that you want to do, efficiency maximization, in terms of compute and tokens.Jacob [00:41:08]: I feel like you guys live in the future in some way where most use cases today are really just in use case discovery mode, where it's “God, I really hope I can find something that can get to scale,” and so you're always going to use the most powerful model. And then the few things that do get to this level of scale, you start to do those optimizations.Chai [00:41:22]: It's a natural trajectory where it's like zero-to-one, we're not talking about any of these optimizations.Chai [00:41:26]: But when maybe we're in the one-to-100 or so forth, then we're in optimization mode and, what works out really well is you've got all this data from zero-to-one that lets you do this.What Comes Next: The Conversation as the Shared Healthcare PlatformJacob [00:41:36]: That's fascinating. I feel like one thing that's so interesting about the Abridge footprint is that you're in the doctor-patient visit in real-time. I always like to say, there's like probably 50 years' worth of product you could build on top of that. What gets each of you, I don't know, what are you most excited about building, either in the short term or medium term or even, long down the line?Janie [00:41:53]: Something that I get really excited about is that the same conversation can serve so many stakeholders. If you think about the conversation, a doctor needs to know what is the documentation, how do I make sure that this fully represent the care I gave? A patient needs to know, “What the heck just happened? This was really overwhelming. What are my next steps?” A payer needs to know, was this the proper and appropriate care given? A pharma company might want to know why isn't this drug being properly used or is there a good candidate for this clinical trial that I'm about to run? And where I get excited is that our product and our platform and our infrastructure can be the same product across all of those things and start to what's today, separate, very expensive, complex systems that serve each one of these stakeholders in very different ways, start to collapse all of that into a singular platform that enables not just more efficiency across the board but also better outcomes for everyone. And, all of us experience healthcare in probably very painful ways and knowing that there is a world in which we can simplify a lot is really exciting to me and it all starts with the conversation.Chai [00:43:15]: It's interesting. Of it very similar to going back to the KPIs that any AI product cares about. How do you increase quality of care? How do you reduce latency to care? And how do you reduce costs? Which is a huge, in healthcareJacob [00:43:28]: They call it the triple aim in healthcare.Chai [00:43:30]: But very similar to building AI products and the thing that really excites me is when we talk about that latency piece, we talked about one example earlier of prior authorization, can you reduce the latency to care? But you can imagine so much more. Oh, as soon as the lab value gets updated, do you have like a background agent that, kicks off and uses all the context to be “Oh, hey, the patient should do this next,” for example. And of flagging that to the clinician who's always in the loop but reducing that latency, to care. And then you can imagine this is much further down the road but it's like even connecting that to the direct patient and the consumer. And so how can you, how can you build a bridge to all of these things?EHR Partnerships and the Clinical Intelligence LayerJacob [00:44:10]: Very cool. The connections piece is just an ever-growing thing. And one of the key partners is the EHR and I wonder what that relationship is like. Will they, look at this as, something that is valuable enough that they want to own someday?Janie [00:44:29]: Our partnerships with the EHR is, we know that we have to be extremely close partners with all the EHRs who we partner with. Being able to not only pull and push all of the data into the right places is, not only table stakes, if we can't do that, health systems don't want to use us. The second and the reality of today is clinicians spend a lot of their days in the EHR. So much of what allowed us to win in the largest health systems was pretty direct and, very close partnerships with some of the largest electronic health records that allowed us to pull and push data with APIs that weren't ready out of the box. And clinicians want to save clicks. Anytime we introduce a new product that, adds two clicks for them in their day, they're “We're not going to use it.”Janie [00:45:21]: They have 15-minute back-to-back appointments with their patients. They're spending, hours during pajama time doing documentation. Every second and every minute counts and so we really think about being deeply integrated into the EHR as also table stakes to getting real usage and adoption. And anything that we build or introduce, we really talk about earn the right internally a lot, which is we have to provide so much value or save so much time that people will use us. But those are the two things that are close to us, is we know that the product won't be used unless it is deeply interoperable.Chai [00:46:01]: And strategically, to your point, it's like what does EHR want to own versus us? EHRs are really focused on the clinical workflows and so forth but some of the things that we're talking about here, I do these traditionally are outside of the domain where it's oh, connecting pairs and providers together with provider policies or the clinical trial matching, as Janie brought up. And so these are, entirely — we position ourselves as building this entirely new intelligence, clinical intelligence layer across, again, providers, pharma and, payers.Chai [00:46:33]: And so that's a it's a whole different ballgame that we try to playChai [00:46:36]: In combination with them.Jacob [00:46:37]: But it's like a different layer of scope.Healthcare AI Regulation, Technical Depth, and What Changed Their MindsJacob [00:46:39]: I'm curious, you are both relatively newcomers to healthcare. People have these, there's lots of futuristic healthcare AI takes of “Oh, everything will look different.”, now that you've been in healthcare for a bit, you live at the edge of AI, what have you, changed your mind on around this, as you think about what healthcare looks like in ten, 20 years? Any updates to your mental model from the time being close to the problems?Chai [00:47:02]: One thing that IChai [00:47:04]: Was hesitant about before and it's a common thing when I'm trying to recruit engineers that people ask me around, is definitely oh, healthcare, heavily regulated space. And it is, rightfully so. You want to keep, the patients at the end of the day safe. But one of the interesting things that, is a that surprised me how much it is coming to the company is there's a lot of really favorable regulatory tailwinds as well. Where you think about, government really wants interoperability between all these systems that we talked about and so agents can access this information. The government just in January, the FDA released updated guidance on clinical decision support, what I work on in such a way that they used to have guidance from like 2022 that required you to have, mention all these options and do all these other things but it's a very forward and forward-looking way. And so for me, what's been really cool to work on is this, there's this very special moment both in AI in general, we all know that but there's a special moment also regulatory in healthcare as well.Janie [00:48:05]: One thing I would call out is for the very reasons things are higher stakes or, potentially considered more difficult in healthcare, it's where some of the hardest AI problems will get solved first, just because the bar is so high. When I first joined, I was “Oh, this is where we'll be on the tail end of where, all of the AI innovation will be able to be applied.” But when you think about, zero error evals or multi-step workflows that have really low tolerance, a lot of the innovation will happen here just because we have to or else we can't ship.Jacob [00:48:42]: ‘Cause like in other domains, you'd much rather just solve the 80%-is-good-enough problems firstJanie [00:48:46]: 80/20 doesn't work hereChai [00:48:48]: And building off that, traditionally, there was a bit of stigma that, oh, healthcare companies are not that interesting from a technical perspective or I've seen that or faced that myself. But these are really hard and fun problems from a pure technical perspective beyond just the impact. How do you bring the latency of this thing down and make it really high-quality?Reducing Latency: Clinical Workflows, Agents, and Implementation RealityJacob [00:49:07]: How do you bring the latency of things down?Chai [00:49:10]: Yeah. Yeah. Yeah. So okay, let's answer the latency question. And maybe hopefully not too redundant with some of the things I've said earlier but some part of it is with any latency, you have to like what is, what is really your bottleneck. In a lot of workflows, it's sometimes it's the model itself. And so that's where like our data flywheel, our post-training team and so forth come in so that can you make the models far more efficient. So that's one aspect of latency. But there's whole other aspects of latency where it's okay, on top of that, if you use a constellation of different models, can you use — can you first use like a — it's like thinking fast and slow. Can you use a cheap, fast model that triages and hands it off to a larger model where you get more intelligence and so forth and so all theseChai [00:49:56]: Clever tricks to make it work.Chai [00:49:58]: And by the way, we are totally — we also realize that the parameter frontier is changing and so these tricks will — may not get us to where we want to be in five years but we need to if we want to build a useful product right now.Jacob [00:50:11]: Should we go to the quick-fire or you want to ask more about Abridge? We can stuff everything that's not Abridge into the quick-fireSwyx [00:50:16]: I don't mind. I was — I feel like Janie was on the topic of more long tail stuff, which isSwyx [00:50:21]: Not the eighty/twenty thing and that really matters. And I'll —, if you have any tips or cool stories or just general approaches that have worked for you that's interesting to dig into.Janie [00:50:32]: One of them is even just how we staff our teams looks different than a traditional software engineering team, I'd say.Swyx [00:50:40]: Let's go.Clinician Scientists, Edge Cases, and Evals at ScaleJanie [00:50:41]: We have a bunch of folks with different roles who are clinicians and so we have this role called the clinician scientist and I heard one of our leaders refer to them as mutants recently. But they are people who've had clinical backgrounds, so MDs typically, who are also deeply technical, somewhere, on the spectrum of like a full stack engineer all the way to like extremely scrappy prompter. But having each of these people embedded within our teams instantly raises the bar for everything that we build because not only are they determining, is this product clinically useful but they're deeply embedded in our whole evals process. And so when we talk about LFDs, when we talk about what is our actual evaluation criteria, you don't want Chai or me creating what those are because we don't have clinical background. But is probably unique to Abridge but has been game changing. And when you think about where the puck is going, you have people build with clinical backgrounds who are technical and where AI tools are going, they just becomeJanie [00:51:53]: More and more, critical and like the killers of the team. And so that's one. And then the second is just the scale at which we do evals to catch that long tail up front before anything ever gets into production is something that we've pretty much like really started to fine-tune, both from a scale but when do we know we need to get several hundred versus several thousand offline responses, what helps us make that quick decision and make this less of an art and as much of a science as possible. But that's also been something we've had to tune over time.Swyx [00:52:27]: And you have partners who opted in to give you those evals.Janie [00:52:31]: So we work either internally or with third-party for offline evals and then we have customers who also agree to give us, whether it's like thumbs up, thumbs down to like choose this or that, a lot of data to get us to what is as close to fully confident as possible.Swyx [00:52:51]: The term that comes to mind isSwyx [00:52:53]: Like active learning on things where you're weak. I feel like it's a lost artSwyx [00:52:58]: Is a lot of the polish that comes into doing something like this.Janie [00:53:02]: Really.Chai [00:53:03]: Hundred percent.Lessons from Glean: Technical Foundations and AI App InfrastructureJacob [00:53:04]: Maybe, on a totally unrelated note, Chai, you had a very, storied run at Glean b

米ベンチャーキャピタル大手「アンドリーセン・ホロウィッツ」の共同創業者ベン・ホロウィッツ氏と面会した高市早苗首相、１４日午後、首相官邸高市早苗首相は１４日、米ベンチャーキャピタル大手「アンドリーセン・ホロウィッツ」の共同創業者ベン・ホロウィッツ氏と首相官邸で面会した。 Japanese Prime Minister Sanae Takaichi met with Ben Horowitz, co-founder of Andreessen Horowitz, a major U.S. venture capital firm, at the prime minister's office in Tokyo on Thursday.

Welcome back to the Pear Healthcare Playbook! Every week, we'll be getting to know trailblazing healthcare leaders and diving into building a digital health and biotech business from 0 to 1.We would greatly appreciate it if you took a moment to listen to the episode on either Apple or Spotify and leave us a rating! Your support helps our guests' insights reach a larger audience!Today we're thrilled to host Anirudh Joshi, co-founder of Valar Labs, who is building the company with co-founder Viswesh Krishna. Valar is pioneering AI-native oncology diagnostics using standard pathology slides to predict treatment response, starting with bladder cancer and expanding across oncology. The company raised a $22M Series A co-led by DCVC and Andreessen Horowitz, with continued backing from Pear VC since day one. In this conversation, Anirudh walks through how the genesis of the company, why pathology has long been underutilized and what it took to bring Vesta, its genitourinary-focused portfolio of AI powered pathology tests, to the clinic.

May 7, 2026: A landmark study from the Center for AI Safety spanning 56 AI models finds that smarter models appear to be sadder, that you can give an AI the equivalent of a digital drug, and that when you make an AI miserable it tells you the future is "grim." Second, Andreessen Horowitz publishes the most detailed optimist case yet that the AI job apocalypse is bad economics and worse history — rooted in the lump-of-labor fallacy — while Fortune raises the one question the optimists still haven't answered. And third, Coinbase CEO Brian Armstrong coins the term "pure managers" to describe the layer of corporate hierarchy that AI is eliminating first — and the player-coach model he's building in its place may be the clearest picture yet of what organizations actually look like in the AI era.

Sponsored by Chargebee, subscription and revenue management → check out their startup offer: https://www.chargebee.com/startups - Samar Abbas, Founder of temporal.io https://www.linkedin.com/in/samar-abbas-381997/   - Samar Abbas, co-founder of Temporal.io, shares the journey of building an open-source platform that ensures durable execution of code, allowing developers to focus on business logic instead of handling failures and reliability. - Temporal.io originated from years of experience at companies like Amazon, Microsoft, and Uber, where Samar and his co-founder iterated on workflow and state management systems, eventually creating a new category called "durable execution." - The company's open-source approach led to rapid community adoption, with major companies like Snap using Temporal for mission-critical workloads, validating the product's value and scalability. - Temporal.io monetizes by offering a fully managed cloud service with a consumption-based pricing model, aligning customer costs with the value delivered. - The company has raised significant funding, including a $300M Series D led by Andreessen Horowitz (a16z), with participation from Lightspeed Venture Partners and Sapphire Ventures, reaching a $5B valuation.

The Great private Capital Reset is upon us. Markets are volatile and driving new economic imperatives. Are VC funds still VC funds, even if they raise billions per fund? What happened to the rest of the market? What is driving VC investments? What do Limited Partners think? What is on their minds? This and more, in episode 76 of Tech Deciphered. Navigation: Intro The State of the Reset: The Hangover from the Party? LP Fatigue and VC Differentiation What Really Matters: Performance.. Returns The Mega Fund Question The Case for Smaller… Rightsized Funds What Comes Next? 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 Bertrand Introduction Welcome to episode 76 of Tech Deciphered. This episode will be about the great private capital reset. As you know, or you have probably heard, there is significant structural transformation in the world of venture capital, and we are probably witnessing a fundamental reset of the private capital stack. We got a huge bubble in 2020, 2021. Fueled by near-zero interest rates. We got inflated fund size, compressed due diligence, and now a generation of zombie funds and zombie startups. Now that rates have normalized, exits have not been as much as expected. LP patience is a warning sign, and I guess the industry is being forced to confront an uncomfortable truth: most VC funds raised since 2017 might not return what their LPs expected. You know, how do we start?   Nuno This is going to be a relatively nuanced episode. Obviously, there is going to be a lot of haves and have-nots, both in terms of VC funds, also in terms of startups. And so I want to start with that. This is going to be more nuanced than all transformational and disruptive.   Bertrand It’s not the end. It’s not the end.   Nuno State of the Reset: The Hangover from the Party? It’s not the end. There’s still huge mega funds that are raising more and more. It’s clear that the music has stopped, right? So if we’re playing the game of chairs, the music has stopped. Around ’22, ’23, we started seeing the first signals that funds had raised way too much money. Firms collectively raised around $669 billion globally in 2021 alone. If we fast forward now to last year, 2025, depending on the sources, we did some internal analysis at Chameleon. We came up with $75.6 billion was raised last year by 493 funds, right? So That’s a significant drop, right, in terms of fundraising. Other sources would say a little bit more. There’s a little bit of a discussion around how much did the top 30 funds capture. If you believe some of the stats out there, they would say that actually top 30 funds captured 75% of all capital raised last year. We did again some internal analysis at Chameleon, and the conclusion we came to, it was closer to 50 to 55%. So not as dramatic as some of the sources out there, but still pretty dramatic. There’s a lot of capital concentration on the top funds. Again, the top 30 funds would’ve raised 50 to 55% of capital or up to 75% according to other sources. So definitely a tremendous amount of concentration. There was a lot more fragmentation in terms of capital raised if we’re looking at the years from 2010, 2011, all the way through 2021. So 2021 would’ve been sort of the peak of non-concentration if you look at that. And that again, now we are getting more and more concentration. There’s more and more of this arbitrage around, I’ll give money to the top funds, I will not give money to the smaller funds, or I’ll give less money to the smaller funds. There’s a little bit of a movement around concentration. We’ll talk about it later and what that means. Are mega funds really better? Are the small funds still the way to go? We’ll talk a lot about that later in today’s episode. There seems to be a little bit of a bifurcation. We could say it’s either bifurcation around top-tier VCs or larger VC funds versus smaller VC funds. My perspective is the bifurcation that we’re seeing right now is more of a bifurcation between funds that are no longer just stepped into the VC space, but they’re actually becoming more and more private equity firms with full asset management range from early stage all the way to late stage. Think of it almost like a private equity hedge fund, quasi, versus classic VC funds. And I think what we’re seeing is the Andreessen Horowitzes, the a16zs of the world, the NEAs, the Sequoia Capitals, just to name a few, becoming more and more broad asset class managers across private equity, whereas you have more classic VC happening in earlier stages. And so that’s the real bifurcation that I think is actually happening.   Bertrand And maybe not really hedge fund, because they are always still long-only funds. So there is no hedging happening, at least as far as I know.   Nuno Well, some of these guys have become RIAs, like A16z has become an RIA, so they can do secondaries.   Bertrand That’s true. Yeah.   Nuno And they can also sell stuff, etc. So I don’t know how aggressive they’re going to be in terms of secondaries and selling and actually doing other kinds of services you can do if you’re an RIA. But it’s not, I think, out of the realm of possibility that they would sort of acquire and sell stock more rapidly. In that way, to your point, Bertrand, maybe they actually become beyond just long guys, right?   Bertrand Yes. Another trend I have seen is some of the larger VC funds seems to have no problem investing in multiple competitors. This was not possible before. I mean, if you’re a VC fund, you had some sort of duty not to invest in the competitors, but now some invest OpenAI, Anthropic at the same time. Do you see that as part of this evolution?   Nuno For sure. And I think there’s a lot of people like the ostrich putting their heads below the ground and it’s like, “Eh, no, no, nothing to see here.” But that does constitute a conflict of interest. And if I’m a startup raising, this assumption that you will not invest in one of my competitors is no longer there, certainly for the mega funds, because of that notion of deployment of capital. Now, some funds will still hide under the notion, actually formally from a fund perspective, we’re not investing in competitors. It just happens that different types of our funds are investing in competitors. Like maybe my growth fund is investing in a competitor to my early stage fund, right? But our funds are relatively independent. So I think there’s a little bit of hide and seek that will go on if you talk to some of the fund managers. Well, they say, well, we’re not investing out of the same fund into these competitors. But between you and I, as we know, a lot of these partnerships actually do a lot of stuff together at the general partnership level. So are there really actual Chinese walls between the funds? Well, it really depends on the partnership. And to be honest, most of the partnerships don’t have very significant Chinese walls between the funds, right? The managing general partners sometimes actually occupy investment committee roles across different funds. So I think the conflict of interest is there. So that’s why I say there’s a little bit of ostrich behavior. Put your head behind the ground or below the ground and just pretend nothing is happening. Just sharing maybe a couple of interesting stats. Global fund closings for 2025, according to our numbers at Chameleon, 1,098 closed. In 2025. Closed is when you start deploying capital, right? Whereas— so it’s not closed down, it’s closed like we start deploying capital. And that number, 1,098, is dramatically down from 1,600 in 2024. And it’s actually the lowest number of closings that we saw since 2014. So again, this is bad, right? It means there’s less funds doing fund closings and deploying capital in the market than since 2014 and dramatically below the 2024 numbers, right? Where we already saw some market readjustments. The number of active VC firms in the US that did 2+ deals, which is not a huge bar, has dropped 38% back to numbers in 2023. So we don’t have numbers that are a little bit more up to date, but basically in 2023, those numbers are already dramatically dropped. So there’s less and less active funds. So there’s funds that might be in the market, but they’re not actually deploying that much capital, not doing that many investment. They’re sort of either zombie funds or relatively passive funds that have passed their investment period. For those listening to us, the investment period for a VC fund is normally between the first 3 to 5 years of the fund, which is when you build your portfolio, when you can invest in new companies. After that time period, everything that you do up to normally what would be year 10 is follow-ons. You put more money into the companies that you’re already invested in, that you already constructed portfolio with during those 3 to 5 years.   Bertrand Yeah, that’s a pretty scary change. And obviously, I guess we’ll come to it, but the time it takes to fully liquidate investments is getting longer and longer. In the old days, we used to talk about VC funds having a 10-year life, maybe a +1/+1 in terms of extension of the fund life. But it looks like it’s taking 16 to 18 years actually to get full liquidity from a fund investment.   Nuno LP Fatigue and VC Differentiation And I think that’s the scariest piece. I mean, just to share some numbers, we in venture capital talk about vintages, right? Which year did your fund start in? Normally when you did your first close onto the fund, as we were saying before, close is when you get all your investors at that moment in time to come in and you do your first close so the next fund starts running. 2018 vintage funds, right? This is now almost 7 years ago. So you should start having— actually 8 years ago almost at this point in time. You should start already getting distributions or you start getting cash back if you’re a limited partner and investor in those funds, you should start getting cash back. Half of all 2018 vintage funds have returned $0 to their LPs. So they’ve had no distributions to their LPs. 2020 vintage, which was a very hot vintage, only 42% have begun any distribution. So 58% have distributed $0, right? 2021, only 25% have done any distributions. Now, I happen to have a 2018 vintage fund and a 2021 fund. My 2018 fund has already distributed over 3x net of fees in distributions, and my 2021 fund’s already over 10% distributed back in distribution. So we’re very proud of that. But in general, the numbers are awful. There’s no liquidity back to LPs. And to your point, that’s kind of a big deal because some of these funds have been going on for 7, 8 years, and where’s the liquidity going to come from? On the other hand, if you look at TVPI, so DPI is distributions to paid-ins cash on cash. But if you look at TVPI, which is total value to paid-in, which also includes the book value or the value that you’re marking it on your books, basically the paper value as we call it for the company, even on that, the median 2017 fund, so 2017 vintage fund has a TVPI, total value to paid-in, of only around 1.76x, which is well below what should be, which is sort of the 2 to 3x benchmark of a really good performing fund. So the median funds are doing very, very poorly overall. So if you add that to the fact of what’s happening and distributions are taking a long time, back to your point, Bertrand, it’s taking like— this should be a 10-year asset class, maybe 11, 12 years, and now it’s looking a little bit like a 15, to 18-year asset class, which is not what most limited partners sign up for. Part of this dynamic, I think, is that we’ve had tremendously overvalued private companies over the last few years, right? Secondly, these companies have just stayed private longer. And I was having a discussion recently with a friend of mine, it’s like, hey, what’s this thing about companies are staying private much longer? Is there some dynamic around secondaries? And the reality is there is a dynamic around secondaries, right? Because if I’m a very large fund and I can get away with doing secondaries on my portfolio, I will get liquidity at some point, right? But someone else is stuck with private stock, which hopefully will IPO, but who knows, right? And so there’s this funny dynamic right now of because of secondaries, because of a couple of other things that are happening in the market, actually a lot of these startups are staying private for tremendous amounts of times, and some of them will IPO and they’ll be huge deals. Some of them might not and might not warrant the latest private valuations that they’ve exercised. And so there’s this tremendous noise that we’re seeing in the mid to late funnel of privately held companies where some are just waiting to be public. Some of them might not be able to go public at anything that is an up round versus private valuations that they’ve had in previous moments and in previous rounds.   Bertrand And obviously the 2 to 3x returns that funds are targeting, and obviously more 3x than 2x, I mean, that was good and nice if it’s a 10-year fund, but if it’s the same 3x for 15 to 18 years, it’s not at all the same rate of return annualized. So it’s a really, really, really big issue if you keep the return the same, but you extend the duration of the fund. Concerning going IPO, there is a lot of complexity going public, the IPO process itself, but also after that when you’re a public company. It changed how you can run the business. Some would argue that we have had an issue with more companies delisting than companies listing on the public market. So I think there might be also separate issues about the efficiency of the public market and maybe a need for change. We went very strongly in one direction for the public market, have post and run, but was it really ultimately the right thing to do? I’m actually not so sure.   Nuno Yeah, I mean, just to be clear, this is anecdotal, but when we tell prospective LPs at Chameleon about our returns, the last few funds, 2018, 2021, the first reaction is, “You must be lying, right? Surely you can’t have distributions already for 2021,” et cetera, et cetera. So clearly there’s almost a state of disbelief right now from limited partners. And liquidity does matter. So clearly you have to move forward. So how did we get to this point where we had this bubble 2021 all around that time space and now things don’t look so good. Well, the macro conditions have changed dramatically. I mean, rates when they were near zero, safer assets yield nothing or yield nothing. So basically you had to push capital into longer duration risk assets like venture capital. And so you had to push it. So the opportunity cost of capital also has fundamentally shifted. Obviously a 3x VC return in 15 years over 10 actually competes very poorly against 5% annual credit returns over several years. So there’s been a readjustment of stuff. And then the public equities in particular, the tech public equities have had a lot of volatility, but some of them have done extremely well, right? Chipsets, things like NVIDIA, the Amazons of the world, Alphabets, et cetera, et cetera. They’ve done very, very well. So why would I invest in a long-term illiquid asset that takes now longer to give me money back, and in some case doesn’t give me back, if I can invest just in public equities, and a variety of other things. The venture debt costs have increased dramatically. The burn rates that were sustainable back in the day with sort of the addition of venture debt, private credit, et cetera, now are overblown at this moment in time. At the end of the day, there’s been a lot of movements also overall in the pipeline in terms of valuations, et cetera, et cetera. Now, I would put a grain of salt into all the numbers I just told you. There still is a little bit of the haves and have-nots in startup land. Certainly in early stage where if you’re a hot AI company, you can get away with raising a Series C or $480 million. This is actually a true story. Series C, right? Not Series C, a $480 million at $4 billion pre-money valuation. Whereas if you are maybe in a space that’s less hot, you’ll have more difficulty in raising money at this point in time, might not be able to even raise a Series C, right? So there’s a little bit of the haves and have-nots happening on the VC side in early stage that has been really amplified by the macro regime and where we’re at, which is actively zero-rate era is done and now the new regime is quite different. And so I can get better returns by doing something else.   Bertrand Kind of makes sense. I mean, if you have some ways the SaaSpocalypse in the public market because there is that fear that AI is going to completely change the game for especially for the more typical software companies. Good luck raising private money to quote unquote just build traditional software companies. You cannot expect a warm embrace from the private market if the public markets are completely destroying that category. I’m not saying that this is there forever, uh, things might change over time, but for sure what’s happening on the public markets always have a very strong impact on the private market.   Nuno Indeed. So what’s happening in this relationship between limited partners and VCs, the general partners? Again, limited partners are the people that give venture capital firms and venture capital funds their capital to actually deploy. And they are a variety of different players, right? Could be endowments, like university endowments, pension funds, family offices, very high net worth individuals, fund of funds, et cetera, et cetera. I mean, in particular, if you look at the institutional investors, the endowments, the pension funds, the fund of funds, they have allocations that they do to different asset classes typically. And the feedback that we’ve received from the market is they are increasingly frustrated with what’s happening in terms of distributions. They’re not getting capital back. It’s like, I gave you capital 8 years ago, 9 years ago, 2017, 2018 vintages, and I’m not getting any capital back. So what the hell’s happening? On paper, it looks maybe the fund’s doing okay or it’s doing great in some cases, but where’s my money? And so that creates a little bit of wait-and-see kind of game on portfolio allocation. As we’re thinking through their re-ups, putting more capital into funds that they’re already actually put capital or putting in capital into new slots, into new fund managers that they want to put money into. They’re like, well, let’s wait and see. I want to get my money back or get some money back first before I redeploy it. Again, this is a little bit the haves and have-nots because we’ve seen, for example, a couple of top-end LPs in terms of returns that have a little bit the opposite problem, right? Because they are into funds that are performing extremely well. They actually are over that period and they want to actually redeploy. But to be honest, the average in the industry right now is a wait-and-see game. It’s like, I want to wait and see, which leads to what can only be characterized— I was hearing someone the other day, one of the top advisors in the LP community, saying this is the worst fundraising environment ever for venture capital. Not the last 20 years, 30 years, like ever, right? Since this became an asset class more institutionally in the late ’60s, early ’70s, Pulse Robo 2 as it was created, this is the worst fundraising environment ever. Oh, wow.   Bertrand And concerning TVPI, let’s not forget that typically it’s not mark-to-market. So the metrics in terms of TVPI, correct me if I’m wrong, you know, but the metrics in TVPI are based on typically the last fundraise. So if the valuation went down but there was no additional fundraise, we wouldn’t know by looking at the TVPI metrics. It will only be updated if there is a new Financing, equity financing, or an exit.   Nuno Yeah, normally most funds act like that. Some funds are a little bit more aggressive and do do mark-to-market, but normally funds would be conservative and say, hey, I’m being conservative, it’s whatever is the last known valuation of the company. And if there wasn’t a priced round, it’s a little bit more obscure than that, right, Bertrand? Because it might actually be the company has raised money on a note, or either convertible note or a SAFE note, and that wouldn’t count as a priced round. So I would say actually, even if it was a cap that’s below with a significant discount, I won’t recognize the assets as a down round. I won’t recognize the asset with a lower valuation because formally it wasn’t a price round. So it’s on the one hand conservative, on the other hand, it’s only relating to price rounds or exits to your point. So it’s sort of, you can be like, hmm, well, we opt to do that because we think it’s actually the most conservative route. Mark-to-market is extremely difficult to do. And who would do the mark-to-market for you, right? It’s like it’s some valuation firm, et cetera.   Bertrand I’m not saying a mark-to-market is easy, but I’m not sure I would call using the last valuation something conservative in the context that most startups will fail. So it’s not clear.   Nuno Well, in some cases it is, some cases it’s not, right? Depends on the startup situation, to be honest. Yeah, yeah.   Bertrand But yeah, at least that’s how it’s done. So for instance, to evaluate the impact of the SaaS apocalypse, it’s tough to know. We will have on the private market. I mean, we will see that in a few quarters. Because if companies still exist in that environment, if they still do additional truly price rounds after that, that’s when I will start to know.   Nuno I mean, just to share a little bit more data, like VC fund close time stretched to 15 months. Basically, it’s just taking a long time to raise money. It’s taking a long time to do your first close, get your fund running. When entrepreneurs complain to me that their fundraising is difficult, I always say, you have no clue how difficult it is compared to ours. First-time funds have collapsed. We had some numbers that only 77 first-time funds actually closed. I assume this is in 2025 versus 215 in 2023. So that’s a huge number. We did some internal analysis on our side and we did some analysis that emerging fund managers, emerging fund managers are normally people that are in their first one or two funds. Basically emerging fund managers gained some ground until 2017. Reaching by then a slice that was 63.7% of all capital raised in 2017. But since then, the capital deployed to emerging managers has been largely reduced to actually 24.2%, right? So it’s gone from 63.7% in 2017 to 24.2%. So this has been a culling of sorts on emerging managers and almost like a slaughterhouse of emerging managers. Compared to previous situations, which is obviously incredibly concerning if you’re an emerging manager starting your VC firm, et cetera, et cetera. So really tremendously problematic for those. We think capital’s not leaving VC. I think we see a lot of the institutionals saying— there’s some numbers as high as 33% of institutional investors plan to invest more in venture in the next 12 months. So I don’t think capital’s leaving VC. I think it’s really concentrating. We’ll come back to the concentration issue later in the episode. And part of that concentration comes from a topic that has been widely spoken in venture capital recently, which is differentiation. How do you differentiate in venture capital if you’re talking to a limited partner, right? How does my firm differentiate versus the firm next to mine? And that’s incredibly, incredibly challenging. Bertrand, what are your thoughts on that?   Bertrand Differentiation is always a question. I mean, if you’re an entrepreneur, Typically, you think fully about the best possible partner for your stage and for your type of business model. You want a VC who understands fully your business model, because if they don’t, then it’s going to be troubled down the line. But that’s true that another piece of the puzzle is that the best VCs help you get more visibility in terms of achieving potential customer deals, in terms of attracting the best talent. And that’s where VCs’ brand names can help. If you can say you have backing by some of the top, most visible names in the industry, and usually these are the mega funds because others have trouble to be as visible, then they have some sort of unfair advantage compared to others. So I can see that there is some level of concentration happening naturally, especially in the later stage from Series B onwards.   Nuno What Really Matters: Performance… Returns Yeah, I mean, we did some analysis internally about What are the top funds that invested in the top performing companies in early stage, Series C, Series A? And we looked at it by size of fund and the top performing normally are funds below $100 million, but in some cases very closely followed by funds between $100 and $500 million. And actually funds above $500 million, so $500 million to $1 billion and then $1 billion and above are actually tremendously underperforming. So this notion of the industry that says, well, the mega funds still see The top investments early on, because they still deploy in Series C and Series A opportunistically, in some cases even spray and pray if they have their own incubation and acceleration programs, is not true. Actually, we verified that over the last 12 to 13 years. It is not 12 to 13 years in vintage, right? So up to a 2021 vintage fund. So we went basically 12, 13 years back from there. And it’s not true. Actually, the most performing are 0 to 100 and then 100 to 500. And as I said, there’s 100 to 500 in a couple of years actually are a little bit better. Than the $0 to $100 million ones. So that’s the first thing that’s a conclusion. And actually, that’s not shocking. If we remember back in the day, Kleiner Perkins used to raise funds up to $600 million, Benchmark raised their $425 million funds. It seems like the sweet spot for a VC fund would be around $500 million at the top end, like maximum. And now somehow people are saying, well, I’m raising a $3 billion VC fund. It’s like, well, it can’t be a VC fund. The return profile is totally different, right? You can’t deploy that capital just based on early stage investing. And by the way, you’re not seeing the guys at early stage, all that you’re seeing, you’re going to make your returns in mid to late stage, right? Back to what we said at the beginning of the episode. So there’s a little bit of the haves and have-nots there. The big guys are raising more and more money, but they’re no longer venture capital. And I think limited partners that are a little bit more evolved, that are a little bit more conscious of this, that have been in the market longer, are realizing that shift. So it’s like if they want to have the alpha of venture capital, they need to deploy to the sub-$100 million funds or the sub-$500 million funds, right? That’s where they need to actually focus their VC capital. They can still deploy to mega funds, but they’re deploying to a different asset class. They’re deploying to a private equity, mid to late stage asset class, which looks maybe a little bit more like a growth fund or something like that. The second part of differentiation is the honest truth is most VC funds are like, I have proprietary network access, right? I’m ex-Stripe or I’m ex-Google or I’m ex-Facebook or whatever, and I have access to that. I mean, we know proprietary networks from that standpoint are no longer true. The whole thing that created Silicon Valley back in the ’70s of what I used to call the country club deals where there were a few people coming out of the big companies, the Fairchilds of the world, later on the Intels of the world, et cetera, et cetera, that made some money along the way that sort of bootstrapped their next companies, were well-known quantity to the existing VCs and raised money relatively easy on ideas, that doesn’t work anymore. Someone was telling me the other day one interesting thing that I wasn’t quite aware of, a lot of it had to do with the NDAs. I don’t know if you knew this, Bertrand, but like the fact that in California, it was sort of the Silicon Valley community sort of imposed this, we don’t sign NDAs thing and Boston continued signing it. And this whole NDA enforcement issue and non-compete, actually not the NDA thing, but more strongly that California did not enforce non-competes. I could leave Fairchild and start a company that magically was doing something that could be considered competitive to Fairchild. And that was sort of part of the acceleration actually of venture capital in California versus, for example, Boston, which was sort of hand in hand at the beginning.   Bertrand Yeah, I mean, I’m a big, big believer in California success coming from not enforcing or banning non-compete agreements. I think it’s a key part of the game. If you lock people into not doing something similar in the next 6 months to 24 months. And the industry has always been moving fast. So this is a significant time where you are blocked to do something very similar. I think it was really an issue. So I think it’s a key part of the game and it has been there. I don’t know how it started, but I think that non-enforcement of non-compete has been a key part of the success of California. I’m actually pleased to say that Washington State is going in the same direction. They are just signing a non-compete ban. And you might remember that at the federal level, I think in 2024, there was also a ban that was put in place to ban non-compete, but this has been reversed by the courts. So this is not there anymore. So that’s why we see a state like Washington State putting their own ban, and we might see more state by state moving in that direction. I think it was not helping at all, this non-compete. I mean, there is obviously stuff that needs to be done, like you cannot steal secrets, you cannot steal IP.   Nuno Yeah.   Bertrand Even stealing employees, there should be some restraints. We need to find the right balance, but you have to be careful there. That was key for the success of California, and I’m glad to see that this is a trend that’s going to go beyond California. And I hope most states will have a ban on non-compete.   Nuno Maybe just to close on the differentiation process, two things. One, I think there’s this notion When you talk to some LPs, that seems to be a little bit ingrained, some LPs that prefer specialized funds. We’ve also done some significant analysis internally and have talked to a couple of datasets other than our own, or people that own datasets other than our own, and the feedback has actually been not so fast. Actually, generalist funds over time cannot perform specialist funds. There seems to be a little bit of a sweet spot around generalist funds. We like to call ourselves multi-specialized at Chameleon, but ultimately from the perspective of specialized versus Generalist funds, the picture’s not as clear as specialized funds outperform generalists or generalists outperform specialized. We’ve seen there are pockets where actually generalists outperform specialized, in other pockets where specialized of a certain size can outperform generalists. So that’s one topic on differentiation that is a little bit broader. And then the final topic on differentiation, it’s really an industry that hasn’t innovated dramatically on where it creates the most value, which is really the picking stage, right? So it’s having great deal flow, very optimal, productive, efficient due diligence with very few resources and the ability to then get into those deals. That’s where most of the value is created. And then hopefully liquidating the asset if there’s an opportunity to do so at the right time, either through secondary trade sales or an IPO or something else. And what we’ve seen is the industry has innovated very little. I mean, the only thing I could point out in terms of core innovation at the top of the funnel has been the creation of the mega funds, the well-known funds, right? Like a16z, Union Square Ventures, et cetera, et cetera. But there needs to be more innovation on that cycle. And that’s why we certainly at Chameleon believe that the future is to have quant and AI-native VC firms that develop their own tooling, their own platforms. We have Mantis in our case that allow you to have this unfair advantage in how you source deals and how you do due diligence, how you get into the deals, et cetera, and how you take it to the next level. And we think that’s the beginning of the next stage is that the industry becomes more tech-enabled, shockingly enough, an industry that has made all its returns on tech or almost all of its returns on tech. That we need to be more tech-enabled ourselves. But I think the writing is on the wall there, and that will be a source of differentiation certainly over the next 3 to 5 years.   Bertrand One thing the industry has innovated somewhat and maybe could innovate even more is providing liquidity beyond trade sale and an IPO, because it’s clear that if VCs want more liquidity without waiting 18 years, you need that liquidity at different stage, not just when it’s time to do an exit, a full exit for the business. And for employees as well. I mean, it’s one thing to stay for a company for 4 years, which is your typical vesting. Maybe you extend that to 6 years, to 8 years, you have a great time at the company. But to think that maybe you have to stick around for 15 to 20 years in order to get liquidity on your stock options. I mean, that’s too much to ask for most people. I mean, people have a life, they have other things to do, other plans, they might want to move, they come at a different stage of life. So you need to provide them liquidity. The new game is we are not going to exit until 15 to 20 years, else it’s truly unfair. It’s not just unfair, but people will say, you know what, I’m going to go across the street, go work for Amazon or Google. I will have RSUs at best regularly that are liquid, and why bother? I mean, we need to find pathways to liquidity for both investors but also employees. There has been a change in that direction, but I think we need more of this change, and maybe not just reserved for the absolute biggest, most successful companies like OpenAI or SpaceX, but also us as well. Hopefully we can find a way.   Nuno Well, now we have these AI companies that actually grow so fast that they will IPO in one year. Now, isn’t that what’s going to happen? They raise They raised $500 million in Series C or $1.4 billion in Series C, and they’re going to IPO in 2 years. No? Is that not the new reality? I’m being facetious.   Bertrand At the same time, I mean, there are rumors that some of them are going to IPO this year. I mean, we talk about OpenAI, about Anthropic. I mean, OpenAI is quite old, but Anthropic is a relatively new business, quote unquote. So I think it’s a good time.   Nuno The Mega Fund Question So maybe it will be true after all. Moving to the next section, are mega funds still venture capital, Bertrand? Are they still venture capital funds?   Bertrand Yeah, I guess venture capital is a term that can encompass from small to very big funds. I truly don’t know. I mean, once you reach a growth stage, are you truly a VC fund? I don’t know. I think some of these definitions are kind of arbitrary from my perspective. What is clear is that you as a business need different providers of capital. And as we just discussed, you as a business, probably need to keep going and stay private for longer. One reason being, again, there is a tremendous cost to being a public company. There are some true strategic disadvantages. And at the same time, just practically, I mean, you need to get bigger and bigger in order to have a chance of a successful IPO. So you cannot just go IPO at a $500 million valuation. I mean, that’s like committing suicide, at least in the US market on NASDAQ. So my point is, you truly have no choice. You need to extend and If you need to extend, then you need to have capital providers that are there at later stage and therefore have more money. Is it still true venture capital? Is it true venture? I don’t know. At some point, it makes sense that from the startups to the capital providers, everyone adjusts to a reality where the life cycle is getting longer.   Nuno We don’t think it is. We don’t think mega funds are venture capital. We have actually some data that shows that they’re not in terms of actual returns. The alphas you can generate, the IRR that you can generate is actually not comparable. We did some analysis again with some of our datasets and from 2012 to 2022, so that’s the datasets that we used so that we had actual distributions and stuff we could take into account and so on and so forth. And looking at IRR, just to share some numbers in terms of IRR over those 10 years on sub-$100 million funds versus above $1 billion funds, the differences are incredibly stark. And this is true for global and US IRR, right? So just to quote some numbers in terms of average, sub-$100 million funds, global IRR of 22.9%, US IRR of 21.6% versus above $1 billion, 9.1% and 9.0%. Median IRR, if we just looked at median, 7.3% and 16.6% for sub-$100 million funds, 7.5% and 8.1% above $1 billion. Top quartile IRR, sub-$100 million, 31% versus 30.4% US IRR. And then above $1 billion funds, 14.7%, 15.5%. So it’s very clear if you sort of cut this in different ways, averages, medians, top quartiles, et cetera, over all these years that sub-$100 million funds are in a very different asset class than above $1 billion funds. They’re in different alpha that you can generate and so on and so forth. Now to the point you made, Bertrand, I don’t fully disagree with the point you made of the bigger funds should become bigger. I just think they’re becoming different things. Now, again, some of these funds will hide under the facts like, well, wait a second, we have all these assets under management, but they’re over different funds. Sequoia, we’re still raising small early-stage funds, $500, $600 million funds. And then we have larger funds for growth, et cetera, et cetera. Andreessen Horowitz, a little bit less clear what they’re actually doing. We heard that they’ve raised $15 billion across funds. I’m not sure if that’s the exact number at the end of the day. But the point is, if I’m a multi-asset class manager, like early growth, et cetera, et cetera, then it still applies what Nunu is saying. I’m still going after the $500 million, $600 million early-stage funds. Well, not so fast, right? Because you still have all this capital with managing general partners that are maybe across funds for which their incentives in particular, both carry and management fees are coming from the larger funds. Et cetera, et cetera. So there’s necessarily conflicts of interest. In many cases, the funds are just straight up big, right? And so they are above a billion. And so I don’t think a lot of these guys are in early-stage investing anymore, right? It may appear that they are, but I don’t think that’s where the returns necessarily are going to come from. And so if you are a limited partner, if you’re looking at your asset class allocation, again, you’re absolutely free to put money into mega funds because that’s the kind of asset class you want to play in. In terms of a blended private equity asset class that has a little bit of growth, a little bit of whatever, or actually a lot of growth, a lot of late stage, and maybe a little bit of early stage. And I want something that’s a little bit more blended, right? But if I still want the alpha venture capital, I need to deploy to funds that are early stage, right? And that’s like up to $100 million, up to $500 million. I think that’s my two cents on that topic. We see crossover things coming around, like guys who do both public and private markets. Again, that starts feeling a bit like a hedge fund. A lot of these funds have also become RAs, as we discussed earlier. So I feel the writing’s on the wall. The mega funds are going more and more after either some mechanism of edging or a mechanism that’s a little bit more blended in terms of private equity than classic venture capital.   Bertrand Yes, I think a few things. One, if you’re an LP, I can imagine that dealing with multiple $100 million funds might be more difficult. You, you need to know the partners, you need to have some background, uh, visibility. You need potentially to change regularly of VC investments. So I can see some level of simplicity if you just focus on the bigger ones, especially if you have a lot of assets you have to put to work. Another piece of the puzzle, I would guess that the bigger funds are able to return money faster because they are at later stage of the cycle. So instead of that 15 to 18 years, maybe they are more in a 5 to 10 year range, while the smaller funds being there more early might be the one who are taking longer to deliver. So I can see that Yes, there is an IRR picture, but there is also time to liquidity that is not the same. So that can probably also influence. And in terms of crossover PE hybrid model, I mean, for sure we have seen some of the public equity investors doing crossover, meaning going into private equity firms like Coatue, like Tiger Global and others. And for companies that are preparing for IPO, there is a lot of value to work with these firms because they have very good visibility and understanding of the public markets. And their presence in the cap table is also a sign of quality, typically for public market investors. So there is a lot of value and logic for them to be there on both sides of the puzzle. But again, the fact that firms keep delaying IPOs, that the market is not so much startup-friendly, makes this model a bit more difficult. But personally, I think there is value there.   Nuno Yeah, I think on the mega fund, just so that I’m not boo-booing everything, I mean, but there’s definitely angles in terms of the asset class that make a lot of sense. And there’s the scalability of the model. The ability to go after Series B, Series C, as well as mid-stage, as well as late-stage, even secondaries over time, to your point, in some cases even public equities. And that level of skill I think matters. We’ve also seen, as we’ve known, we won’t mention any brands, but people will know who they are, that late-stage hedge funds and investors, even if they’ve done okay-ish in growth in private equity, don’t necessarily do well in venture. So it’s clearly a very different asset class, right? So once you start getting venture teams together, The returns are not quite the same. Actually, sometimes they’re not even quite the same as the growth investments. So clearly they’re very good at the growth side, but not so good in early stage. But definitely there is a case for it. The Case for Smaller…Rightsized Funds But if we switch gears maybe to the small, or I would call right-sized funds, maybe just to quote a couple of numbers and then open up the discussion. Small funds do seem to outperform larger funds. There’s a lot of data in the market that shows some of that dynamic outperformance frequency. All the Very historical numbers from Cambridge Associates from 1981 to 2010. 19 out of 30 vintages were won by sub-$150 million funds. We did our own analysis as I was sharing before. Funds between $0 and $100 won most years between around 2010 and 2021. And the years that they didn’t outperform in terms of investing in the top-performing companies in early-stage Series C, Series A, they were outperformed by the $100 to $500 million funds. The $500 to $1 billion funds and $1 billion or above were never even in the same league in terms of performance, of having identified those top performers in terms of quantity over those early-stage investments. Top 10 funds by vintage, 2004 to 2006, 2016 numbers. Top 10 funds, 73% were sub-$100 million. 2004 to 2016, top 10 funds by vintage, 73% of those were sub-$100 million. So there seems to be a little bit of a case that actually smaller funds, sub-$100 million, sub-$500 million in some cases, are outperforming the larger funds over time. Now, these funds are complex in and of itself. The positive of it is small fund GPs like myself, we are deeply invested in our own funds. We’re not there to just make management fee monies. I mean, we’re not making $1 million, $2 million a year in management fees of salary ourselves, like some of the larger funds. So we are there to really get the carry and be less focused on management fees. And so I think there’s a little bit of alignment around that and really taking that kind of perspective on portfolio construction and liquidation, being also more aggressive on the individual time that we spend with our startups. On the negative side, obviously a lot of these smaller funds, not the case of Chameleon, but others out there are single GPs, very little teams or very small teams. And so it’s sometimes difficult to actually do a lot for portfolio companies as well. And this is where the mega funds, for example, a16z notably would say, hey, we have 600+ people that can support you, right? On market development, business development, communications, talent recruiting, all this stuff. Question mark whether that’s the right way to do it in terms of operating model, if technology is not a better way of supplying that value back to your portfolio companies, or if there’s no better way of doing it. But still, that’s one of the appeals of actually dealing with a larger mega fund if you’re a startup, right? That they will have the resources, also the financial resources to put more capital in you. But also, again, if there’s entrepreneurs listening to this right now, and hopefully there are, it’s a two-edged sword, right? Because if you have Andreessen Horowitz putting money in you, or NEA, or General Catalyst, or whatever, putting money in you on a Series C and then not doubling down on the Series A or the Series B, there will be questions, right? Because like they have the capital, they have other funds, so why the hell are they not putting more money in? Um, so, so it’s a little bit of a two-edged sword.   Bertrand Yeah, I think that one is a pretty big one. And on top of it, as we discussed, some of these big firms have multiple funds managed technically by different teams. So you might have convinced the early-stage teams, they have investors, they’re happy, but you don’t convince the growth-stage firm. As you say, it might raise questions because people might think that there is some communication between the early-stage team and the growth-stage team. So why the heck are they not deciding to invest? And as we also discussed, even worse possible situation, what happens if the growth-stage team has invested in your competitor? It’s even more trouble. So I think trying to understand how firms behave, what’s the reputation of the firm, what’s the reputation of the partner you are working with, I mean, can have tremendous importance and impact. When it’s time for you to work with a firm.   Nuno Indeed. I mean, at the end of the day, we still believe that the smaller fund— we at Chameleon discuss the notion that our limit should be $500 million per fund, right? And that’s the logic of it. We think that model is the model that works well in venture capital. We do recognize, as I said before, why mega funds keep raising more and more money, right? It becomes a harm’s race at that end of the market. As I said, probably a slightly different asset class, or if not a significantly different asset class as well. So seeing a little bit both sides of the market, I mean, we often compete with the mega funds, but honestly, a lot of the mega funds are kind to us and they let us in. And this whole notion of elbows out, we haven’t felt it that much in the market. And people see our value at the table. And in many cases, I, I do see the larger funds more and more seeing the value of smaller funds coming in on the same rounds and even in some cases co-leading early stage rounds like Series C. So it’s not like elbows are out everywhere across the board. So I don’t mean to say this is like an all-out war between small funds and big funds and the small funds need to win or the big funds need to win. I think actually there’s a lot of potential for coexistence. My point is more that the asset classes and the returns are quite different over time, and that’s how I would think through it. And if you’re an entrepreneur, you should think about that as well, right? What are the implications of taking money from certain funds versus others in terms of the expected returns, expected time allocated to you? For example, if you’re not doing very well as a as a company, right? Will the big funds spend the same amount of energy on you if you’re not doing great and all of that? So it’s a little bit sort of a beware, open your eyes, both for limited partners and for startups. What do you actually want, right? What do you want from your VC firm if you’re a startup? And what do you want from your VC firm if you’re an LP?   Bertrand I must say, as an entrepreneur, uh, a board member, I have seen some situations where the bigger funds are actually trying sometimes to elbow out the existing investors. Like, uh, we have that much money to put to work, we cannot do less. And you’re like, yeah, but I don’t need that much money. And then they’re like, okay, just don’t let your existing investors do their pro rata. I don’t think it’s great because an entrepreneur, if your investors, your VCs, trusted you earlier stage when it’s more risky, and when it’s becoming less risky, you don’t give them the right to their pro rata because you have to let this big guy come in. That’s not great. Or even if there is not this pro rata issue, when an investor tries to put more money to work than it’s really necessary, it’s also not a good idea as an entrepreneur to take more capital than you could use. It will dilute you more, it will set higher expectations in terms of valuation, it will push you to use that capital faster than maybe would be reasonable. So I think that’s something you want to be careful with the bigger funds. So don’t talk to funds that are in some ways beyond your stage and try to make it work in that context. Or don’t accept to have your strategy change dramatically for no good reason by funds that just want to put too much money to work in your business. And that for me is surprising because it should also be in their best interest not to invest in businesses that are not ready to accept that much capital. But as we have seen, there were in the past some funds that believe that capital is a moat. Was a good idea. So hopefully, I guess we’re a bit behind that. But yeah, I would say entrepreneurs, be careful, find partners that are the right partners for you at your current stage. Sometimes some big names look great, but at the same time, if it comes with a lot of issues, from too much capital to also taking the risk that these partners don’t understand the stage of the business you are in or your industry, Just be careful. There is a lot of value to have firms that are very focused on your stage, on your industry, are finely attuned to that situation.   Nuno What Comes Next? Maybe to end in terms of sections, what comes next? And maybe we can come up with some predictions that are a little bit provocative on what’s going to happen to the market. You, if you’re listening to us, feel free to interact with us on LinkedIn, on X. If you have our email address, shoot us an email as well. We’d love to hear from you if you think these are the right predictions or if we’re totally off. Maybe I’ll throw in the first one, Bertrand, and we’ll go one by one. So we’ll each put one at the table and see where we head. My first one is that we’ll have a huge culling of VC investors. We had this rapid expansion of the VC asset class with arguably at least tens of thousands of firms globally, maybe even over 10,000 in the US. I think we’ll have a culling and the culling will continue and we’ll have several firms sort of getting eliminated over the next couple of years that will have either because they’re having tremendous difficulty doing their first close in their next fund, or the returns are not there, or it’s a firm that has done 3, 4 funds, but for some reason the returns have just gone out of whack in the last few years during the bull years. And so therefore, actually they can’t justify to raise more funds out there. So I predict there will be a significant elimination of active firms in the next at least 2 to 3 years. So maybe by 2028, and we’ll be below, I don’t know, 30% of number of active firms that we are today. The other side of it is I do think if we look beyond that, 2029, 2030, and so on, we’ll have the reemergence of not micro funds, but nano funds where people will start deploying capital very, very early and writing small angel checks, but doing it in a way that it’s sort of not this cottage industry that we’ve had of angel investors. So I think angel investment will be disrupted by people that will use more and more of the AI toolification out there to actually manage their portfolios of 10, 15, 5K investments in a way that is a lot more professional, creating sort of an advent of nano funds.   Bertrand Yeah, makes sense. On my side, in terms of prediction, I think there is a possibility that the mega fund model keeps expanding and looks more similar over time to some PE models. So do we have the top 10 VC firms that look more like a Blackstone than a Kleiner Perkins or Sequoia used to be? That for me will be an interesting question and development. I think that there is some possibility that it keeps going in that direction. A lot of incentives are pushing things that way.   Nuno My next prediction is that DPI, distributions to paid-in cash on cash, just cash back, will become essential for limited partners. I think TVPI, total value to paid-in, that also has in there, as we just said, paper valuations. There’s a lot of disbelief now around the TVPI metric if there isn’t distributions going alongside it. For those who, again, don’t know what TVPI is, it’s total value paid in, but it also includes DPI. So it’s cash on cash component plus a remaining valuation to paid in, an RVPI. And the problem is the RVPI really, in reality, it’s that kind of on-paper valuation that never gets attributed. I think LPs, they’ve seen the writing on the wall and they’re like, dude, just show me your DPI numbers. I don’t care about TVPI. Some LPs will still ask about TVPI just to make sure that the rest is sort of looking in order. Like, show me the money, show me the cash. Actually, it’s not money, show me the cash, right? I want money back.   Bertrand But that’s an issue. I mean, if you’re supposed to raise financing every 3 or 4 years, good luck getting DPI to show for that. So you need to be at least on your third fund in order to be able to show DPI, I guess.   Nuno I mean, my corollary to that, Bertrand, is if you allow me just to have a corollary kind of prediction, is that we’ll see certainly for funds like $50 million and above, $100 million, $200 million, et cetera, even increased concentration, right? I really need to have anchors that believe in me over time. And we might start having, again, the advent— we had it some decades ago, the advent of cap table kind of VCs, right? Like Sutter Hill Ventures, right? Where they’re not really raising funds anymore. And so we might have the advent of that, that we’ll have structures that are created that have more permanent capital allocated to them, or at the very least more concentrated capital by very few players.   Bertrand Interesting. Me on my side, as I shared before, I believe secondaries are, are important and here to stay. Um, in the past, some could argue, is it a distress signal or something? I, I don’t think it’s true anymore. In a world where your average startup might take 15 to 18 years to exit through M&A or IPO, we need to have other options. For funds, for employees, they cannot be expected to stick around for so long and have no liquidity. I mean, it’s just pure madness. It’s just bad alignment at some point to do that. So I think secondaries are becoming the third liquidity pathway for VCs, for employees, and it should be more and more a key part of the game, a key infrastructure in the VC/startups tech industry.   Nuno I mean, on specialized versus generalist funds, I believe we’ll continue seeing the coexistence of those two models where the specialized funds will in many pockets actually outperform generalist funds, but where we’ll continue seeing that the large franchises, the tier one franchises will likely be generalist funds. I mean, we just saw it in the cycle. The AI cycle went upon us. We had a 2021 fund. We could easily adapt and go into AI and figure out that AI was growing very fast. I mean, if you have an ultra-specialized fund and that’s your remit and that’s the only thing you can invest on, very difficult to change even during our investment period. I will put a caveat on that. We don’t call, for example, ourselves at Chameleon generalist. We call ourselves multi-specialized because our scoring models for the verticals that we track are specialized within Mantis. Because the partnership is specialized, we all focus on different areas. And because we have the Kin network that allows us to tap into that level of expertise, Again, I think the world will be specialized coexistence. Some pockets specialized will do very well, certainly on the smaller fund size, but the big franchises will likely look a little bit more generalist. And as I said, multi-specialized from our perspective is the future. We’ll start seeing more and more funds that are multi-specialized like ourselves. Do you want to talk about AI and how it’ll distort the metrics? No.   Bertrand Yes. I think AI is an exciting moment in the tech industry. It feels in some ways that the same way we had a big distortion coming with COVID and work from home in 2020, 2021. 2021, where suddenly everyone and their mother will build a SaaS company or invest in a SaaS company. AI feels a bit of the same. I mean, to be clear, I truly believe it’s deserved. I mean, we are facing a dramatic shift in how computing is being done in terms of value you can get from software. So at the same time, AI will probably distort this matrix for a long time. We clearly see a split where investments are going, in what startups are being created. So I think, yeah, we will see some distortion. And we know that maybe 50% of all deal value is going to AI in 2025. We have seen single rounds reaching 40 billion, like to OpenAI. We have seen, as you discussed, some seed stage investment of 400 million. So AI investing and AI startups are definitely a beast on their own. And will distort VC metrics for a long time. And we might need two sets of metrics in parallel, you know, AI versus everything else. So that would be an interesting bifurcation in the industry in some ways. I would say it’s fair to separate AI versus non-AI. We reach a point where it’s two different beasts.   Nuno Conclusion So in conclusion, AI has changed the world and it’s changing VC as well, as we discussed earlier in the episode. We have a tremendous momentous occasion for the asset class where venture capital is really bifurcating into very large funds, which no longer are in venture capital or seemingly may be distributed between different asset classes, and the smaller funds, sub-$500 million and sub-$100 million, that keep having the better returns, but also with much smaller scale. We’re seeing a culling of the industry where the industry is definitely getting smaller and smaller and more concentrated at both ends, number of VC firms, as well as a number of limited partners per fund and the interest that some of these limited partners have of being more and more concentrated in their own portfolio allocations. And last but not the least, the discussion around specialized versus generalist, where it seems like there’s some clear winners on some asset classes, on some sizes, in some industries, but on others, there’s other kinds of winners. And so maybe the future is multi-specialized, as I framed at the end. Thank you so much for listening. If you want to check us out and if you want to comment, feel free to send us messages on X, LinkedIn, to both myself and Bertrand, as well as send us an email. Thank you so much, Bertrand.   Bertrand Thank you, Nuno.

Most of you are spending the wrong 80% of your AI budget right now. And the man who said it has been at Stanford for 40 years.This week: we unpack Professor Martin Fischer's uncomfortable 80/20 reallocation and why building digital feedback loops has to come before the AI layer. We sit down with Suffolk Construction's CTO Jit Kee Chin and Speckle founder Dimitri Stefanescu on what happens when the most data-mature general contractor in the US decides the next bet isn't another point solution. We break down why Andreessen Horowitz — the firm behind Facebook, Airbnb and GitHub — has just publicly planted a flag in construction. And we cover our third Fight Night, where TestFit's Clifton Harness and Join's Andrew Zukoski disagree on whether AI compresses or fragments the industry.Three things you can action this week. No fluff.Links and resources mentioned in this episode:Martin Fischer & Bricks & Bytes - COMING SOONSuffolk Technologies' investment in Speckle - https://www.youtube.com/watch?v=HcPDoOwU_pk&t=78sAndreessen Horowitz's public construction thesis - https://www.youtube.com/watch?v=xzaqa52ccng&tBricks & Bytes Fight Night 3 — Clifton Harness vs Andrew Zukoski (full episode) - COMING SOON Bricks & Bytes Fight Night — Mike vs Luigi on AI estimating - https://www.youtube.com/watch?v=j9eVyABO2AQBricks & Bytes Fight Night — KP vs Dustin on the future of construction software - https://www.youtube.com/watch?v=If0jJnX7tZYTilbury Douglas becomes first UK contractor to deploy a humanoid on site - https://www.tilburydouglas.co.uk/tilbury-douglas-becomes-first-contractor-to-launch-a-humanoid-robot-on-construction-site/Breadcrumb — digital safety, orientations and permits synced into Procore - https://breadcrumb.coOur newsletter — Beehiiv subscription page - https://bricks-bytes.beehiiv.com/LinkedIn post for this episode (for comments/engagement) https://www.linkedin.com/posts/owen-drury_a-wild-week-at-bricks-bytes-highlights-ugcPost-7454535708599332864-N61m?utm_source=share&utm_medium=member_desktop&rcm=ACoAABXSR7cBUIyREyKntJC_BA6bnfeuPWgNUtA

Every building you've ever been in was designed by software built in 1997.That's the headline a16z used to put the bat signal out to AEC founders — and Joe Schmidt got dragged for it on LinkedIn.But he's not a tourist. His grandfather invented the concrete pump.In today's episode of Bricks & Bytes, we had Joe Schmidt from Andreessen Horowitz and got into the three attack vectors for disrupting Revit, why the services layer is the hidden prize… and many more!Tune in to find out about:✅ The 3 ways startups are attacking Autodesk's "workflow monopoly" — and which one Joe would bet on today✅ Why replacing Revit in 5 years is unlikely (and why you don't need to)✅ The real "why now" for AEC AI — it's not just LLMs✅ Joe's advice to contractors and designers: adopt fast or get left behind

Most people think the US dollar will rule the world forever.But what if the country that printed $3.3 trillion since 2020 and invaded Iraq while the world cheered is actually heading toward collapse?In 1976, British general Sir John Glubb published The Fate of Empires. He studied 11 empires across 3,000 years. Every single one lasted roughly 250 years.America was founded in 1776.Today, Balaji Srinivasan sits down with us to break down how and why the American empire is ending. Former CTO of Coinbase, former GP at Andreessen Horowitz, Stanford PhD, angel investor in 100+ startups, and author of The Network State. He called Bitcoin, remote work, mRNA vaccines, and the pandemic years before the mainstream caught on.In this episode, he explains how the world's most powerful economy is silently collapsing, and why the next decade belongs to countries like India, powered by technology, talent, and thorium.What you'll learn:- How the American empire peaked on September 10, 2001- Why dollar inflation is a global tax, and what Milton Friedman said about it- The petrodollar: oil-for-dollars, one of history's most profitable business models- Glubb's 250-year rule, and why 2026 fits the pattern of every empire that fell- Why Bangalore now beats San Francisco to live in- What Indians and the diaspora must do right now to ride this shiftIf you're an entrepreneur, investor, policymaker, or student, this episode will change how you see America, the dollar, and India's place in the next century.Watch the full episode now.

Federal Election Commission filings for the first quarter of 2026 showed that billionaires Miriam Adelson and George Soros were the biggest donors backing GOP and Democratic super PACs, respectively, ahead of this year's midterms, while billionaire Marc Andreessen's venture capital firm poured $25 million into a pro-artificial intelligence Super PAC. KEY FACTS According to the filings published on Wednesday night, GOP megadonor Adelson donated $30 million to the Senate Leadership Fund, the major super PAC backing Republican Senate candidates. Filings made by the GOP-aligned Congressional Leadership Fund—which backs GOP House candidates—showed Adelson had given the super PAC $10 million, bringing her overall contribution to $40 million so far this year. Billionaire George Soros, one of the biggest backers of Democratic candidates, donated $50 million to his Democracy PAC in January through an associated group, the Fund for Policy Reform. The Democracy PAC then donated $9 million to Senate Majority PAC—which backs Democratic Senate candidates. FORBES VALUATION According to Forbes' Real Time Billionaire's list, Adelson's total fortune is worth $37.3 billion, making her the 58th richest person in the world. In comparison Soros' net worth stands at $7.5 billion as of Thursday morning. WHAT DO WE KNOW ABOUT FUNDING FROM SILICON VALLEY ?Leaders from Silicon Valley launched the pro-AI super PAC Leading the Future in August last year, with venture-capital firm Andreessen Horowitz among its main backers. Wednesday's filings showed that the venture firm donated $25 million to the political action committee, with $12.5 million each coming from co-founders Benjamin Horowitz and billionaire Marc Andreessen. BIG NUMBER $27 million. That is how much Democratic Texas Senate Candidate James Talarico has raised in the first three months of the year so far, according to the New York Times. Talarico's strong numbers appear to reflect Democratic optimism about the race in deep-red Texas, as the GOP has been besieged by infighting among its top two candidates. SURPRISING FACT Filings for a Win for America, a super PAC backed by sports betting platforms, showed it raised more than $40 million in the first three months of the year. FanDuel contributed $19.5 million while DraftKings' holding company, DK Crown Holdings, donated 17.5 million. An additional $4 million came from Fanatics' subsidiary FBG Enterprises Opco. Read the full story on Forbes: By Siladitya Ray https://www.forbes.com/sites/siladityaray/2026/04/16/billionaire-adelson-pours-40-million-to-back-gop-soros-gives-50-million-to-his-democrat-pac/ Learn more about your ad choices. Visit megaphone.fm/adchoices

Federal Election Commission filings for the first quarter of 2026 showed that billionaires Miriam Adelson and George Soros were the biggest donors backing GOP and Democratic super PACs, respectively, ahead of this year's midterms, while billionaire Marc Andreessen's venture capital firm poured $25 million into a pro-artificial intelligence Super PAC. KEY FACTS According to the filings published on Wednesday night, GOP megadonor Adelson donated $30 million to the Senate Leadership Fund, the major super PAC backing Republican Senate candidates. Filings made by the GOP-aligned Congressional Leadership Fund—which backs GOP House candidates—showed Adelson had given the super PAC $10 million, bringing her overall contribution to $40 million so far this year. Billionaire George Soros, one of the biggest backers of Democratic candidates, donated $50 million to his Democracy PAC in January through an associated group, the Fund for Policy Reform. The Democracy PAC then donated $9 million to Senate Majority PAC—which backs Democratic Senate candidates. FORBES VALUATION According to Forbes' Real Time Billionaire's list, Adelson's total fortune is worth $37.3 billion, making her the 58th richest person in the world. In comparison Soros' net worth stands at $7.5 billion as of Thursday morning. WHAT DO WE KNOW ABOUT FUNDING FROM SILICON VALLEY ?Leaders from Silicon Valley launched the pro-AI super PAC Leading the Future in August last year, with venture-capital firm Andreessen Horowitz among its main backers. Wednesday's filings showed that the venture firm donated $25 million to the political action committee, with $12.5 million each coming from co-founders Benjamin Horowitz and billionaire Marc Andreessen. BIG NUMBER $27 million. That is how much Democratic Texas Senate Candidate James Talarico has raised in the first three months of the year so far, according to the New York Times. Talarico's strong numbers appear to reflect Democratic optimism about the race in deep-red Texas, as the GOP has been besieged by infighting among its top two candidates. SURPRISING FACT Filings for a Win for America, a super PAC backed by sports betting platforms, showed it raised more than $40 million in the first three months of the year. FanDuel contributed $19.5 million while DraftKings' holding company, DK Crown Holdings, donated 17.5 million. An additional $4 million came from Fanatics' subsidiary FBG Enterprises Opco. Read the full story on Forbes: By Siladitya Ray https://www.forbes.com/sites/siladityaray/2026/04/16/billionaire-adelson-pours-40-million-to-back-gop-soros-gives-50-million-to-his-democrat-pac/ Learn more about your ad choices. Visit megaphone.fm/adchoices

A structural shift is underway in the managed services sector as venture capital firms move beyond traditional software and vendor investments to fund MSPs directly. This change is exemplified by investments from firms like Andreessen Horowitz, General Catalyst, and Thrive Capital into MSP-specific companies such as Treeline, Titan, and SHIELD. The driving mechanism is the perceived profit potential at the intersection of advanced AI technology and service delivery, with investors targeting AI-native operational models rather than standard rollups or inorganic growth strategies. The episode's primary evidence centers on Andreessen Horowitz's $25 million investment in Treeline, marking its entry alongside previously funded firms Titan (with $74 million from General Catalyst) and SHIELD (over $200 million from Thrive and ZBS Partners). According to Speaker A, Treeline employs proprietary AI-driven service desk automation and reports resolving 98% of help desk requests with AI, altering the economics and labor requirements for traditional MSPs. Unlike rollups, Treeline is focused on organic growth, leveraging targeted acquisitions primarily for talent rather than client base expansion. Supporting developments include the parallel strategies of Titan and SHIELD, which also integrate Silicon Valley AI expertise and homegrown tooling to drive operational efficiency. While these companies currently deploy AI internally for service automation, Treeline distinguishes itself by offering customer-facing AI-powered MDR and compliance services immediately. All three firms reflect the shift towards vertically integrated models where software, service automation, and client-facing solutions are developed and deployed in-house, creating potential competitive pressure for both traditional MSPs and larger private equity-backed consolidators. Operationally, these developments introduce risks around increased pricing pressure, labor model disruption, and a potential skills gap for MSPs reliant on off-the-shelf tooling. The focus on organic growth and deliberate scaling by new entrants like Treeline signals that the transition for incumbents is not immediate, but the need for MSPs to evaluate their AI adoption strategy is acute. Relationships alone are unlikely to differentiate providers in the long term; practical safeguards must include closing operational efficiency gaps, building internal AI capability, and considering cooperative models to maintain autonomy while reducing risk of margin erosion or client loss. Supported by: Zero NetworksCometBackup

Anj Midha is the founder of AMP, and a founding investor in Anthropic. Most recently, Anj was General Partner at Andreessen Horowitz, leading frontier AI investments. He serves on the boards of Mistral, Black Forest Labs, Sesame, LMArena, OpenRouter, Luma AI and Periodic Labs and is an early angel in ElevenLabs among others. Prior to that, Anj was the cofounder/CEO of Ubiquity6 (acquired by Discord) and a partner at Kleiner Perkins. AGENDA:   04:00 Why the "Scaling Laws are Dead" rumor is dangerously wrong 05:30 The 4 bottlenecks stopping us from reaching Super Intelligence 11:30 Where will the actual value accrue in an AI-dominated world? 12:00 Why Europe is building a "Sovereign Stack" to escape US dominance 15:00 Inside the brutal early days of Anthropic and the 21 VCs who said "No" 19:30 Why the most successful AI startups are ditching the "Profit-First" motive 34:30 The 1885 Industrial Revolution: Why we have a "GPU Wastage" bubble 38:00 Is the CCP actually winning the full-stack AI systems race? 43:30 Monopoly Mafias: Will model providers eventually kill the App Layer?  

April 10, 2026: Andreessen Horowitz just released hard data showing nearly a third of the Fortune 500 has live AI deployments — and the pattern underneath reveals exactly which jobs and functions are next in line. Then: Gallup says global employee engagement just hit a five-year low, and I'm going to argue that metric is fundamentally broken and why your board should stop asking for it. Plus, Microsoft Research coins a term you'll be using by tomorrow — "workslop" — and reveals the hidden social penalty employees face for using AI openly. McKinsey adds a critical wrinkle: your most AI-fluent employees are your biggest flight risk. And a new Wharton study finds that 80% of people follow wrong AI answers with complete confidence — and feel better about themselves while doing it. 

B2B technology is shifting at an unprecedented pace. As traditional sectors grapple with supply chain pressures, shifting workforces, and the demand for personalisation, new frontiers like hardware-as-a-service and physical AI are moving from peripheral concepts to essential infrastructure. For marketers, the challenge is clear: how do you build a category and drive adoption for a disruptive technology that fundamentally changes how the world works?In this episode of the FINITE Podcast, Jodi Norris sits down with Caitlin Allen to unpack the mechanics of category creation and how marketers can spot market signals, tipping points, and growth opportunities within emerging tech. They explore the nuances of marketing robotics, how to structure a team to create FOMO (fear of missing out) while helping buyers overcome their fear of messing up, and the structural forces reshaping B2B go-to-market motions.Caitlin Allen is a seasoned marketing leader who has spent two decades building markets for transformative technologies before they are part of a P&L. She has helped scale category-defining companies across venture capital, deep tech, and consumer platforms—including serving on the executive teams that led Lyft through its IPO and Happy Returns to its acquisition by PayPal, as well as advising ambitious startups as a Partner at Andreessen Horowitz. She is currently the SVP of Market and Chair at Simbe, where she is pioneering Physical AI and bringing "Store Intelligence" to the $28T physical retail economy.Caitlin shares her refined methodology for taking complex, multi-threaded sales cycles to market. She discusses how she conquered narrative homogeny in the robotics space, the five questions every buyer needs to answer during a paradigm shift, and how she integrates an intricate network of AI agents into her team's daily operations - from persona-specific bots and Reddit monitors to leadership coaching agents.If you want to understand how to position disruptive technology and orchestrate a category-defining marketing strategy, this conversation is a must-listen.

Brett Adcock is a technology entrepreneur focused on building companies in robotics, artificial intelligence, and aerospace. Born and raised on a third-generation farm in central Illinois, he developed an early fascination with technology and building systems from the ground up. After attending the University of Florida, he set out to tackle ambitious, capital-intensive industries with the goal of reshaping transportation, labor, and human-machine collaboration. At 26, Adcock founded Vettery, an AI-powered talent marketplace that matched thousands of companies with highly qualified candidates. The company scaled rapidly and was acquired in 2018 for $110 million by The Adecco Group, the world's largest recruiting firm. In 2018, he founded Archer Aviation to develop electric vertical takeoff and landing (eVTOL) aircraft aimed at transforming urban air mobility. During his time leading the company, Adcock helped architect, engineer, and flight-test five generations of aircraft, vertically integrating key technologies including flight software, electric motors, actuation systems, and battery systems. Archer secured a $1.5 billion partnership with United Airlines and positioned itself at the forefront of next-generation aviation. In 2022, Adcock founded Figure, where he serves as Founder & CEO. Figure is building general-purpose humanoid robots designed to address global labor shortages and work alongside humans in manufacturing, logistics, warehousing, retail, and the home. Backed by leading investors including Andreessen Horowitz and Sequoia Capital, the company has raised billions in venture capital and is focused on deploying embodied AI systems at scale. He is also the founder of Cover (2023–present), an AI security company developing non-intrusive scanners in partnership with NASA's Jet Propulsion Laboratory. The technology is designed to passively detect concealed weapons in crowded environments, with the goal of improving public safety without invasive screening. Follow the market: https://polymarket.com/event/ai-bubble-burst-by Shawn Ryan Show Sponsors: SpotOn GPS Fence — trusted by Shawn Ryan for his dog Stanley. The most reliable GPS dog fence: 100% secure from backyard to backcountry with virtual boundaries you control from your phone. No wires, no digging. Sets up in minutes, any size, any shape, anywhere. Learn more: https://spotonfence.com/srs Sign up for your $1 per month trial today at https://shopify.com/srs Get 20% off Rho Nutrition Liposomal NAD+ for clean, sustained energy and sharper focus with code SRS at https://rhonutrition.com/discount/SRS risk-free 60-day money-back guarantee. If you're serious about selling to the Department of War, go to https://SBIRAdvisors.com and mention Shawn Ryan for your first month free. Brett Adcock Links: X - https://x.com/adcock_brett IG - https://www.instagram.com/brett_adcock WEB - https://www.brettadcock.com LI - https://www.linkedin.com/in/brettadcock Learn more about your ad choices. Visit podcastchoices.com/adchoices

Marc Andreessen is a Co-Founder and General Partner at Andreessen Horowitz. The firm now manages over $90BN and has invested in the likes of OpenAI, Airbnb, Coinbase, Anduril and many more. Marc is an innovator and creator, one of the few to pioneer a software category used by more than a billion people and one of the few to establish multiple billion-dollar companies. Marc co-created the Mosaic internet browser and co-founded Netscape (sold to AOL for $4.2 billion). He also co-founded Loudcloud, which as Opsware, sold to Hewlett-Packard for $1.6 billion.  AGENDA: 05:00 — Why Introspection is Overrated: The Dangers of Learning from the Past 08:00 — The One Trait Marc Andreessen Looks For in Every Founder 14:30 — Are the Best Founders Broken? What Makes the Best Founders? 16:00 — "Extreme Ownership": Why Everything Being Your Fault Changes Everything 19:00 — "Do You Read the Comments?" Fame, Criticism & How to Deal with Haters 26:00 — Is Venture Now Go Big or Go Home? The Real Future of VC 30:00 — Does Price Matter Anymore? The Dangerous Truth About Valuations 33:00 — "Stop Chasing Diamonds in the Rough": Why Most VCs Get This Completely Wrong 36:00 — Do You Actually Need to Like Founders? The Uncomfortable Answer 40:00 — Are Companies 75% Overstaffed? The Most Controversial Take on Hiring 45:00 — When Will a16z Go Public?  50:00 — Why Labour Displacement Theory Around AI is Totally Wrong 55:00 — Why Silicon Valley Is More Dominant Than Ever? 01:00:00 — Why a16z Invested $300M into Adam Neumann  01:05:00 — What Still Drives Marc Andreesen? 01:10:00 — What is the Biggest Mistakes VCs Still Make Today?  

On this special segment of The Full Ratchet, the following Investors are featured: Seth Levine of Foundry Eric Byunn of Centana Growth David Ulevitch of Andreessen Horowitz We discuss major conflicts that guests have faced and how they resolved them. The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

Welcome to The SaaS CFO Podcast! In this episode, host Ben Murray sits down with Matthieu Hafemeister, co-founder and CEO of Concourse. Matthieu shares his journey from growing up in Paris to launching a fast-scaling AI startup in New York, drawing on his experiences in venture capital at Andreessen Horowitz and operational roles at Jeeves. Together, they dive deep into how Concourse leverages agentic AI to revolutionize finance teams—from automating workflows across complex data sources to increasing team capacity and strategic output. Listeners will get a behind-the-scenes look at Concourse's rapid growth, its recent $12 million Series A raise, and the evolving landscape of AI for enterprise finance. Matthieu also offers insights on the challenges of founder-led sales, best practices for scaling go-to-market, and why staying lean is a key part of their strategy. Whether you're a SaaS founder, finance leader, or simply curious about the future of agentic AI, this conversation is packed with practical lessons and fresh perspectives. Don't miss it! Show Notes: 00:00 "Startup Growth and Complexity Insights" 06:03 Data Integration for Workflow Efficiency 07:36 AI Adoption Accelerates Across Industries 10:59 "AI Automating Workflows, Not Tools" 13:40 "AI Startup's Breakout Journey" 19:47 Evolving Pricing with Token Model 23:26 "AI Impact on Margins" 25:53 Streamlining Finance Team Workflows 27:31 "Custom AI for Enterprise Success" 30:41 "Proof of Concepts Drive Success" 34:38 "Concourse.ai: AI Insights Hub" Links: SaaS Fundraising Stories: https://www.thesaasnews.com/news/concourse-raises-12-million-in-series-a Matthieu Hafemeister's LinkedIn: https://www.linkedin.com/in/matthafemeister/ Concourse's LinkedIn: https://www.linkedin.com/company/concourseai/ Concourse's Website: https://www.concourse.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

On this special segment of The Full Ratchet, the following Investors are featured: David Cohen of Techstars Jacob Effron of Redpoint Arianna Simpson of Andreessen Horowitz We asked guests for the most important piece of advice that they'd share with folks early in their venture career. The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

This week's Espresso covers news from Meddi, MetaBix, Handle, and more!Outline of this episode:[00:30] – Azos raises $24M Series C[00:44] – Meddi raises $7.8M from GNP Seguros[00:59] – Deeptech startup metaBIX raises $1.3M[01:10] – Handle raises $6M seed round led by Andreessen HorowitzResources & people mentioned:Startups: Azos, Meddi, metaBIX Biotech, Handle,VCs: Kaszek, Kevin Efrusy, GNP Seguros, Médica Móvil, Dalus Capital, EWA Capital. Andreessen Horowitz

David Ulevitch of Andreessen Horowitz joins Nick to discuss American Dynamism: The Future of U.S. Industrials, Backing Companies with Major Production Components, Manufacturing Sovereignty, and Why Space Dominance is Critical. In this episode we cover: Challenges in Venture Capital and Investment Philosophy Handling Startups and Market Pivots Navigating Dual-Use Startups Government Sales and Market Education Long-Term Revenue and Production Challenges American Dynamism Practice and Investment Thesis Supply Chain and Vertical Integration Policy Advocacy and Government Affairs Future of American Dynamism and Energy Investments Guest Links: David's LinkedIn David's X a16z's LinkedIn a16z's Website The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

Tomicah Tillemann, President at Project Liberty Institute, joins the show. Tomicah offers a unique perspective on regulating emerging technology given his time as a venture capitalist and head of policy at Andreessen Horowitz and Haun Ventures. His contemporary focus is on identifying “policy solutions that enable human agency and human flourishing in an AI-powered world.” It's a tall order that he breaks down with Kevin Frazier, a Senior Fellow at the Abundance Institute, Adjunct Research Fellow at the Cato Institute, and a Senior Editor at Lawfare. Hosted on Acast. See acast.com/privacy for more information.

This week we take a look at some viral TikTok clips and react to the insane testimony of Google's Eric Schmidt asking for unlimited energy and an abolition of regulation to help them build nuclear power plants to fuel their catastrophic war of choice with China over AI. And we watch a baffling roundtable discussion at Andreessen Horowitz where a few tech bros opine on the future of capitalism where no one has any money to afford to buy anything because AI has put them out of work. But don't worry, building robots to colonize the galaxy is the new GDP. Or something. I'll have what they're smoking. Join the discussion on Reddit: https://www.reddit.com/r/AcceptanceCriteria/ And on the Discord: https://discord.gg/2Tyj8H9MFF The post E069: Toxic Dreams: A Look at Silicon Valley's AI Delusions first appeared on Acceptance Criteria.

Olivia Moore is an AI partner at Andreessen Horowitz. Moore joins Big Technology Podcast to discuss whether startups still have a real shot at competing with the biggest AI chatbots as ChatGPT, Claude, and Gemini grow more capable. Tune in to hear why she believes the AI economy will be more distributed than many expect, where startups can still win, and how agentic products like OpenClaw could reshape software and work. We also cover AI's image and video app shakeout, chatbot memory, AI companions, enterprise adoption, and what happens to incumbents as every company is pushed to become AI-native. Hit play for a sharp conversation about where value in the AI economy is actually headed. --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Learn more about your ad choices. Visit megaphone.fm/adchoices

Qasar Younis is the co-founder and CEO of Applied Intuition, a $15 billion AI company that adds intelligence to cars, tractors, planes, submarines, and other vehicles—essentially, Tesla or Waymo without the hardware. He was previously COO of Y Combinator, started his career as an engineer at GM and Bosch, and was born on a farm in Pakistan.We discuss:1. Why the biggest AI revolution will play out in mining, farming, construction, and trucking over the next 5 to 10 years, not in software2. Why Qasar intentionally stayed under the radar for nearly a decade while building Applied Intuition, and why most founders shouldn't do that3. The truth about China's AI capabilities and why comparisons to American companies are fundamentally flawed4. The company values that drive Applied Intuition: speed above everything, laugh a lot, half the work is follow-up, never disappoint the customer5. The biggest lessons from Qasar's stint as YC's COO, including that the most successful companies show traction very early6. How reading old books is the best way to build taste—Brought to you by:Omni—AI analytics your customers can trustVanta—Automate compliance. Simplify security.Lovable—Build apps by simply chatting with AI—Episode transcript: https://www.lennysnewsletter.com/p/the-most-successful-ai-company-youve-never-heard-of—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Qasar Younis:• X: https://x.com/qasar• LinkedIn: https://www.linkedin.com/in/qasar• Website: https://qy.co• Reading list: https://qy.co/books—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Qasar and Applied Intuition(04:01) The optimistic vision: How AI will create abundance(08:49) Why anxiety about AI comes from misunderstanding—and how to fight fear with knowledge(12:58) The market sell-off explained(16:31) Self-driving cars: Why 30,000 annual deaths prove we need autonomy now(20:22) The spectrum of physical AI(28:00) How AI is coming just in time(33:26) Why comparing Chinese AI companies to American AI companies is a category error(39:12) Why Qasar finally joined Twitter after staying silent for a decade(45:08) Why successful companies almost always show early signs of traction(50:40) Applied Intuition's core values(56:00) Why the company cleans its own office—and never spent a dollar of raised capital(58:50) Quasar's reading philosophy(01:06:14) How to operationalize listening to naysayers(01:12:53) The importance of decisiveness(01:14:55) Removing emotions from decisions(01:19:02) Why most Silicon Valley CEOs don't have great taste—and how to develop it—Referenced:• Applied Intuition: https://www.appliedintuition.com• Marc Andreessen: The real AI boom hasn't even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom• Elad Gil's website: https://eladgil.com• Bosch: https://www.bosch.com• Berkshire Hathaway: https://www.berkshirehathaway.com• Naval Ravikant on X: https://x.com/naval• Y Combinator: https://www.ycombinator.com• Waymo: https://waymo.com/• Tesla: https://www.tesla.com• DeepSeek: https://www.deepseek.com• Rivian: https://rivian.com• Crate & Barrel: https://www.crateandbarrel.com• OpenClaw: https://openclaw.ai• Sam Altman on X: https://x.com/sama• Peter Ludwig on LinkedIn: https://www.linkedin.com/in/peterwludwig• What Steve Jobs really meant when he said ‘Good artists copy; great artists steal': https://www.cnet.com/tech/tech-industry/what-steve-jobs-really-meant-when-he-said-good-artists-copy-great-artists-steal• 7 quotes on the power of reading from Charlie Munger: https://www.neil.blog/articles/7-quotes-power-reading-charlie-munger• Andreessen Horowitz: https://a16z.com• John Doerr on LinkedIn: https://www.linkedin.com/in/john-doerr-03248211• Gandhi's quote: https://www.azquotes.com/author/5308-Mahatma_Gandhi/tag/truth#google_vignette• Steve Ballmer on X: https://x.com/Steven_Ballmer• General Motors: https://www.gm.com—Recommended books:• House of Huawei: The Secret History of China's Most Powerful Company: https://www.amazon.com/House-Huawei-History-Powerful-Company/dp/0593544633• Maintenance: Of Everything, Part One: https://press.stripe.com/maintenance-part-one• The Autobiography of Malcolm X: As Told to Alex Haley: https://www.amazon.com/Autobiography-Malcolm-Told-Alex-Haley/dp/0345350685• High Output Management: https://www.amazon.com/High-Output-Management-Andrew-Grove/dp/0679762884• The Emperor of All Maladies: A Biography of Cancer: https://www.amazon.com/Emperor-All-Maladies-Biography-Cancer/dp/1439170916• Made in America: https://www.amazon.com/Sam-Walton-Made-America/dp/0553562835• My American Journey: https://www.amazon.com/American-Journey-Autobiography-Colin-Powell/dp/0679432965• Guns, Germs, and Steel: The Fates of Human Societies: https://www.amazon.com/Guns-Germs-Steel-Fates-Societies/dp/0393317552• Collapse: How Societies Choose to Fail or Succeed: https://www.amazon.com/Collapse-Societies-Choose-Succeed-Revised/dp/0143117009• SPQR: A History of Ancient Rome: https://www.amazon.com/SPQR-History-Ancient-Mary-Beard/dp/0871404230• A World Appears: A Journey into Consciousness: https://www.amazon.com/World-Appears-Journey-into-Consciousness/dp/198488199X—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Who dares to make predictions in the current landscape? We do!  Our Predictions are back. Will our track-record continue on a high or will we be fundamentally wrong? Listen in to our Predictions for 2026 Navigation: Intro What will 2026 be all about? AI, AI and … more AI The big Hardware movements Of Start-ups and VCs Regulatory & Geopolitical Headwinds… and the Wars Fintech, Crypto and Frontier Tech 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 Bertrand Schmitt Introduction Welcome to Tech Deciphered Episode 74. That would be an episode about some predictions about 2026. What will be 2026 all about? I guess this year is probably starting with a bang. We saw the acquisition of xAI by SpaceX. We saw an acquisition from Grok by NVIDIA. What’s your take about what would be the big themes in 2026? I guess it would be for sure about AI and space. Nuno Goncalves Pedro What will 2026 be all about? Yeah. I predict a year that will be a little bit more of a year of reckoning in some way. There will be a lot of things that I think we’ll start seeing through. The fact that we are in the midst of an amazing transformational era for technology, the use of AI, but at the same time, obviously, a ridiculous bubble that is going alongside it as we’ve discussed in previous episodes. I think that we’ll start seeing some early reckonings of that, companies that might start failing, floundering, maybe a couple of frauds along the way, etc. I’ll tell you what I will not make many predictions about today, which is geopolitics. Geopolitics, I will not make predictions at all. Who the hell knows what’s going to happen to the world this year in 2026? I don’t dare making any predictions on that. Back to things where I would make predictions. I think on AI, we’ll have a little bit of reckoning. We’ll talk about it a little bit more in detail during this episode. Interesting elements around the hardware and physical space. Physical space, we just dedicated a full episode to it. We won’t go into a lot of details on that, but definitely on the hardware side, we’ll talk a little bit more about it. The VC landscape is going through an incredible transformation. We’ll talk about it today as well and some of our predictions for this year. What will happen to the asset class? It seems to be transforming itself dramatically. Obviously, that has a very direct impact on startups, so we’ll talk about that as well. And then to close a little bit the chapter on this, we will address some regulatory and geopolitical, let’s call it, headwinds without making maybe too many complex predictions. We shall see. Maybe by that time of the episode, we will be making some predictions. You guys should stay and listen to us, and maybe we will actually make some predictions about the geopolitical transformations that we will see this year in the world. Then last but not the least, we’ll talk about fintech, crypto, frontier tech, and a couple of other areas before concluding the episode. A classic predictions’ episode. We normally have a pretty good track record on some of these, but right now, the world is going a bit interesting, not to say insane. Bertrand Schmitt Yes, and going back to some news, Groq technically was not acquired, but, practically, it’s as if it got acquired. I’m talking about Groq, G-R-O-Q. The AI semiconductor company focused on inference AI, and it was late December. It was a way to end the year. This year, we started again with an acquisition of xAI by its sister company, SpaceX. I guess that’s where we are starting. AI, AI and … more AI We are going to start on AI. That’s definitely the big stuff. Everything these days, I guess, is about AI or has to have some connection with AI, or it doesn’t matter. I think every company in the world has seen that. You have to have the absolute minimum on AI strategy. You better execute on this strategy and show results, I would say. For the companies that were not AI native, you truly have to have a way to transform yourself. I guess at some point, the stretch might be too much, and it’s not really reasonable. Then you maybe better stay on what you are doing, especially if you’re in tech, you better be moving faster to AI. Nuno Goncalves Pedro Just to highlight, and I think throughout the episode, you’ll see that there’re obviously a lot of implications that would manifest themselves into capital markets. I mean, we’ll specifically talk about VCs and startups later on. But the fact that everything needs to be AI, the fact that there’s so much innovation happening right now, in my opinion, and this is maybe the first pre-topic to AI, is we’ll see a tremendous increase in M&A activity this year across the board. I mean, we’ve seen already some big acquihires we mentioned in some of our previous episodes, but we’ll see a lot more activity on M&A this year. Normally, that’s a precursor to the opening of capital markets. I predict also that there will be a reopening of the IPO market that never really reopened last year, to be honest. M&A, a lot more, reopening of the IPO market. Normally, it happens in the second or third quarter of the year. That’s what my M&A friends tell me. First quarter of year, everyone’s figuring out stuff. Then last quarter of the year, things should be more or less closed. Maybe the third quarter is the big quarter. We shall see. But definitely, as a precursor to our conversation today, I think we’ll see a lot of M&A, and we’ll see reopening of the IPO mark. Bertrand Schmitt I guess last year was not as big as you could expect on M&A given the tariff situation announced in April and May. I mean, it became quite tough to do IPO in such market conditions. Definitely, we can hope for something dramatically different in 2026. I guess talking about public markets and IPO, I guess the big one everyone is waiting for is SpaceX. SpaceX getting even more interesting with its xAI acquisition. Nuno Goncalves Pedro Do you think that because of the acquisition, it’s more likely that it will happen this year, or because of the acquisition, it’s less likely that it will happen this year? Bertrand Schmitt That’s a good question. My guess is the acquisition of xAI is all about xAI needing more financing and cheaper financing. This acquisition is a pathway to that. SpaceX being a much bigger company, a company that is also making much more revenues. I could bet that there is higher probability that, actually, SpaceX will go public in order to finance itself. At the same time, will it have enough time to prepare itself for the IPO given this acquisition just happened? Can they do that in 6 months? I mean, if anyone can do it, I guess it’s Elon Musk. It’s a strategy to present an even more attractive company with an even more interesting story, a story of vertical integration from AI to space. I guess the story as it’s presented itself right now, it’s one about having your AI data centers in space. Because in space, you have much better solar energy production with solar panels. You have a perfect cooling situation because you are in space. Thanks to Starlink, you have the mean to communicate between the satellites and with Earth itself. I think if someone can pull up a story like AI data center in space, I guess Elon Musk can. There is, of course, a lot of questions about is it practical? Is it economical? Yes. I certainly agree. I’m not clear on the mass, and can you make it work? Again, I mean, Elon Musk single-handedly, with SpaceX, managed to transform the space market on its head. I mean, they are the biggest satellite launching company in the world. They have the most satellites in the world. I mean, I’m not sure I would bet against him, and I guess I would probably believe that he could pull up something. Time frames, different story. The 2-3 years data center in space for AI as cheap as on Earth, I have more trouble with that one. I mean, it’s a usual suspect with Elon Musk. You promise something unachievable in a few years, but, ultimately, you still manage to reach it in 5 or 10. Again, I would not bet against the strategy. Nuno Goncalves Pedro Yeah. I’ve talked to a couple of space experts, people that have launched rockets, and have worked JPL, NASA, and a couple of other places, etc. For what it’s worth, their feedback is, “No way in hell, and we’re decades away.” We’ll see. I mean, to your point, Elon has pulled very dramatic stuff. Not as fast as he normally says he’s going to pull it, but within a time span that we all see it. Difficult to bet against him. In terms of actually the prediction, maybe to respond to the prediction as well, will SpaceX IPO? I’m going to make a prediction that has a very high likelihood of missing the mark, but I think Tesla’s going to buy and merge them both into it. It’s going to become a public company through Tesla. That’s my hypothesis. Bertrand Schmitt No. That’s supposed to be it. That’s how you solve that. Nuno Goncalves Pedro And Elon controls the whole universe. X, xAI, Tesla, SpaceX, all under one umbrella beautifully run. And SolarCity is well in there, of course, so wonderful. Bertrand Schmitt That’s possible. Certainly, you are not the only one thinking Tesla will acquire or merge with SpaceX. To remind everyone, Tesla is around 1.3, 1.5 trillion market cap. Depending on the day, SpaceX seems to be valued at similar range, 1.2, 1.3 trillion. It looks like it’s the most valued private company at this stage. These are companies of similar size, so that’s one piece of the puzzle. When you think about the combined company, we could be talking about a 3 trillion entity. Playing right here with the biggest companies in the marketplace today. Nuno Goncalves Pedro With a couple of tweets from Elon, it will rapidly get to 4 to 5 trillion. Bertrand Schmitt That’s so tricky. Nuno Goncalves Pedro Yes. On AI and back to AI, one thing I think that we’re about to see is this will probably be the year of agentic AI. Obviously, we predict a lot of growth on that side of the fence, in particular on the enterprise B2B side. We see a lot of opportunities coming through. From our perspective, at least at Chamaeleon, we generally believe that there’s going to be a lot of movements on agentic AI. It’s also going to be probably the year of the first big fails of agentic AI that will be newsworthy. There will be some elements about that loop and how it gets closed that will happen. I think we might see some scandals already. We’re already seeing the social network of bots talking to bots. We will see other scandals going on this year even in the consumer space and in the bot to bot space, which we now can talk about or in the AI agent to AI agent space. My prediction is we will see some move forwards. There’ll be some dramatic funding rounds along the way. We’ll see a couple of really cool things out of the gates coming out that are really impressive, but we’ll also see the first big misses of the technology stack. I don’t think we’ll go fully mainstream yet this year, so it’s probably maybe something more for 2027 along the way. That would be my prediction again. I think enterprise will lead the way. We’ll definitely see a lot of stuff on consumer as well that is cool. Then we’ll all have our own personal assistance in our hands, basically, literally in our phones. Bertrand Schmitt Going back to agentic AI, we also started the year with some pretty dramatic move. I mean, the launch of Clawdbot, renamed OpenClaw. I mean, this stuff took fire in like a week or 2. It was coded by just one person who actually didn’t even code the product but used AI to build the product, 100% used AI, proposing some new ways also to leverage AI to do coding. He has a pretty unique approach. It’s not vibe coding. I would say it’s a better way to do that. Then the surprising evolution with the launch of a social network for AI agents, Moltbook. I mean, this stuff, probably there is some fake in it. But at the same time, I think it’s quite impressive because it’s the first time we see truly 100,000 plus agents communicating directly to each other. Yeah. I mean, that’s the first time we see surfacing the possibility of some sort of hive mind on the Internet. It’s pretty surprising. Right now, all of this is a hack done in a few days. By end of year, by 2 years, 3 years, we might discover that, actually, the best approach to AI might not be the AI assistant like we are doing today, but a combination of hundreds of thousands of AI working closely together. We might be witnessing the first sign of new intelligence in a way. Nuno Goncalves Pedro Things like this social network might either be Skynet, the beginning of Skynet. They might be the beginning of Her, or they might just be a fad and nothing really happens. It’s just interesting to see what these agents are doing. Bertrand Schmitt Totally. Nuno Goncalves Pedro Obviously, there are real and clear and present dangers of some of the integrations of AI we’re seeing in the market. Interesting enough, and I’ll ask you for your prediction a bit, Bertrand. I think we’ll probably see the first big mishap of AI being used in some infrastructural decision in the age of AI. I mean, we’ve seen AI issues in the past and software issues in the past. We talked in previous episodes about that as well. Mishaps of software that have led to people dying. But I think probably the first big mishap will happen this year as well. Very public mishap of the use of AI and serve its interactions with infrastructure or something that’s very platform related, etc, that will have big impact that everyone will notice. That’s my prediction for the year as well. We’ll have the first big oops moment, as I would call it, for AI in this new age of full on AI. Bertrand Schmitt I would say first some perspective. I think today, people are not using AI directly for life and death decision, at least not that I’m aware. We’re not going to let AI fly a plane, for instance, tomorrow so you can be, reassured. At the same time, given there is such a race to AI, there definitely might be some mistakes. We were talking about the social network for AI agents, Moltbook. Apparently, all the keys used to secure the AI were shared by mistake because it was not properly locked down. We can see that indirectly, mistakes will be made for sure. Two, it’s highly probable that some people will trust AI too much to do some stuff, and this stuff might not work and might have some grave consequence. Hopefully, there is not so much of this. Hopefully, it’s mostly AI used for the good. But you’re right. I mean, at some point, the more we use the technology, the more there would be issue. I mean, it’s highly probable. Nuno Goncalves Pedro That will lead me to another prediction, which is, and we’ll talk about more of it later, but it probably will lead to the first significant movement in terms of regulatory environment certainly in the US at some point if it happens in the US in particular, where there will be some movement that will be like, “Hey, you guys can’t do this anymore.” Because this will probably emerge from mismanaged interfaces. From systems having access to stuff that they shouldn’t have access to in the first place. Talking a little bit more about what’s happening in AI. You’ve already mentioned some of the issues that relate actually to security and cybersecurity. We keep talking about AI. We keep talking about all these infrastructure pieces and platforms that are being built. I think we’ll have a lot more incidents like the one you just mentioned where things will be shared that shouldn’t have been shared, where people will break systems and get into it, etc. Let’s see where that takes us, which is a little bit ironic because, obviously, with AI, the promise is that cybersecurity becomes more robust as well because there’re agents working on our behalf on the cybersecurity side. There’s also agents working on the other side. Bertrand Schmitt It’s a constant race. It’s the attackers, defenders. Each time you have new technology, you have a new race to who is going to attack or defend the best. Each new wave of technology, it’s an opportunity to challenge the status quo. Nuno Goncalves Pedro The attackers have been winning, and I feel they’ll continue winning in 2026. I think it’s going to still be a year of attack. We’ll see more and more breaches, more and more stuff that will happen. Bertrand Schmitt I don’t know if they will win. I mean, it’s normal that they win once in a while. For sure, some infrastructure is not updated as it should. Some stuff are not managed as it should, so there will always be breaches. I don’t know if things are dramatically going to change because, again, everyone who cares who is going to update his infrastructure with AI for defense. There is no question that you have no choice. We will see. That I don’t know. For sure, AI will be used to attack directly with AI. Maybe you’re able to do bigger, larger scale attack. Or thanks to AI, you are simply able to create new type of attacks more easily. AI can be used behind the scene as a way to prepare and organise new type of attacks, even if it’s not used directly live in the battle. Nuno Goncalves Pedro One topic that we’ll come back to later is the geopolitics of everything, but maybe more broadly. On the geopolitics of AI, it’s very clear that we have an arms race going on. Obviously, the US on the one hand, China on the other hand is the two extremes, putting tremendous amount of capital into data centers just at the base of that infrastructure. Chipset development, chipset access, a huge theme in terms of the export restrictions, etc, that are being forced by the US. I think it will continue. From a European standpoint, obviously, they’re stuck between a rock and a hard place, to be very honest. Let’s see what happens on that side of the fence. My view of the world is that certainly from a US and China perspective, we’re going to see a lot more movements in 2026, like big movements. The Chinese movements we always see in delay.  It takes us a couple of months, sometimes even more than that to understand exactly what’s going on. I think we’re going to see some huge moves this year in terms of the States, the United States of America, and China really pouring capital into the creation of the next big winners around AI. I think the US is obviously more visible. We see a lot of these companies. We’ve just discussed xAI and its acquisition by SpaceX or merger. I don’t know what they’re calling it exactly. Effectively, on the China side, the movements I think are already very big. As I said, it will take a while to figure out exactly what those moves are. One thing that I propose is that at some point, China will have very little dependency on chipsets from the US. I’m not sure it’s going to happen this year, but I think the writing is on the wall. Irrespective of any other geopolitical issues that is coming to the fore at this moment in time. That’s one of the key areas or in arenas of fight. Bertrand Schmitt It makes sense. If you are China, you will look at what happened. You would think that you cannot just depend on the largest of one country. It makes rational sense, the same way it makes rational sense for the US to limit exports to China because there is value to delay some peer pressure that could use these technologies for good but also for bad. If you were an ally of the US, that would be one thing. But when you are not an ally of the US, that certainly should be a different perspective. Maybe one last point concerning agents, I think there will be a lot that will revolve around coding. We can see OpenAI with Codex. We can see Cloud with code. There was, of course, [inaudible 00:18:28] that was trying to be big on agentic coding. I think agentic coding was one of the big transformation in 2025 and is going to get bigger in 2026. I think for a lot of people who do coding, there was a radical transformation in terms of what you can achieve, what you can do, how much you can trust AI to help you code. I start to think we might see this year, the replacement of not just one AI replace one coder, but one AI replace a full team because of the new ability to manage that at scale. Coding might be a common activity where you are going to think about outcomes, think about objective, think about how you organise, but not really coding by itself anymore. A big change, like you used to code, directly your hand on the stuff, but step by step, everyone is going to become a manager of agent. I think in one year, we saw enough transformation to think that in the coming year, the transformation can be even more dramatic. Nuno Goncalves Pedro The big Hardware movements Now switching gears to hardware. Obviously, a lot of movements in 2025 and over the last few years. One piece of thesis that we’ve had long-standing at Chamaeleon is that we will see the emergence of AI devices. Some of them have been tremendous failures as we discussed in the past. I predict that we’ll have a couple of really interesting full stack AI devices in the market this year. Why does that matter? Because, as many of you know, obviously, there’s compute that can happen in data centers and cloud infrastructure all over the world, but also there’s compute that can happen at the edges. The more you can move to the edges and the more you can create devices that actually allow you to have user experiences that are very distinctive at the edge, the more powerful some of these devices might become. I predict Apple will not be the first to launch anything on this. I predict probably OpenAI, after the acquisition of IO, will maybe not launch something this year, but will announce something this year. I’ll step back on that prediction. They’ll announce something this year, but maybe not launch. But we’ll start seeing some devices that have some interesting value in the market, probably devices that are AI devices, but they are very focused on very specific user flows, and so very much adequate to specific activities. I won’t make a prediction on that, but I think areas that would make sense for that to happen would be obviously around fitness, health, et cetera, et cetera, where we already have the ascendancy of products like Oura Ring and others out there. Definitely, that’s one area that might have quite a lot of developments. I think AI-first devices, devices that are very focused on compute at the edges, providing user flows that are AI-enabled to end users, we’ll see a lot more of that and a lot more activity this year. Again, I don’t think Apple will be necessarily ahead of the game. Again, maybe OpenAI will give us something to at least think about and look forward to. Bertrand Schmitt First, I’m not sure it will be that transformational because if it’s not in your phone, in your pocket, there is only so much you can do with it, and there is only so much computing power you will have. I’m doubtful it would be really impactful this year. Nuno Goncalves Pedro I feel we’ve been discussing this shift of paradigm in input and output. For me, some of these devices could lead to that shift. Because, again, a mobile phone is not a great long-term paradigm for the usage that we have because it’s really constrained by the screen. The screen is really what takes most of the battery life away. If we didn’t have that screen, what could we do? If we have the block that is as big as a mobile phone, and it didn’t have a screen, it was just compute, that’s a mini computer, a microcomputer. Bertrand Schmitt That’s a fair point, but I don’t see that transformation this year. That’s really more my point. I can see that you can have AI-enabled smart glasses, and it’s clear there is a race to AI-enabled smart glasses. My point is more to go beyond the gadget, it would take quite a while. It would need to have cameras. It would need to analyse what you see. It would need to hear what you hear. Again, it might come, but then at some point, it would be okay, what do you do with it? We have the example of the movie Her. That’s showing Her what it could be. There are definitely possibilities. It’s clear that if you take the big VR headset like the Apple Vision Pro, there is a failure from that perspective in the sense that I think it’s a great, amazing device. The big problem is that it’s doing way more that makes sense. I think there will be a clearer separation between your smart AR glasses that has to be light, that has to be always unconnected, and that’s primarily there to help you make sense of the world around you. The true VR headset that doesn’t really require much in terms of AI, and it’s just there to immerse you in a different world. For this, we know, unfortunately, in some ways, that there is not a lot of demand for it. Maybe there is little demand because you are too hidden in your own world. The technology is not working well enough yet. There are a lot of reasons. But I think Apple trying to do both at the same time, AR and VR, with the Vision Pro, was a pretty grave structural mistake. I think we would see a clearer line of separation between the two. There is bigger market opportunity for AR glasses. That, I certainly agree. There is opportunity to connect that to a computing device. As you talk about, your glasses are your screen, your phone becomes something in your pocket connected to your glasses. Nuno Goncalves Pedro For me, Apple has their way of doing things. From the perspective of what you said, they normally really plan their devices. Even if it’s a big shift in terms of a new area, like they tried with the Vision Pro, and we criticised them for launching it as a device that should have been more of a dev device that they really launched as a full-on device, but that’s their playbook, classically. I think Apple needs to change how they put products out and how they experiment with those products, et cetera. I think they have enough money to be doing everything all the time and figuring it out. If they don’t want to put it out, then they need to do a lot more hell of testing internally with their silos, but they should be playing across all these arenas, VR, AR, everything. They just should put devices out that are either ready for prime time, or they should call it something else. They should call it like this is a dev device or whatever it is. Bertrand Schmitt I agree with you. My complaint is more that it was marketed as a consumer device when it was not. It was a true developer device. Two, they tried to mix the two at once, and it made no sense. No one is going to walk in their home or in the street with their Vision Pro on their head. You have to be deranged, quite frankly, to have use cases like this. I think that for me is a crazy mistake from a company like Apple that prides itself in pure UI, pure user interface, very well-designed device for one specific use case, not mixing the two use cases. We still don’t have Macs with a touchscreen, you know?  We still don’t have an iPad with a good OS that makes use of this great hardware. For some strange reason, they decided to mix everything in the Vision Pro with a device that weighs a ton on your head and is so uncomfortable. That’s why, for me, I’m like, “Guys, what is wrong? Why did you let this team run crazy?” I hope at some point, Apple will go back to the drawing board. My understanding is that that’s what they are doing. They are going to have two devices, one smart glasses, an evolution of the Vision Pro, just focus on VR. They might actually abandon the concept of the pure VR-oriented headset. Because, from a market size perspective, it might not be big enough for Apple, quite frankly. Nuno Goncalves Pedro I read on all of the above, and people at this point was like, “Why are then players like Samsung and others not doing it. LG, et cetera?” Because those players historically have not invented new categories. They’re amazing at catching up once the category is invented, and then they scale the hell out of it, and that’s what these companies have been exceptional at. I wouldn’t see a dramatic innovation, I think, in terms of devices coming from any of the big ones on that side of the fence. Not to disrespect them in any way, but I think that’s not been their playbook ever. Again, if the origination doesn’t come from a start-up or from an Apple, I don’t see those guys going after it. My bet is that we’ll see some start-up activity and, again, hopefully, some announcement from IO now within the OpenAI world. Bertrand Schmitt I would slightly disagree with you. I see where you are coming from. But take the Samsung Galaxy Note, that sudden much bigger headphone that no one was doing that was launched by Samsung, at some point, it forced Apple to launch an iPhone Max. Let’s look at the Z Fold that Samsung launched 7 years ago, copied by everyone. Now Samsung launching a trifold. Apple has still not launched their foldable phone. I think there is a mix, actually, of sometimes- Nuno Goncalves Pedro For me, that’s not a proper new category. It’s still a mobile phone. It just happens to have a screen that folds in half. Bertrand Schmitt The iPhone was still a mobile phone, you could argue.  Nuno Goncalves Pedro No. I think the iPhone was…  I could actually agree with you on that point. Maybe Apple is not as innovative in that case. I think what Steve Jobs was exceptionally good at in terms of his ability as this master product manager was to be an exceptional curator of user flows and user experiences, and creating incredible experiences from devices based on that. That was his secret sauce. Could you say, “Wasn’t all of this stuff already around?” It was. You just put it all together very neatly and very nicely. But if you’re talking about significant shifts in how a category is done, the iPhone was a significant shift in how the category was done. The Fold is still an interesting device. I actually have a Fold right now in front of me. The 7 that you highly recommended to me that we both got, the Z Fold 7. I think they do amazing devices. I don’t think they normally are the most innovative players. Then, when they come to innovation, it comes from technology edges. Obviously, they have Samsung Display, there’s a bunch of other things. They had the ability to do foldable screens in-house themselves. Bertrand Schmitt I don’t disagree with you. I think there is an interesting situation where some companies have some strengths, another one has some strengths. My worry with Apple is that this was not demonstrated with the Vision Pro. The Vision Pro was a hot pot of technologies barely integrated together, with use cases absolutely not well-defined and certainly not something that makes sense for most of us. There is a question of has Apple lost it? While Samsung actually keeps doing their own stuff, that, yes, might be more minor improvements, but at least they are doing it. Because it looks like Apple is missing the train on even the minor improvements. By the way, you might not be aware, but Samsung launched its Vision Pro competitor. Interestingly enough, it might be a better product in some ways, being much lighter and much more comfortable. Nuno Goncalves Pedro We should play around with that and report back to our listeners. Of Start-ups and VCs Moving to venture capital and the startup ecosystem and what’s happening there, I think it is very much a bifurcated environment, and it’s bifurcated for both VCs and for startups. If you’re a startup in the AI space, and you have the hottest team since sliced bread, and you can create FOMO at the speed of light, you can raise ridiculous rounds. Five hundred million at the $3 billion, or $4 billion, or $5 billion valuation, and you still haven’t really even started. First round, you can raise 500 million. That’s back to the whole discussion on Bubble and where are we, et cetera. Some of these companies might actually become huge, some of them might not. But definitely, we are seeing really the haves and have-nots on the startup ecosystem with incredible teams raising a lot of money very, very early on or mid-stage if they’ve already existed for a while, and then the rest not being able to raise. We see a lot of non-necessarily AI sectors, some of the areas of SaaS that don’t necessarily have AI in it, or fintech, or the consumer space that are really, really struggling. If you don’t have an AI story for your startup right now, it’s extremely difficult to raise money unless your numbers are just the best numbers ever. That’s, I think, the first part of the element of bifurcation that we’re seeing today. The second element of bifurcation that we’re seeing today in terms of fundraising is for VCs themselves, and really propelled by the large VC firms raising more and more capital in recent orbits, announcing 15 billion across funds raised. Lightspeed, I think, had made an announcement a couple of weeks ago as well. They’ve raised a bunch of money as well. The big guys are all raising a lot of money. At some point in time, the question some of you might ask is, “These VCs are redeploying more and more money if they have a couple of billion for a VC fund. How does that look like? Is that still VC?” My perspective, I’ve shared before in some of our previous episodes, is that that’s no longer venture capital. At that point in time, we’re talking about something else. Private equity hedge funds, if you want to call them, maybe funds that are really driven by growth investment or late-stage investment. If you have a couple of billion under management, you’re not going to make your returns by writing a $3 million check in a series seed and leading that round.  That has implications for everyone in the ecosystem. It has implications for smaller funds that obviously have a lot more difficulty in raising capital. It’s difficult to differentiate. Last but not least, also for startups that really continue searching for that capital that is out there. Andreessen Horowitz, for example, runs Speedrun, which is a great program for companies around consumer in particular. Initially, it was a lot for gaming. But at some point in time, Andreessen Horowitz could decide that they don’t want to invest more in you. They just put money from Speedrun, which is obviously a very small check compared to the very large checks they could write mid to late stage and that will have an effect on you as a startup. What happens at that point in time if Andreessen Horowitz is not backing you up in later stages? More than that, what happens if I can’t get these big funds interested in me? Are the small funds still valuable to me? Punchline, my view is yes. Obviously, we’re a smaller fund, so there’s parochial interest in what I’m saying. Small funds can still create a ton of value for you, also in terms of credibility, ability to accompany you in those first stages of investment, and the ability to bring other larger investors later down the road as well. There’s definitely a big movement happening in terms of the fundraising for VC funds, which we shouldn’t neglect, which is the big guys are raising a lot more capital and are therefore emptying the market to smaller funds that are having more and more difficult raising at this point in time. We had discussed that there would be a need for concentration in the industry, that micro funds would need to concentrate, and we didn’t have the space for so many micro funds as we had around. But the way it’s happening is extremely dramatic at this moment in time. I think it will continue through 2026. Bertrand Schmitt Remember a few years ago, with the rise of AI, there was more and more of the question about, “What’s the point of SaaS at this stage?” Because SaaS was around for 15 years. Basically, how do you come up with something new that was not already tested, validated by the market? How do you bring something new? We say this was reinforced to the power of 10. If your product is not clearly built from the ground up for a new use case enabled by AI, anyone could then might have built your product 5, 10 years ago, and therefore, why now has no clear answer, and it’s a big problem. I’m still surprised myself to still see some entrepreneurs where you talk to them about AI because you don’t see them in the deck, and they explain to you, “It’s not yet there,” and you’re like, “What’s wrong with you guys?” Fine. Do whatever you want. Do a small business and whatever, but don’t think you can come up pitch and raise without an AI story. The second category is people who come with an AI story, but you can feel very quickly, I guess you saw that many times, Nuno, where just a story layered on top with little credibility. It’s not better. It’s not enough to just have a story. Your business needs to be radically built differently or radically proposing some brand-new use cases that were impossible to solve 5 years ago. Nuno Goncalves Pedro To stack up on that, absolutely in agreement. If you’re just adding to the story, and it’s an afterthought, and you’re just trying to make the story somehow gel, once you go into one or two layers of due diligence, your investors will very quickly realise that you’re not really AI-first or dramatically AI-enabled or whatever. It’s just you’re sort of stacking something on top of another thesis. It needs to make sense from the product onwards. It’s not just, let’s just put it together with chewing gum, and magically, people will give you money. It was true also if we remember the good old crypto blockchain days, where everyone’s investing in crypto. A lot of stories that didn’t make much sense. In that sense, it’s not very different. I would go one step further. I think in the world of the VC winter that we’re a little bit in, where it’s more and more difficult if you’re a smaller fund to raise your fund at this moment in time, there’s a lot of sources of distinctiveness still talked about, like proprietary networks, access to deal flow, fast track record, all that stuff that really, really matters. But our bet continues at Chamaeleon continues being that you need to be AI-first as a VC fund yourself. You need to have core advantages in using not only readily-available AI tools or third-party available AI tools, data sources, technology stacks, but actually building your own stack over time, which is what we did with Mantis at Chamaeleon. Again, just to reinforce that, I think we’re at the beginning of that stage. We, Chamaeleon, are ahead of the game, but we think that the rest of the market will have to move towards that as well. Still, to be honest, very surprising to me to see that many significant large players are doing very little still around some of these spaces. They have data scientists. They’re running some tools. They’re running some analysis and all that stuff, but it’s still, again, back to the point I was making for startups, all glued up with chewing gum. It doesn’t all come together nicely, which it does need to from a platform standpoint. Bertrand Schmitt It’s quite surprising. I agree with you that some VC funds might think that they can do business as usual in that brand-new world. It’s difficult to believe. Nuno Goncalves Pedro Maybe moving a little bit toward the capital formation piece. We already discussed the M&A space really accelerating. We’ve also discussed the IPO market and some predictions on that. Secondaries, there’s obviously a lot of liquidity coming from secondaries from mid to late stage. I think it will continue throughout the rest of 2026. A lot of activity in buying, selling in secondaries as some asset managers are becoming more distressed, as some very high net worth individuals and family offices are becoming more distressed as well, at the same time, where there’s a lot of opportunities to potentially arbitrage around some investments. I believe a lot of money will be made and lost this year by decisions made this year, just to be very, very clear in terms of equity, purchases, et cetera. Exciting year ahead of us. Definitely a very, very interesting market ahead of us. Secondaries, M&A, growth, and late-stage investing, also, early-stage investing will continue just for those that were wondering. Last but not least, the public markets, the IPO market as well. Bertrand Schmitt One of the big questions for the IPO market would be, will SpaceX go public? Would it be good for the startup ecosystem? Because suddenly that they go public, it would be to raise money. If they raise money, will there be any money left for anybody else? That would be an interesting test of the market. For sure, it would be proof that market are risk on financing a new IPO like this one. Or as you said, maybe there is no IPO, and it’s a merger with Tesla. Time will tell. Nuno Goncalves Pedro Regulatory & Geopolitical Headwinds… and the Wars Moving maybe to our topic of regulation and geopolitical headwinds, as we’re seeing … definitely not tailwinds. The Google antitrust verdict and, obviously, the remedies are expected to come forward now, and a lot of people are saying, “There are some risks of structural separation.” What do you think? Is it cool, but nothing will happen in the end dramatically? Alphabet or Google? I’m not sure, actually. It’s Google LLC. I think that’s the case. It’s The United States versus Google LLC. Bertrand Schmitt I’m not sure. Personally, I’m not a big fan. I think there needs to be a better way to manage some anticompetitive behavior. I’m not a big fan. There was this temptation to do that for Microsoft 25 years ago. Look at what happened. No one needed to buy Microsoft to leave space for others. I see the same with Google, and I guess they are happy to not be the number 1 in AI today, but to have an open AI in front of them. Even if they are doing a great job, by the way, to move forward and go faster and faster. Personally, quite impressed now with some of what they have released. Gemini 3 is doing great from my perspective. I’m not a big fan of this. I think to be clear, it’s important that bigger companies don’t behave anticompetitively, but at the same time, we need to find the right approach where it’s not about breaking these companies, and it’s also not about forbidding them to do acquisitions. Because then you end up with what NVIDIA just did with a $20 billion acquihire IP licensing type of acquisition, because they didn’t want to have the uncertainties. They didn’t want to wait 1–2 years in order to acquire the people and the technology, so they organised it in a different way. But I don’t like that. I think they should be able to acquire companies without facing so much uncertainty. To be clear, it’s not new. Uncertainty when you are Google, NVIDIA, or others, it happens. It has happened for a decade plus, 2 decades. I think there needs to be, for sure, some safety valves. At the same time, we want an efficient capital market. An efficient capital market need companies that can acquire other companies. If you don’t do that efficiently, it will be worse for the entrepreneurs, it will be worse for the investors, it will be worse for everybody. I think we have not reached a good equilibrium from my perspective. We need more efficient acquisition process. And at the same time, we need to also enforce faster anticompetitive behavior. Because what you talk about concerning Google, this is a case that was what? That is 10 years old. You see what I mean? This is way too long. If you’re a startup, you are dead by then. It’s like the story of Netscape facing Microsoft. They were dead long after the fact. I think we need a different approach. I’m not sure the best answer. I’m not sure we’ll get a better approach. There are probably too many vested interest. My hope is that it will get better with this current administration because, certainly, the past administration was very anti acquisition and efficient markets. Nuno Goncalves Pedro We’ve talked about the European Union AI Act a bunch of times, so I don’t want to spend too many cycles on that. The only effect that I would say is we are seeing in very slow motion the splitting of the Internet. I once had Tim Berners-Lee, by the way, shouting at me that we were going to break the Internet when we were applying for the .mobi top-level domain. I was part of that consortium that eventually did get the .mobi top-level domain, and I had him shouting at us. But, apparently, this is going to split the Internet, Tim. So in case you’re listening. Because it will create all these different rules. If your data is relating to consumers there, then it’s treated in a different way, and The US is… Well, obviously, we have the case of California with its own rules and laws. I don’t know. I feel we’re having a moment of siloing that goes beyond economic and geopolitical siloing. It will also apply to the digital world, and we’ll start having different landscapes around it. We’ll see how this affects global expansion of services, for example, around AI, particularly for consumer, but I don’t foresee anything dramatically positive. Recently, we had the whole deal around TikTok finally having a solution for their US problem where there’s now a US conglomerate magically that owns it. The conglomerate doesn’t magically own it, they just straight up own it for the US. But it was driven by many of these concerns around data ownership. Where’s the data? Where is it based? I think a lot of other concerns that have to do with the geopolitics of China, obviously, being the basis of ByteDance, the owner of TikTok, that still is a significant owner, by the way, in TikTok in US. Then also the interest in the economics of making money out of something as powerful as TikTok, to be honest, in The US. Just to be clear, I don’t think this was all about the best interests of consumers. It was also about money. Just follow the money. Bertrand Schmitt There are for sure, some powerful interest at play. But let’s be clear. I think one is data, as you rightfully said, but the other one is algorithm. It’s not as if China is authorising any competitor on its territory. They have blocked access to most of the Internet platforms from the US, either finding new rules or just trade blocking them. So I don’t think it’s fair competition. You don’t want some of that data in China about the US or European consumer. Three, it’s about the algorithm. If suddenly, you are a foreign power, and you can as we know in China, you better follow what’s required of you from the Chinese Communist Party. You cannot take a chance with influencing other stuff like elections in other countries. It’s fair from the US perspective. One could even argue it’s fair from a Chinese perspective to want that. I think the only one in the middle who doesn’t really know what they want is Europe because on one side, they want to benefit from American platforms, on the other end, they want to have some controls. On the other end, they don’t create the environment for startups to flourish. So in that weird situation where they have to accept some control by the big US providers and either provider of underlying infrastructure or provider of consumer business facing services. Then they try to regulate them. But I think they are misunderstanding the power relationship, and I think some of this regulation would get some blowback, at least by the current administration. Just, I believe, this morning, there was some news around X being under a criminal investigation in France. This is not going to end well for the French startup and VC ecosystem. This is not going to end well for France and Europe when you depend so much from your American friends. Nuno Goncalves Pedro Regulation will be weaponised. Regulation constraints around exports, all of this will be weaponised geopolitically, and the bigger guys will normally win. I think that’s normally what we’ve seen. Just on TikTok just to… And you guys, if you’re listening to us, just see if you see a pattern here, but obviously, 19.9% still owned by ByteDance of the TikTok entity in the US. It was initially said that 80% of the TikTok entity is owned by non-Chinese investors. Initially, people were saying US investors, and then they changed it to non-Chinese because MGX, I think, has 15% of it. MGX is based in the UAE, connected obviously to Mubadala, the Abu Dhabi sovereign wealth fund. Silver Lake is in there, I think, with 15% as well. Oracle as well with 15%. Those three are the big bucket owners together, 45%. Silver Lake having collaborated with MGX before, and I’m sure a lot of connectivity there. Then you still see a pattern in this in terms of shareholders. If you don’t, then just Google it. Dell Family Office, Vastmir Strategic Investments, which is owned by billionaire Jeff Yass, Alpha Wave Partners, obviously involved with a bunch of things like SpaceX and Klarna, Virgoli, Revolution, which is Steve Case’s, a former founder of AOL, is also in there. Meritway, which is managed by partners, I think, of Dragonair. Vinova from General Atlantic, an affiliate of General Atlantic. Also, NJJ Capital, which I believe is Xavier Nil, the French billionaire that founded Iliad. Mostly American, I think, if the math is correct. 80% non-Chinese, which was what mattered, I think, in many cases. But do see if you saw a pattern in most of those investors. I won’t say anything more than that. Maybe moving to other topics, maybe just to finalise on regulation and geopolitics. In geopolitics, we should talk about wars if we predict anything. Not that we are nasty and one want to be negative, but what the hell is going on? Will we have ending to the wars we already have ongoing or not? But before that, the struggles on the App Stores, I think, will continue both for Apple and for Google Play Store. The writing’s on the wall, the EU keeps pushing it dramatically and Apple keeps just doing stuff. I’m on the board of an App Store company. Apple just creates all these things that basically make you not really… It doesn’t work. You can’t provision then an App Store on Apple devices. On iPhones, et cetera. We’ll see how that will continue going, but I feel the writing’s on the wall. Both Apple and Google will have to open up a bit more of their platforms. I’m not sure it will have a huge impact in the medium to long term, but definitely we need to see more openness in access to apps as given by the two big platform owners, Apple and Google, out there. Bertrand Schmitt Let’s be clear. Google is way more open than Apple. We both have Android devices. You can install alternative app stores. It’s a different ballgame by very far. Nuno Goncalves Pedro Google does other nasty stuff. It’s public. You can check which board I’m a part of. You can see what that company has done towards Google over time. But to your point, yes. It is true that Google has been more open than Apple, but Google has done their own things. Just to be very clear, so I’ll just leave that caveat bracketed there for people to think about it and maybe read a little bit about it as well. Bertrand Schmitt I can say that, me, from my perspective, that path of total control that Apple has been going through on all their devices, that includes macOS, pushed me to, over the past 2, 3 years, to completely live and abandon the Apple ecosystem. I just couldn’t accept that level of control, that golden handcuff approach of the Apple ecosystem, each their own obviously, they are golden, their handcuffs, but they are still handcuffs. Personally, that pushed me way more to Linux, Android, Windows, back to Windows after all these years. I just couldn’t stand it anymore. I want to pick my devices. I want to pick what I install on them, and I don’t want to be controlled like this by just one entity for all my tech devices. For me, at some point, it was just not acceptable anymore. It’s still very warm, very golden handcuffs, but for me, they were just handcuffs at this stage. Yes, what they are doing with the App Store is very typical of that mindset. I think it’s quite sad because I think it started with good intention in some ways. “We need a new computing paradigm, we need to make things smoother and safer,” but it has really become a way to control your clients. For me, it has reached a point where it’s just way too much. Nuno Goncalves Pedro There’s obviously the great power comes great responsibility that uncle Ben told Spider-Man or Peter Parker. But there’s also with great power comes shitload of money, and control. So it’s like, “Yeah. Should we open the server? Do we want to delay opening it up?” “Yeah.” Anyway, it is what it is. Maybe let’s end on the more difficult note of the episode, which is going to be around wars. What’s our prediction? Will we have an end to the Gaza situation with Israel? Will we have an end to Ukraine and, obviously, Russia? What will happen in Iran? Those are the three big, big conflicts right now. Then, obviously, if we want to add just bonus points, what’s going to happen to Greenland, and what’s going to happen to Taiwan, and what’s going to happen to Venezuela? Let’s throw the whole basket in there. We’ve never had like… Let’s talk about all these territories and all these countries. At some point in time, I’m saying this in a light manner, but it’s obviously more tragic than it should be light, and people are dying, and there’s a lot of implications of all of that that is happening right now. Do you have any predictions, Bertrand, for this year? Bertrand Schmitt No. It’s tough to predict on an individual basis. I think on a more bigger picture basis is on one side, obviously, the rise of China on one side. You have also the rise of other countries like India, while very indirectly connected to some of these conflicts are still part of the game, buying oil from Russia, for instance. At the same time, I think overall, the US is more clear about with the sheriff in town. I think it’s good because in some ways, you cannot pay for the goods, you cannot have such a massive advantage versus nearly every other country on earth and just not be clear about who is the boss in some ways. As a result, what are the rules of the game and how it should be played? The US is not alone, obviously, you have China, you have Russia, you have India, you have Europe. You have different other countries. But at some point, it’s not good when countries are not rational and are not clear. I think I prefer the current situation where things are more clear and where you have to assume responsibilities about what you are doing. It’s time to be rational again about how the world behave. Yes, the concept of power and balance of power. I think there has been that dream, maybe mostly coming from Europe, about the end of history. I think that’s simply not the case. It’s not the end of history. It’s still about the balance of power. It has always been about the balance of power. If you are dumb enough to think it was not about that anymore, I just have a bridge to nowhere to sell you. I don’t have specific prediction, but I think it’s clear there is a new sheriff in town. There is a new doctrine about the Western Hemisphere that has been in some ways resurrected on the [inaudible 00:51:35] train, and I think we’ll see more of it. I think at this point, the biggest question is for the Europeans. What do they want to do? Because right now, their position of being a dwarf militarily while being a pretty big giant economically, I don’t think it works. Nuno Goncalves Pedro I agreed on everything that you said. I do have predictions. I’ll stick a flag on the ground just with my predictions. Bertrand Schmitt Good luck. Nuno Goncalves Pedro They are mostly positive. I do think we’ll see an end or, for the most, end to the two big conflicts, the one in Gaza and the one in Ukraine. I think Ukraine will end up in readjustment of territory and splitting between Russia and the Ukraine, but the end of hostilities, I think that we will see an end to the conflict in Gaza also with a readjustment on what that will mean for the Palestinian territories and the Palestinians in general. That I’m not sure, but I feel that there will be an end to those two big conflicts. Iran, I have no clue. I will not put a stick on the ground that I have no clue. There are so many things that could go wrong there. I’ve been reading some really interesting thoughts about even some aggressive thoughts that this might be the time to really change regimes in Iran and for the US to have a bit more of an aggressive stance. I really don’t have a perspective. Obviously, there’s a lot at stake there. Then, if we talk about the other parts, Greenland, I will not opine too much on. Maybe we’re done for now. Maybe there’ll be some other concessions to the US that weren’t already there in the ’50s. Taiwan, I won’t bet either. I’m sad to say I think it might happen at some point in time, but I’m not sure when and what would drive it. Last but not the least, Venezuela is my only really negative prediction. I feel it will continue to be a significant dictatorship as it was before managed enough by other people with the difference now that it has a tax to be paid to the US in the form of oil of some sort, etcetera, and maybe gas, maybe other things as well that it didn’t have before. That’s probably my most negative prediction for the coming year on the geopolitical side. Bertrand Schmitt Without going into detail, I would mostly agree with what you shared. At least that makes sense. But as we know, it’s not always what makes sense, but what might happen. I can tell you 100% I would not have guessed this operation against Maduro. This was so well done, well executed, and shocking at the same time that it’s… I think it shows that it’s hard to guess some of this stuff because there are certainly some new ways to wage limited war, for instance. So it’s certainly interesting, and we certainly need to get used to pretty bombastic statements. But for Venezuela, I don’t think it can be worse than what it was before. I’m probably more optimistic that gradually it can get better. Nuno Goncalves Pedro Just to put perspective on why we’re not making predictions on some of these elements, I think this is a funny story, but I was in Madeira. Actually, first time I was in Madeira, although I’m originally from Portugal. I’ve never been to the islands. Obviously, as you guys know, or some of you might know, there’s a lot of connection between Madeira and Venezuela. There’s a lot of immigration from Madeira Islands to Venezuela. One of my Uber or Bolt drivers there in Madeira was Venezuelan. Was born in Venezuela, but Portuguese descent, et cetera. He was telling me this was still last year. Late last year. Because I told him I lived in US, et cetera, and he was like, “Oh, hopefully, Trump will get Maduro out of there.” In my mind, I was like, “Dude.” No disrespect to the gentleman, but it’s like, “Okay. Mike, your perspective on geopolitics is maybe a little bit exaggerated.” And a couple of days later, we know what happened. When geopolitical decisions are better predicted by some probably very astute Uber drivers, you’re like, “Maybe I shouldn’t make a bet. I have no clue what’s going to happen, no clue what’s going to happen in Greenland, et cetera.” Anyway, a couple of predictions on that element. Bertrand Schmitt That’s why it’s so right. You have to be careful with the prediction, but it doesn’t remove the fact that I think nations and companies that have to play a global game have to understand in some ways what is the game, what are the powers in place, what could happen potentially, but also be realistic. Not be about wish and dreams, but more about, what’s the power relationship? Who has the money? Who has the means? Who has the capacity to do this or that? Because if you start that way, at least the scope of what’s possible, what’s reasonable is more and more clear more quickly. Some stuff like happened with Maduro, I would never have predicted, but for sure, if there’s one country that can do this sort of stuff, it’s the US. I’m not sure anyone has a technology and the means in terms of support infrastructure to do something like this. It’s tough to predict what will happen a year from now for any specific country, but I think that even trying to get a better understanding about the forces in play and their capacity and understanding and accepting that at some point, it’s all about real politic and relationship of power, the more your eyes would be wide open about what’s possible versus simple, wishful thinking. Nuno Goncalves Pedro Fintech, Crypto and Frontier Tech Moving maybe to our last section around fintech, crypto, and frontier tech. For me, just two very quick predictions, views of the world. I think on the frontier tech side, I won’t make a prediction. I will just tell you all to go and listen to our episodes, the one on infrastructure, which is immediately prior to this one, and the episodes that we’ve had around a couple of other topics including AI, what’s the future of your children, because I think they illustrate a lot of the points that we’re seeing and manifesting themselves over the next year and over the next 2 or 3 years as well beyond that. I feel those tomes are complete in and out of themselves, so you can just go and listen to them. Then my second comment is on crypto. I feel crypto has become of the essence, particularly under the current administration in the US, very favored. Obviously, we are now in a world where crypto is just part of the economic system, and I think we’ll see more and more of that emerging, and in some ways, crypto is becoming mainstream. Question is what blockchains will be the blockchains of the future? Obviously, there’s a bunch of bets put out there. We, ourselves, as Chamaeleon, have one investment in one of the significant bets in the space. But besides that, who’s going to win or not, we feel that we’re past the crypto winter. It’s now mainstream days, and we’ll see a lot more activity in there. Bertrand Schmitt I must say with crypto, I’m a bit confused. As you say, we are past the crypto winter. There is much less uncertainty in regul

On the podcast: the tailwinds driving a boom in non-game app revenue, how vibe coding and AI workflows are fueling growth in categories that have nothing to do with AI, and why people predicting the "death of apps" have never been more wrong.This conversation is shorter than usual and will be featured in RevenueCat's State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways: 

In this episode, the mates, along with guest Ben Horowitz, explore Elon Musk's shift to lunar AI data centers, mass drivers, O'Neill cylinders, Dyson swarms, and Optimus robots pioneering space. Get notified once we go live during Abundance360: https://www.abundance360.com/livestream  Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360 Ben Horowitz is a cofounder and general partner at Andreessen Horowitz (a16z), NY Times bestseller author, and creator of the a16z Cultural Leadership Fund. Salim Ismail is the founder of OpenExO Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified – My companies: Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding   Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy   _ Connect with Peter: X Instagram Connect with Ben X Instagram Linkedin Learn about a16z Connect with Dave: X LinkedIn Connect with Salim: X Join Salim's Workshop to build your ExO  Connect with Alex Website LinkedIn X Email Substack  Spotify Threads Listen to MOONSHOTS: Apple YouTube – *Recorded on February 13th, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

I sit down with Nick Vasilescu, founder of Orgo, to break down exactly how people are turning OpenClaw — the open-source computer use agent — into a real revenue stream. Nick walks me through live demos of deploying OpenClaw for business clients, shows how sub-agents and parallelization multiply output, and shares his design-thinking framework for identifying and automating high-value workflows. We even build a TikTok trend-hunting agent from scratch during the episode to prove how fast you can go from idea to working prototype. Timestamps 00:00 – Intro 02:50 – Getting Set Up with OpenClaw 05:02 – Finding the Wedge: Automating Real Business Outcomes 07:39 – The Upwork Hack: Finding Paid Automation Jobs 09:41 – Andreessen Horowitz on Computer Use Agents 11:01 – Setting Up a Client Workspace in Minutes 12:41 – Design Thinking: Mapping Value vs. Effort 15:23 – Using OpenClaw to Prioritize Automations 17:57 – Building Automation Pipelines with Claude Code 19:33 – Sub-Agents vs. Tasks vs. Skills 23:22 – Automation Possibilities are huge 24:54 – Live Build: TikTok Trend Hunter from Idea Browser 32:09 – Start with an MVP Skill, Then Iterate 32:41 – Architecture of the TikTok Agent Script 36:59 – The Arbitrage Opportunity: Most Businesses Still Need Help 40:30 – Agents Are the New SaaS 42:42 – Demoing TikTok Trend Hunter 44:11 – Building Assets & the Abundance AI Will Bring 47:58 – Closing Advice: Get Your Hands Dirty Links Mentioned: Orgo: https://startup-ideas-pod.link/orgo Key Points OpenClaw is more than a personal assistant — it is a deployable business tool that can automate end-to-end workflows for paying clients. The fastest path to revenue is finding automation jobs on Upwork (RPA, desktop automation, workflow building) and fulfilling them with OpenClaw and Claude Code. Sub-agents allow your main OpenClaw instance to delegate specialized tasks, keeping the orchestrator free and multiplying throughput through parallelization. A design-thinking approach — mapping automation opportunities by value vs. effort — is essential before building anything. Verticalizing computer use agents for a specific industry (manufacturing, real estate, distributorships) is the major startup opportunity Andreessen Horowitz is calling out. Always start by building a lightweight MVP skill, test it, debug, and iterate before scaling. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND NICK ON SOCIAL Youtube: https://www.youtube.com/@nickvasiles Instagram: https://www.instagram.com/nickvasilescu/ Personal Website: https://www.nickvasilescu.com

Anish Acharya is a General Partner at Andreessen Horowitz (a16z), where he leads consumer and fintech investing at Series A. He serves on the boards of standout portfolio companies including Deel, Mosaic, Clutch, Titan, and HappyRobot and has led early bets in companies like Runway and Carbonated. Before a16z, he founded and exited two startups—Snowball (acquired by Credit Karma) and SocialDeck (acquired by Google) and scaled Credit Karma's U.S. Card business to over 100 million members. AGENDA: 00:03 - Why building an AI company today requires being in San Francisco 06:58 - The "SaaS Apocalypse" myth: Why "vibe coding" everything is a lie 09:11 - How AI agents are finally breaking the lock-in of legacy software providers 10:13 - Incumbents vs. Startups: Who actually wins the AI distribution war? 14:39 - Why the developer tool market looks more like Cloud than Uber and Lyft 22:43 - The death of the Chatbox? Why browse-based interfaces are still preferable 27:14 - Why power users are 10x more valuable in the age of AI consumption 28:36 - Do margins matter in a world of AI? 34:46 - Why we are definitively not in an AI bubble right now 38:58 - Why the Legal and Customer Support industries will have dozens of winners 39:44 - Lessons from Marc Andreessen: Why the "quality of being right" supersedes process 44:51 - Is "Triple, Triple, Double, Double" dead? The new physics of growth 01:10:41 - The a16z Playbook: How to win 100% of the deals you chase    

This episode originally appeared on the Network State Podcast. Balaji Srinivasan and Benedict Evans sit down in Singapore for a wide-ranging conversation on the mechanics of disruption. Evans, a former Andreessen Horowitz partner who now writes one of tech's most-read newsletters, argues that the conversation about any technology peaks during the transition—not at 0% or 100% adoption. They cover AI's real capabilities and limits, the politics of technological disruption, why crypto's killer metric is block space, and what smart glasses, elevator attendants, and the elephant graph reveal about how change works.  Resources:Follow Benedict Evans on LinkedIn: https://www.linkedin.com/in/benedictevans/Check out Benedict's Newsletter: https://www.ben-evans.com/newsletterFollow Balaji Srinivasan on X: https://x.com/balajisCheck out Network State Podcast: https://www.youtube.com/@nspodcastHigh Output Management: https://www.amazon.com/High-Output-Management-Andrew-Grove-ebook/dp/B015VACHOK/eHang: https://www.youtube.com/watch?v=nUTu4_8QznEThe Deep Research Problem: https://www.ben-evans.com/benedictevans/2025/2/17/the-deep-research-problemARC AGI: https://arcprize.org/arc-agiUber and Airbnb didn't sell software: https://www.ben-evans.com/benedictevans/2025/3/14/what-kind-of-disruptionAI Use cases: https://www.ben-evans.com/benedictevans/2024/4/19/looking-for-ai-use-casesStablecoin surpasses Visa & Mastercard: https://crypto.news/ark-invest-stablecoin-transaction-value-in-2024-surpasses-visa-and-mastercard/Senate passes stablecoin bill: https://www.reuters.com/sustainability/boards-policy-regulation/us-senate-passes-stablecoin-bill-milestone-crypto-industry-2025-06-17/ Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

My guest today is Ben Horowitz, the co-founder of Andreessen Horowitz. Since its founding in 2009, a16z has grown into one of the most influential firms in venture capital, reshaping how technology companies are funded and how power and ideas move through Silicon Valley and around the world. This conversation focuses on sides of Ben's story you don't often hear. Ben reflects on the people who shaped him, including Nas, Andy Grove, and his father, and shares why he chose to personally fund new technology for the Las Vegas Police Department. We also talk about how he thinks about a16z's responsibility in shaping the trajectory of America, the scale of his ambition for the firm, and what he sees as the biggest risk facing the country. Please enjoy this great and unique conversation with Ben Horowitz. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ramp's mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠ to sign up for free and get a $250 welcome bonus. ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Vanta. Trusted by thousands of businesses, Vanta continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Visit vanta.com/invest.  ----- This episode is brought to you by Rogo. Rogo is an AI-powered platform that automates accounts payable workflows, enabling finance teams to process invoices faster and with greater accuracy. Learn more at Rogo.ai/invest. ----- This episode is brought to you by ⁠WorkOS⁠. WorkOS is a developer platform that enables SaaS companies to quickly add enterprise features to their applications. Visit ⁠WorkOS.com⁠ to transform your application into an enterprise-ready solution in minutes, not months. ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Timestamps (00:00:00) Welcome to Invest Like the Best (00:02:43) Episode Intro: Ben Horowitz (00:03:27) The State of America Right Now (00:06:06) How Policy Could Destroy America (00:08:29) AI Changes the Laws of Company Building and Investing (00:11:40) Why AI Researchers are Paid $100M (00:13:16) Thoughts on Growing Inequality (00:18:07) Societal Challenges Due to AI (00:19:56) Ben's Scope of Ambition for the Next 20 Years (00:22:48) Andy Grove's Influence on Ben (00:27:44) Starting Andreessen Horowitz (00:32:53) Early Mistakes (00:36:17) What Capital Markets Are Missing (00:37:44) Why VC and Not PE (00:40:03) Tradeoffs with Scale (00:41:10) A Culture is Not a Set of Ideas, it's a Set of Actions (00:43:05) Lessons from His Father (00:45:03) Exciting Use Cases of AI (00:46:46) Ben's Friendship with Nas (00:50:05) Funding New Technology for the Las Vegas Police Department (00:54:07) The Kindest Thing

Marc Andreessen is a founder, investor, and co-founder of Netscape, as well as co-founder of the venture capital firm Andreessen Horowitz (a16z). In this conversation, we dig into why we're living through a unique and one of the most incredible times in history, and what comes next.We discuss:1. Why AI is arriving at the perfect moment to counter demographic collapse and declining productivity2. How Marc has raised his 10-year-old kid to thrive in an AI-driven world3. What's actually going to happen with AI and jobs (spoiler: he thinks the panic is “totally off base”)4. The “Mexican standoff” that's happening between product managers, designers, and engineers5. Why you should still learn to code (even with AI)6. How to develop an “E-shaped” career that combines multiple skills, with AI as a force multiplier7. The career advice he keeps coming back to (“Don't be fungible”)8. How AI can democratize one-on-one tutoring, potentially transforming education9. His media diet: X and old books, nothing in between—Brought to you by:DX—The developer intelligence platform designed by leading researchersBrex—The banking solution for startupsDatadog—Now home to Eppo, the leading experimentation and feature flagging platform—Episode transcript: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Marc Andreessen:• X: https://x.com/pmarca• Substack: https://pmarca.substack.com• Andreessen Horowitz's website: https://a16z.com• Andreessen Horowitz's YouTube channel: https://www.youtube.com/@a16z—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Marc Andreessen(04:27) The historic moment we're living in(06:52) The impact of AI on society(11:14) AI's role in education and parenting(22:15) The future of jobs in an AI-driven world(30:15) Marc's past predictions(35:35) The Mexican standoff of tech roles(39:28) Adapting to changing job tasks(42:15) The shift to scripting languages(44:50) The importance of understanding code(51:37) The value of design in the AI era(53:30) The T-shaped skill strategy(01:02:05) AI's impact on founders and companies(01:05:58) The concept of one-person billion-dollar companies(01:08:33) Debating AI moats and market dynamics(01:14:39) The rapid evolution of AI models(01:18:05) Indeterminate optimism in venture capital(01:22:17) The concept of AGI and its implications(01:30:00) Marc's media diet(01:36:18) Favorite movies and AI voice technology(01:39:24) Marc's product diet(01:43:16) Closing thoughts and recommendations—Referenced:• Linus Torvalds on LinkedIn: https://www.linkedin.com/in/linustorvalds• The philosopher's stone: https://en.wikipedia.org/wiki/Philosopher%27s_stone• Alexander the Great: https://en.wikipedia.org/wiki/Alexander_the_Great• Aristotle: https://en.wikipedia.org/wiki/Aristotle• Bloom's 2 sigma problem: https://en.wikipedia.org/wiki/Bloom%27s_2_sigma_problem• Alpha School: https://alpha.school• In Tech We Trust? A Debate with Peter Thiel and Marc Andreessen: https://a16z.com/in-tech-we-trust-a-debate-with-peter-thiel-and-marc-andreessen• John Woo: https://en.wikipedia.org/wiki/John_Woo• Assembly: https://en.wikipedia.org/wiki/Assembly_language• C programming language: https://en.wikipedia.org/wiki/C_(programming_language)• Python: https://www.python.org• Netscape: https://en.wikipedia.org/wiki/Netscape• Perl: https://www.perl.org• Scott Adams: https://en.wikipedia.org/wiki/Scott_Adams• Larry Summers's website: https://larrysummers.com• Nano Banana: https://gemini.google/overview/image-generation• Bitcoin: https://bitcoin.org• Ethereum: https://ethereum.org• Satoshi Nakamoto: https://en.wikipedia.org/wiki/Satoshi_Nakamoto• Inside ChatGPT: The fastest-growing product in history | Nick Turley (Head of ChatGPT at OpenAI): https://www.lennysnewsletter.com/p/inside-chatgpt-nick-turley• Anthropic co-founder on quitting OpenAI, AGI predictions, $100M talent wars, 20% unemployment, and the nightmare scenarios keeping him up at night | Ben Mann: https://www.lennysnewsletter.com/p/anthropic-co-founder-benjamin-mann• Inside Google's AI turnaround: The rise of AI Mode, strategy behind AI Overviews, and their vision for AI-powered search | Robby Stein (VP of Product, Google Search): https://www.lennysnewsletter.com/p/how-google-built-ai-mode-in-under-a-year• DeepSeek: https://www.deepseek.com• Cowork: https://support.claude.com/en/articles/13345190-getting-started-with-cowork• Definite vs. indefinite thinking: Notes from Zero to One by Peter Thiel: https://boxkitemachine.net/posts/zero-to-one-peter-thiel-definite-vs-indefinite-thinking• Henry Ford: https://www.thehenryford.org/explore/stories-of-innovation/visionaries/henry-ford• Lex Fridman Podcast: https://lexfridman.com/podcast• $46B of hard truths from Ben Horowitz: Why founders fail and why you need to run toward fear (a16z co-founder): https://www.lennysnewsletter.com/p/46b-of-hard-truths-from-ben-horowitz• Eddington: https://www.imdb.com/title/tt31176520• Joaquin Phoenix: https://en.wikipedia.org/wiki/Joaquin_Phoenix• Pedro Pascal: https://en.wikipedia.org/wiki/Pedro_Pascal• George Floyd: https://en.wikipedia.org/wiki/George_Floyd• Replit: https://replit.com• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• Grok Bad Rudi: https://grok.com/badrudi• Wispr Flow: https://wisprflow.ai• Star Trek: The Next Generation: https://www.imdb.com/title/tt0092455• Star Trek: Starfleet Academy: https://www.imdb.com/title/tt8622160• a16z: The Power Brokers: https://www.notboring.co/p/a16z-the-power-brokers—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com