팟캐스트Hear the voice. See the shape of the thought.

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 Benioff가 Jason Calacanis, David Friedberg, Chamath Palihapitiya(David Sacks 불참)와 함께 폭넓은 대화를 나눈다. 이번 에피소드는 두 개의 실시간 이슈를 중심으로 전개된다. 2017년 이후 처음 열리는 트럼프-시 정상회담, 그리고 AI가 기업 소프트웨어 밸류에이션을 흔드는 현실이다. 사우디 국빈 만찬, 윈저 성, 이번 정상회담 대표단에 모두 참석한 Benioff는 미중 민간 외교의 최전선을 직접 전하고, Salesforce가 AI 격변의 수혜자로 자리할 수 있는 이유를 설명한다. 후반부에서는 OpenAI와 애플의 충돌, Thinking Machines의 실시간 멀티모달 데모, Friedberg의 충격적인 엘니뇨 데이터, Anthropic의 SPV 다층 구조 단속을 다룬다. ## [00:00] Salesforce CEO Marc Benioff, 쇼에 합류하다! 이번 주 Sacks는 자리를 비웠고, Benioff가 그 자리를 채웠다. Jason은 곧바로 Benioff의 정치적 입장을 묻는다. 과거 민주당 후원자였던 그가 사우디 국빈 만찬에 참석하고 현 행정부와도 마찰 없이 교류한다는 점을 짚었다. Benioff는 당파적 시각을 단호히 거부한다. > *"나는 민주당원도 공화당원도 아닙니다. 나는 미국인입니다."* Chamath는 Benioff가 윈저 성, 찰스 왕세자의 미국 방문, 사우디 국빈 만찬 초청을 연달아 받았다고 짚었다. 정권이 바뀌어도 마찰 없이 움직이는 드문 테크 CEO라는 것이다. 이 장면은 정상회담 현장을 실시간으로 지켜본 Benioff가 얼마나 독보적인 증언자인지를 보여준다. ## [01:14] 트럼프-시 정상회담, 미국 기업의 중국 비즈니스, 미국인과 중간선거에 미칠 영향 이란 전쟁으로 두 달 늦춰진 트럼프-시의 일곱 번째 대면 회담이 베이징에서 열렸다. 시진핑은 대만 문제를 잘못 다루면 양국 관계가 "극히 위험한 상황"에 처할 수 있다고 경고했다. Polymarket에서는 2026년 침공 확률이 2,300만 달러 거래량 기준 6%로 집계됐다. 무역 측면에서 시진핑은 대두, 미국 LNG, 보잉 제트기 200대 구매를 약속하며 "더 넓은 무역의 문"을 열겠다고 했다. 미국 대표단은 마치 기업 이사회 같다. Jensen Huang은 반도체를, Kelly Ortberg는 항공기를, Cargill의 Brian Sykes는 대두를 팔고, Visa와 Mastercard는 결제 시장 개방을 요구했다. Friedberg는 투키디데스 함정의 틀로 정상회담을 해석했다. 부상하는 강국과 쇠퇴하는 강국이 마주치면 역사적으로 충돌이 일어나지만, AI와 바이오테크가 만드는 자원 팽창의 순간이 그 패턴에서 벗어날 드문 탈출구가 될 수 있다고 봤다. > *"AI, 자동화, 바이오테크 같은 기술 전환이 눈앞에서 펼쳐지고 풍요의 시대가 열릴 수 있는 이 순간, '어쩌면 세계가 더 다극적으로 갈 수 있다'고 말할 완벽한 타이밍인 것 같습니다."* Benioff는 Salesforce가 중국 본토에 사무실이나 직원이 전혀 없다고 밝혔다. 데이터 현지화 규정을 충족하기 위해 모든 중국 매출은 알리바바와의 독점 파트너십을 통해 흘러간다. 그는 이번 정상회담이 대표단 전반에 걸쳐 실질적인 수주로 이어질 것이라고 내다봤다. Chamath는 중국의 하향식 유교적 위계 구조 때문에 CEO급 직접 외교가 관료적 채널보다 훨씬 효과적이며, 인플레이션으로 생활이 빠듯해진 미국인들에게도 이 합의가 반드시 작동해야 한다고 강조했다. ## [18:46] 대만, 반도체, AI 모델, 그리고 무역을 통한 평화 Benioff는 대만이 시진핑의 핵심 우선 과제라는 전제에 반박했다. 영토 야욕보다 경제 번영과 중산층 성장이 시진핑에게 더 중요하다는 것이다. "미국이 대만을 봉쇄에서 지켜야 하는가"라는 직접적인 질문에는 이분법을 거부했다. "중국과 대만은 화해할 것"이라고 잘라 말했다. Chamath는 구조적 관점을 제시했다. 미국이 국내 반도체 공정 수준에서 1~2 나노미터 격차만 남겨두고 있으며, 그 격차가 좁혀지면 대만의 전략적 가치는 실존적 문제가 아니라 경제적 문제로 바뀐다고 봤다. > *"우리는 대만이 전략적으로 해줘야 하는 것을 우리 스스로 할 수 있는 지점에서 1~2 나노미터 정도 떨어져 있습니다. 지금은 그게 경제적인 문제이고, 그것이 협상 테이블에서 사라지면 대만을 보는 시각도 크게 달라질 것입니다."* Chamath의 처방: 어차피 반도체를 팔아라. 화웨이가 반도체 경쟁에서 이기도록 두는 것이 KYC 조건 아래 Nvidia가 중국에 파는 것보다 더 나쁘다. Benioff도 동의했다. 반도체 규제에도 불구하고 중국 AI 모델이 미국 모델과 대등한 수준에 이르렀다는 점은 수출 금지 논거를 약화시킨다. Friedberg는 중국이 자국 팹과 장비를 구축할수록 정치적 결과와 무관하게 대만의 대체 불가능성이 자연스럽게 줄어들 것이라고 덧붙였다. ## [31:41] AI가 소프트웨어에 미치는 영향: 어떤 SaaS가 살아남고 어떤 SaaS가 죽는가? Jason은 재평가 현실을 거침없이 짚었다. Salesforce 37%, ServiceNow 42%, Workday 45% 하락—AI가 매니지드 SaaS를 쓸모없게 만들 것이라는 가정 하에 합산 시가총액 약 1,800억 달러가 증발했다. Benioff는 정면돌파했다. > *"솔직히 이게 내가 처음 겪는 SaaS 묵시록은 아니지만, 지금의 SaaS 묵시록인 건 맞죠."* 그의 논리: 시장은 잘못된 전제 위에서 재평가를 단행했다. Salesforce의 베팅은 Agentforce다. 환각 가능성이 있는 범용 모델이 아니라 실제 기업 데이터에 기반한 AI 에이전트다. 80억~90억 달러 규모의 Informatica 인수는 에이전트를 신뢰할 수 있게 해주는 데이터 조화 계층을 제공한다. "AI는 매우 확률적이어서 진실에, 하나의 단일 진실 소스에 고정되지 않으면 제대로 작동하지 못합니다." Benioff는 Salesforce가 내부 코딩 에이전트용으로만 올해 Anthropic에 약 3억 달러를 지출해 구현 사이클을 대폭 줄이고 있다고 덧붙였다. Chamath는 시장을 둘로 나눴다. 저가 시장은 끝났다. 깊은 고객 관계 없이 단일 기능만 제공하는 솔루션은 사라진다. 반면 Salesforce가 속한 고가 시장은 공개 시장이 AI에 대한 "황홀경"에서 깨어나 3조 달러의 자본 지출이 무엇을 낳았는지 묻기 시작할 때 오히려 수혜를 입을 위치다. 살아남는 기업은 C레벨 관계망, 마이너스 이탈률, AI 역량을 측정 가능한 성과로 패키징하는 능력을 갖춘 곳이다. ## [47:26] OpenAI, ChatGPT 연동 실패로 애플 소송 검토 중 Bloomberg 보도에 따르면 OpenAI가 계약 위반을 이유로 애플 소송을 검토 중이다. 2024년 ChatGPT-Siri 계약은 실제로는 작동하지 않았다. 애플이 사용자가 명시적으로 "ChatGPT"라고 말할 때만 연결하고 연동을 홍보하지 않았으며, OpenAI는 기대했던 구독 매출을 끝내 보지 못했다. 애플의 반론은 OpenAI의 데이터 처리 관행에 대한 개인정보 우려다. Benioff는 이 사안을 AI 랩들의 전략 분기 이야기로 재해석했다. Grok은 컴패니언과 "섹스봇"을 만들었고, OpenAI는 Sora와 광고 네트워크를 밀었고, Gemini는 Nano를 출시했다. Anthropic은 그 모든 것을 무시하고 코딩 에이전트에만 집중했는데—Anthropic이 옳았다. 그는 Slack 네이티브 코딩 기능도 미공개 상태로 언급했다. > *"Anthropic은 '우리는 그런 섹스봇도, Nano 바나나도 모르겠고, 코딩 에이전트를 만들겠다'고 했습니다. 그리고 Anthropic이 옳았죠. 로켓이 날아오른 겁니다."* Chamath는 더 근본적인 질문을 던졌다. AI 인터랙션 계층이 기기 밖으로 완전히 이동하면 애플에게 무슨 일이 생길까? 그는 예상치 못한 하드웨어 플레이어로부터 "아이폰 모먼트"가 올 것이라고 예측했다. 항상 켜져 있는 얇은 앰비언트 기기가 AI 추론에서 MacBook Pro를 무의미하게 만드는 시나리오다. Friedberg는 애플의 현재 전략이 선도적 비전보다는 빈틈 메우기에 가깝다고 짚으면서, G Suite가 기업 생산성 시장에서 애플 스택을 조용히 잠식하고 있다고 덧붙였다. ## [56:54] Thinking Machines, 실시간 모델 공개…소비자 AI의 미래와 다중감각 모델 Mira Murati의 Thinking Machines가 실시간 멀티모달 모델을 공개했다. 200ms 간격으로 두 개의 병렬 파이프라인—하나는 심층 회고적 추론, 하나는 실시간 응답—을 통해 데스크톱 화면, 주변 오디오, 웹캠 입력을 동시에 처리한다. 애플은 AirPods 내부 카메라 관련 특허를 동시에 출원했다. > *"다중감각 모델은 AI의 다음 큰 물결입니다. 그 단계에 도달해도 우리는 아직 AGI에는 이르지 못한 상태입니다."* Benioff는 언어 데이터로만 학습된 LLM의 근본적 한계를 지적했다. 인간의 인지는 눈, 귀, 고유감각을 생물학적 하드웨어 위에서 동시에 처리한다. 다중감각 기반이 바로 그 빠진 고리다. 토큰 경제학도 극적이다. 사용자당 하루 8시간 실시간 앰비언트 모니터링은 현재 기업 소비량의 1,000배에 달한다. Benioff는 "더 큰 모델 = 더 좋은 결과"라는 군비 경쟁에 반기를 들었다. 앱과 기기에 내재된 분산 지능이 단순 모델 규모보다 더 중요해질 것이며, 앰비언트 감지와 기업 맥락을 통합할 "주목받을 신생 기업"의 공간이 열릴 것이라고 봤다. ## [62:24] 사이언스 코너: 2026년 역대급 엘니뇨의 충격 Friedberg는 해수면 온도 이상 데이터를 제시했다. 1877년 이후 최대 편차를 향해 달리는 해수 온도—기준치보다 약 4°C 높다. 저장된 열에너지는 1,100만 테라와트시로, 인류의 연간 에너지 소비량 25,000 테라와트시와 비교된다. > *"저 바다에는 인류 500년치 에너지가 담겨 있습니다. 그리고 앞으로 몇 달에 걸쳐 그 에너지가 대기로 방출될 것입니다. 99% 확신을 갖고 말씀드리는데, 올해는 역대 가장 더운 해가 될 것이며 그 격차도 압도적일 것입니다."* 연쇄 효과: 변화한 무역풍이 대기하천을 캘리포니아와 걸프 연안으로 몰아넣고, 열돔이 피닉스와 캐나다 내륙 위로 확장되며, 인도 몬순이 높은 확률로 실패해 1억 5천만 명의 농민과 15억 명의 식량 의존 인구를 위협한다. 브라질의 인도네시아·필리핀行 농산물 수출이 무너지고 밀 가격이 세계적으로 급등한다. 5월에 피닉스는 이미 106°F를 기록했다. 상품 시장은 이미 엘니뇨 익스포저를 활발히 거래 중이다. Friedberg가 제시하는 부분적 희망: 작물 유전학이 가뭄 내성을 높였고 시베리아 농지가 확장 중이다—그러나 그 이득이 2026년 수확 시즌을 구하지는 못한다. ## [71:40] Anthropic, "다크 SPV"를 정조준하다 Anthropic은 소매 투자자에게 다층 SPV를 판매하는 플랫폼—"치과 의사에게 10% 수수료를 물리는" 구조—을 공식적으로 문제 삼고, 무허가 구조를 통해 팔린 주식을 무효화하겠다고 밝혔다. Chamath는 전폭적인 지지를 표명했다. IPO 전 모든 기업이 이 선례를 따르고 공개 시장으로 나아가 이런 구조를 사라지게 해야 한다는 것이다. > *"SpaceX가, Anthropic이, OpenAI가 상장하고 나면 SPV 판매자들과의 소송이 줄줄이 터질 것입니다. 이 구조는 허용되어서는 안 됩니다."* Chamath는 주요 AI 기업들이 상장하고 소매 SPV 투자자들이 수익 계산이 맞지 않는다는 걸 깨닫는 순간, 대규모 법적 후폭풍이 밀려올 것이라고 예측했다. 마지막에는 Benioff가 Salesforce의 1-1-1 박애주의 모델을 소개했다. 창업 당시 지분 1%, 이익 1%, 직원 시간 1%를 기부하는 이 모델은 지금 5만 개의 비영리 단체에 플랫폼을 무료로 제공하고 있다. 그리고 Susan Wojcicki에 대한 감동적인 추모로 챕터를 마무리했다. ## 등장인물 - **Marc Benioff** (인물): Salesforce 회장 겸 CEO; 이번 에피소드 게스트; 1-1-1 박애 모델과 Agentforce AI 에이전트 플랫폼의 설계자 - **David Friedberg** (인물): 진행자; The Production Board CEO; 엘니뇨 사이언스 코너 발표 - **Chamath Palihapitiya** (인물): 진행자; Social Capital CEO; Salesforce 고가 SaaS 생존론과 Nvidia 반도체 확산론 주장 - **Salesforce / Agentforce** (소프트웨어): 기업용 CRM 및 에이전트 플랫폼; 데이터 기반 AI 에이전트가 SaaS 사망 선고의 반대 증거라는 Benioff의 베팅 - **Anthropic** (조직): AI 안전 기업; Benioff가 선호하는 코딩 에이전트 공급사(Salesforce의 연간 계획 지출 약 3억 달러); 무허가 SPV 구조 단속 주도 - **OpenAI** (조직): ChatGPT-Siri 연동 실패로 애플 소송 검토 중; Anthropic의 성공을 따라 코딩 에이전트로 피벗 - **Thinking Machines / Mira Murati** (조직): 200ms 간격으로 데스크톱·오디오·웹캠을 동시 처리하는 실시간 앰비언트 멀티모달 모델 공개 - **투키디데스 함정** (개념): 부상하는 강국과 쇠퇴하는 강국의 충돌 주기를 설명하는 정치학 프레임; Friedberg가 미중 정상회담의 협력적 풍요 기회를 조명하는 데 인용 - **다크 SPV** (개념): AI 비상장 기업의 주식을 소매 투자자에게 판매하는 다층 특수목적법인; 높은 수수료와 법적 불확실성 문제로 논란

Charles Koch와 그의 아들 Chase가 David Friedberg와 함께, Koch Inc.가 어떻게 9,000배 성장했는지를 이야기합니다. 1961년 오클라호마의 직원 300명짜리 석유 회사에서 시작해 에너지, 화학, 산림 제품, 소비재, 벤처 캐피털에 걸친 13만 명 규모의 비상장 기업으로, 단 한 번도 상장하지 않고 이뤄낸 성장입니다. 대화의 중심은 원칙 기반 경영(PBM)입니다. Koch의 모든 채용 결정, 인수, 문화 변화를 이끄는 41개 원칙 체계예요. Charles와 Chase는 'Koch'라는 이름에 붙은 좁은 정치적 이미지도 직접 다루며, 당파적 자유주의에서 교육 개혁과 인간 번영에 집중하는 Stand Together 연합으로의 전환을 설명합니다. 에피소드는 AI와 자본주의로 마무리됩니다. 두 사람 모두 허가 없는 혁신과 상향식 권한 부여만이 앞에 놓인 경제적 압박을 헤쳐나갈 유일한 신뢰할 수 있는 길이라고 봅니다. ## [00:00] David Friedberg, Charles & Chase Koch 환영 인사 David Friedberg는 Forbes 행사에서 대화를 시작하며, Chase Koch와는 2013년 농업 분야에서 인연이 닿아 이후 사업 파트너가 됐다고 소개합니다. Koch Inc.를 "숨겨진 이야기"로 표현합니다. 세계에서 가장 수익성 높은 가족 소유 비상장 기업일 가능성이 높지만, 상장사 대비 거의 알려지지 않은 회사라고 하죠. 또한 All-In 청중에게 기대감을 심어줍니다. Koch Inc. 회장과 차세대 사장이 함께하는 생방송 인터뷰는 매우 드문 기회라고요. > "저는 항상 Koch Industries가 숨겨진 이야기라고 느껴왔습니다. 아마 세계에서 가장 수익성 높은 가족 소유 비상장 기업일 겁니다." > — David Friedberg ## [01:04] Koch Inc. 개요: 규모, 사업 부문 및 역사 Friedberg가 기본 통계를 제시합니다. Koch가 상장사였다면 매출 기준 Fortune 500 상위 25위에 들었을 겁니다. 1940년 Fred Koch가 위치타, 캔자스에 창업한 이 회사는 지금 60개국에서 12만 명 이상의 직원과 함께 에너지, 농업, 화학, 건축 자재, 소비재, 클라우드 컴퓨팅, 그리고 활발한 소수 지분 투자 포트폴리오를 운영합니다. Koch는 이익의 90%를 사업에 재투자합니다. 분기 실적에 최적화된 상장사와 구별되는 구조적 선택이죠. Charles는 이 대화의 진정한 주제를 신호합니다. 매출 이정표가 아니라, 지속적인 성장 복리를 가능하게 한 원칙들, 그리고 실패들이라고요. > "파괴적 혁신 원칙, 이익의 90%를 신규 사업과 성장에 재투자하는 방식, 능력주의적 가치관을 포함한 매우 독특한 운영 모델이 있습니다." > — David Friedberg ## [02:21] 사업 구축: 초창기와 Charles Koch의 합류(1961) Charles Koch는 1961년 25살에 MIT와 Arthur D. Little 경영 컨설팅을 거쳐 가업에 합류했습니다. 아버지 Fred의 최후통첩은 직접적이었습니다. "돌아와서 회사를 운영하지 않으면 팔아야 겠다. 몸이 좋지 않고 회사 상황도 나쁘고 오래 살 것 같지 않다"고요. 당시 회사는 직원 약 300명에 두 개의 핵심 사업(분리 트레이 제조와 오클라호마 원유 수송)을 운영하고 있었는데, 운영상 많은 문제가 있었습니다. 초기의 교훈이 핵심 Koch 원칙을 결정했습니다. 산업 중심이 아닌 역량 중심의 성장이에요. 분리 트레이 사업이 실패한 이유 중 하나는 하향식으로 엔지니어와 고객 모두를 소외시킨 사장 때문이었습니다. Charles는 "우리가 어떤 산업에 있나?"가 아니라 "우리가 남보다 더 잘할 수 있는 것이 무엇이고, 가치 사슬의 어디에서 가장 큰 가치를 창출하나?"를 묻기 시작했습니다. 이 관점의 전환이 수십 년에 걸쳐 반복적으로 적용되면서 Koch가 진출한 얼핏 무관해 보이는 산업들의 연속을 설명해줍니다. > "아들아, 회사를 운영하러 돌아오지 않으면 팔아야 겠다. 몸이 좋지 않고 회사 상황도 나쁘고 오래 살 것 같지 않구나." > — Charles Koch, 아버지 Fred Koch의 말을 인용하며 ## [11:31] 실패, 창의적 파괴, 그리고 실수에서 배우기 Charles는 도발적인 말로 시작합니다. "모든 것에서 실패하지 않는다면, 새로운 것을 하고 있지 않은 거예요." 석유 코크스를 활성탄으로 전환하려다 실패한 시도 등 초기 손실들을 이야기하고, 필요한 역량 없이 사업에 진입한 패턴을 설명합니다. 진정한 배움은 각 실패가 왜 일어났는지를 진단하는 데서 왔는데, 거의 항상 Koch의 운영 원칙 중 하나를 위반한 것이었죠. Chase는 역량 포트폴리오 관점을 추가합니다. Koch의 원유 수송에서 천연가스, 화학, 비료, 그리고 산림 제품으로의 확장은 무작위 다각화가 아니라 같은 핵심 역량을 새로운 적용 분야로 방향 전환한 것이라고요. 또한 자신이 설립한 Koch Disruptive Technologies(KDT)가 구조적으로 안정적인 수익성을 확보하기 어려웠다고 솔직하게 평가합니다. 사업 종료 또는 방향 전환 결정은 결국 하나의 테스트로 귀결된다고 Charles는 말합니다. "고객을 위해 탁월한 가치를 창출하고 보상받을 역량을 잃었는가?" > "충분히 크게 잃었을 때, 그게 충분히 잃은 거예요. 우리가 고객에게 탁월한 가치를 창출하고 보상받을 역량이 없다고 판단할 때죠." > — Charles Koch ## [19:22] 문화와 원칙 기반 경영 이 부분이 에피소드의 지적 중심입니다. Charles는 PBM 시스템의 기원을 Koch의 최악의 실패들에서 추적합니다. 모두 공통된 근본 원인을 가지고 있었어요. 나쁜 가치관을 가진 사람을 리더 자리에 앉힌 것이죠. 두 가지 거의 재앙 수준의 사례가 두드러집니다. 1973년 중동 전쟁 당시 회사를 파산 위기로 몰아간 무모한 트레이딩 운영, 그리고 "파괴적 동기"를 가진 리더들이 실패를 숨기면서 성공을 꾸며낸 에피소드입니다. 해결책은 가치관을 먼저, 재능을 두 번째로 채용하고, 기여 동기, 즉 남을 도우면서 성공하고 싶다는 마음이 권력 추구를 압도하는 문화를 구조화하는 것이었습니다. Chase는 핵심을 꿰뚫는 틀을 제시합니다. 회사의 모든 사람이 지시 없이도 무엇을 해야 할지 안다면 어떨까요? 그것이 PBM이 만들어내려는 목표 상태입니다. 변화 관리 전략은 하향식 명령을 피합니다. 원칙을 가장 열성적으로 시도하려는 소집단을 찾아 결과를 보여주고, 수요가 그 변화를 조직 전체로 끌어당기게 합니다. 집단 지식이 상층부 몇몇 영리한 사람의 판단을 대체하는 거죠. > "크든 작든 어떤 규모의 기업이나 문화에서도 모든 사람이 지시 없이도 무엇을 해야 할지 안다면 어떨까요?" > — Chase Koch ## [33:53] Georgia-Pacific 인수와 문화 전환 2005년 Georgia-Pacific 인수는 당시 Koch의 가장 큰 베팅이었습니다. Chase는 "엄청난 베팅"이라고 표현했는데, 그때 회사가 훨씬 작았기 때문이죠. Charles는 그 논리를 설명합니다. Koch는 Georgia-Pacific의 원자재 펄프 및 제지 사업을 자사의 화학 공정 역량의 자연스러운 연장으로 봤고, 그 연결은 Fred Koch의 MIT 메인 펄프 관련 논문까지 거슬러 올라갔습니다. 처음에는 원자재 부문만 사겠다고 제안했는데, 계류 중인 소송 때문에 그 거래가 성사되지 않자 회사 전체를 사겠다고 제안했죠. 그다음에는 수년에 걸친 문화 전환이 이어졌습니다. 하향식 관료주의로 돌아가던 51층짜리 애틀랜타 본사를 바꾸는 작업이었어요. Koch는 리더십을 교체하고, 비효율을 발견하고 고친 직원들에게 보상을 주고, 비용 절감을 찾아낸 노조원들과 그 절감액을 나눴습니다. Chase는 Koch의 일선 업무에서 보낸 자신의 몇 년, 즉 가축 야적장의 단칸 트레일러에서 생활하고 가스 액화 공장에서 일한 경험이 나중의 신뢰할 수 있는 리더십의 토대가 됐다고 설명합니다. 문화 변화는 어떤 인수자도 예상하는 것보다 훨씬 오래 걸리고, 거의 항상 기존 패러다임을 고수하는 리더십 집단을 교체해야 합니다. > "문화를 바꾸는 데는 생각보다 훨씬 오래 걸려요. 그리고 거의 모든 경우에 상향식 권한 부여 패러다임을 갖고 원칙을 배우고 적용하는 리더십을 교체해야 해요." > — Chase Koch ## [56:17] 교육 개혁과 사회 변화 Stand Together, Charles가 다양한 이름으로 60년간 구축해온 비영리 네트워크는 이제 미국 최대 자선 단체 중 하나입니다. Chase는 origination과 파트너십을 담당하며, 그 사명을 재정의합니다. 정치적 옹호가 아니라 같은 Koch 원칙을 교육에서 시작해 사회적 도전에 적용하는 것이라고요. COVID-19가 여론을 크게 바꿨습니다. 2020년 이전에는 약 20%의 가족만이 전통적 학교 교육의 대안에 열려 있었는데, 아이들이 Zoom 강의보다 YouTube에서 더 많이 배우는 걸 목격하면서 그 수치가 급증했습니다. Stand Together는 이후 5,000개 이상의 마이크로스쿨 설립을 지원했습니다. Joe Limont의 Alpha School 같은 파트너 프로그램은 게임화와 프로젝트 기반 학습을 활용해 실패하는 학생들을 3개월 만에 최우수권으로 끌어올립니다. Chase는 비교 우위 원칙을 자신에게도 적용합니다. 더 나은 역량을 가진 사람이 있다고 인식하고 Koch Fertilizer 사장직에서 스스로 물러났고, 같은 관점으로 Koch 13만 명 직원 전체의 역할을 재편합니다. > "COVID 이전에는 약 20%의 가족만이 새로운 교육 모델에 열려 있었어요. 모두 COVID 때 시스템이 얼마나 엉망인지를 봤고, 아이들이 교실보다 YouTube에서 훨씬 많이 배웠다는 걸 알게 됐죠." > — Chase Koch ## [72:37] AI, 경제적 도전, 그리고 자본주의의 미래 Friedberg가 Charles에게 Koch 정치적 서사, 즉 수십 년간의 자유당 참여와 결국 Stand Together의 광범위한 연합으로의 전환에 대해 묻습니다. Charles는 솔직합니다. 모든 원칙에서 자신과 동의하는 사람들하고만 일하는 데 너무 많은 세월을 보내 그 범위가 좁아졌다고요. Viktor Frankl의 통찰, "점점 더 많은 사람들이 삶의 수단은 있지만 살아갈 의미가 없다"가 그의 생각을 정치적 처방보다 사회적 붕괴의 동기적 뿌리로 재정향시켰습니다. 교훈: 자유의 전략은 전체주의에서 빌릴 수 없다는 것. 연합의 순수성 검증은 그것을 파괴합니다. AI에 대해 Chase의 입장은 분명합니다. 허가 없는 혁신, 개방형 시스템, AI 도구로 사람들에게 권한 부여, 금지가 아니라요. Koch는 PBM을 AI 네이티브 프레임워크로 운영하고 있으며, Chase는 독자들이 원칙과 직접 상호작용할 수 있는 AI 동반자를 만들었는데, 이는 Chase를 공동 저자로 초대했을 때 Charles가 예상한 것을 훨씬 뛰어넘는 것이었습니다. 에피소드는 Charles의 유산 목표로 끝납니다. 미국이 독립선언서의 약속을 더 온전히 실현하는 것이라고요. > "오늘날의 문제는 점점 더 많은 사람들이 삶의 수단은 있지만 살아갈 의미가 없다는 것입니다." > — Charles Koch, Viktor Frankl의 말을 인용하며 ## 등장인물 - **David Friedberg** — 진행자; The Production Board 공동 창업자; 2013년 농업 분야에서 인연이 닿아 Chase Koch의 사업 파트너가 됨 - **Charles Koch** — 1967년부터 Koch Inc. 회장 겸 CEO; MIT 출신 엔지니어; 원칙 기반 경영 책 공동 저자; Koch의 9,000배 가치 성장을 이끌어 옴 - **Chase Koch** — Koch Inc. 사장; Koch Disruptive Technologies 설립자; Charles와 PBM 책 공동 저자; Stand Together origination 및 파트너십 담당 - **Koch Inc.** — 위치타, KS 본사 비상장 가족 기업; 1940년 Fred Koch 창업; 에너지, 화학, 산림 제품, 소비재, 소프트웨어, 벤처 캐피털에 걸쳐 13만 명 이상 직원 - **Principle-Based Management (PBM)** — Koch의 41개 원칙 운영 프레임워크; 기여 동기, 가치관 우선 채용, 상향식 권한 부여, 각 사업 단위를 실험실로 대우하는 것을 강조 - **Georgia-Pacific** — Koch가 2005년 인수한 산림 및 소비재 제품 회사; Koch 최대 인수; PBM 하에서의 문화 전환 주요 사례 연구 - **Koch Disruptive Technologies (KDT)** — Chase Koch가 설립한 벤처 부문; 파괴적 기술 회사에 대한 소수 지분 투자; 구조적으로 안정적인 수익성 확보가 어렵다고 설명됨 - **Stand Together** — 2003년부터 활동 중인 Charles Koch의 자선 네트워크; 교육 개혁, 빈곤 감소, 당파를 초월한 사회 변화에 집중; COVID 이후 5,000개 이상 마이크로스쿨 설립 지원

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