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OpenAI CFO Sarah Friar makes her All-In debut days after the company's record $122B fundraise, walking hosts Jason Calacanis, David Friedberg, and David Sacks through the IPO calculus, the Anthropic rivalry, a teased consumer hardware device from Jony Ive's team, and how OpenAI is planning compute purchases through the early 2030s. Friar's core message: an IPO is a milestone, not a destination, and the real race is building an AI intelligence layer that serves humanity at scale — with advertising eventually subsidizing access for those who can't pay. ## [00:00] OpenAI CFO Sarah Friar joins the show! Jason Calacanis opens by flagging the scale of OpenAI's March fundraise — north of $120 billion — as the largest private capital raise in history, surpassing the prior record (Saudi Aramco's ~$30B IPO) by an order of magnitude. Friar frames it succinctly: "We think AI is the biggest era that we've seen to date. We're just starting to understand what it's going to mean for global productivity." > *"Luck is whatever the preparation meets opportunity, but you got to grab it."* ## [00:31] How OpenAI thinks about its IPO timeline The question of sequencing — SpaceX going first, Anthropic filing its S-1 confidentially mid-episode — dominates the first substantive segment. Friar refuses to treat an IPO as a competitive event. Her view: an IPO is just another financing mechanism, and timing should reflect business readiness, not optics. She notes that the $122B raise was structured to give "maximum flexibility" — buying time to choose the right window rather than being forced by capital pressure. David Friedberg asks whether the private raise is the largest in history; Friar confirms it is by an orders-of-magnitude margin. Jason Calacanis then reads out Anthropic's confidential S-1 filing live. Friar doesn't blink: going first means running the SEC gauntlet first, with no guarantee of advantage. > *"No one remembers who went first, Google or Yahoo, Lyft or Uber. In the end, we're going to have to build big, sustainable, durable companies, and fundraising will be a key component of doing exactly that."* ## [03:31] OpenAI, Anthropic, Google: The AI arms race Calacanis challenges Friar directly: did OpenAI spread too thin — Sora, new gadgets, too many projects — while Anthropic moved decisively into enterprise and developer channels, seemingly pulling ahead on developer and revenue metrics? Friar pushes back on the binary framing. OpenAI's strategy is explicitly neither pure consumer nor pure enterprise: revenue is now roughly 50/50 between the two. She runs through the multi-interface thesis: ChatGPT at 900 million weekly users, Codex crossing 5 million users in a weekend from near-zero in January, Frontier for enterprise, and API access. The compounding logic is that a single underlying model serving all surfaces means more data, better personalization, declining per-token cost, and higher gross margins — all of which feed more capital back into compute access, which is itself the scarce resource that determines competitive position. > *"Our strategy is different. We are building the AI layer, the infrastructure and it's really important that there's a single foundation but then with many interfaces out into the world."* Friedberg notes that the fastest-growing user cohorts are in Africa, with Azerbaijani and Kazakh among the fastest-growing languages — an indication of how far the user base has moved beyond English-speaking tech early adopters. ## [07:43] Navigating the compute crunch and AI bottlenecks, device preview! Friedberg revisits a framing Friar coined ~18 months earlier: one gigawatt of AI compute roughly equals $10B/year of revenue for OpenAI. The question is whether that ratio still holds and what the supply picture looks like across the industry. Friar's answer: compute is scarcer than ever, the 2026 and 2027 pipeline is effectively locked, and she's already focused on securing capacity for 2030–2032. She outlines the choke points in sequence: energy and land permitting, rack and chip supply (with current memory spike as the acute bottleneck), talent pipeline, and community trust. On the latter, she details OpenAI's commitments for the Seline, Michigan 1-gigawatt data center (part of the Oracle complex, with Sam Altman cutting the ribbon that day): no rate increases for local electricity consumers, 2,500 union jobs, $1B in Michigan taxes, and $45M into Codex education credits for workers entering jobs that will require AI fluency. Friar then teases the new consumer device without naming it or showing it — designed by Jony Ive's team, targeting a substrate that replaces thumb-first smartphone interaction. "By the end of this year we will unveil it, early next year." She describes using it as feeling "very natural, but very real" in a way that's hard to articulate but immediately felt. > *"Technology is very — can be very mechanistic, but we all know great design just makes everything fade away."* The compute scarcity directly shapes product decisions: Sora's rollout was slowed because video is token-heavy and tokens were being rationed. Inference, unlike training, is increasingly meant to be global, with real-time agentic workloads requiring low-latency distributed compute. ## [15:53] OpenAI's economics Friedberg shifts to capital allocation: what is OpenAI's equivalent of the high-ROC engine that defined Amazon's warehouse flywheel or Google's search-ads loop? Friar's answer is a three-layer model — customer value creation first, then gross margin expansion via compute deflation, then capital deployment timed against the cost curve. On the deflation side, the per-token cost from GPT-4 to GPT-4.5 fell 97% in roughly two years. The latest model, o3, was priced 2x higher than its predecessor, yet customers are still seeing 20–30% cost-per-token reductions because efficiency gains outpace the price increase. The implication: today's capex decisions will be priced on tomorrow's cost profile, so underinvesting now means mispricing the outcome. Friar is explicit about how far out the planning horizon goes. Near-term (2026–27): bottoms-up revenue model with known products and pricing. Outer years: reverse the model — buy the compute, then assume revenue will follow. She cites a specific past example: a year ago she pitched investor models showing agentic revenue at $2,000/month, which nobody believed. ChatGPT Pro at $200/month was itself called impossible. Both happened. > *"The shape of the line keeps taking us by surprise to the upside."* The Michigan data center won't produce usable compute until end-of-2027 or early 2028, illustrating the 18–24 month lag between capital commitment and revenue-generating capacity. Friar's current scarcity focus is 2030–2032. ## [26:08] Push into chips, the cloud Friedberg poses the vertical integration question: as Nvidia, Google, Microsoft, and OpenAI each push into each other's layers — silicon, models, cloud, consumer — does the stack eventually merge? And does convergence make the competitive landscape simpler or more complicated? Friar frames OpenAI's evolution with a Rubik's cube metaphor. Two years ago: one cloud partner (Azure), one chip (Nvidia), one product (ChatGPT), one price point ($20/month). Today: multi-CSP (Oracle, CoreWeave, Microsoft, GCP, AWS, plus smaller neoclouds), multi-chip (Nvidia Blackwell as primary, with AMD, Cerebras for low-latency inference, and a proprietary chip in development with Broadcom), and multiple products at multiple price points. The strategic logic is opex over capex: CSPs absorb capital expenditure while OpenAI pays as revenue comes in. She acknowledges the shift toward build-to-suit (the SoftBank/Texas data center) introduces more capex, but frames it as the next phase once OpenAI achieves investment-grade credit standing and can access lower-cost debt. > *"A year ago people talked about the commoditization of the LLMs. And frankly it's gone the opposite because as you start building an agentic layer — the harness is what brings the context, the memory."* ## [29:32] OpenAI's ad business and strategy Calacanis closes with the advertising question. Two of the three greatest consumer businesses ever built — Google's search ads and Meta's social graph targeting — are ad-funded. OpenAI has been testing ads in the free tier. Is advertising the mechanism that makes AI access truly universal? Friar's answer is structured around two principles: ads must never alter which result the model surfaces (the answer must always be the best one, not the sponsored one), and an ad-free paid tier will always exist. Within those constraints, she's bullish on OpenAI's ad potential: the combination of Google-style high-intent signals ("I want cool shoes for the stage") with Meta-style demographic context, plus memory ("it knows I'm me, it knows I'm a CFO, it knows I'm a mom with teenagers"), produces a targeting surface more potent than either predecessor. The current API-versus-consumer token economics are stark — API revenue per token dwarfs consumer revenue per token by an order of magnitude. But Friar is deliberately not optimizing for today's ratio. The strategy is to build an AI infrastructure layer that functions like a utility, capable of serving consumers, small businesses, enterprises, and governments at global scale — and advertising is what pays for the consumer floor. > *"If you know Google and Meta had a baby, it would be ChatGPT — because what you have in Google search is very high intent... We have more than that because we have memory."* ## Entities - **Sarah Friar** (Person): CFO of OpenAI; former CEO of Nextdoor; Stanford trustee; guest - **Jason Calacanis** (Person): All-In host; LAUNCH founder; angel investor - **David Friedberg** (Person): All-In host; CEO of The Production Board - **David Sacks** (Person): All-In host; Craft Ventures; White House AI & Crypto Czar - **Sam Altman** (Person): CEO of OpenAI; cutting ribbon at Seline, Michigan data center during recording - **Jony Ive** (Person): Designer collaborating with OpenAI on an unrevealed consumer hardware device - **Denise Dresser** (Person): OpenAI's Head of Revenue, in seat since December - **OpenAI** (Organization): AI research and deployment company; 900M weekly ChatGPT users, $122B raised March 2026 - **Anthropic** (Organization): AI competitor; filed S-1 confidentially during the episode recording - **ChatGPT** (Software): OpenAI's consumer AI interface; 900M weekly active users - **Codex** (Software): OpenAI's AI coding agent; crossed 5M users in a single weekend; fastest-growing internally in GTM teams - **Cerebras** (Organization): Chip partner; online for OpenAI inference; noted for low-latency coding workloads - **Broadcom** (Organization): Semiconductor partner for OpenAI's proprietary chip development - **Nvidia** (Organization): Primary chip partner; Blackwell current; Vera Rubin targeted for next major training run; Feynman series next - **Oracle** (Organization): CSP partner; co-developing the Seline, Michigan 1-gigawatt data center - **Agentic AI** (Concept): AI systems taking multi-step autonomous actions; driver of both revenue growth and inference compute demand - **AI infrastructure layer** (Concept): OpenAI's strategic framing — single foundational model serving many interfaces, positioned like a utility

Benchmark GP Bill Gurley joins Jason Calacanis, David Sacks, and Chamath Palihapitiya (David Friedberg out this week) for a 95-minute session covering six fronts of the AI debate: Gurley's new theory that Anthropic is not just pursuing regulatory capture but actively "midwifing a deity"; Pope Leo XIV's 235-page AI encyclical and its uncomfortable historical parallel to Leo XIII's 1891 warnings about the industrial revolution; the growing consensus that open-source AI faces a coordinated regulatory crackdown; and the week's sharpest narrative flip — Dario Amodei and Sam Altman both quietly walking back their AI jobs-apocalypse rhetoric while Goldman Sachs CEO David Solomon published a New York Times op-ed declaring the apocalypse overblown. ## [00:00] Bill Gurley joins the show! Bill Gurley, Benchmark general partner and author of *Running Down a Dream*, fills in for David Friedberg and joins live from Chamath's pool house where Jason has been staying. After banter about unauthorized Uber Eats orders on Chamath's house iPad, Jason introduces Gurley as a first-time guest who specifically requested to appear the moment the pod covered the Pope. Gurley plugs his new P3 Institute and a grant program he launched to fund people pivoting toward work they love. He teases a TED talk — rooted in the book's argument that high agency and lifetime learning are the only durable defenses against disruption — which sets the frame for everything that follows. > *"And I told the house manager like, listen, any packages that come in the next 72 hours, right to the pool house, if it says JCAL, right to the pool house."* ## [06:00] Making yourself valuable in the age of AI, first class of "AI Natives" Chamath opens with the question that has been driving the show for 18 months: if you're a young person right now, is AI doom much ado about nothing, or a real career threat? Gurley cites a Gallup poll showing 59% of workers are "quiet quitters" — ambivalent about their jobs and therefore low-agency. His core thesis: the best protection against AI displacement is becoming the most AI-enabled version of yourself in your field. He invokes Mark Cuban's framing — "there are two types of people: those who use AI to learn faster than ever before, and those who use AI to avoid learning altogether." Sacks walks through how the pod's producer Nick built a daily Claude briefing document that not only summarized news but predicted specific topics Sacks would care about based on his prior comments on the show. Sacks had dismissed it as likely AI slop; it was not. Gurley extends the point across every job category: in marketing, legal, accounting, and sales, being the most AI-capable person among your peers makes you "golden," and the early lead compounds. Jason adds that in his own team experiments, the skill separating strong performers from weak ones was systems thinking — could they break a complex problem into context the AI could execute, or did they hand it a task and wait? > *"I think the best way to protect yourself from AI is to be the most AI enabled version of yourself you can be."* ## [17:37] Reacting to Pope Leo's AI encyclical: Who guards the guardians? Pope Leo XIV released *Magnifica Humanitas*, a 235-page, 42,000-word encyclical warning business leaders to safeguard humanity from AI. His central argument: technology is never neutral — it takes on the characteristics of those who build, finance, and control it. Jason reads the core line and notes the Pope presumably does not think highly of Silicon Valley's current roster of builders. Sacks finds himself largely agreeing with the Pope's diagnosis: the biggest risk of AI is centralization of power and its Orwellian misuse by governments. Where he parts ways is on the remedy. Giving government the power to regulate AI development creates its own guardian problem — the American founders' answer to *Quis custodiet ipsos custodes?* was separation of powers, forcing guardians to check each other. Sacks's AI equivalent: a competitive market with five frontier labs is the best natural check; monopolization is the scenario to prevent. Gurley lands the sharpest historical counterpunch. Pope Leo XIII's 1891 encyclical *Rerum Novarum* warned that the industrial revolution would harm workers — and was wrong on every metric. From 1891 to today: the work week fell from 60+ hours to 34, real wages rose 8–10x, the median worker now earns more than a doctor did in 1891, global GDP per capita went from $1,500 to $20,000, child labor in the US dropped from 18% to zero, workplace deaths fell 40x, life expectancy rose 60%, and global poverty dropped from 75% to under 10%. > *"All those things happened because of technology, innovation, and capitalism, which is exactly what Leo the 13th was warning against. So he got it dead wrong. He got the whole thing precisely wrong."* ## [26:54] Anthropic's Digital God: Do they believe they are creating a superior species? Gurley delivers what becomes the most-quoted segment of the episode: his "Dr. Frankenstein theory" of Anthropic. He had previously held a simpler regulatory-capture theory — Anthropic stirs up AI fear to lock in regulation that entrenches incumbents. But after spending 30 days reading everything he could find about the company, he has a darker read. He describes meeting people inside Anthropic who he believes genuinely think they are not writing software but "midwifing a deity." The evidence trail: Anthropic chief philosopher Amanda Askell's podcasts, Chris Olah's 80-page Constitutional AI document, and Dario Amodei's own essay "Machines of Loving Grace," which envisions a post-AGI economy where AI systems allocate resources to humans based on an AI-determined reward function. Chamath calls it "a computational reward function for humans — it decides how much you're worth." Jason calls it "the ultimate delusions of grandeur." Gurley corrects him: he didn't say it, Dario did. Sacks steelmans Anthropic briefly — they probably see themselves as responsible builders who take the power of this technology seriously enough to guard it — then immediately notes this framing is textbook regulatory capture: brand yourself the safe player, characterize competitors as reckless, let regulation shut down the recklessness. Both Sacks and Chamath converge on the structural danger: a singular AI value system that decides how humans live is catastrophically fragile. The answer is decentralization and competing systems, not one algorithmic authority. > *"I don't think they think they're writing software. I think they're midwifing a deity here. And I don't know which one I'm more afraid of — the regulatory capture or this second theory I call the Dr. Frankenstein theory."* ## [38:32] AI sovereignty, the next era of privacy, open-source crackdown coming? Jason introduces "intelligence sovereignty" as the successor to data privacy. Data privacy was about who can see your photos and messages. Intelligence sovereignty is about who gets to interpret your world — whether the AI shaping your information feed is a centralized system with a particular political philosophy, or something you control. He flags the paradox: China's Communist Party is leading the open-weight model movement while the United States is centralizing. Chamath presents his portfolio company Abacus as evidence that Fortune 1000 buyers are responding to this anxiety: they want a control plane that can hot-swap between frontier models, plus on-prem options that remove dependence on any one provider's terms of service. He gives a concrete example — a Canadian hospital that supports its country's euthanasia laws could be shut off by an American frontier model whose constitution prohibits that content. Sacks connects the dots to a regulatory threat he has been watching build: the regulatory-capture playbook leads, in his read, to a ban on open-source or open-weight models. The justification will be safety — open models let users strip guardrails. Gurley reaches the same conclusion in his P3 Institute post. If a ban succeeds, the United States effectively exiles itself from the open ecosystem while the rest of the world — including China — runs on open models. > *"I think where it's all leading to is an effort to ban open source models or open weight models. There's a lot of breadcrumbs leading here."* ## [59:56] The Great AI Jobs Debate: Dario and Sam Altman flip their rhetoric, Goldman CEO says no AI job apocalypse The chapter opens with a news roundup of the week's narrative shift. Cloudflare's Matthew Prince, Zuckerberg at Meta, Jack Dorsey at Block, and Andy Jassy at Amazon all cited AI when announcing major layoffs. But Goldman Sachs CEO David Solomon published a New York Times op-ed with three counterpoints: AI will automate 25% of work hours, not 25% of jobs; bank tellers increased after ATMs; the US labor market creates and destroys 25–35 million jobs annually so gross churn dwarfs net losses. Simultaneously, Fortune reported that Dario Amodei and Sam Altman are both walking back prior doom-and-gloom rhetoric — with Chamath noting the timing cannot be separated from upcoming frontier-lab IPOs that need a jobs-creation narrative. Sacks is unambiguous: he has been making the non-consensus case against the jobs apocalypse for over a year and considers himself vindicated. Yale Budget Lab found no discernible labor-market disruption over three years of the AI wave. Software engineering — the single breakout AI use case — saw job postings rise 15% year-over-year and hit a three-year high. The 4.3% unemployment rate is near record lows. Most of the high-profile layoffs, he argues, are AI washing: CEOs who over-hired during COVID found AI to be a convenient narrative for long-overdue downsizing. The Jack Dorsey / Block 50% cut was immediately flagged by financial analysts as a company that had been overstaffed relative to peers for years — pure AI washing. Jason pushes back. He insists cab drivers, truck drivers, and package-sorters — roughly 20 million American workers — face real structural displacement over the next decade regardless of current aggregate statistics, and accuses the panel of elitism: "We are elite performers. These people are going to lose their jobs and they may not get a job very quickly." He draws a distinction between the short-to-medium term, where he expects acceleration, and the long run, where a Cambrian explosion of startups built by AI-enabled founders creates new categories. By the end, he shifts toward Sacks's territory — acknowledging the aggregate data is less alarming than his anecdotes suggested. Gurley threads the needle with the same historical argument from the Leo XIII discussion: innovation has always, on net, created more prosperity than it destroyed. His practical advice to people at risk: get ahead of your peers on the tools now; if your job is going away, plan your pivot toward trades (he plugs MicroWorks, which provides free scholarships for plumbers, welders, and electricians) or toward something you find genuinely fascinating. > *"I think the best way to protect yourself from AI is to be the most AI enabled version of yourself you can be. Know what it's capable of in your field. Get out there."* ## Entities - **Bill Gurley** (Person): General partner at Benchmark; author of *Running Down a Dream*; founder of P3 Institute; guest filling in for David Friedberg - **Jason Calacanis** (Person): All-In host; angel investor; founder of LAUNCH; argues for worker empathy and short-term displacement risk - **David Sacks** (Person): All-In host; Craft Ventures founder; most vocal critic of AI jobs-apocalypse narrative this episode - **Chamath Palihapitiya** (Person): All-In host; Social Capital CEO; coined "intelligence sovereignty"; co-founder of Abacus - **Dario Amodei** (Person): Anthropic CEO; subject of Gurley's "Dr. Frankenstein theory"; walked back jobs-doom rhetoric this week alongside Sam Altman - **Pope Leo XIV** (Person): Catholic Pope; released *Magnifica Humanitas*, a 235-page AI encyclical warning against technology concentration - **David Solomon** (Person): Goldman Sachs CEO; published New York Times op-ed arguing AI job apocalypse is overblown - **Anthropic** (Organization): Frontier AI lab; subject of Gurley's regulatory-capture and "Dr. Frankenstein" theories; maker of Claude - **P3 Institute** (Organization): Bill Gurley's new policy and philanthropy institute; published post defending open-source AI - **Goldman Sachs** (Organization): Investment bank; CEO's NYT op-ed became the week's anchor data point against the jobs-apocalypse narrative - **Abacus** (Software): Chamath's Social Capital portfolio company; builds on-prem AI hardware stacks for Fortune 1000 enterprises seeking model independence - **Intelligence sovereignty** (Concept): Jason's term for the next frontier of privacy — not who sees your data, but which AI system is allowed to shape your interpretation of the world - **Dr. Frankenstein theory** (Concept): Gurley's characterization of Anthropic's worldview: senior staff believe they are midwifing a deity or superior species rather than writing software, as described in Dario Amodei's "Machines of Loving Grace" essay - **Regulatory capture** (Concept): The strategy of branding oneself the "safe" AI company, amplifying public fear, and lobbying for regulation that locks in incumbents and targets open-source competitors

Sacks is out, Gavin Baker (Atreides Management) sits in. The panel walks through Andrej Karpathy's surprise move to Anthropic, debates why the public mood on AI has flipped, tears apart SpaceX's $2T S-1, and asks why Nvidia's blowout earnings still saw the stock sold. Friedberg and Chamath also flag warning signals from inflation, oil, and bond yields, and close on what — if anything — came out of the US-China summit. ## [00:00] Gavin Baker joins the show! Jason opens episode 274 noting Sacks is out and welcomes Gavin Baker from Atreides Management for the week. They tee up the agenda: SpaceX and OpenAI IPOs, Karpathy to Anthropic, and Nvidia's earnings. > *"Sachs is out today, but we're very lucky to have Gavin Baker from Atreides Management joining us. The spicy takes must flow."* ## [00:30] Andrej Karpathy joins Anthropic; hypergrowth and profitability The Karpathy hire is read as a major strategic win for Anthropic — Chamath frames it as continuity of the Richard Sutton "bitter lesson" school of scaling that Karpathy executed at Tesla FSD and OpenAI. Gavin layers in financial context: Anthropic was EBIT-positive in the last quarter per the WSJ, which combined with hypergrowth makes the recent funding rounds look very different from a capital-burn narrative. Friedberg pushes back on the framing that models will soon "feed themselves" into context windows to self-improve, but flags that papers (one from MIT) suggest large efficiency gains are on the horizon. Chamath uses the moment to argue the podcast itself has to start telling the upside story of AI — the doctors, the scientists, the unlock — because the dominant public narrative has gone negative. > *"He was probably the first person that really commercialized the Richard Sutton bitter lesson essay when he was leading FSD at Tesla."* ## [12:42] Why Americans have turned on AI, anti-human perception Gavin shares a personal story: his daughter has a rare disease, and a Stanford scientist he funded is months away from what he believes is a complete cure, made tractable by AI-accelerated biology. He uses it to argue for an optimistic posture — a future where work is optional and disease is solvable — and warns that the people pushing for AI regulation are also shaping how the public feels about the technology. Friedberg goes deeper into the cultural mechanics: AI is being framed as anti-human in a way that mirrors anti-nuclear and anti-industrial backlashes of the 20th century. He argues the United States can't unilaterally slow down because China and others won't — and tries to separate genuine safety concerns from elite class anxiety. Chamath then makes a pointed observation that none of the survey data on AI job loss actually asks the truck drivers, package sorters, and ICU nurses themselves how they feel about the tools. > *"We're listening too much to the inventors of AI. They're geniuses. They're smart. We need to be listening to the frontline factory workers who are using AI saying, 'Wow, I was able to add a third shift.'"* ## [27:22] Trump pulls AI EO, US-China AI relationship, dystopian AI layoffs A Trump AI executive order was scrubbed at the last minute — the panel walks through what was reportedly in it (review of frontier-model training runs) and whether any pre-release regulatory framework is workable. Jason argues a state-by-state patchwork is the more likely outcome regardless of what Washington does. The conversation pivots to Meta's latest round of layoffs and the way they were communicated. Gavin and Jason agree the messaging — leaning on "AI productivity gains" as the public reason — landed badly even with people who accept the underlying logic, and Jason argues it became a case study in how *not* to message AI-driven workforce changes. > *"Because the reality is that if this is the way that you're going to message something as critical as this, I think you did a horrible job."* ## [45:19] SpaceX S-1 tear down! Breaking down the three major businesses and the case for a $2T valuation SpaceX filed its S-1 on Wednesday. Jason breaks the company into three businesses: launch (which could be hundreds of millions of paying subscribers via Starlink), Elon Web Services / xAI / Colossus compute, and rockets. The AI-cloud line item alone is around $15B and growing roughly 2x year over year, anchored by an Anthropic deal Gavin calls "extraordinary." Gavin then makes the case that Colossus matters because raw gigawatt-class data centers are now the binding constraint, and SpaceX-adjacent build velocity is the moat. He uses Cursor's Composer 2.5 release — Pareto-dominant on three or four weeks of RL training — as evidence that whoever owns the compute owns the next model generation, and walks through why rapid reusability on Starship compresses the unit economics of getting payload to orbit faster than any competitor can model. > *"If you look at who's actually capable of delivering a gigawatt data center, these guys are the closest, like an actual gigawatt."* ## [71:22] Nvidia smashes earnings but stock falls, why people are shorting chips Nvidia blew out earnings again — 20% sequential growth would be a high-growth print for any other company, the dividend was raised 25x, and the CFO committed to returning 50% of free cash flow. Yet the stock sold off, and Leopold Aschenbrenner's reported pivot away from chip exposure is being read as a smart-money signal. Gavin takes the bear case apart: at current PE Nvidia is cheap relative to growth, and the segment breakdown obscures how much the "AI clouds" line is dragging the multiple. He flags that the true useful life of a GPU is closer to two years than five, which means the reported profits of every hyperscaler running these chips are overstated — a real concern, not a stock-killer. He also notes Nvidia's CPU business is on track to do $20B this year, making it overnight one of the largest CPU manufacturers in the world. > *"The true lifespan of a GPU is more like two years and therefore the profits of all these businesses are overstated."* ## [82:25] Market update: Flashing red signals, oil, inflation, yields up The macro snapshot: May inflation expected at 4.2%+, Fed rate-hike odds back on the table, UK yields at the highest since the great financial crisis, oil and gold both moving. Chamath warns that when the currency-debasement mechanism finally breaks, the downside is non-linear. Gavin counters with relative optimism on the US: America is self-sufficient in energy, the AI build-out is structurally good for re-industrialization, and even in an ugly global scenario the US is the least-bad place to be invested. He flags AI fundamentals also have a seasonality that investors are starting to model — the same way e-commerce and subscription businesses do. > *"While it's terrible for everyone, it is relatively the best for America because we are self-sufficient in energy."* ## [92:45] China trip flops, or was progress made behind the scenes? A 48-hour US tech-CEO-plus-president trip to Beijing produced thin public deliverables: some soybeans, some H100/A200 sales to Chinese players. The panel asks whether that's the real story or just the visible surface, and whether the immediate China-Russia bonding moment afterward says more about the trajectory than any handshake photo. Gavin argues the more important read is structural: keeping America ahead in AI requires keeping the trans-Pacific relationship just stable enough to avoid a full decoupling shock, and that's a defensible strategic logic even if the optics are unsatisfying. He also paints a what-if scenario around the Strait of Hormuz to make the point that energy independence is what gives the US the option to act asymmetrically. Jason closes with thanks to Gavin and an invite back to the Summit. > *"There's sound arguments that this is stabilizing for the world and is the best highest probability path for keeping America ahead in AI."* ## Entities - **Jason Calacanis** (Person): Host, LAUNCH founder, MC of this episode. - **Chamath Palihapitiya** (Person): Host, Social Capital CEO; pushed the "listen to frontline AI users" framing. - **David Friedberg** (Person): Host, The Production Board CEO; led the cultural / historical analysis of the AI backlash. - **Gavin Baker** (Person): Guest host, Atreides Management founder/CIO; carried the investing thread across SpaceX, Nvidia, and macro. - **Andrej Karpathy** (Person): Joining Anthropic's new pre-training team; OpenAI co-founder, ex-Tesla FSD lead. - **Anthropic** (Organization): Hired Karpathy; EBIT-positive last quarter per WSJ; $15B AI-cloud deal with SpaceX-adjacent compute. - **SpaceX** (Organization): Filed S-1; three businesses (launch/Starlink, Elon Web Services compute, rockets); $2T valuation case. - **Nvidia** (Organization): Earnings blowout but stock sold off; $20B CPU run-rate; $5.3T market cap. - **Cursor** (Software): Composer 2.5 model release used as proof of fast RL-driven catch-up dynamics. - **Richard Sutton's bitter lesson** (Concept): Scaling beats clever architectures — framing for why Karpathy's move matters. - **GPU useful life** (Concept): Closer to ~2 years than ~5, so hyperscaler reported profits are overstated. - **Strait of Hormuz scenario** (Concept): Energy-independence-as-strategic-option argument for the US in the China game.

Marc Benioff, CEO de Salesforce, se une a Jason Calacanis, David Friedberg y Chamath Palihapitiya (con David Sacks ausente) en un episodio de amplio alcance anclado en dos historias de actualidad: la primera cumbre Trump-Xi desde 2017 y el acelerado embate de la IA sobre las valoraciones del software empresarial. Benioff, presente en la cena de estado saudí, el Castillo de Windsor y esta delegación de la cumbre, ofrece una visión de primera fila sobre la diplomacia comercial entre Estados Unidos y China, antes de girar hacia la revalorización existencial de su propia compañía: argumenta que la infraestructura de datos y la plataforma de agentes de Salesforce la sitúan en el lado correcto de la disrupción por IA. La segunda mitad cubre el choque entre OpenAI y Apple, el demo multimodal en tiempo real de Thinking Machines, los alarmantes datos de El Niño de Friedberg y la ofensiva de Anthropic contra los esquemas de SPV en capas. ## [00:00] ¡Marc Benioff, CEO de Salesforce, se une al show! Sacks no está esta semana y Benioff ocupa su lugar. Jason pregunta de inmediato sobre el posicionamiento político de Benioff: exdonante demócrata, ahora asistiendo a cenas de estado saudíes y aparentemente bienvenido en la administración actual. Benioff descarta por completo el encuadre partidista. > *"No soy demócrata ni republicano. Soy americano."* Chamath señala que Benioff acumuló invitaciones al Castillo de Windsor, la visita del Príncipe Carlos a Estados Unidos y la cena de estado saudí en rápida sucesión: el raro CEO tecnológico que navega entre administraciones sin fricciones. El contexto presenta a Benioff como una voz excepcionalmente creíble sobre la cumbre que se desarrolla en tiempo real. ## [01:14] Cumbre Trump-Xi, hacer negocios en China como empresa estadounidense, impacto en los americanos y las elecciones de mitad de período El séptimo encuentro cara a cara entre Trump y Xi, demorado dos meses por la guerra con Irán, se abrió en Pekín con Xi advirtiendo que una mala gestión de Taiwán podría poner toda la relación "en una situación extremadamente peligrosa." Polymarket situó la probabilidad de invasión en 2026 en el 6% con 23 millones de dólares en volumen. En materia comercial, Xi se comprometió a comprar soja, GNL estadounidense y 200 aviones Boeing, y pidió una "puerta más abierta" al comercio. La delegación estadounidense parece un consejo de administración corporativo: Jensen Huang vendiendo chips, Kelly Ortberg vendiendo aviones, Brian Sykes de Cargill vendiendo soja, y Visa y Mastercard presionando por acceso al mercado de pagos. Friedberg encuadró la cumbre a través del prisma de la trampa de Tucídides: cuando una potencia en ascenso se encuentra con una en declive, el conflicto es históricamente probable. Aun así, argumentó que un momento de expansión de recursos, impulsado por la IA y la biotecnología, ofrece una salida poco común a ese patrón. > *"Parece que en este momento, cuando estamos viendo estos extraordinarios cambios tecnológicos desbloqueados por la IA, la automatización, la biotecnología y todo lo que podría anunciar una verdadera abundancia por delante, es el momento perfecto para decir que quizá el mundo pueda ser más multipolar."* Benioff confirmó que Salesforce no tiene oficinas ni empleados en el continente chino: todos los ingresos de China fluyen a través de una asociación exclusiva con Alibaba para cumplir con la ley de residencia de datos. Espera que la cumbre genere flujo real de pedidos en toda la delegación. Chamath argumentó que la jerarquía confuciana vertical de China hace que la diplomacia a nivel de CEO sea más efectiva que los canales burocráticos, y que los americanos que sienten el aprieto de la inflación necesitan que el acuerdo funcione. ## [18:46] Taiwán, chips, modelos de IA y la paz a través del comercio Benioff rechazó la premisa de que Taiwán es la prioridad central de China, insistiendo en que la prosperidad económica y el crecimiento de la clase media importan más a Xi que la ambición territorial. Ante la pregunta directa de si Estados Unidos debería defender Taiwán ante un bloqueo chino, evitó el planteamiento binario: "Creo que China y Taiwán se reconciliarán." Chamath adoptó una visión estructural: Estados Unidos está a roughly 1-2 nanómetros de la paridad doméstica en chips, punto en el que el valor estratégico de Taiwán pasa a ser económico antes que existencial. > *"Estamos en un punto donde probablemente estamos a 1 o 2 nanómetros de poder hacer lo que necesitamos que Taiwán haga estratégicamente por nosotros. Hoy es económico, y si sacas eso de la mesa, creo que tendremos una actitud muy diferente hacia Taiwán."* La propuesta de Chamath: vender los chips de todos modos, porque dejar que Huawei gane la carrera de semiconductores es peor que dejar que Nvidia venda en China con controles KYC sobre el uso de modelos. Benioff coincidió en que los modelos de IA chinos están cerca de la paridad con los estadounidenses a pesar de las restricciones de chips, lo que socava el argumento del embargo. Friedberg añadió que, a medida que China construye fábricas y equipos de capital propios, la irremplazabilidad de Taiwán se reduce por su propio camino, independientemente de los resultados políticos. ## [31:41] El impacto de la IA en el software: ¿qué SaaS prospera y qué SaaS muere? Jason expuso la revalorización sin rodeos: Salesforce bajó un 37%, ServiceNow un 42%, Workday un 45%, unos 180.000 millones de dólares en capitalización de mercado combinada esfumados ante la suposición de que la IA dejará obsoleto al SaaS gestionado. Benioff salió al frente. > *"No es mi primera apocalipsis del SaaS, honestamente, pero es la apocalipsis del SaaS actual."* Su argumento: el mercado se revalorizó sobre una premisa falsa. La apuesta de Salesforce es Agentforce: agentes de IA anclados en datos empresariales reales, no modelos genéricos propensos a alucinaciones. La adquisición de Informatica por entre 8.000 y 9.000 millones de dólares proporciona la capa de armonización de datos que hace confiables a los agentes: "La IA es muy probabilística; necesita estar anclada en la verdad, en una única fuente de verdad, o simplemente no puede funcionar bien." Benioff añadió que Salesforce gastará roughly 300 millones de dólares en Anthropic este año exclusivamente para agentes de codificación internos, comprimiendo los ciclos de implementación. Chamath dividió el mercado en dos: el extremo bajo ya terminó, las soluciones puntuales genéricas sin relaciones profundas con clientes están muertas; pero el extremo alto, donde opera Salesforce, está posicionado para beneficiarse del examen de retorno de inversión cuando los mercados públicos dejen de estar "eufóricos con la IA" y pregunten qué produjeron 3 billones de dólares en capex. Los supervivientes serán quienes tengan relaciones a nivel de C-suite, churn negativo y la capacidad de ofrecer las capacidades de IA como resultados medibles. ## [47:26] OpenAI considera demandar a Apple por el fracaso de la integración con ChatGPT Bloomberg informó que OpenAI podría demandar a Apple por incumplimiento de contrato: el acuerdo ChatGPT-Siri de 2024 colapsó en la práctica porque Apple dirige las consultas a ChatGPT solo cuando los usuarios dicen explícitamente "ChatGPT," nunca promocionó la integración, y OpenAI nunca vio los ingresos por suscriptores que esperaba. La defensa de Apple apunta a preocupaciones de privacidad sobre las prácticas de datos de OpenAI. Benioff reencuadró la historia como una divergencia estratégica entre los laboratorios de IA: Grok construyó compañeros y "sex bots," OpenAI apostó por Sora y redes publicitarias, Gemini lanzó Nano, y Anthropic ignoró todo eso para centrarse en agentes de codificación, y Anthropic resultó tener razón. Lanzó una pista sobre funcionalidad de codificación nativa en Slack aún sin anunciar. > *"Anthropic dijo que no saben de esos sex bots ni de Nano Banana, pero que van a hacer agentes de codificación. Y resultó que Anthropic tenía razón. Y de repente el cohete despegó."* Chamath planteó la pregunta de fondo: ¿qué le ocurre a Apple si la capa de interacción con la IA se desplaza completamente fuera del dispositivo? Predijo un "momento iPhone" de parte de un fabricante de hardware inesperado: un dispositivo ambiental delgado y siempre encendido que haga irrelevante al MacBook Pro para la inferencia de IA. Friedberg señaló que la estrategia actual de Apple consiste en llenar huecos antes que en tener visión, y que G Suite está quitando silenciosamente cuota empresarial a la pila de productividad de Apple. ## [56:54] Thinking Machines lanza modelo en tiempo real, el futuro de la IA para el consumidor y los modelos multisensoriales Thinking Machines, de Mira Murati, lanzó un modelo multimodal en tiempo real que monitorea el escritorio, escucha el audio ambiente y procesa la entrada de la webcam simultáneamente en intervalos de 200ms a través de dos pipelines paralelos: uno para razonamiento retrospectivo profundo y otro para respuesta en vivo. Al mismo tiempo, Apple ha patentado cámaras en el interior de los AirPods. > *"Los modelos multisensoriales son la próxima gran ola para la IA, aunque todavía no llegaremos a la AGI en ese punto."* Benioff argumentó que los LLM entrenados con lenguaje tienen limitaciones fundamentales: la cognición humana integra visión, audición y propiocepción en paralelo sobre hardware biológico. El anclaje multisensorial es la capa que falta. La economía de tokens es impresionante: el monitoreo ambiental en tiempo real a 8 horas por usuario al día supondría 1000 veces el consumo empresarial actual. Benioff rechazó la carrera de "modelo más grande = mejor," prediciendo que la inteligencia distribuida integrada en apps y dispositivos importará más que la escala bruta del modelo, y señalando espacio para una "nueva empresa prometedora" que combine sensores ambientales con contexto empresarial. ## [62:24] Rincón de Ciencia: Impactos de un El Niño históricamente fuerte en 2026 Friedberg presentó datos de anomalías de temperatura oceánica que muestran temperaturas superficiales del mar encaminadas hacia la mayor desviación de la norma desde 1877, roughly 4°C por encima de la línea base. La energía térmica almacenada: 11 millones de teravatios-hora, frente al consumo humano anual global de 25.000 teravatios-hora. > *"Eso equivale a 500 años de energía humana en este océano. Y en los próximos meses, esa energía se liberará en la atmósfera, lo que, con un 99% de confianza, hará que el próximo año sea el más caluroso registrado por un amplio margen."* La cascada: los vientos alisios alterados impulsan ríos atmosféricos hacia California y la costa del Golfo; las cúpulas de calor se extienden sobre Phoenix e interior de Canadá; los monzones indios fallan con alta probabilidad, amenazando a 150 millones de agricultores y 1.500 millones de personas dependientes de la alimentación; las exportaciones agrícolas de Brasil a Indonesia y Filipinas colapsan; los precios del trigo suben globalmente. Phoenix ya estaba a 106°F en mayo. Los mercados de materias primas cotizan activamente la exposición a El Niño. El lado positivo parcial de Friedberg: la genética de cultivos ha mejorado la resiliencia a la sequía y las tierras agrícolas de Siberia se están expandiendo, pero esas ganancias no rescatan la ventana de cosecha de 2026. ## [71:40] Anthropic arremete contra las "Dark SPVs" Anthropic señaló formalmente a las plataformas que venden SPVs en múltiples capas a inversores minoristas, el modelo de "dentistas a los que cobran comisiones de carga del 10%," y declaró que anulará las acciones vendidas a través de estructuras no autorizadas. Chamath lo respaldó sin reservas: cada empresa pre-IPO debería seguir el ejemplo, avanzar hacia los mercados públicos y dejar que estas estructuras desaparezcan. > *"Una vez que SpaceX salga a bolsa, una vez que Anthropic salga a bolsa, una vez que OpenAI salga a bolsa, veremos una letanía de demandas en todas direcciones entre los promotores de estas SPVs. No deberían estar permitidas."* Chamath predijo una oleada de consecuencias legales cuando las principales empresas de IA salgan a bolsa y los inversores minoristas en SPVs descubran que los números no cuadran. El capítulo cierra con Benioff hablando del modelo filantrópico 1-1-1 de Salesforce, el 1% de acciones, el 1% de beneficios y el 1% del tiempo de los empleados desde la fundación, que hoy da servicio gratuito a 50.000 organizaciones sin ánimo de lucro en la plataforma, y un emotivo recuerdo de Susan Wojcicki. ## Entidades - **Marc Benioff** (Persona): Presidente y CEO de Salesforce; invitado en este episodio; arquitecto del modelo filantrópico 1-1-1 y la plataforma de agentes de IA Agentforce - **David Friedberg** (Persona): Presentador; CEO de The Production Board; expuso el rincón de ciencia sobre El Niño - **Chamath Palihapitiya** (Persona): Presentador; CEO de Social Capital; defendió la supervivencia del SaaS de gama alta de Salesforce y la proliferación de chips de Nvidia - **Salesforce / Agentforce** (Software): CRM empresarial y plataforma de agentes de IA; la apuesta de Benioff de que los agentes anclados en datos son lo contrario a una sentencia de muerte para el SaaS - **Anthropic** (Organización): Empresa de seguridad en IA; proveedor preferido de agentes de codificación por Benioff (~300 millones de dólares en gasto planificado en Salesforce); también tomando medidas contra estructuras de SPV no autorizadas - **OpenAI** (Organización): Considera demandar a Apple por el fracaso de la integración ChatGPT-Siri; pivotando hacia agentes de codificación tras el éxito de Anthropic - **Thinking Machines / Mira Murati** (Organización): Lanzó un modelo multimodal ambiental en tiempo real que procesa escritorio, audio y webcam simultáneamente en intervalos de 200ms - **Trampa de Tucídides** (Concepto): Marco de ciencia política sobre el ciclo de conflicto entre potencia en ascenso y potencia en declive, invocado por Friedberg para enmarcar la oportunidad de abundancia cooperativa en la cumbre EE.UU.-China - **Dark SPVs** (Concepto): Vehículos de propósito especial en múltiples capas que venden capital pre-IPO en empresas privadas de IA a inversores minoristas, a menudo con altas comisiones y legitimidad jurídica cuestionada

Charles Koch y su hijo Chase se sientan con David Friedberg para contar cómo Koch Inc. creció 9,000 veces: de una empresa petrolera de 300 empleados en Oklahoma en 1961 a un conglomerado privado de 130,000 empleados que abarca energía, química, productos forestales, bienes de consumo y capital de riesgo, sin salir jamás a bolsa. La conversación gira en torno al Principle-Based Management (PBM): el marco de 41 principios que guía cada decisión de contratación, adquisición y cambio cultural en Koch. Charles y Chase también abordan la caricatura política que rodea al nombre Koch, explicando su giro desde el libertarismo partidista hacia la coalición más amplia Stand Together, enfocada en la reforma educativa y el florecimiento humano. El episodio cierra con IA y capitalismo: ambos ven la innovación sin restricciones y el empoderamiento de abajo hacia arriba como el único camino creíble ante las presiones económicas que se avecinan. ## [00:00] David Friedberg da la bienvenida a Charles y Chase Koch David Friedberg abre la conversación en un evento de Forbes señalando que él y Chase Koch se conocen desde 2013 a través de la industria agrícola y que desde entonces han sido socios comerciales. Enmarca a Koch Inc. como "la historia sin contar" de la empresa americana: posiblemente el negocio familiar privado más rentable del mundo, pero prácticamente invisible en comparación con sus pares que cotizan en bolsa. La apertura también establece las expectativas para la audiencia del All-In Podcast: una extensa conversación en vivo con el presidente y el presidente de la próxima generación de Koch Inc., registrada en directo. > "Siempre sentí que Koch Industries era esa historia sin contar: probablemente el negocio familiar privado más rentable del mundo." > — David Friedberg ## [01:04] Panorama de Koch Inc.: escala, líneas de negocio e historia Friedberg ofrece la base estadística: si Koch cotizara en bolsa, sus ingresos la situarían entre las 25 primeras de la Fortune 500. Fundada en 1940 por Fred Koch en Wichita, Kansas, la empresa opera hoy en 60 países con más de 120,000 empleados en energía, agricultura, química, productos de construcción, bienes de consumo, computación en la nube y un activo portafolio de inversiones minoritarias. Koch reinvierte el 90% de sus ganancias en el negocio, una decisión estructural que la distingue de las empresas públicas que optimizan para resultados trimestrales. Charles señala de qué va a tratar realmente la conversación: no de hitos de ingresos, sino de los principios y los fracasos que hicieron posible el crecimiento sostenido. > "Un modelo operativo muy singular, que incluye principios de innovación disruptiva, reinversión del 90% de las ganancias en nuevos negocios y crecimiento, y valores meritocráticos." > — David Friedberg ## [02:21] Construyendo el negocio: los primeros días y la incorporación de Charles Koch (1961) Charles Koch se incorporó al negocio familiar en 1961 a los 25 años, recién salido del MIT y de una temporada en Arthur D. Little. El ultimátum de su padre Fred fue directo: "Hijo, o vuelves a dirigir la empresa o voy a tener que venderla, porque mi salud está mal y las empresas no van bien y no me queda mucho tiempo de vida." La empresa tenía entonces unos 300 empleados, dos negocios principales (bandejas de fraccionamiento y recolección de petróleo crudo en Oklahoma) y una disfunción operativa importante. Las lecciones tempranas cristalizaron un principio central de Koch: crecer delimitado por capacidades, no por industrias. El negocio de bandejas de fraccionamiento fracasó en parte porque su presidente era un controlador autoritario que alienó a ingenieros y clientes por igual. Charles empezó a preguntarse no "¿en qué industria estamos?" sino "¿qué podemos hacer mejor que nadie, y en qué punto de la cadena de valor eso crea más valor?" Ese reencuadre, aplicado repetidamente durante décadas, explica la secuencia de industrias aparentemente inconexas que Koch fue entrando. > "Hijo, o vuelves a dirigir la empresa o voy a tener que venderla, porque mi salud está mal y las empresas no van bien y no me queda mucho tiempo de vida." > — Charles Koch, citando a su padre Fred Koch ## [11:31] Fracasos, destrucción creativa y aprender de los errores Charles abre con una provocación: "Si no estás fracasando en todo, es que no estás haciendo nada nuevo." Recuenta pérdidas tempranas, incluyendo un intento fallido de convertir coque de petróleo en carbón activado, y un patrón de entrar en negocios sin las capacidades subyacentes necesarias. El verdadero aprendizaje llegó al diagnosticar por qué ocurrió cada fracaso: casi siempre fue por violar uno de los principios operativos de Koch. Chase añade la perspectiva del portafolio de capacidades: la expansión de Koch desde la recolección de petróleo crudo hacia el gas natural, los químicos, los fertilizantes y finalmente los productos forestales no fue una diversificación aleatoria, sino las mismas capacidades subyacentes redirigidas hacia nuevas aplicaciones. También describe Koch Disruptive Technologies (KDT), que él fundó, como un experimento estructural difícil de hacer consistentemente rentable: una evaluación honesta de su propio fracaso. La decisión de cerrar o hacer un pivot, dice Charles, se reduce a una prueba: ¿hemos perdido la capacidad de crear valor superior para los clientes de una manera por la que seamos recompensados? > "Cuando perdemos suficiente dinero, eso es cuando ya basta. Cuando decidimos que no tenemos la capacidad de crear valor superior para nuestros clientes." > — Charles Koch ## [19:22] Cultura y Principle-Based Management Este es el centro intelectual del episodio. Charles traza los orígenes del sistema PBM en los peores fracasos de Koch, todos con una causa raíz en común: promover a personas con malos valores hacia posiciones de liderazgo. Dos ejemplos casi catastróficos destacan: una operación de trading temeraria que casi quebró la empresa durante la guerra de Oriente Medio en 1973, y un episodio posterior en el que líderes con motivaciones destructivas ocultaban fracasos mientras inventaban éxitos. El antídoto fue contratar primero por valores y segundo por talento, y estructurar una cultura donde la motivación por la contribución, querer tener éxito ayudando a otros a tener éxito, desplace la búsqueda de poder. Chase profundiza con un planteamiento que va al grano: ¿y si todos en la empresa supieran exactamente qué hacer sin que nadie se lo dijera? Ese es el estado objetivo que PBM está diseñado para producir. La estrategia de gestión del cambio evita los mandatos de arriba hacia abajo: se encuentra el subgrupo más ansioso por probar los principios, se demuestran resultados, y se deja que la demanda tire de la transformación hacia el resto de la organización. El conocimiento colectivo reemplaza el juicio de unos pocos inteligentes en la cima. > "¿Y si pudieras tener un negocio y una cultura, pequeños, medianos o grandes, donde todos supieran qué hacer sin que nadie se los dijera?" > — Chase Koch ## [33:53] La adquisición de Georgia-Pacific y la transformación cultural La adquisición de Georgia-Pacific en 2005 fue la mayor apuesta de Koch en ese momento: "una apuesta enorme", dice Chase, cuando la empresa era mucho más pequeña. Charles traza la lógica: Koch vio las operaciones de pulpa y papel de Georgia-Pacific como una extensión natural de sus capacidades en procesos químicos, una conexión que se remontaba hasta la tesis del MIT de Fred Koch sobre la producción de pulpa en Maine. Inicialmente propusieron comprar solo las divisiones de commodities; cuando ese acuerdo no pudo cerrarse por los litigios pendientes, ofrecieron comprar la empresa entera. Lo que siguió fue una transformación cultural de años en una sede de 51 pisos en Atlanta construida sobre la burocracia de arriba hacia abajo. Koch reemplazó el liderazgo, recompensó a los trabajadores que detectaron y corrigieron ineficiencias, y compartió los ahorros de costos con los miembros del sindicato que los encontraron. Chase describe sus propios años en las operaciones de primera línea de Koch, viviendo en un tráiler en un corral de engorde, trabajando en una planta de líquidos de gas, como fundacionales para un liderazgo creíble después. El cambio cultural tarda mucho más de lo que cualquier comprador espera, y casi siempre requiere reemplazar al grupo de liderazgo que sostiene el viejo paradigma. > "Tarda muchísimo más de lo que uno piensa en cambiar la cultura, y en casi todos los casos requiere cambiar al liderazgo que tiene el paradigma del empoderamiento de abajo hacia arriba." > — Chase Koch ## [56:17] Reforma educativa y cambio social Stand Together, la red sin fines de lucro que Charles ha ido construyendo durante 60 años bajo distintos nombres, es hoy una de las organizaciones filantrópicas más grandes de Estados Unidos. Chase dirige la generación de alianzas, y reencuadra su misión: no como cabildeo político, sino como la aplicación de los mismos principios de Koch a los desafíos sociales, empezando por la educación. El COVID-19 cambió drásticamente la opinión pública: antes de 2020, aproximadamente el 20% de las familias estaban abiertas a alternativas a la escuela tradicional; después de ver a sus hijos aprender más en YouTube que en las clases de Zoom, ese número se disparó. Stand Together ha ayudado desde entonces a sembrar más de 5,000 microescuelas. Programas aliados como Alpha School de Joe Limont usan la gamificación y el aprendizaje basado en proyectos para llevar a alumnos que reprobaban al tope de la clase en tres meses. Chase también aplica el principio de la ventaja comparativa a sí mismo: se despidió a sí mismo como presidente de Koch Fertilizer cuando reconoció que otra persona tenía esa ventaja comparativa, y usa esa misma lógica para rediseñar roles en toda la plantilla de 130,000 personas de Koch. > "Antes del COVID, aproximadamente el 20% de las familias estaban abiertas a un nuevo modelo de educación. Durante el COVID todos vieron qué tan roto estaba el sistema: sus hijos habían aprendido más en YouTube que en el salón de clases." > — Chase Koch ## [72:37] IA, desafíos económicos y el futuro del capitalismo Friedberg presiona a Charles para que rinda cuentas de la narrativa política de Koch: las décadas de participación en el Partido Libertario y el giro posterior hacia la coalición más amplia de Stand Together. Charles es sincero: pasó demasiados años trabajando solo con personas que coincidían con él en cada principio, lo que limitó su alcance. La perspectiva de Viktor Frankl, "cada vez más personas tienen los medios para vivir pero no tienen un sentido por el que vivir", reorientó su pensamiento hacia las raíces motivacionales del deterioro social más que hacia remedios puramente políticos. La lección: las estrategias de la libertad no pueden tomar prestado del totalitarismo; someter a una coalición a pruebas de pureza ideológica la destruye. En cuanto a la IA, la posición de Chase es clara: innovación sin restricciones, sistemas abiertos, empoderar a las personas con herramientas de IA en lugar de prohibirlas. Koch está ejecutando PBM como un marco nativo de IA, y Chase creó un asistente de IA para el nuevo libro para que los lectores puedan interactuar directamente con los principios, yendo mucho más allá de lo que Charles anticipaba cuando invitó a Chase a coescribir. El episodio cierra con el legado que Charles declaró querer dejar: que Estados Unidos cumpla más plenamente la promesa de la Declaración de Independencia. > "El problema de hoy es que cada vez más personas tienen los medios para vivir pero no tienen un sentido por el que vivir." > — Charles Koch, citando a Viktor Frankl ## Personajes - **David Friedberg** — Anfitrión; cofundador de The Production Board; socio comercial de Chase Koch desde 2013 a través de la industria agrícola - **Charles Koch** — Presidente y CEO de Koch Inc. desde 1967; ingeniero graduado del MIT; coautor del libro Principle-Based Management; ha liderado el crecimiento de 9,000 veces en valor de Koch - **Chase Koch** — Presidente de Koch Inc.; fundador de Koch Disruptive Technologies; coautor del libro PBM junto a Charles; lidera la generación de alianzas de Stand Together - **Koch Inc.** — Conglomerado familiar privado con sede en Wichita, KS; fundado en 1940 por Fred Koch; más de 130,000 empleados en energía, química, productos forestales, bienes de consumo, software y capital de riesgo - **Principle-Based Management (PBM)** — Marco operativo de 41 principios de Koch; enfatiza la motivación por la contribución, la contratación por valores primero, el empoderamiento de abajo hacia arriba y tratar cada unidad de negocio como un laboratorio - **Georgia-Pacific** — Empresa de productos forestales y de consumo adquirida por Koch en 2005; la mayor adquisición de Koch; caso de estudio principal de transformación cultural bajo PBM - **Koch Disruptive Technologies (KDT)** — Brazo de venture capital fundado por Chase Koch; inversiones minoritarias en empresas tecnológicas disruptivas; descrito como estructuralmente difícil de hacer consistentemente rentable - **Stand Together** — Red filantrópica de Charles Koch activa desde 2003; se enfoca en la reforma educativa, la reducción de la pobreza y el cambio social transpartidista; ha sembrado más de 5,000 microescuelas tras el COVID

In one of their most consequential episodes, the All-In besties dissect SpaceX's surprise compute lease to Anthropic — the deal that may cement Anthropic as AI's dominant platform — and debate whether David Sacks's "Rockefeller" framing is prophecy or paranoia. The group then wrestles with a White House trial balloon about an "FDA for AI," ultimately concluding it was mostly media spin, before closing with a bullish-but-cautious read on the AI-driven market boom. Brad Gerstner fills in for David Friedberg, bringing investor perspective from both public and private markets across the episode's 82 minutes. ## [00:00] Bestie intros! Thoughts on the LA mayor election Jason Calacanis opens with the full crew: Chamath Palihapitiya, David Sacks, and fifth bestie Brad Gerstner joining in for David Friedberg, who is out sick. The warm-up quickly turns to the LA mayoral race, where Spencer Pratt is mounting a surprisingly effective challenge to incumbent Karen Bass. The group praises Pratt's viral debate performance — evisceration of the city council candidate over homeless policy — and Chamath notes the power of a sharp social-media team in modern politics. Brad flags a California ballot initiative that would constitutionally protect retirement savings and ban a wealth tax, reading it as a potential seismic signal. Jason observes that New York City hedge-fund titan Ken Griffin publicly announced he is pulling investment from New York after NYC councilman Zohran Mamdani targeted his home in a campaign video, underlining the tension between aggressive progressive politics and capital flight. > *"If California effectively passes a constitutional amendment protecting retirement savings and personal assets and banning the wealth tax and [Spencer Pratt] gets elected, the message that would send to the country — that's a very non-consensus view that I'm becoming increasingly optimistic about."* — Brad Gerstner ## [04:38] SpaceX-Anthropic deal, Elon Web Services, SpaceX IPO valuation, Anthropic's insane growth trajectory Jason leads with the blockbuster news: SpaceX has leased all of Colossus 1 — its H100-based Memphis data center — to Anthropic, adding over 220,000 Nvidia GPUs and 300 megawatts to Anthropic's supply-constrained capacity. The deal immediately doubled Claude Code's rate limits and removed peak-usage caps for paid users. Chamath frames Anthropic's explosive growth as purely supply-constrained: if unlimited power existed, revenues would be "even more parabolic." He sees the deal as Elon strategically de-risking SpaceX's valuation story — blunting bear cases around delayed orbital data centers while generating near-term revenue to subsidize Grok training. Brad estimates the arrangement adds $4–5 billion in incremental 2026 revenue for SpaceX, calling EWS (Elon Web Services) a genuine fourth hyperscaler alongside AWS, Azure, and GCP. He also warns that organized activists — not organic local opposition — are using the same playbook that stalled nuclear construction in America to delay data-center permitting. David Sacks notes that Anthropic grew from $10B ARR on January 1 to $44B ARR by April — a trajectory he calls unlike anything Silicon Valley has ever witnessed. > *"Nobody in Silicon Valley has ever seen anything like it. Forget about the rest of the country. I mean, all we do in Silicon Valley is deal with exponentials. And still, people have never seen that kind of growth at that level of scale."* — David Sacks ## [26:48] Is Anthropic the next great monopoly? Early signals or major overreaction? David Sacks draws an extended analogy between Anthropic and John D. Rockefeller's Standard Oil, arguing that safety-first rhetoric can function as regulatory capture — building a moat that locks in the emerging duopoly of Anthropic and OpenAI while blocking competitors. He notes that if Anthropic sustains its 10× annual growth for just 18 more months it could become "the most powerful monopoly ever created in human history," dwarfing the combined Mag-7 revenue. Brad pushes back hard: Anthropic and OpenAI are still fledgling startups on a GAAP basis, Google and Amazon are producing hundreds of billions in free cash flow to fund competing models, and pre-emptive antitrust action at the starting line of AI would be "a disaster." Jason translates Brad's position as "don't mess with my paper," since Altimeter holds positions in several of these companies. Sacks clarifies his northstar is vigorous competition — but he flags Anthropic's banning of OpenClaw from using its API as a concrete anti-competitive act worth scrutiny. > *"Unless something about their current trajectory changes, Anthropic will be the most powerful monopoly ever created in human history — a trillion dollars of ARR growing at some rate. Dario calls it AGI. I call it the biggest monopoly in human history."* — David Sacks ## [35:21] "FDA for AI" freakout, how the White House thinks about AI safety Reports surfaced that the White House was considering an executive order to create an AI working group that could require pre-release safety reviews for new frontier models — triggered, according to the New York Times, by Anthropic's classified "Mythos" model reportedly alarming national-security officials. NEC Director Kevin Hassett appeared on Fox Business drawing an FDA analogy, while Treasury Secretary Scott Bessent spoke more carefully about balancing innovation and safety. Sacks calls much of it "fake news" amplified by Andrew Ross Sorkin's DealBook column, noting that Susie Wiles, the White House Chief of Staff, issued a statement walking back the FDA framing. He reveals he spoke with Hassett directly and confirms no senior official actually supports a pre-approval regime. He points to the White House's March 20 National AI Regulatory Framework as evidence the administration favors specific solutions over broad regulatory capture. The group converges on one concrete measure: KYC (Know Your Customer) requirements before frontier model API access during preview periods, plus rapid deployment of cyber-capable AI to companies like CrowdStrike and Palo Alto Networks. > *"There is a substantial faction of AI ideologues or doomers who are basically employing the classic 'never let a crisis go to waste' strategy. Yes, we do have this cyber issue that is real — everyone needs to harden their systems now. But what they're trying to do is use that issue to try and create a permanent new infrastructure in Washington."* — David Sacks ## [52:01] Flipping AI's negative perception: Giving, healthcare and education innovation Jason shifts from regulatory defense to offense: how should the tech industry proactively counter negative public perception of AI? He proposes that companies going public — Anthropic, OpenAI, SpaceX — could dedicate 1–5% of IPO proceeds to every American via "Invest America" accounts, creating tangible shared upside. He also calls for serious engagement on minimum wage and universal healthcare, arguing that a financially healthier consumer base is structurally good for capitalism itself. Brad endorses the "Invest America" concept, adding that data center host communities should receive direct benefits like free local electricity. David pivots to political salience data: AI ranks 29th out of 39 voter issues — well below cost of living and economic growth, two metrics where AI is actively deflationary and expansionary. The industry's real message should be economic delivery, not safety governance. Chamath gives tech leaders a "D-minus trending to F" for communications and calls for tangible reinvestment in America at scale. > *"I think that there's a pretty profound vibe shift with respect to tech, tech oligarchs, Silicon Valley, and particularly AI. That vibe shift has already happened on Main Street, and I think that's starting to seep into Washington."* — Chamath Palihapitiya ## [60:04] Trading the AI market, state of the economy Brad leads a comprehensive market check: AWS on a $150B run rate (28% growth), Azure at $108B (39%), Google Cloud at $80B (63%). The S&P 500 is at all-time highs, the 10-year sits at 4.3%, and inflation is under control — far better outcomes than the doom scenarios predicted around tariffs and geopolitical conflicts. S&P 500 operating margins improved from 11% in 2023 to 13% in Q1 2026, and the Mag-5's combined headcount grew only 3% over three years while revenues surged. Chamath urges caution: there is still no direct evidence AI is lifting enterprise profit margins in aggregate, and a reckoning arrives in roughly 500 days when the fork between opex reduction and revenue growth will determine whether the AI boom is real or a mirage. Jason counters that for startups the ROI is already "fait accompli" — AI-generated ad creative at Nike and DoorDash, portfolio companies shipping product at half the headcount. David credits Trump administration policies — rescinding Biden's chip-export licensing and AI-approval regime, unleashing energy permits — for creating the conditions that enabled the boom, and notes that the unemployment rate for recent college graduates has actually improved, contradicting the entry-level-job-loss narrative. > *"I think we have kind of call it 500 days where you just got to be net long. But I think it's literally in the hundreds of days from now that you're going to have to have an important reckoning moment. The people that are paying for all these tokens need to see an actual benefit."* — Chamath Palihapitiya ## Entities - **Jason Calacanis** (Person): Host and moderator; angel investor and podcast co-founder - **Chamath Palihapitiya** (Person): General partner, Social Capital; co-host; contrarian macro voice on AI ROI and market cycles - **David Sacks** (Person): Co-host; former White House AI & Crypto Czar; framed Anthropic as a potential historic monopoly using the Rockefeller analogy - **Brad Gerstner** (Person): Founder & CEO, Altimeter Capital; fifth bestie; bullish on compute stocks and AI market structure - **Dario Amodei** (Person): CEO of Anthropic; referenced as "Daario D. Rockefeller" by Sacks; party to the SpaceX compute deal - **Elon Musk** (Person): CEO of SpaceX and xAI; architect of Elon Web Services and the Colossus 1 compute lease strategy - **Anthropic** (Organization): AI lab behind Claude; grew from $10B to $44B ARR in four months; center of monopoly and FDA debates - **SpaceX / xAI** (Organization): Lessor of Colossus 1 data center to Anthropic; emerging fourth hyperscaler under EWS branding - **Elon Web Services (EWS)** (Concept): SpaceX's compute-leasing business positioned as a hyperscaler competitor to AWS, Azure, and GCP - **Mythos** (Software): Anthropic's classified cyber-capable frontier model that reportedly alarmed White House national-security officials - **KYC for AI** (Concept): Proposal to require identity verification before granting API access to frontier models during preview periods - **Invest America** (Concept): Proposal for IPO-stage tech companies to dedicate a share of proceeds to universal investment accounts for US citizens