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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.

Salesforce CEO Marc Benioff joins Jason Calacanis, David Friedberg, and Chamath Palihapitiya (David Sacks absent) for a wide-ranging episode anchored by two real-time stories: the first Trump-Xi summit since 2017 and AI's accelerating assault on enterprise software valuations. Benioff — who has attended the Saudi state dinner, Windsor Castle, and this summit delegation — offers a front-row view of US-China commercial diplomacy, then turns to his own company's existential rerate, arguing Salesforce's data infrastructure and agent platform put it on the right side of AI disruption. The back half covers OpenAI's blowup with Apple, Thinking Machines' real-time multimodal demo, Friedberg's alarming El Niño data, and Anthropic's crackdown on layered SPV schemes. ## [00:00] Salesforce CEO Marc Benioff joins the show! Sacks is out this week, and Benioff fills the seat. Jason asks immediately about Benioff's political positioning — past Democratic donor, now attending Saudi state dinners and apparently welcome in the current administration. Benioff brushes off the partisan framing entirely. > *"I'm not a Democrat or Republican. I'm an American."* Chamath notes Benioff collected invites to Windsor Castle, Prince Charles's US visit, and the Saudi state dinner in quick succession — the rare tech CEO who moves across administrations without friction. The setup frames Benioff as an unusually credible voice on the summit unfolding in real time. ## [01:14] Trump-Xi summit, doing business in China as a US company, impact on Americans and the midterms Trump and Xi's seventh face-to-face meeting — delayed two months by the Iran war — opened in Beijing with Xi warning that mishandling Taiwan could put the entire relationship "in an extremely dangerous situation." Polymarket put the 2026 invasion probability at 6% on $23M in volume. On trade, Xi committed to buy soybeans, US LNG, and 200 Boeing jets, and called for a "wider door" on commerce. The US delegation reads like a corporate board: Jensen Huang selling chips, Kelly Ortberg selling planes, Brian Sykes of Cargill selling soybeans, Visa and Mastercard pushing for payment market access. Friedberg framed the summit through the Thucydides trap lens — as a rising power meets a declining power, conflict is historically likely — but argued that a resource-expansive moment, turbocharged by AI and biotech, offers a rare exit from that pattern. > *"It seems like in this moment when we are seeing these extraordinary technology shifts unlocked by AI and automation and biotech and all of these kind of moments of which could be true abundance ahead of us, it seems like the perfect moment to say maybe the world can be more multipolar."* Benioff confirmed Salesforce has zero offices or employees on the mainland — all China revenue flows through an exclusive Alibaba partnership to satisfy data residency law — and expects the summit to generate real order flow across the delegation. Chamath argued that China's top-down Confucian hierarchy makes CEO-level diplomacy more effective than bureaucratic channels, and that Americans who are feeling squeezed by inflation need the deal to work. ## [18:46] Taiwan, chips, AI models, and peace through trade Benioff pushed back on the premise that Taiwan is China's core priority, insisting economic prosperity and middle-class growth matter more to Xi than territorial ambition. On the direct question — should the US defend Taiwan if China blockades it? — he refused the binary: "I think China and Taiwan will reconcile." Chamath took a structural view: the US is roughly 1-2 nanometers away from domestic chip parity, at which point Taiwan's strategic value becomes economic rather than existential. > *"We are at a point where we're probably 1 to 2 nanometers away from being able to do what we need Taiwan to strategically do for us. Today it's economic and if you take that off the table, I think we'll have a very different attitude to Taiwan."* Chamath's prescription: sell the chips anyway, because letting Huawei win the semiconductor race is worse than letting Nvidia sell into China under KYC guardrails for model usage. Benioff agreed Chinese AI models are near-parity with US models despite chip restrictions, undercutting the case for an embargo. Friedberg added that as China builds domestic fabs and capital equipment, Taiwan's irreplaceability diminishes on its own timeline regardless of political outcomes. ## [31:41] AI's impact on software: What SaaS thrives, what SaaS dies? Jason laid out the rerate bluntly: Salesforce down 37%, ServiceNow down 42%, Workday down 45% — roughly $180 billion in combined market cap erased on the assumption that AI will make managed SaaS redundant. Benioff came out swinging. > *"It's not my first SaaS apocalypse, honestly, but it's the current SaaS apocalypse."* His argument: the market rerated on a false premise. Salesforce's bet is Agentforce — AI agents grounded in real enterprise data, not hallucination-prone generic models. The $8-9B Informatica acquisition provides the data harmonization layer that makes agents reliable: "The AI is very probabilistic — it needs to be locked down into the truth, into a single source of truth, or it just cannot work well." Benioff added that Salesforce will spend roughly $300M on Anthropic this year purely for internal coding agents, collapsing implementation cycles. Chamath split the market in two: the low end is finished — generic point solutions with no deep customer relationships are dead — but the high end, where Salesforce operates, is positioned to benefit from the ROI reckoning when public markets stop being "breathless about AI" and ask what $3 trillion in capex produced. The survivors will be those with C-suite relationships, negative churn, and the ability to package AI capability as measurable outcomes. ## [47:26] OpenAI is considering suing Apple over failed ChatGPT integration Bloomberg reported OpenAI may sue Apple for breach of contract: the 2024 ChatGPT-Siri deal collapsed in practice because Apple routes queries to ChatGPT only when users explicitly say "ChatGPT," never promoted the integration, and OpenAI never saw the subscriber revenue it expected. Apple's defense is privacy concerns over OpenAI's data practices. Benioff reframed the story as a strategic divergence among AI labs: Grok built companions and "sex bots," OpenAI pushed Sora and ad networks, Gemini shipped Nano, and Anthropic ignored all of it to focus on coding agents — and Anthropic turned out to be right. He teased unannounced Slack-native coding functionality. > *"Anthropic and they go we don't know about those sex bots and we don't know about Nano Banana but we're going to do coding agents. And it turned out Anthropic was right. And all of a sudden the rocket ship took off."* Chamath raised the deeper question: what happens to Apple if the AI interaction layer moves off the device entirely? He predicted an "iPhone moment" from an unexpected hardware player — a thin, always-on ambient device that makes the MacBook Pro irrelevant for AI inference. Friedberg noted Apple's current strategy is gap-filling rather than visionary, and that G Suite is quietly taking enterprise share from Apple's productivity stack. ## [56:54] Thinking Machines releases real-time model, future of consumer AI, multi-sensory models Mira Murati's Thinking Machines released a real-time multimodal model that watches your desktop, listens to ambient audio, and processes webcam input simultaneously at 200ms intervals across two parallel pipelines — one for deep retrospective reasoning, one for live response. Apple has simultaneously patented cameras inside AirPods. > *"Multi-sensory models are the next big wave for AI and then but we're still not at AGI at that point."* Benioff argued that LLMs trained on language are fundamentally limited: human cognition runs eyes, ears, and proprioception in parallel on biological hardware. Multi-sensory grounding is the missing layer. The token economics are dramatic — real-time ambient monitoring at 8 hours per user per day would be 1000x current enterprise consumption. Benioff pushed back on the "bigger model = better" arms race, predicting distributed intelligence embedded in apps and devices will matter more than raw model scale, and flagging space for a "hot new company" that aggregates ambient sensing with enterprise context. ## [62:24] Science Corner: Impacts of a historically strong El Nino in 2026 Friedberg presented ocean temperature anomaly data showing sea surface temperatures headed for the largest deviation from normal since 1877 — roughly 4°C above baseline. The stored thermal energy: 11 million terawatt-hours, against global annual human consumption of 25,000 terawatt-hours. > *"That's 500 years worth of human energy in this ocean. And over the next few months, that energy is going to be released into the atmosphere — and that will, with 99% confidence, make the upcoming year the hottest year on record by far."* The cascade: altered trade winds drive atmospheric rivers into California and the Gulf Coast; heat domes extend over Phoenix and interior Canada; Indian monsoons fail at high probability, threatening 150 million farmers and 1.5 billion food-dependent people; Brazil's crop exports to Indonesia and the Philippines collapse; wheat prices spike globally. Phoenix was already at 106°F in May. Commodity markets are actively trading El Niño exposure. Friedberg's partial upside: crop genetics have improved drought resilience, and Siberian farmland is expanding — but those gains don't rescue the 2026 harvest window. ## [71:40] Anthropic goes after "Dark SPVs" Anthropic formally called out platforms selling multi-layered SPVs to retail investors — the "dentists getting charged 10% loading fees" model — and stated it will negate shares sold through unauthorized structures. Chamath gave full-throated support: every pre-IPO company should follow suit, push toward public markets, and let these structures die. > *"Once SpaceX goes public, once Anthropic goes public, once OpenAI goes public, you're going to see a litany of these lawsuits back and forth between the purveyors of these SPVs — they should not be allowed."* Chamath predicted a wave of legal fallout once the major AI companies go public and retail SPV investors discover the math doesn't work. The chapter closes with Benioff discussing Salesforce's 1-1-1 philanthropy model — 1% equity, 1% profit, 1% employee time at founding, now running 50,000 nonprofits free on the platform — and a moving remembrance of Susan Wojcicki. ## Entities - **Marc Benioff** (Person): Chair and CEO of Salesforce; guest on this episode; architect of the 1-1-1 philanthropy model and Agentforce AI agent platform - **David Friedberg** (Person): Host; CEO of The Production Board; delivered the El Niño science corner - **Chamath Palihapitiya** (Person): Host; CEO of Social Capital; made the case for Salesforce's high-end SaaS survival and Nvidia chip proliferation - **Salesforce / Agentforce** (Software): Enterprise CRM and agent platform; Benioff's bet that data-grounded AI agents are the opposite of a SaaS death sentence - **Anthropic** (Organization): AI safety company; Benioff's preferred coding agent provider (~$300M planned spend at Salesforce); also cracking down on unauthorized SPV structures - **OpenAI** (Organization): Reportedly considering lawsuit against Apple over failed ChatGPT-Siri integration; pivoting toward coding agents following Anthropic's success - **Thinking Machines / Mira Murati** (Organization): Released a real-time ambient multimodal model processing desktop, audio, and webcam simultaneously at 200ms intervals - **Thucydides Trap** (Concept): Political science framework (rising vs. declining power conflict cycle) invoked by Friedberg to frame the US-China summit opportunity for cooperative abundance - **Dark SPVs** (Concept): Multi-layered special purpose vehicles selling pre-IPO equity in private AI companies to retail investors, often with high fees and disputed legal standing

Charles Koch e seu filho Chase sentam com David Friedberg para contar como a Koch Inc. cresceu 9.000 vezes: de uma empresa de petróleo com 300 funcionários em Oklahoma em 1961 para um conglomerado privado com 130.000 funcionários nos setores de energia, químicos, produtos florestais, bens de consumo e capital de risco, sem nunca abrir o capital. A conversa gira em torno da Gestão Baseada em Princípios (PBM): o framework de 41 princípios que orienta cada decisão de contratação, aquisição e mudança cultural na Koch. Charles e Chase também abordam a caricatura política estreita associada ao nome Koch, explicando sua virada de uma política libertária partisan para a coalização mais ampla do Stand Together, focada em reforma educacional e florescimento humano. O episódio termina em IA e capitalismo: ambos veem a inovação sem permissão e o empoderamento de baixo para cima como o único caminho crível diante das pressões econômicas à frente. ## [00:00] David Friedberg recebe Charles & Chase Koch David Friedberg abre a conversa num evento da Forbes, observando que ele e Chase Koch se conhecem desde 2013 pela indústria de agricultura e desde então foram parceiros de negócios. Ele enquadra a Koch Inc. como "a história não contada" da empresa americana: provavelmente o negócio familiar privado mais lucrativo do mundo, mas praticamente invisível comparado aos seus pares de capital aberto. A abertura também define as expectativas para o público do All-In: um raro encontro estendido com o presidente do conselho e o presidente da próxima geração da Koch Inc., gravado ao vivo. > "Sempre achei que a Koch Industries era essa história não contada — provavelmente o negócio familiar privado mais lucrativo do mundo." > — David Friedberg ## [01:04] Visão Geral da Koch Inc.: Escala, Linhas de Negócio e História Friedberg fornece a linha de base estatística: se a Koch fosse de capital aberto, sua receita a colocaria entre as 25 maiores do Fortune 500. Fundada em 1940 por Fred Koch em Wichita, Kansas, a empresa hoje opera em 60 países com mais de 120.000 funcionários nas áreas de energia, agricultura, químicos, produtos de construção, produtos de consumo, computação em nuvem e um portfólio ativo de investimentos minoritários. A Koch reinveste 90% dos lucros no negócio — uma escolha estrutural que a separa das empresas públicas que otimizam para resultados trimestrais. Charles sinaliza o que a conversa realmente vai abordar: não marcos de receita, mas os princípios e os fracassos que tornaram o crescimento composto sustentado possível. > "Um modelo operacional muito único, incluindo princípios de inovação disruptiva, reinvestimento de 90% dos lucros em novos negócios e crescimento, valores meritocráticos." > — David Friedberg ## [02:21] Construindo o Negócio: Os Primeiros Dias e Charles Koch Entra (1961) Charles Koch entrou no negócio familiar em 1961 com 25 anos, recém-saído do MIT e de uma passagem pela consultoria de gestão Arthur D. Little. O ultimato do pai Fred foi direto: "Ou você volta para tocar a empresa ou vou ter que vendê-la — minha saúde está ruim, as empresas não estão indo bem e não tenho muito tempo de vida." A empresa tinha então cerca de 300 funcionários, dois negócios principais (bandejas de fracionamento e coleta de petróleo bruto no Oklahoma) e disfunção operacional significativa. As lições iniciais cristalizaram um princípio central da Koch: crescimento guiado por capacidades, não por setor. O negócio de bandejas de fracionamento fracassou em parte porque seu presidente era um controlador de cima para baixo que alienou engenheiros e clientes. Charles começou a perguntar não "em que setor estamos?" mas "o que podemos fazer melhor do que qualquer um, e onde na cadeia de valor isso cria mais valor?" Esse enquadramento, aplicado repetidamente ao longo de décadas, explica a sequência aparentemente aleatória de setores em que a Koch depois entrou. > "Filho, ou você volta pra tocar a empresa ou vou ter que vendê-la porque minha saúde está ruim e as empresas não estão indo bem e não tenho muito tempo de vida." > — Charles Koch, citando seu pai Fred Koch ## [11:31] Fracassos, Destruição Criativa e Aprender com os Erros Charles começa com uma provocação: "Se você não está falhando em tudo, não está fazendo nada novo." Ele conta os prejuízos iniciais, incluindo uma tentativa mal-sucedida de converter coque de petróleo em carvão ativado, e um padrão de entrar em negócios sem as capacidades subjacentes necessárias. O aprendizado real veio do diagnóstico de por que cada fracasso aconteceu — quase sempre uma violação de um dos princípios operacionais da Koch. Chase adiciona a perspectiva do portfólio de capacidades: a expansão da Koch da coleta de petróleo bruto para gás natural, químicos, fertilizantes e por fim produtos florestais não foi diversificação aleatória — foram as mesmas capacidades subjacentes redirecionadas para novas aplicações. Ele também descreve a Koch Disruptive Technologies (KDT), que fundou, como um experimento estrutural que se mostrou difícil de tornar consistentemente lucrativo — uma avaliação honesta de fracasso aplicada à sua própria criação. A decisão de encerrar ou pivotar, diz Charles, se resume a um teste: perdemos a capacidade de criar valor superior para os clientes de uma forma pela qual seremos recompensados? > "Quando perdemos dinheiro demais — é quando chega a hora de dizer basta. Quando decidimos que não temos a capacidade de criar valor superior para os nossos clientes." > — Charles Koch ## [19:22] Cultura e Gestão Baseada em Princípios Esse é o centro intelectual do episódio. Charles traça as origens do sistema PBM até os piores fracassos da Koch, todos com uma causa raiz em comum: promover pessoas com valores ruins para posições de liderança. Dois exemplos quase catastróficos se destacam: uma operação de trading imprudente que quase faliu a empresa durante a guerra do Oriente Médio em 1973, e um episódio posterior em que líderes "motivados destrutivamente" escondiam fracassos enquanto inventavam sucessos. O antídoto foi contratar valores primeiro e talento depois, e estruturar uma cultura onde a motivação por contribuição — querer ter sucesso ajudando os outros a ter sucesso — supera a busca por poder. Chase estende isso com um enquadramento que vai direto ao ponto: e se todos na empresa soubessem exatamente o que fazer sem precisar ser mandados? Esse é o estado-alvo que o PBM visa produzir. A estratégia de gestão de mudança evita mandatos de cima para baixo: encontre o subgrupo mais ansioso para experimentar os princípios, demonstre resultados e deixe a demanda puxar a transformação pelo restante da organização. O conhecimento coletivo substitui o julgamento de poucas pessoas inteligentes no topo. > "E se você pudesse ter um negócio e uma cultura — pequeno, médio ou grande — onde todos soubessem o que fazer sem precisar ser mandados?" > — Chase Koch ## [33:53] Aquisição da Georgia-Pacific e Transformação Cultural A aquisição da Georgia-Pacific em 2005 foi a maior aposta da Koch até então — "uma aposta enorme", diz Chase, quando a empresa era bem menor. Charles traça a lógica: a Koch viu as operações de celulose e papel commodity da Georgia-Pacific como uma extensão natural de suas capacidades de processos químicos, uma conexão que remontava até a tese de MIT de Fred Koch sobre produção de celulose no Maine. Inicialmente propuseram comprar apenas as divisões de commodity; quando esse acordo não fechou por causa de litígios pendentes, ofereceram comprar a empresa inteira. O que se seguiu foi uma transformação cultural de anos numa sede de 51 andares em Atlanta construída sobre burocracia de cima para baixo. A Koch substituiu a liderança, recompensou trabalhadores que identificaram e corrigiram ineficiências, e compartilhou economias de custo com membros do sindicato que as encontraram. Chase descreve seus próprios anos nas operações de linha de frente da Koch — morando numa casa móvel num confinamento de gado, trabalhando numa usina de gás liquefeito — como fundamentais para uma liderança crível posteriormente. A mudança cultural leva muito mais tempo do que qualquer adquirente espera, e quase sempre requer substituir o grupo de liderança que mantém o velho paradigma. > "Demora muito mais do que você pensa para mudar a cultura — e em quase todos os casos requer mudar a liderança que tem o paradigma do empoderamento de baixo para cima." > — Chase Koch ## [56:17] Reforma Educacional e Mudança Social O Stand Together — a rede sem fins lucrativos que Charles vem construindo há 60 anos sob vários nomes — é hoje uma das maiores organizações filantrópicas dos Estados Unidos. Chase lidera a origination e as parcerias, e reencadra sua missão: não advocacia política, mas aplicar os mesmos princípios da Koch a desafios sociais, começando pela educação. A COVID-19 mudou drasticamente a opinião pública: antes de 2020, cerca de 20% das famílias estavam abertas a alternativas ao ensino tradicional; após ver seus filhos aprendendo mais no YouTube do que nas aulas virtuais, esse número disparou. O Stand Together desde então ajudou a criar mais de 5.000 microescolas. Programas parceiros como o Alpha School de Joe Limont usam gamificação e aprendizado baseado em projetos para levar alunos que estavam fracassando ao topo da turma em três meses. Chase também aplica o princípio da vantagem comparativa a si mesmo — ele se demitiu da presidência da Koch Fertilizer quando reconheceu que outra pessoa tinha essa vantagem comparativa — e usa esse mesmo prisma para remodelar funções em toda a força de trabalho de 130.000 pessoas da Koch. > "Antes do COVID, cerca de 20% das famílias estavam abertas a um novo modelo de educação. Todo mundo viu durante o COVID como o sistema estava uma bagunça — seus filhos tinham aprendido mais no YouTube do que na sala de aula." > — Chase Koch ## [72:37] IA, Desafios Econômicos e o Futuro do Capitalismo Friedberg pressiona Charles a dar conta da narrativa política Koch — as décadas de envolvimento no Partido Libertário e a eventual virada para a coalizão mais ampla do Stand Together. Charles é candido: passou anos trabalhando apenas com pessoas que concordavam com ele em cada princípio, limitando seu alcance. A percepção de Viktor Frankl — "cada vez mais pessoas têm os meios para viver e nenhum sentido para viver" — reorientou seu pensamento para as raízes motivacionais da desestruturação social, em vez de remédios puramente políticos. A lição: as estratégias da liberdade não podem tomar emprestado do totalitarismo; testar a pureza de uma coalizão a destrói. Sobre IA, a posição de Chase é clara: inovação sem permissão, sistemas abertos, empoderar as pessoas com ferramentas de IA em vez de proibi-las. A Koch está rodando o PBM como um framework nativo de IA, e Chase criou um companion de IA para o novo livro para que os leitores possam interagir com os princípios diretamente — indo muito além do que Charles esperava quando convidou Chase para coescrever. O episódio termina com o objetivo de legado declarado de Charles: que os Estados Unidos vivam mais plenamente a promessa da Declaração de Independência. > "O problema hoje é que cada vez mais pessoas têm os meios para viver e nenhum sentido para viver." > — Charles Koch, citando Viktor Frankl ## Personagens - **David Friedberg** — Apresentador; cofundador de The Production Board; parceiro de negócios de Chase Koch desde 2013 pela indústria de agricultura - **Charles Koch** — Presidente do Conselho e CEO da Koch Inc. desde 1967; engenheiro formado pelo MIT; coautor do livro Gestão Baseada em Princípios; liderou o crescimento de 9.000x da Koch - **Chase Koch** — Presidente da Koch Inc.; fundador da Koch Disruptive Technologies; coautor do livro PBM com Charles; lidera origination e parcerias no Stand Together - **Koch Inc.** — Conglomerado familiar privado com sede em Wichita, KS; fundado em 1940 por Fred Koch; mais de 130.000 funcionários nas áreas de energia, químicos, produtos florestais, bens de consumo, software e capital de risco - **Gestão Baseada em Princípios (PBM)** — Framework operacional de 41 princípios da Koch; enfatiza motivação por contribuição, contratação com valores em primeiro lugar, empoderamento de baixo para cima e tratar cada unidade de negócio como laboratório - **Georgia-Pacific** — Empresa de produtos florestais e consumo adquirida pela Koch em 2005; maior aquisição da Koch; principal estudo de caso em transformação cultural sob o PBM - **Koch Disruptive Technologies (KDT)** — Braço de venture capital fundado por Chase Koch; investimentos minoritários em empresas de tecnologia disruptiva; descrito como estruturalmente difícil de tornar consistentemente lucrativo - **Stand Together** — Rede filantrópica de Charles Koch ativa desde 2003; foca em reforma educacional, redução da pobreza e mudança social bipartidária; criou mais de 5.000 microescolas após a 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