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  • Gavin Baker on Orbital Compute, TSMC, Frontier AI Models, Anthropic’s Vertical Take Off, and the Coming Wafer Shortage

    Gavin Baker, founder and CIO of Atreides Management, returns to Patrick O’Shaughnessy’s Invest Like the Best for his sixth appearance. He calls the current AI moment the most extraordinary moment in the history of capitalism, walks through what Anthropic’s vertical takeoff in revenue actually means, lays out why orbital compute is closer than skeptics believe, dissects the TSMC bottleneck that may be the only thing standing between today’s market and a full-on AI bubble, and rates every hyperscaler on how they have positioned for a world where frontier model providers may stop selling API access altogether.

    TLDW

    Anthropic added eleven billion dollars of ARR in a single month, which is roughly the combined business of Palantir, Snowflake, and Databricks built over a decade. That is the setup. From there Gavin Baker covers the March and April selloff, the contrarian read that a closed Strait of Hormuz was actually bullish for American manufacturing competitiveness, why Anthropic and OpenAI multiples may be misleadingly cheap on an unconstrained run rate basis, why Elon Musk’s discipline on SpaceX valuation created a superpower of permanent access to capital, the practical engineering case for orbital compute as racks in space rather than Pentagon sized space stations, why TSMC’s capacity discipline is the single most important variable in whether the AI cycle becomes a bubble, what Terafab in Texas changes, why the Pareto frontier of AI models has flipped from Google dominance to Anthropic and OpenAI dominance in nine months, the shift from all you can eat AI subscriptions to usage based pricing and what that means for revenue scaling, Richard Sutton’s bitter lesson as the largest risk to the AI trade, why frontier tokens still capture an overwhelming share of economic value, the role of continual learning as the third great open question, why most new chip startups should not try to build a better GPU, why Cerebras did something different and hard, why disaggregated inference may extend GPU useful lives to ten or fifteen years and rescue the private credit industry, why being in the token path is the new venture filter, the new prisoner’s dilemma around releasing frontier models via API, an honest rating of Google, Meta, Amazon, and Microsoft, why personal safety is becoming a real AI era risk, and why he remains an AI optimist maximalist who believes this could be the next Pax Americana.

    Key Takeaways

    • Anthropic added eleven billion dollars of ARR in one month, more than the combined businesses of Palantir, Snowflake, and Databricks built across a decade. There is no precedent for this in the history of capitalism.
    • The SaaS and cloud revolution created between five and ten trillion dollars of value over twenty years. AI is replaying that compression on a timeline measured in months.
    • The March selloff was a drawdown driven by disagreement with price action, not invalidated thesis. That is the kind of drawdown an investor can lean into.
    • Deep Seek Monday in January 2025 was a similar setup. By the day of the selloff, AWS Asia GPU prices had already doubled, GPU availability had fallen, and it was obvious reasoning models would be vastly more compute hungry at inference. The market priced the opposite.
    • The Strait of Hormuz closing was actually positive for America. US natural gas (the primary input into US electricity, which feeds AI) fell twenty percent on Bloomberg while Asian and European natural gas doubled or tripled. American manufacturing competitiveness improved overnight.
    • The US is now the world’s largest producer and exporter of oil and gas. The economy is dramatically less energy intensive than in the 1970s. The shortage trauma comparison does not hold.
    • Tech as a sector traded as cheaply versus the rest of the market in early April as at any point in the last ten years, into the single most bullish moment for AI fundamentals on record.
    • Anthropic is dramatically more capital efficient than OpenAI, having burned roughly eighty percent less to reach a similar revenue scale. They have very different structural returns on invested capital.
    • Anthropic at roughly nine hundred billion for fifty billion of ARR (growing a thousand percent) is striking. Adjusted for compute constraint, the unconstrained run rate could be one hundred fifty to two hundred billion, putting the implied multiple closer to five times.
    • Claude Opus generates roughly seventy percent fewer tokens for the same question than previously, with token quantity tied to answer quality. Subscribers on flat-fee plans are getting a lobotomized model.
    • Elon Musk’s superpower is twenty years of making investors money. He never pushes valuation. SpaceX compounded low thirty percent per year for a decade because Musk treats fair pricing as a sacred covenant.
    • Capitalism will solve the watts shortage. The current bottleneck has shifted from chips and energy to zoning and political approval. Many capex decisions are paused until after the US midterms.
    • The watts shortage probably begins to alleviate in 2027 and 2028. Orbital compute solves it longer term.
    • Orbital compute is not Pentagon sized data centers in space. It is racks in space. A Blackwell rack is three thousand pounds, eight feet tall, four feet deep, three feet wide. SpaceX has shown a satellite roughly that size.
    • The satellites operate in sun synchronous orbit so solar wings (around five hundred feet per side) always face the sun and the radiator on the dark side always points to deep space.
    • Starlink V3 satellites already run at around twenty kilowatts. A Blackwell rack runs at one hundred kilowatts. SpaceX engineers express genuine confidence they have already solved cooling and radiator design at these scales.
    • Racks in space are connected with lasers traveling through vacuum, the same lasers already on every Starlink. SpaceX operates the world’s largest satellite fleet and, via xAI Colossus, the world’s largest data center on Earth.
    • Inference will move to orbit. Training will stay on Earth for a long time. Terrestrial data centers remain valuable for the rest of an investor’s career.
    • The wafer bottleneck is structural and political. TSMC is essentially Taiwan’s GDP, water, and electricity. The leaders see themselves as inheritors of Morris Chang’s sacred legacy and they do not behave like a Western public company.
    • Jensen Huang has never had a contract with TSMC. The relationship is run on handshakes and the assumption that things will be fair over time.
    • If TSMC did everything Jensen wanted, Nvidia could be selling two to three trillion dollars of GPUs in 2026 and 2027. TSMC’s discipline is the single largest factor preventing a true AI bubble.
    • Historically, foundational technologies always get a bubble. Railroads, canals, the internet. The current AI buildout is overwhelmingly funded out of operating cash flow, GPUs are running at one hundred percent utilization, and that is fundamentally different from the year 2000 fiber overbuild.
    • If one of Intel or Samsung Foundry catches up at the leading node, the other will follow, and TSMC’s discipline collapses. Watch TSMC capacity decisions to predict a bubble.
    • Terafab, the SpaceX and Tesla joint venture to build the world’s largest fab in America, has a partnership with Intel that grants access to fifty years of institutional foundry knowledge. The A teams at ASML, KLA, Lam Research, and Applied Materials will follow Elon’s reputation in hardware engineering.
    • The hiring playbook for Terafab includes building Taiwan Town, Japan Town, and Korea Town next to the fab. Recruit the engineers and import their families, their restaurants, and their staff.
    • Frontier tokens still capture an overwhelming share of all economic value created at the model layer. This is surprising and is one of the three big open questions for AI investing.
    • The Pareto frontier of intelligence versus cost has flipped. Nine months ago Google’s TPU dominated every point on the frontier. Today Anthropic and OpenAI dominate, with Grok 4.3 on the frontier and Gemini 3.1 hanging on.
    • Google’s conservative TPU V8 design (partly an attempt to reduce dependence on Broadcom and Nvidia) is the leading explanation for the loss of per token cost leadership.
    • AI pricing is shifting from all you can eat to usage based, mirroring the cellular and long distance industries. Cellular stopped being a great growth industry when it went all you can eat. AI just made the opposite move.
    • OpenAI and Anthropic together could exceed two hundred billion in ARR this year if compute keeps coming online and frontier token pricing holds.
    • The two hundred fifty dollar a month consumer AI plan is no longer enough to evaluate frontier capability. Enterprise plans with usage based billing are required because rate limits are now severe.
    • The three biggest open questions for AI investors are: violation of the bitter lesson via ASI or human ingenuity, whether frontier tokens keep commanding their premium, and when continual learning arrives.
    • Today’s continual learning is crude reinforcement learning during mid training on verifiable tasks. True continual learning means weights updating dynamically, like a human who learns the first time they touch fire.
    • Trying to build a better GPU is a losing strategy. Jensen will copy any one to three percent share design. Startups should target one percent share, do something different, and make it hard enough that Nvidia cannot fast follow.
    • Disaggregated inference (separating prefill and decode) opens new design canvases. Prefill is memory capacity bound. Decode is memory bandwidth bound. Each can be optimized independently.
    • Cerebras did something different and hard with wafer scale computing. Three generations of chips and real grit to get there.
    • Disaggregation of inference may stretch GPU useful lives to ten or fifteen years, dropping financing costs from low sevens to five or six percent, mathematically lowering the cost of the AI buildout and likely saving the private credit industry from its SaaS loan exposure.
    • Sellers of shortage outperform buyers of shortage. But owning the largest installed base of what is currently in shortage (hyperscaler CPU fleets, for example) is also a strong position.
    • Most of the economic value at the application layer of AI has been destroyed, not created. The exceptions are companies in the token path or in niches small enough that frontier labs ignore them.
    • Coding may be the shortest path to ASI. If you can write code, you can write code that does anything. Cursor, Cognition, and Anthropic correctly focused on it.
    • Jensen could probably get close to the frontier with his own Nemotron family of models whenever he wants. The fact that he chooses not to is a strategic decision about not commoditizing his customers.
    • The new prisoner’s dilemma in AI is whether frontier labs release their best model via API. If everyone agrees not to, Chinese open source falls behind. If anyone defects, the defector pulls ahead on revenue and resources, forcing everyone else to defect.
    • Google still owns the largest compute installed base. Without TPU’s prior cost advantage, this matters more. YouTube data has real value in a world of robotics. GCP is going crazy.
    • Meta deserves credit for becoming AI first internally faster than any other internet giant. Musa, their first MSL model, is impressively close to the Pareto frontier.
    • Amazon is strong because of Trainium and robotics driven retail P&L efficiency. Nova is better than it gets credit for.
    • Microsoft flinched on capex in early 2025 and lost position. Satya Nadella’s current decision to use Microsoft compute for Microsoft products rather than reselling to OpenAI is a courageous and probably correct call, even at the cost of an eight hundred dollar stock price.
    • The hyperscalers most engaged with startups are Amazon and Nvidia by a mile, followed by Google. Broadcom is the favorite ASIC partner. AMD, Microsoft, and Meta have minimal startup engagement and that will cost them as the best teams are now at startups.
    • Personal safety in an AI era requires a family or company safe word that cannot be socially engineered. Deepfake voice and video extortion at the speed of FaceTime is already feasible.
    • Ukraine is winning largely on the back of having the best battlefield AI outside America and Israel. Adversaries are starting to internalize what AI dominance means geopolitically.
    • An optimistic read is that this becomes a new Pax Americana, the way the post 1945 American nuclear monopoly was used to rebuild Germany and Japan rather than dominate.
    • AI cured a friend’s daughter’s rare disease by spinning up a research effort that identified a market drug capable of impacting her condition. That is the upside that keeps Gavin an AI optimist maximalist.

    Detailed Summary

    The most extraordinary moment in the history of capitalism

    Gavin’s framing of the current moment is unusually direct. Anthropic added eleven billion dollars of annual recurring revenue in a single month. The three highest profile SaaS companies of the last decade plus, Palantir, Snowflake, and Databricks, took a decade and tens of thousands of employees collectively to build the combined business that Anthropic added in thirty days. He has been investing through every major tech cycle and says there is no historical analog. Not the dotcom era, not the cloud transition, not mobile. This is its own thing.

    The market response, then, was peculiar. The NASDAQ sold off into the single most bullish moment for AI fundamentals on record. Tech traded at roughly its widest discount versus the rest of the market in a decade. Investors who said they wished they had bought into AI during 2022, during COVID, or during Deep Seek Monday got the same valuation setup again in early April, this time with an even clearer inflection.

    Why the Strait of Hormuz closing was secretly bullish for America

    One reason the macro fear in March may have been mispriced is that the same geopolitical event that drove the selloff was, in practice, a relative benefit to the United States. American natural gas, the input into American electricity, which is the input into American AI training and inference, fell roughly twenty percent. Asian and European natural gas prices doubled or tripled. The US emerged with sharply improved relative manufacturing competitiveness, which is exactly what the current administration cares about.

    The 1970s comparison does not hold. The US economy is dramatically less energy intensive, it is now the world’s largest producer and largest exporter of oil and gas, and there are no shortages, only price moves. That backdrop made it easier for disciplined investors to stay focused on AI fundamentals through the volatility.

    Anthropic and OpenAI valuations on an unconstrained run rate

    Anthropic at roughly nine hundred billion for fifty billion of ARR sounds rich until you adjust for the fact that the company is severely compute constrained. Gavin estimates that, unconstrained, Anthropic might be at one hundred fifty to two hundred billion in run rate revenue, putting the implied multiple closer to five times. He also points out that Claude Opus now generates roughly seventy percent fewer tokens for the same question than it used to. Token quantity correlates with answer quality, and Anthropic is rate limiting and shrinking outputs to ration capacity across its user base.

    Anthropic and OpenAI are also structurally very different. Anthropic has burned around eighty percent less cash than OpenAI to reach a comparable revenue scale. That implies very different long term returns on invested capital, though OpenAI has done a better job locking in compute and Sarah Friar is one of the most exceptional CFOs Gavin has worked with.

    Why neither lab is raising at a three trillion dollar valuation

    The answer Gavin gives is that both labs are deliberately leaving valuation on the table the way Elon has done for two decades. SpaceX compounded at low thirty percent annually for a decade because Elon never pushed price. The result is a permanent superpower of access to capital. Investors trust him because they have made money with him for twenty years. That is a moat that compounds with every round.

    Anthropic could probably raise at a one hundred percent premium to its rumored latest mark. They are choosing not to. In an uncertain world (Ukraine, Russia, Iran, Taiwan), preserving the ability to raise more capital later at fair prices is more valuable than maximizing this round.

    Watts and wafers, the two real constraints

    Capitalism is solving the watts problem. The leading PE infrastructure investors now say zoning and political approval, not chips or energy, are the gating factors. Companies are deferring big capex announcements until after the US midterms. Turbine capacity is being doubled at the manufacturers. Companies like Boom Aerospace are repurposing jet engines for grid use. Watts probably ease meaningfully in 2027 and 2028 and then orbital compute does the rest.

    Wafers are the harder problem because they live in Taiwan, run on handshakes, and depend on a corporate culture that does not respond to public market incentives. TSMC is essentially the GDP, water consumption, and electricity consumption of Taiwan. Its leadership treats the company as the legacy of Morris Chang. The Silicon Shield doctrine is real and internal.

    Orbital compute as racks in space

    The biggest mental update Gavin asks listeners to make is to stop picturing data centers in space as Pentagon sized space stations. A Blackwell rack is three thousand pounds and roughly the size of a refrigerator. SpaceX has shown a concept satellite of about that size. Solar wings extend five hundred feet to each side and the radiator extends hundreds of feet behind, both possible because the orbit is sun synchronous and the orientation is fixed relative to the sun.

    SpaceX engineers Gavin has spoken to at Starbase express genuine confidence that they have solved cooling at these power levels. They have. Starlink V3 satellites already operate at twenty kilowatts. A Blackwell rack is one hundred kilowatts. The same company operates the world’s largest satellite fleet and the world’s largest data center on Earth via xAI Colossus. The racks are connected to each other with lasers traveling through vacuum, technology already deployed in every Starlink. The naysayers, Gavin observes, are armchair skeptics and Larry Ellison’s response (he is out there landing rockets, no one else is) is the right frame.

    Terafab in Texas and the threat to TSMC’s discipline

    Terafab, the SpaceX and Tesla joint venture, intends to be the largest fab in the world. The partnership with Intel grants access to fifty years of foundry institutional knowledge, allowing Terafab to start three to five quarters behind the leading node rather than fifteen years behind. The A teams at the semicap equipment companies (ASML, KLA, Lam Research, Applied Materials) will follow Elon’s reputation in hardware engineering the same way they followed TSMC twenty years ago when Intel stumbled.

    The talent strategy is the part most observers underestimate. Recruit the best engineers globally, then import their families, their restaurants, their staff. Build Taiwan Town, Japan Town, and Korea Town next to the fab. Optimize the human experience for the people whose work matters. Intel and Samsung do not think that way.

    Bubble watch and the year 2000 comparison

    Every foundational technology in modern history has had a bubble. Railroads, canals, the internet. Carlota Perez documented why. Markets correctly identify the importance, diversity of opinion collapses, supply gets ahead of demand, the bubble crashes. The current cycle has two important differences. The buildout is overwhelmingly funded out of operating cash flow, not debt. Every GPU is running at one hundred percent utilization, while at the peak of the fiber bubble ninety nine percent of fiber was unused.

    TSMC discipline is the single largest reason a bubble has not formed. If Jensen could buy everything TSMC could theoretically make, Nvidia could sell two to three trillion dollars of GPUs in 2026 and 2027. At some point that becomes more than the market can absorb. If Intel or Samsung Foundry catches up at the leading node, the other will too. TSMC’s pricing discipline collapses and the bubble starts.

    The Pareto frontier and the loss of Google’s cost advantage

    The most important chart in AI is the Pareto frontier of model intelligence versus per token cost. Nine months ago, Google’s TPU based models dominated every point on it. OpenAI, Anthropic, and xAI sat inside the frontier. Today the frontier is dominated by Anthropic and OpenAI, with Grok 4.3 on the frontier and Gemini 3.1 hanging on by subsidization more than economics. The most likely cause is Google’s conservative TPU V8 design, an attempt to reduce dependence on Broadcom and Nvidia that sacrificed per token economics.

    The bitter lesson, frontier tokens, and continual learning

    Three open questions dominate AI investing. The first is whether Richard Sutton’s bitter lesson (more compute beats human algorithmic cleverness) gets violated by ASI itself optimizing for efficiency. Closer observers of AI are more skeptical of a violation. Gavin thinks ASI’s first move will be to make itself more efficient and more resourced, which is technically a temporary violation.

    The second is whether frontier tokens keep capturing the overwhelming share of economic value at the model layer. Today they do, surprisingly. Gemini 3.1 Pro was mindblowing nine months ago and is intolerable today. The third is when continual learning arrives. Today’s models need a million fire touches to learn what a human learns from one. True continual learning would mean dynamic weight updates in real time and would produce a fast takeoff.

    From all you can eat to usage based AI pricing

    AI is shifting from flat fee plans to usage based pricing. The historical analogy is cellular and long distance. Both stopped being great growth industries when they went all you can eat. AI just made the opposite move. The consequence is that flat fee subscribers, even on premium consumer plans, get a rate limited and token throttled version of the frontier model. Enterprise plans with usage based billing are now required to evaluate true capability. Gavin thinks the combination of new compute coming online and usage based pricing is what gets OpenAI and Anthropic past two hundred billion in combined ARR this year.

    Chip startups, prefill decode disaggregation, and Cerebras

    Trying to build a better GPU is the wrong move. The four scaled players (Nvidia, AMD, Trainium, TPU) have copy capability for any one to three percent share design that looks attractive. The good news for startups is that disaggregated inference (separating prefill and decode) opens a richer design canvas. Prefill is memory capacity bound. Decode is memory bandwidth bound. Each can be optimized independently. Andrew Fox’s analogy is a British naval ship of the eighteenth century. Prefill is loading the cannon. Decode is firing it.

    Cerebras is the model. Wafer scale computing is genuinely different and genuinely hard. It took three generations of chips to get right. Andrew Feldman and his team had the grit to keep going through chip one being a failure. The design has a high ratio of on chip compute and memory relative to shoreline IO, which is why Cerebras is now experimenting with putting an optical wafer on top of the compute wafer to solve scale out.

    GPU useful lives and the rescue of private credit

    One of the strongest claims in the conversation is that disaggregated inference will stretch GPU useful lives to ten or fifteen years. The skeptical narrative (GPUs are obsolete in two years, companies are cooking their depreciation books) is wrong. You can put a Cerebras system or Groq LPU in front of older Hopper or Ampere parts, use them only for prefill, and run them until they physically melt. Private credit, which is in pain from SaaS loans and which underwrote GPU loans on three to four year lives, may be saved by this.

    If GPU financing rates can come down from low sevens to five or six percent, the mathematics of the AI buildout improves materially. That is a structural tailwind that compounds for years.

    The application layer, the token path, and a new prisoner’s dilemma

    Trillions of dollars of value have been destroyed at the application layer, not created. Cursor and Cognition are the rare scaled exceptions, and they got there by focusing on coding very early. As Amjad Masad noted, coding is plausibly the shortest path to ASI because a coding agent can write itself into any new domain. Jamin Ball’s frame is that the new venture filter is whether the company is in the token path. Data Bricks is. Most application layer startups are not.

    Jensen could probably get close to the frontier with Nemotron whenever he wants, and the strategic question of whether to do that is a new prisoner’s dilemma. If every frontier lab agrees not to release best models via API, Chinese open source falls steadily behind. If anyone defects, the defector gains revenue and resources, and everyone else has to defect. The same dynamic exists between TSMC, Intel, and Samsung. If Nvidia or AMD ever truly used an alternative foundry, that foundry would catch up rapidly.

    Rating the hyperscalers

    Google has the largest compute installed base, the YouTube data that matters in a robotics world, and a search business that prints. Their loss of TPU cost leadership is the surprise of the year. If Google IO in five days does not produce a leapfrog model, the Nvidia centric narrative gets even stronger.

    Meta deserves real credit. Zuckerberg made Meta AI first internally faster than any other internet giant, paid up for the talent contracts when no one else would, and shipped Musa as a first model from MSL that is close to the Pareto frontier. Amazon is well positioned on Trainium, robotics in retail, and a Nova model line that is better than it gets credit for. Microsoft flinched on capex in early 2025 and lost position. Satya Nadella’s current decision to use Microsoft compute for Copilot rather than reselling to OpenAI is courageous and probably correct, even at the cost of stock price.

    The most interesting cross hyperscaler metric is startup engagement. Nvidia and Amazon engage deeply with startups. Google is next. Broadcom is the favored ASIC partner. AMD, Microsoft, and Meta have minimal startup engagement, which Gavin believes will cost them as the best teams now sit at startups.

    Personal safety, geopolitics, and the Pax Americana case

    The closing section turns darker. Personal safety in an AI era requires a family or company safe word that cannot be socially engineered. Deepfake voice and video extortion via something that looks exactly like your child calling on FaceTime is already feasible. Political violence against AI leaders is a real concern. Geopolitically, Ukraine is winning largely because it has the best battlefield AI outside America and Israel. How adversaries respond to that asymmetry is the next great variable.

    Gavin’s optimistic frame is the Pax Americana. After 1945 the US had a nuclear monopoly and could have controlled the world. Instead it rebuilt Germany and Japan, both of which became the most reliable American allies for the next eighty years. If AI dominance plays out similarly, this is a generationally positive story rather than a destabilizing one. The personal anecdote that closes the conversation is a friend whose daughter was diagnosed with a rare genetic condition. He spun up agents, identified a drug already on the market that addresses her mutation, and her life is immeasurably different because of AI. That is the upside.

    Thoughts

    The Anthropic eleven billion in a month framing is the kind of stat that resets priors. The right way to interpret it is not as a one off but as a measure of how fast value can compound when the underlying technology improves on a curve steeper than the ability of the rest of the economy to absorb it. The skeptical question is whether that ARR is durable or whether it is heavily tied to a customer base of other AI companies that are themselves on a single venture funded year of runway. The bullish answer is that frontier coding, frontier research, and frontier enterprise tasks are not going to stop being valuable, and Anthropic is the best at all three. Both can be true. The number is still extraordinary.

    The argument that TSMC discipline is the only thing preventing a bubble is the analytically tightest part of the conversation. The implied trade is to watch TSMC capacity additions like a hawk and to be more, not less, cautious if Intel Foundry or Samsung Foundry ever announce real share at the leading node. The Terafab thesis is more speculative but more interesting. If Elon’s talent recruiting playbook works and the Intel partnership gives Terafab a real seat at the table within five years, the geometry of the global semiconductor industry shifts in a way that is bullish for American manufacturing, bullish for power and water infrastructure in Texas, and ambiguous for TSMC itself.

    The Pareto frontier discussion deserves more attention than it usually gets. Pricing leadership in AI is not a vanity metric. It determines who can subsidize free tier usage, who can absorb compute shortages, who can ship cheaper enterprise plans, and ultimately whose model becomes the default for any given workload. Google losing per token leadership in nine months is one of the most under analyzed events in the sector and it explains a lot about why Anthropic and OpenAI are growing the way they are. If Google IO does not produce a leapfrog model, the implied verdict on TPU V8 design choices gets a lot harsher.

    The application layer destruction point is worth sitting with. Founders building on top of frontier models are competing in a world where the model itself moves faster than any moat they can build, where the model lab can absorb their niche if it gets interesting, and where the only protection is either deep token path integration or a niche so small the lab does not bother. That is a much harsher venture environment than the early SaaS era. The compensating opportunity is that one human can now run a hundred agents, so the ceiling on what a small team can build is correspondingly higher. The bet is that productivity per founder rises faster than competitive pressure from the labs. We will find out.

    The orbital compute pitch is the section that will polarize listeners. The naive read is that this is science fiction. The closer read is that every component (sun synchronous orbit, laser interconnect, twenty kilowatt satellite buses, ten thousand satellite manufacturing cadence, full rocket reusability) already exists. The remaining engineering problems are repair, maintenance, and radiator scale, all of which are real but tractable on a five to ten year horizon. The strategic implication is that the political and zoning ceiling on terrestrial data centers becomes less binding if orbital compute is a credible alternative for inference workloads. The investor implication is that being short the watts and cooling complex on a five year horizon is a real trade, not a meme.

    Watch the full conversation here.

  • Pershing Square’s Bold Plan: Relist Fannie Mae & Freddie Mac on NYSE in November 2025 – Taxpayers Could Gain $300B+

    Pershing Square’s Bold Plan: Relist Fannie Mae & Freddie Mac on NYSE in November 2025 – Taxpayers Could Gain $300B+

    TL;DR:

    Bill Ackman’s Pershing Square Capital Management just released a 28-page investor presentation urging the Trump administration to immediately (1) deem the Treasury’s Senior Preferred Stock repaid, (2) exercise the 79.9% warrants, and (3) relist Fannie Mae (FNMA) and Freddie Mac (FMCC) on the NYSE — all while keeping the GSEs in conservatorship. They claim this can be done before the end of November 2025 and would instantly value the U.S. taxpayer’s stake at over $300 billion without disrupting mortgage affordability.

    Key Takeaways

    • Fannie & Freddie OTC shares have already more than doubled in 2025 on Trump administration statements.
    • The three-step plan (repay SPS → exercise warrants → NYSE relisting) can be executed immediately by Treasury and FHFA.
    • Post-relisting, Treasury would own 79.9% of two NYSE-listed companies worth a combined ~$387 billion (Pershing estimate).
    • Taxpayers have already received $301 billion in dividends — $25 billion more than required under the original 10% deal.
    • Pershing strongly opposes any conversion of Senior Preferred into common — calls it value-destructive and legally risky.
    • Relisting unlocks massive institutional buying (many funds are barred from OTC stocks) and fulfills Trump’s campaign promise timing.
    • Conservatorship continues for years, giving the administration runway to finalize capital rules, backstop structure, and governance.

    Detailed Summary of the Pershing Square Presentation (November 2025)

    In a presentation titled “Promises Made, Promises Kept”, Pershing Square lays out a politically and financially attractive path for the second Trump administration to deliver on its GSE reform pledges without raising mortgage rates or rushing a full privatization.

    The core argument: the government has already been fully repaid (and then some) via $301 billion of dividends since 2008. The Obama-era 2012 “Net Worth Sweep” was paused under Mnuchin, but never fully reversed. Pershing says a simple letter agreement between Treasury and FHFA can officially retire the Senior Preferred Stock today.

    Once the SPS is gone, Treasury can exercise its long-held warrants for 79.9% of the common stock at essentially zero cost. The GSEs already meet every NYSE listing requirement (market cap, float, share price, shareholder count, etc.). FHFA can approve relisting while keeping full conservatorship powers intact — no change to operations, no new capital raises, no dividend payments to juniors until fully recapitalized.

    Pershing’s valuation math (as of 12/31/2025):

    • Fannie Mae: 16× 2026E EPS → ~$42–45/share → Treasury 79.9% stake ≈ $196 billion
    • Freddie Mac: 13× 2026E EPS → ~$44/share → Treasury 79.9% stake ≈ $114 billion
    • Total taxpayer value: >$310 billion (plus junior preferred)

    They explicitly reject the idea of converting Senior Preferred into common, warning it would trigger new litigation, force government consolidation onto the federal balance sheet, and slash valuations by 27–56% depending on the multiple the market would assign to a company that wiped out private shareholders.

    My Thoughts

    This is classic Ackman: aggressive, detailed, and perfectly timed to influence policy while he has a massive economic interest (Pershing owns large common positions in both GSEs). The beauty of the proposal is that it is genuinely low-risk from a mortgage-market standpoint and gives the administration an instant “win” before Thanksgiving 2025.

    The politics line up perfectly: Trump gets to post on Truth Social that he turned two “bailed-out” companies into a $300 billion+ taxpayer windfall, keeps 30-year mortgage rates stable (or even lower), and still retains total control to shape the final exit over the next three years.

    If Treasury and FHFA actually follow the three steps before November 30, 2025, the OTC-to-NYSE pop could be one of the largest wealth-transfer events in market history — and almost entirely to existing common shareholders (retail + hedge funds that held on since 2008).

    Watch for any joint Treasury/FHFA announcement or letter agreement in the next two weeks. That will be the trigger.

    Disclosure: Like Pershing Square, the author may have direct or indirect exposure to FNMA/FMCC securities.

  • Global Madness Unleashed: Tariffs, AI, and the Tech Titans Reshaping Our Future

    As the calendar turns to March 21, 2025, the world economy stands at a crossroads, buffeted by market volatility, looming trade policies, and rapid technological shifts. In the latest episode of the BG2 Pod, aired March 20, venture capitalists Bill Gurley and Brad Gerstner dissect these currents with precision, offering a window into the forces shaping global markets. From the uncertainty surrounding April 2 tariff announcements to Google’s $32 billion acquisition of Wiz, Nvidia’s bold claims at GTC, and the accelerating AI race, their discussion—spanning nearly two hours—lays bare the high stakes. Gurley, sporting a Florida Gators cap in a nod to March Madness, and Gerstner, fresh from Nvidia’s developer conference, frame a narrative of cautious optimism amid palpable risks.

    A Golden Age of Uncertainty

    Gerstner opens with a stark assessment: the global economy is traversing a “golden age of uncertainty,” a period marked by political, economic, and technological flux. Since early February, the NASDAQ has shed 10%, with some Mag 7 constituents—Apple, Amazon, and others—down 20-30%. The Federal Reserve’s latest median dot plot, released just before the podcast, underscores the gloom: GDP forecasts for 2025 have been cut from 2.1% to 1.7%, unemployment is projected to rise from 4.3% to 4.4%, and inflation is expected to edge up from 2.5% to 2.7%. Consumer confidence is fraying, evidenced by a sharp drop in TSA passenger growth and softening demand reported by Delta, United, and Frontier Airlines—a leading indicator of discretionary spending cuts.

    Yet the picture is not uniformly bleak. Gerstner cites Bank of America’s Brian Moynihan, who notes that consumer spending rose 6% year-over-year, reaching $1.5 trillion quarterly, buoyed by a shift from travel to local consumption. Conversations with hedge fund managers reveal a tactical retreat—exposures are at their lowest quartile—but a belief persists that the second half of 2025 could rebound. The Atlanta Fed’s GDP tracker has turned south, but Gerstner sees this as a release of pent-up uncertainty rather than an inevitable slide into recession. “It can become a self-fulfilling prophecy,” he cautions, pointing to CEOs pausing major decisions until the tariff landscape clarifies.

    Tariffs: Reciprocity or Ruin?

    The specter of April 2 looms large, when the Trump administration is set to unveil sectoral tariffs targeting the “terrible 15” countries—a list likely encompassing European and Asian nations with perceived trade imbalances. Gerstner aligns with the administration’s vision, articulated by Vice President JD Vance in a recent speech at an American Dynamism event. Vance argued that globalism’s twin conceits—America monopolizing high-value work while outsourcing low-value tasks, and reliance on cheap foreign labor—have hollowed out the middle class and stifled innovation. China’s ascent, from manufacturing to designing superior cars (BYD) and batteries (CATL), and now running AI inference on Huawei’s Ascend 910 chips, exemplifies this shift. Treasury Secretary Scott Bessent frames it as an “American detox,” a deliberate short-term hit for long-term industrial revival.

    Gurley demurs, championing comparative advantage. “Water runs downhill,” he asserts, questioning whether Americans will assemble $40 microwaves when China commands 35% of the global auto market with superior products. He doubts tariffs will reclaim jobs—automation might onshore production, but employment gains are illusory. A jump in tariff revenues from $65 billion to $1 trillion, he warns, could tip the economy into recession, a risk the U.S. is ill-prepared to absorb. Europe’s reaction adds complexity: *The Economist*’s Zanny Minton Beddoes reports growing frustration among EU leaders, hinting at a pivot toward China if tensions escalate. Gerstner counters that the goal is fairness, not protectionism—tariffs could rise modestly to $150 billion if reciprocal concessions materialize—though he concedes the administration’s bellicose tone risks misfiring.

    The Biden-era “diffusion rule,” restricting chip exports to 50 countries, emerges as a flashpoint. Gurley calls it “unilaterally disarming America in the race to AI,” arguing it hands Huawei a strategic edge—potentially a “Belt and Road” for AI—while hobbling U.S. firms’ access to allies like India and the UAE. Gerstner suggests conditional tariffs, delayed two years, to incentivize onshoring (e.g., TSMC’s $100 billion Arizona R&D fab) without choking the AI race. The stakes are existential: a misstep could cede technological primacy to China.

    Google’s $32 Billion Wiz Bet Signals M&A Revival

    Amid this turbulence, Google’s $32 billion all-cash acquisition of Wiz, a cloud security firm founded in 2020, signals a thaw in mergers and acquisitions. With projected 2025 revenues of $1 billion, Wiz commands a 30x forward revenue multiple—steep against Google’s 5x—adding just 2% to its $45 billion cloud business. Gerstner hails it as a bellwether: “The M&A market is back.” Gurley concurs, noting Google’s strategic pivot. Barred by EU regulators from bolstering search or AI, and trailing AWS’s developer-friendly platform and Microsoft’s enterprise heft, Google sees security as a differentiator in the fragmented cloud race.

    The deal’s scale—$32 billion in five years—underscores Silicon Valley’s capacity for rapid value creation, with Index Ventures and Sequoia Capital notching another win. Gerstner reflects on Altimeter’s misstep with Lacework, a rival that faltered on product-market fit, highlighting the razor-thin margins of venture success. Regulatory hurdles loom: while new FTC chair Matthew Ferguson pledges swift action—“go to court or get out of the way”—differing sharply from Lina Khan’s inertia, Europe’s penchant for thwarting U.S. deals could complicate closure, slated for 2026 with a $3.2 billion breakup fee at risk. Success here could unleash “animal spirits” in M&A and IPOs, with CoreWeave and Cerebras rumored next.

    Nvidia’s GTC: A $1 Trillion AI Gambit

    At Nvidia’s GTC in San Jose, CEO Jensen Huang—clad in a leather jacket evoking Steve Jobs—addressed 18,000 attendees, doubling down on AI’s explosive growth. He projects a $1 trillion annual market for AI data centers by 2028, up from $500 billion, driven by new workloads and the overhaul of x86 infrastructure with accelerated computing. Blackwell, 40x more capable than Hopper, powers robotics (a $5 billion run rate) to synthetic biology. Yet Nvidia’s stock hovers at $115, 20x next year’s earnings—below Costco’s 50x—reflecting investor skittishness over demand sustainability and competition from DeepSeek and custom ASICs.

    Huang dismisses DeepSeek R1’s “cheap intelligence” narrative, insisting compute needs are 100x what was estimated a year ago. Coding agents, set to dominate software development by year-end per Zuckerberg and Musk, fuel this surge. Gurley questions the hype—inference, not pre-training, now drives scaling, and Huang’s “chief revenue destroyer” claim (Blackwell obsoleting Hopper) risks alienating customers on six-year depreciation cycles. Gerstner sees brilliance in Nvidia’s execution—35,000 employees, a top-tier supply chain, and a four-generation roadmap—but both flag government action as the wildcard. Tariffs and export controls could bolster Huawei, though Huang shrugs off near-term impacts.

    AI’s Consumer Frontier: OpenAI’s Lead, Margin Mysteries

    In consumer AI, OpenAI’s ChatGPT reigns with 400 million weekly users, supply-constrained despite new data centers in Texas. Gerstner calls it a “winner-take-most” market—DeepSeek briefly hit #2 in app downloads but faded, Grok lingers at #65, Gemini at #55. “You need to be 10x better to dent this inertia,” he says, predicting a Q2 product blitz. Gurley agrees the lead looks unassailable, though Meta and Apple’s silence hints at brewing counterattacks.

    Gurley’s “negative gross margin AI theory” probes deeper: many AI firms, like Anthropic via AWS, face slim margins due to high acquisition and serving costs, unlike OpenAI’s direct model. With VC billions fueling negative margins—pricing for share, not profit—and compute costs plummeting, unit economics are opaque. Gerstner contrasts this with Google’s near-zero marginal costs, suggesting only direct-to-consumer AI giants can sustain the capex. OpenAI leads, but Meta, Amazon, and Elon Musk’s xAI, with deep pockets, remain wildcards.

    The Next 90 Days: Pivot or Peril?

    The next 90 days will define 2025. April 2 tariffs could spark a trade war or a fairer field; tax cuts and deregulation promise growth, but AI’s fate hinges on export policies. Gerstner’s optimistic—Nvidia at 20x earnings and M&A’s resurgence signal resilience—but Gurley warns of overreach. A trillion-dollar tariff wall or a Huawei-led AI surge could upend it all. As Gurley puts it, “We’ll turn over a lot of cards soon.” The world watches, and the outcome remains perilously uncertain.

  • What’s Coming: Ray Dalio on the Changing Domestic and World Orders Under the Trump Administration

    What's Coming: Ray Dalio on the Changing Domestic and World Orders Under the Trump Administration

    Renowned investor and economic thinker Ray Dalio offers a profound analysis of the anticipated shifts in both domestic and international orders under the Trump administration. Dalio emphasizes the importance of understanding these changes to make informed decisions.

    A Giant Renovation of Government

    Dalio predicts two significant transformations:

    1. Domestic Overhaul: A comprehensive renovation aimed at enhancing government efficiency, potentially leading to internal political struggles as this vision unfolds.
    2. “America First” Foreign Policy: A strategic focus on preparing for external conflicts, particularly with China, perceived as America’s most significant threat.

    Corporate Raider Approach to Government

    The administration plans to reform the government akin to a corporate takeover:

    • Leadership Choices:
      • Elon Musk and Vivek Ramaswamy: Set to lead the new Department of Government Efficiency.
      • Matt Gaetz: Nominated for Attorney General, aiming to push legal boundaries.
      • RFK Jr.: Expected to overhaul the healthcare system as Secretary of Health and Human Services.
      • Marco Rubio, Tulsi Gabbard, and Pete Hegseth: Appointed to key defense and intelligence positions.

    Purging the “Deep State”

    A systematic replacement of officials not aligned with the new vision is anticipated:

    • Targeted Agencies: Military, Department of Justice, FBI, SEC, Federal Reserve, among others.
    • Implementation of “Schedule F”: Reclassifying certain government jobs to remove civil service protections.

    Economic Implications

    • Positive Outlook for Wall Street: Deregulation and tax reductions may benefit financial sectors.
    • Tech Sector Freedom: Pro-Trump tech companies might experience fewer restraints.
    • Stimulative Monetary Policies: Potential pressure on the Federal Reserve to ease monetary policies.

    Changing International World Order

    Shift from Post-WWII Systems

    • End of Multilateralism: Moving away from global institutions like the UN and WTO.
    • Law-of-the-Jungle Dynamics: A more self-interested approach with clear allies and adversaries.

    Focus on China

    • Primary Adversary: China’s rising power and ideological differences place it at the center of foreign policy concerns.
    • Capitalism vs. Communism: The age-old ideological battle resurfaces in contemporary contexts.

    Global Alliances and Neutrality

    • Allies: Japan, the UK, and Australia are key, though challenges in collaboration exist.
    • Europe’s Position: Preoccupied with internal issues and hesitant to engage fully.
    • Opportunities for Non-Aligned Countries: Neutral nations may find economic opportunities amidst the U.S.-China rivalry.

    Specific Policy Shifts to Anticipate

    1. Increased Government Influence: A tilt towards achieving national objectives over free-market mechanisms.
    2. Massive Deregulation: Easing restrictions to promote cost-efficient production.
    3. Immigration Actions: Tightening borders and deporting undocumented immigrants with criminal records.
    4. Trade and Tariff Reforms: Adjustments to protect domestic industries and raise revenue.
    5. Challenges with Allies: Navigating relationships with key nations amid shifting priorities.
    6. Economic Costs of Dominance: Balancing the expenses of maintaining global leadership.
    7. Tax Policies: Potential reductions to stimulate productivity and satisfy the electorate.
    8. Healthcare Reforms: Significant changes aimed at overhauling the current system.

    Ray Dalio’s analysis highlights a transformative period under the Trump administration that promises significant changes reshaping both the domestic landscape and international relations. Understanding these shifts is crucial for businesses, policymakers, and individuals alike to navigate the evolving environment effectively.

  • The Triumph of Counter-Elites: How Peter Thiel and Silicon Valley’s Outsiders Are Reshaping American Power

    The Triumph of Counter-Elites: How Peter Thiel and Silicon Valley’s Outsiders Are Reshaping American Power

    Peter Thiel sees America’s political and cultural landscape shifting, with counter-elites rising to challenge traditional power structures. Led by figures like Elon Musk and Vivek Ramaswamy, Trump’s new Department of Government Efficiency (DOGE) reflects this outsider influence. Thiel argues that identity politics and celebrity culture are losing sway, while Silicon Valley is shifting away from wokeness in favor of pragmatism.

    Thiel advocates for tariffs and controlled immigration to revive U.S. manufacturing and reduce economic strain. On foreign policy, he warns against both excessive intervention and appeasement, favoring a realistic approach over neoconservative ideals. In education, Thiel criticizes elite institutions for promoting conformity and waste, urging structural reforms.

    He views the internet as a disruptor that’s exposed institutional flaws, destabilizing trust in traditional authority. Thiel believes history is far from over; counter-elites are reshaping it by challenging established norms and ideologies. The result? A new American revolution driven by intellectual diversity, economic independence, and a rethinking of governance.

    As the political winds in America shift, a new force is rising, upending not only traditional political elites but the very culture that has long bolstered them. At the center of this counter-elite movement is billionaire investor and iconoclast Peter Thiel, who views this moment as a turning point—a rejection of identity-driven politics, a realignment of Silicon Valley’s politics, and a cultural revolution spearheaded by unorthodox figures like Elon Musk and Vivek Ramaswamy. With Donald Trump’s return to the White House in 2024, bolstered by influential Silicon Valley insurgents, the counter-elite movement has taken a leading role in rethinking governance, culture, and American society at large.

    New Department of Government Efficiency (DOGE): A Meme in the White House?

    Thiel sees Trump’s creation of the “Department of Government Efficiency” (DOGE), headed by Musk and Ramaswamy, as a sign of the times—a joke on meme culture now embedded in government and a clear sign that America’s outsiders are gaining power over traditional elites. This new department signifies a radical, tech-savvy approach to government reform, built on ideas from Silicon Valley’s most successful (and often controversial) figures. For Thiel, it’s more than just a meme—it’s the embodiment of counter-elite victory.

    Key Insight: DOGE is more than just a play on internet culture; it reflects a profound shift toward anti-establishment governance led by entrepreneurial thinkers and doers, rather than career politicians.

    The Rise of the Rebel Alliance Against the Liberal “Empire”

    Thiel draws a parallel between the traditional liberal elite and the Empire in Star Wars. This liberal “Empire,” he argues, includes entrenched elites in academia, Hollywood, and mainstream media, who cling to an outdated and now disintegrating identity-based ideology. This shift is most visible in the changing role of celebrity endorsements in elections. For the 2024 election, Trump’s endorsements came not from A-list celebrities but from a range of unconventional influencers, including podcast hosts and internet entrepreneurs—a clear sign of the shifting political landscape.

    Thiel and his counter-elite cohort, from Musk to venture capitalist David Sacks, represent what he calls the “Rebel Alliance”: a coalition of outsiders, innovators, and free thinkers challenging the monolithic control of traditional cultural elites. For Thiel, this alliance isn’t merely a political alternative—it’s a new way of organizing society around intellectual diversity, self-reliance, and questioning authority.

    Key Insight: Thiel’s counter-elite “Rebel Alliance” frames Silicon Valley’s entrepreneurial class as the true radicals, while Hollywood and academia are cast as enforcers of an outdated and dogmatic status quo.

    Silicon Valley’s Political Transformation: From Woke to Pragmatic

    Thiel observes that Silicon Valley is finally tiring of woke culture, seeing it as a distraction from the real issues of innovation, productivity, and organizational health. Leaders like Musk have taken visible steps to resist what they view as an unproductive and authoritarian mindset in tech, moving toward policies that prioritize results over ideology. According to Thiel, this marks a significant shift in corporate governance, as tech giants rethink workplace cultures that have leaned heavily into social and political agendas.

    In his view, the liberal “Empire” has morphed into a machine that enforces orthodoxy and punishes dissent—a trend that is pushing many tech innovators to align themselves with counter-elite and anti-establishment politics.

    Key Insight: Silicon Valley’s turn against wokeness signals a deeper shift in tech culture, as leaders choose productivity and innovation over ideological rigidity.

    Thiel on Trade and Tariffs: A Strategic Re-evaluation

    Thiel is vocal about the need to reevaluate trade policies, advocating for tariffs that protect American manufacturing and counterbalance China’s economic power. He views free trade as an outdated doctrine that no longer serves U.S. interests, particularly as globalization has been increasingly weaponized by authoritarian regimes. For Thiel, effective economic policy should serve national interests, and he sees tariffs as a tool for regaining economic independence, especially in the Rust Belt states that have borne the brunt of outsourcing.

    Key Insight: Thiel champions a re-imagining of trade policy to curb America’s reliance on foreign manufacturing, a move aimed at revitalizing U.S. industry and defending against foreign economic aggression.

    Immigration Reform and the “Economic Overload” Problem

    Thiel has a pragmatic, albeit skeptical, take on immigration. While he doubts the feasibility of Trump’s proposed mass deportations, he does believe that unchecked immigration can strain the social fabric and drive economic inequality. Thiel argues that the economic impact of immigration, especially in urban areas with housing shortages, contributes to skyrocketing real estate prices, income inequality, and the financial instability of working-class communities. He suggests that the U.S. needs a more balanced approach that considers the economic realities alongside cultural integration.

    Key Insight: Thiel’s critique of immigration emphasizes its economic impact on working-class Americans, highlighting the need for policies that address both cultural and economic concerns.

    A Contrarian View on Foreign Policy: Caution Over Interventionism

    Thiel questions America’s longstanding role as the global enforcer, especially in the wake of costly and inconclusive interventions. He warns of a possible World War III triggered by entangling alliances and urges a more restrained approach, focused on direct national interest rather than ideological crusades. Thiel’s view aligns with the shift away from neoconservatism within the Republican Party, epitomized by figures like J.D. Vance, who are wary of foreign entanglements, particularly in conflicts like Ukraine.

    He frames the rise of counter-elite foreign policy as a rejection of “neocon utopianism” in favor of a more hard-nosed realism. This realism, he argues, values stability and strategic alliances over open-ended nation-building projects that often backfire.

    Key Insight: Thiel’s vision for foreign policy is one of cautious realism, opposing both excessive interventionism and blind isolationism.

    Reconsidering Higher Education and the “Gatekeeping” Class

    Higher education, in Thiel’s view, has become a bloated, ideological machine that perpetuates elitism and groupthink. He supports defunding certain aspects of academia, particularly university overhead expenses that he sees as wasteful and unaccountable. Thiel believes that colleges, particularly elite institutions, no longer offer the intellectual rigor they once did, having morphed instead into bastions of conformity. Thiel even advocates for reduced student loan funding, arguing that without drastic reform, academia will continue to churn out debt-laden graduates with few job prospects.

    Key Insight: Thiel’s critique of higher education focuses on the system’s ideological uniformity and financial inefficiency, calling for structural changes to make education accountable and effective.

    The Internet, Transparency, and the Collapse of Institutional Trust

    Thiel argues that the internet has played a significant role in deconstructing traditional power structures by exposing the hidden flaws of once-revered institutions. With information more accessible than ever, he notes that authority figures now struggle to maintain credibility, as their decisions are scrutinized by a skeptical, hyper-informed public. This transparency, while empowering, has also destabilized the credibility of institutions, revealing that many were more fragile and corrupt than previously thought.

    While Thiel acknowledges the economic and social potential of the internet, he remains skeptical of its ability to drive material progress, particularly in comparison to past technological advancements. He sees digital culture as potentially corrosive, replacing genuine wealth creation with superficial online engagement.

    Key Insight: Thiel views the internet as a double-edged sword—one that has democratized information but also undermined public trust in institutions by exposing their flaws.

    The End of Liberal History and the Rise of Human Agency

    Thiel dismisses the once-popular belief in the “end of history”—a world where liberal democracy reigns supreme and ideological battles are obsolete. Instead, he sees human agency as vital to shaping a dynamic future, suggesting that history is far from over. In this vision, counter-elites like Thiel, Musk, and their peers serve as agents of disruption, challenging stagnant institutions and outdated ideologies. He predicts that the internet will only intensify these cultural and political shifts, pushing society to embrace more radical ideas and question long-held assumptions about authority and governance.

    Key Insight: Thiel believes history is back in full force, driven by the rise of counter-elites and a public increasingly willing to challenge institutional norms.

    The Counter-Elites and the New American Revolution

    In Thiel’s view, the counter-elites’ ascent signals a new chapter in American history, where entrenched institutions are being tested, and new paradigms are emerging from unlikely alliances between tech leaders, populist politicians, and contrarian thinkers. The counter-elite movement reflects a broader cultural shift toward intellectual diversity, economic independence, and a willingness to question the fundamental tenets of liberal governance.

    The success of this counter-elite experiment remains uncertain, but for Thiel, its emergence is both a necessary correction to establishment failures and a radical reimagining of America’s future.

    Final Takeaway: Thiel’s counter-elite revolution is a daring redefinition of American power, rejecting both liberal orthodoxy and traditional conservative dogma, and challenging the institutions that have shaped American society for generations.