A16z Podcast

a16z’s Chris Lyons speaks with Earvin "Magic" Johnson about his 30-year journey from athlete to billionaire businessman. They cover the art of deal-making, lessons from mentors Michael Ovitz and Dr. Jerry Buss, why boring businesses often make the best investments, and Magic's sports ownership portfolio, from the Dodgers to the Commanders to the Sparks. They also discuss what the next generation of athletes and entertainers should know about equity, building teams, and taking risks. Resources:Follow Magic Johnson on X:  https://twitter.com/MagicJohnsonFollow Chris Lyons on X: https://twitter.com/chrislyons 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 ho

Cisco president and CPO Jeetu Patel speaks with a16z cofounder Marc Andreessen about why AI may finally break a 50-year productivity slump—and what's at stake if America doesn't win the race. They discuss where value will accrue in the AI stack, why open source complicates the US-China competition, and what's blowing Andreessen's mind right now. Resources:Follow Marc Andreessen on X:  https://twitter.com/pmarcaFollow Jeetu Patel on X: https://twitter.com/jpatel41 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,

a16z Head of Investor Relations Jen Kha speaks with general partner David George about the state of AI and private technology markets. David shares data on why AI companies are growing 2.5x faster than traditional software while spending significantly less on sales and marketing, driven by massive market pull and record-breaking ARR per employee. They discuss the rise of Model Busters, which are companies that grow faster and longer than anyone would have modeled, like the iPhone. They also highlight real-world adoption at Chime and Rocket Mortgage alongside portfolio breakouts like Harvey, Abridge, and ElevenLabs. Resources:Follow David on X: https://x.com/DavidGeorge83Follow Jen on X: https://x.com/jkhamehlRead The State of Markets - https://a16z.com/state-of-markets/ 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:

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.

Christopher Mims and Tim Higgins of the Wall Street Journal sit down with a16z General Partner Martin Casado on WSJ’s Bold Names to ask whether the AI spending boom is a bubble waiting to burst. Martin explains why the fundamentals differ dramatically from the dot-com era—when WorldCom had $40 billion in debt versus today's tech giants with hundreds of billions on their balance sheets—and why a speculative valuation correction shouldn't be confused with systemic collapse. They also discuss where a16z sees opportunity in the "long tail" of AI companies beyond the state-of-the-art large language models.Follow Martin Casado on X: https://twitter.com/martin_casadoFollow Christopher Mims on X: https://twitter.com/mimsFollow Tim Higgins on X:  https://twitter.com/timkhigginsCheck out WSJ’s Bold Names: https://www.wsj.com/podcasts/wsj-the-future-of-everything 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

a16z general partner Erik Torenberg speaks with Justin Mares, founder and CEO of Truemed. They discuss why American health outcomes are so poor compared to the rest of the developed world, how crop subsidies created a food system that "systematically outputs unhealthy people," and what it would take to treat the chronic disease crisis as a national security issue. Mares explains how TrueMed allows people to spend tax-free HSA and FSA dollars on lifestyle interventions like gym memberships, sleep aids, and healthier food—and why he believes this could redirect hundreds of billions of dollars toward prevention. They also explore the case for psychedelics as mental health therapy and why peptides could disrupt the pharmaceutical industry. Resources:Follow Justin Mares on X: https://x.com/jwmaresFollow TrueMed on X: https://x.com/truemed Timestamps:00:00 — Introduction0:44 — The Environment That Makes Us Sick 04:19 — What Went Wrong in the 1970s6:10 — The Subsidy Problem 8:49 — Universal Ozempic Won't Save Us12:2

Recorded live at our Founders Summit, a16z general partner Chris Dixon speaks with Palmer Luckey, founder of Anduril and Oculus VR. They talk about what it takes to build hardware at scale, where the biggest technological bottlenecks are today, and why optimism is still warranted despite geopolitical turmoil and regulatory constraints. They also cover crypto, stablecoins, modern warfare, the U.S.–China technology race, AI and manufacturing, and frontiers like fusion and quantum computing—plus lessons from Oculus, the founding of Anduril, and how to build mission-driven teams. Resources:Follow Palmer Luckey on X: https://twitter.com/PalmerLuckeyFollow Chris Dixon on X: https://twitter.com/cdixon 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 A

a16z general partner David Haber spoke with Goldman Sachs CEO David Solomon and a16z cofounder Ben Horowitz on the current macro environment, enterprise AI adoption, and crypto and AI policy. Solomon describes what he calls the "sweetest spot" he's seen in 40 years and explains Goldman's "One GS 3.0" initiative to reimagine core processes with AI. Horowitz discusses why "leads aren't what they once were" in AI and how a16z grew from a startup VC to capturing 18% of all US venture capital. Resources: Follow David Solomon on X: https://twitter.com/DavidSolomonFollow Ben Horowitz on X: https://twitter.com/bhorowitzFollow David Haber on X: https://twitter.com/dhaber Timestamps: 00:00 — Introduction02:09 — Goldman's Evolution from Partnership to Public Company08:54 — How a16z Went from Top Tier to 18% of All US Venture Capital15:33 — "As Sweet a Spot" as Solomon Has Seen in 40 Years19:00 — M&A Outlook: "Whatever the Question Is, the Answer Is Maybe"21:33 — Why Leads Aren't What They Once Were in AI23:03 — Cryp

Netlify's CEO, Matt Biilmann, reveals a seismic shift nobody saw coming: 16,000 daily signups—five times last year's rate—and 96% aren't coming from AI coding tools. They're everyday people accidentally building React apps through ChatGPT, then discovering they need somewhere to deploy them. The addressable market for developer tools just exploded from 17 million JavaScript developers to 3 billion spreadsheet users, but only if your product speaks fluent AI—which is why Netlify's founder now submits pull requests he built entirely through prompting, never touching code himself, and why 25% of users immediately copy error messages to LLMs instead of debugging manually. The web isn't dying to agents; it's being reborn by them, with CEOs coding again and non-developers shipping production apps while the entire economics of software—from perpetual licenses to subscriptions to pure usage—gets rewritten in real-time. Resources:Follow Matt Biilmann on X: https://x.com/biilmannFollow Martin Casado on X: https://x.com

Recently, Marc Andreessen joined Lenny Rachitsky on Lenny's Podcast. They talked about why 2025 may be the most significant year in tech history, how AI is reshaping the future of product managers, designers, and engineers, and what founders need to understand about building in this moment—from where moats actually exist in AI to what the most AI-native companies are doing differently to the skills Marc is teaching his own kids to thrive in what comes next. Resources:Follow Marc Andreessen on X: https://twitter.com/pmarcaFollow Lenny Rachitsky on X: https://twitter.com/lennysanCheck out Lenny’s Podcast: https://www.lennysnewsletter.com/podcast 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

Can a country be built from the internet up? Not as a metaphor or an online community, but as a system that replaces institutions we usually think of as fixed, money, law, and governance.In this conversation taken from The Network State Podcast, a16z cofounder Ben Horowitz joins Balaji Srinivasan to explore how internet native institutions are beginning to mirror and challenge traditional state structures. Drawing parallels to China’s early special economic zones, they discuss how constrained experiments like Shenzhen tested new rules without rewriting the entire system, and why similar experimentation is now happening online.The discussion examines crypto, digital identity, and network states as attempts to turn code into coordination and coordination into legitimacy, while grappling with a core tension. Code is deterministic, but societies are not. Ben and Balaji explore where these systems work, where they break, and whether network states are a curiosity or the next phase of governance. Resources:Follow B

Out-of-Pocket is a healthcare education company founded by Nikhil Krishnan that helps people understand how healthcare works and how to navigate it in practice. In this episode, a16z investing partner Jay Rughani and Nikhil discuss why health insurance is losing its role as the default way people access care. They explain how rising costs are pushing more consumers to pay out of pocket for diagnostics, preventive care, and navigation. The conversation also looks at what this shift means for startups, AI-powered tools, regulation, and access as healthcare continues to move beyond insurance.Resources:Follow Jay Rughani on X:  https://twitter.com/JayRughaniFollow Nikhil Krishnan on X: https://twitter.com/nikillinitRead Out of Pocket’s 2026 Predictions: https://www.outofpocket.health/p/out-of-pockets-2026-predictionsStay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsPlease note that the content here is for informational purposes only; should

In this episode, Jen Kha, Head of Investor Relations, and David George, General Partner, discuss how late-stage private markets are evolving as AI reshapes scale, capital intensity, and growth timelines. They explain why AI-driven companies are staying private longer, how infrastructure spending is changing return profiles, and what this moment means for durability, value creation, and long-term outcomes in private markets.Timecodes:0:00 — Introduction04:21 — The Market Opportunity for AI26:48 — Pricing, Monetization, and Cash Burn43:15 — Companies Staying Private Longer51:30 — Portfolio Composition and Construction57:18 — Team Culture and Collaboration Resources:Follow Jen Kha on X: https://x.com/jkhamehlFollow David George on X: https://x.com/DavidGeorge83 Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com

Mintlify is a documentation platform built by cofounders Han Wang and Hahnbee Lee to help teams create and maintain developer docs. In this episode, Andreessen Horowitz general partners Jennifer Li and Yoko Li speak with Han and Hahnbee about how coding agents are changing what “good docs” mean, shifting documentation from a human-only resource into infrastructure that powers AI tools, support agents, and internal knowledge workflows. They share Mintlify’s early journey, including eight pivots, the two-day prototype that landed their first customer, and the “do things that don’t scale” sales motion that helped them win early traction. The conversation also covers why docs go out of date, what “self-healing” documentation requires to actually work, and how serving fast-moving customers has shaped both their product priorities and their pace.Follow Jennifer Li on X: https://twitter.com/JenniferHliFollow Yoko Li on X: https://twitter.com/stuffyokodrawsFollow Han Wang on X: https://twitter.com/handotdevFollow Hah

Inferact is a new AI infrastructure company founded by the creators and core maintainers of vLLM. Its mission is to build a universal, open-source inference layer that makes large AI models faster, cheaper, and more reliable to run across any hardware, model architecture, or deployment environment. Together, they broke down how modern AI models are actually run in production, why “inference” has quietly become one of the hardest problems in AI infrastructure, and how the open-source project vLLM emerged to solve it. The conversation also looked at why the vLLM team started Inferact and their vision for a universal inference layer that can run any model, on any chip, efficiently.Follow Matt Bornstein on X: https://twitter.com/BornsteinMattFollow Simon Mo on X: https://twitter.com/simon_mo_Follow Woosuk Kwon on X: https://twitter.com/woosuk_kFollow vLLM on X: https://twitter.com/vllm_project Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple Podcas

In this feed drop from The Six Five Pod, a16z General Partner Martin Casado discusses how AI is changing infrastructure, software, and enterprise purchasing. He explains why current constraints are driven less by technical limits and more by regulation, particularly around power, data centers, and compute expansion.The episode also covers how AI is affecting software development, lowering the barrier to coding without eliminating the need for experienced engineers, and how agent-driven tools may shift infrastructure decision-making away from humans.Watch more from Six Five Media: https://www.youtube.com/@SixFiveMedia Resources:Follow Martin Casado on X: https://twitter.com/martin_casado  Follow Patrick Moorhead on X:  https://twitter.com/PatrickMoorheadFollow Daniel Newman on X: https://twitter.com/danielnewmanUV 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/a16zL

Sourcegraph's CTO just revealed why 90% of his code now comes from agents—and why the Chinese models powering America's AI future should terrify Washington. While Silicon Valley obsesses over AGI apocalypse scenarios, Beyang Liu's team discovered something darker: every competitive open-source coding model they tested traces back to Chinese labs, and US companies have gone silent after releasing Llama 3. The regulatory fear that killed American open-source development isn't hypothetical anymore—it's already handed the infrastructure layer of the AI revolution to Beijing, one fine-tuned model at a time. Resources:Follow Beyang Liu on X: https://x.com/beyangFollow Martin Casado on X: https://x.com/martin_casadoFollow Guido Appenzeller on X: https://x.com/appenz Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.co

The a16z AI Apps team outlines how they are thinking about the AI application cycle and why they believe it represents the largest and fastest product shift in software to date. The conversation places AI in the context of prior platform waves, from PCs to cloud to mobile, and examines where adoption is already translating into real enterprise usage and revenue. They walk through three core investment themes: existing software categories becoming AI-native, new categories where software directly replaces labor, and applications built around proprietary data and closed-loop workflows. Using portfolio examples, the discussion shows how these models play out in practice and why defensibility, workflow ownership, and data moats matter more than novelty as AI applications scale. Resources:Follow  Alex Rampell on X: https://twitter.com/arampellFollow Jen Kha on X: https://twitter.com/jkhamehlFollow David Haber on X: https://twitter.com/dhaberFollow Anish Acharya on X: https://twitter.com/illscience Stay Updated:If

The Stanford PhD who built DSPy thought he was just creating better prompts—until he realized he'd accidentally invented a new paradigm that makes LLMs actually programmable. While everyone obsesses over whether LLMs will get us to AGI, Omar Khattab is solving a more urgent problem: the gap between what you want AI to do and your ability to tell it, the absence of a real programming language for intent. He argues the entire field has been approaching this backwards, treating natural language prompts as the interface when we actually need something between imperative code and pure English, and the implications could determine whether AI systems remain unpredictable black boxes or become the reliable infrastructure layer everyone's betting on. Follow Omar Khattab on X: https://x.com/lateinteractionFollow Martin Casado on X: https://x.com/martin_casadoCheck out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. Please note that the content here is for inf

a16z cofounders Marc Andreessen and Ben Horowitz join a16z general partner Erik Torenberg and Not Boring founder Packy McCormick for a conversation on how the media and information ecosystem has changed over the past decade. The discussion breaks down the shift toward a more open and decentralized speech environment, the rise of writer- and creator-led platforms like Substack, and the erosion of centralized media gatekeepers. Marc and Ben also tie these dynamics to their investing worldview, outlining how supply-driven markets, major technological step changes, and reputation-driven venture platforms shape outcomes in the AI era.Timecodes: 00:00  Introduction00:46  How the media ecosystem is changing4:20  Why a16z invested in Substack6:28  Supply-driven markets and new content creation8:07  Why writers felt trapped by media companies10:09  Databricks and the 10x cloud multiplier13:58  Long-form podcasting proves demand15:40  What the new fund signals about the future16:24  AI as a universal problem solver18:4