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  • Elon Musk Announces SpaceX AI Satellites, Starship Mass to Orbit, and a Moon Mass Driver to Climb the Kardashev Scale

    Elon Musk sat down with the SpaceX Starlink team for a wide ranging update that connects every recent SpaceX move into one thesis: harness far more of the sun’s energy by putting AI compute in orbit. In this SpaceX conversation, the group walks from galaxy sized framing (the Kardashev scale) all the way down to the engineering specifics of a new AI satellite, the manufacturing buildout in Bastrop, Texas, and a long term plan that ends with a mass driver on the moon. The pitch is that none of it requires magic, just scaling technology SpaceX already flies.

    TLDW

    Musk frames civilizational progress with the Kardashev scale, a measure of how much power a species harnesses, and points out that humanity uses less than a trillionth of the sun’s output, barely registering even on the Type 1 (planet) level. Because most of Earth is water and the usable sunlit land is limited, the only way to capture a meaningful fraction of the sun’s energy is to go to space, where cooling is also easier since heat radiates straight into the vacuum. Three limiting factors must be solved: mass to orbit (handled by fully and rapidly reusable Starship, which already beats the Saturn V on thrust and aims for millions of tons to orbit per year), solar power plus radiators, and AI chips. SpaceX unveils its first AI satellite design, AI1, a roughly 70 meter wingspan craft at 150 kW peak and 120 kW sustained power that matches an Nvidia GB300 rack, reuses Starlink V3 solar technology, links by laser, and runs at only a few milliseconds of latency from low orbit. Chips start as off the shelf Nvidia GB300 and Rubin parts plus a TPU reference design, then scale through a planned 100 million square foot “Terafab” toward a terawatt per year of compute, about twice current US electricity use. The endgame pushes another 1,000x by manufacturing on the moon and using a lunar mass driver to fling satellites into deep space without rockets.

    Thoughts

    The most important reframe in this conversation is that Starlink, Starship, the xAI acquisition, and a new chip factory are not separate bets. They are one bet expressed as a single number: the percentage of the sun’s energy that civilization can capture and put to work. By anchoring everything to the Kardashev scale, Musk turns “build more satellites” into a measurable physics goal rather than a product roadmap. It is a rhetorically powerful move because it makes today’s hyperscale AI buildout, which already strains terrestrial grids, look like the obvious forcing function for going to space. If you accept that compute demand keeps compounding, then the constraint stops being chips and becomes power and cooling, and space genuinely is better at both.

    The cleverest engineering insight is almost understated: an AI satellite is simpler than a Starlink satellite, not harder. A Starlink craft carries complex phased array and parabolic antennas to talk to millions of dispersed users. An orbital data center mostly needs solar cells, radiators, some laser links, and the chips. SpaceX has already industrialized the hard parts (mass produced solar arrays, constellation flight operations at 10,000 satellites, laser mesh networking), so the new product is closer to a remix of proven subsystems than a clean sheet program. That is the real argument for why SpaceX, specifically, can do this when “data center in space” has sounded like science fiction for a decade.

    The numbers are where skepticism should live, and to his credit Musk says to take the timeline with a grain of salt. An annualized gigawatt of space compute by the end of next year, scaling roughly 10x per year toward a terawatt, is an extraordinary ramp. A terawatt is about twice the entire electricity consumption of the United States, delivered as orbiting hardware. Getting there leans on Starship hitting rapid reusability and on a 100 million square foot chip fab that is ten times Gigafactory Texas. Each of those is itself a moonshot, and stacking them multiplies the risk. The honest read is that the architecture is coherent even if the schedule is aspirational.

    The moon segment is where the talk turns from aggressive to genuinely speculative, and it is the part worth watching. A lunar mass driver, essentially a long linear motor that accelerates payloads to escape velocity, only makes sense once you are already moving enormous mass and want to escape Earth’s gravity well and atmosphere entirely. It is a classic Musk pattern: solve the near term problem (mass to orbit with Starship) in a way that creates the precondition for the next, larger problem (local production on the moon). Whether or not the dates hold, the dependency chain is logical, and it explains why SpaceX keeps investing in capabilities that look excessive for today’s market.

    One underrated takeaway for readers outside aerospace: this is as much a manufacturing story as a space story. The bottleneck is not whether a single AI satellite works, it is whether you can stamp out thousands to a million of them, plus the solar, plus the chips, at volume and low cost. That is why so much of the conversation is about Bastrop production lines, a solar manufacturing facility already under construction, and the Terafab. The space hardware is the visible part; the factories are the actual product.

    Key Takeaways

    • The whole strategy is framed around the Kardashev scale, a measure of how much power a civilization harnesses, named for Russian physicist Nikolai Kardashev.
    • Type 1 harnesses a planet’s available power, Type 2 a star’s full output, and Type 3 a galaxy’s; humanity sits at the very bottom of even Type 1.
    • We currently use much less than a trillionth of the sun’s power output, and a trillion is a million times a million.
    • The sun is about 99.86% of all mass in the solar system; most of the remaining 0.14% is Jupiter, and Earth is a tiny dust mote by comparison.
    • Incident solar energy on Earth’s cross section is roughly a half billionth of the sun’s total power output.
    • Most of that sunlight is unusable because about 70% of Earth is water and much of the land is at the poles or far north where solar is weak.
    • Reaching one millionth of the sun’s output, a “micro” on the Kardashev 2 scale, would be an epic achievement relative to today, and 1% would make a civilization vastly more powerful than ours.
    • Space avoids building massive ground power plants and makes cooling easier, because waste heat can radiate directly into the vacuum.
    • Three limiting factors must be solved to scale: mass to orbit, solar power plus radiators, and AI chips.
    • Starship provides the mass to orbit and is the first rocket designed for full and rapid reusability, the breakthrough behind both multiplanetary life and ascending the Kardashev scale.
    • SpaceX catches the booster with the launch tower instead of adding heavy landing legs, an extreme mass optimization measure.
    • Starship V3 already produces more than double the thrust of the Saturn V; V4 will be roughly three times, making it the largest, heaviest, most powerful moving object ever built.
    • Starship is targeted to eventually fly more than once per hour.
    • SpaceX already delivers roughly 85 to 90% of all Earth mass to orbit with Falcon 9 and Falcon Heavy.
    • The plan is to go from around 2,500 tons to orbit per year to millions of tons per year, reaching a million tons per year in about three years.
    • The AI satellite, called AI1, is actually simpler than a Starlink satellite because it lacks the complex phased array and parabolic antennas.
    • AI1 targets 150 kW peak power and 120 kW sustained power, roughly matching an Nvidia GB300 rack of 72 GPUs.
    • Design assumptions are about 250 watts per square meter for the solar array and about 1,400 watts per square meter for the double sided radiators, both expected to improve over time.
    • Radiators are oriented knife edge to the sun and radiate from both sides; each satellite has roughly a 70 meter wingspan.
    • Each satellite carries on the order of a terabit of laser link connectivity.
    • Satellites connect to each other or to the Starlink constellation by laser, and Starlink relays data to the ground over existing Ka and Ku antennas plus laser to ground links.
    • At 600 to 800 km altitude latency is only around 3 milliseconds, since light travels about 300 km per millisecond.
    • SpaceX has about 10,000 Starlinks in orbit and is the only operator with experience flying constellations at that scale.
    • The constellation could eventually grow to thousands or even up to a million satellites; space is big enough to pack and fly them safely.
    • The satellites and solar will be built in Bastrop, Texas, where a solar manufacturing facility is already under construction.
    • The AI satellite production building and solar production are expected to be operating at reasonable volume by the end of next year.
    • SpaceX keeps making Starlink user terminals in Bastrop and is turning on new, higher volume production lines, with possibly a few hundred million terminals eventually, plus a direct to cell constellation that connects straight to phones.
    • Initial chips are off the shelf: the reference design targets Nvidia GB300 or Rubin chips, with a TPU reference design as well, and essentially any existing chip can be put into orbit.
    • The chip industry looks set to reach maybe 100 gigawatts a year of AI compute, far short of the terawatt SpaceX wants.
    • To close that gap, SpaceX plans a “Terafab,” a chip factory around 100 million square feet, roughly 10 times the size of Tesla Gigafactory Texas.
    • A terawatt of chip output per year is like a billion full reticle equivalent chips, each running about a kilowatt, plus a lot of memory.
    • The timeline targets an annualized rate of a gigawatt per year of space compute by the end of next year, scaling roughly 10x per year: 10 GW in about 2.5 years, 100 GW in about 3.5 years, then a terawatt per year, which is 1,000 GW and about twice current US electricity consumption.
    • Beyond a terawatt, the only path to another 1,000x is the moon, using local production of photovoltaics, solar, and radiators so most mass does not have to be shipped from Earth.
    • A lunar mass driver (a linear electric motor or rail gun) could accelerate AI satellites into deep space without rockets, thanks to the moon’s lack of atmosphere and one sixth gravity.
    • Bringing that much mass to the moon would also make it possible for anyone who wants to go to the moon to go, and even live there.
    • Musk stresses none of this requires magic; the AI satellite reuses Starlink V3 solar technology, and he frames the timelines as a best guess rather than a promise.
    • SpaceX has acquired xAI, now referred to as SpaceX AI, folding its AI ambitions directly into the space company.

    Detailed Summary

    The Kardashev Scale and Why Earth Barely Registers

    Musk opens with the question of how you objectively measure a civilization’s progress, the metric an alien species would use to calibrate us. The answer he reaches for is the Kardashev scale, named for the Russian physicist who proposed it, which ranks civilizations by the power they harness: a planet’s worth (Type 1), a star’s worth (Type 2), or a galaxy’s worth (Type 3). Humanity is extremely low even on Type 1. To dramatize the scale of the sun, he notes it is about 99.86% of all the mass in the solar system, with most of the rest being Jupiter and Earth a tiny dust mote in the miscellaneous category. The incident solar energy hitting Earth’s cross section is only about a half billionth of the sun’s total output, and we capture a vanishingly small slice of even that.

    Why Energy at Scale Means Going to Space

    Because roughly 70% of Earth is water and much of the remaining land sits at the poles or in far northern regions where solar is weak and few people live, the usable area for ground solar is small. To reach any meaningful percentage of the sun’s energy, you have to go to space. Musk sets the aspiration at a millionth of the sun’s output as a first “micro” milestone, noting that even 1% would make a civilization vastly more powerful than today’s. Orbit also solves two practical problems at once: you avoid building enormous terrestrial power plants, and cooling becomes easier because waste heat can be radiated straight into the vacuum rather than fought against in an atmosphere.

    The Three Limiting Factors

    Scaling to space based compute comes down to three things: a large mass to orbit capability, a lot of solar power and radiators, and a lot of AI chips. To put a hundred gigawatts and ultimately a terawatt into space, you need a terawatt of solar generation, the radiators to reject the heat, and a terawatt of AI chips. The rest of the conversation works through each limiting factor in turn, starting with the one SpaceX has spent two decades on.

    Starship and the Reusability Breakthrough

    Starship supplies the mass to orbit. Musk argues that full and rapid reusability is the fundamental breakthrough required for both multiplanetary life and climbing the Kardashev scale, since expendable rockets are simply too expensive and you cannot build enough of them. Every other mode of transport, from cars to planes to bicycles, is reusable; rockets are uniquely hard because Earth has a deep gravity well and thick atmosphere, which is why many prior reusable rocket attempts were abandoned. SpaceX pushes mass optimization to the extreme, even catching the booster with the launch tower instead of carrying heavy landing legs. The goal beyond catching the rocket is reflying it with no refurbishment, like an aircraft. Starship V3 already more than doubles the Saturn V’s thrust, V4 will be roughly triple, and the vehicle is the largest and most powerful moving object ever made, targeted to fly more than once per hour. SpaceX already lifts an estimated 85 to 90% of all Earth mass to orbit, and plans to scale from about 2,500 tons per year to millions of tons per year, reaching a million tons per year in roughly three years.

    Inside the AI Satellite (AI1)

    The team explains that a data center in space is not a building with engines bolted on; it reduces to chips plus the power and cooling to run them. The AI satellite, dubbed AI1, is actually simpler than a Starlink satellite because it skips the complex phased array and parabolic antennas, leaving mostly solar cells, a radiator, and some laser links. The draft version targets 150 kW peak power and 120 kW sustained, matching roughly what an Nvidia GB300 rack of 72 GPUs draws. Design assumptions are about 250 watts per square meter of solar array and about 1,400 watts per square meter for double sided radiators oriented knife edge to the sun, both numbers expected to improve. The result is a craft with around a 70 meter wingspan and roughly a terabit of laser connectivity. Compute racks link to each other or to the Starlink constellation by laser, and data reaches the ground via existing Ka and Ku antennas or laser to ground links. From 600 to 800 km up, latency is only about 3 milliseconds, since light travels 300 km per millisecond, so the common worry about high latency does not apply.

    Operating a Constellation of a Million Satellites

    The satellites are large, but space is enormous, so even thousands or up to a million of them would not crowd orbit; viewed against the Earth they are nearly invisible. SpaceX leans on hard won operational experience, with about 10,000 Starlinks already flying and a unique track record of operating constellations at that scale safely. Knowing how tightly satellites can be packed and flown without collisions is treated as the number one constraint when designing the constellation.

    Manufacturing in Bastrop, Texas

    The satellites and solar will be built in Bastrop, Texas, in a facility the hosts describe as already massive and about to be dwarfed by what comes next. A solar manufacturing facility is already under construction, and the AI satellite production building will follow, with both expected to operate at reasonable volume by the end of next year. The same site keeps producing Starlink user terminals and is spinning up new, higher volume lines. Musk projects there could eventually be a few hundred million Starlink terminals, alongside a direct to cell constellation that connects straight from a phone to space for high bandwidth communication.

    Chips, the Terafab, and the Road to a Terawatt

    In the near term, SpaceX simply launches chips that already exist. The current reference design targets Nvidia GB300 or Rubin chips, with a TPU reference design as well, and essentially any existing chip can be flown. The problem is that the chip industry as a whole may only reach about 100 gigawatts a year of AI compute, which does not answer how you get to a terawatt. The answer is a gigantic chip factory, a “Terafab” around 100 million square feet, roughly ten times the size of Tesla Gigafactory Texas, big enough that Musk jokes about needing Starship point to point to cross it. Even with no new fundamental breakthroughs, scaling existing chip technology to a terawatt of output per year is, from a logic die standpoint, like a billion full reticle equivalent chips each running a kilowatt, plus a lot of memory. The stated timeline is an annualized gigawatt per year of space compute by the end of next year, then scaling roughly an order of magnitude per year: about 10 GW in 2.5 years, 100 GW in 3.5 years, and eventually a terawatt per year, which is 1,000 GW, about twice the current electricity consumption of the United States. Musk repeatedly flags these as best guesses, not promises.

    The Moon, a Mass Driver, and the Next 1,000x

    Asked why stop at a terawatt, Musk says a terawatt is actually very small. Getting another three orders of magnitude, a 1,000x jump, points to the moon. The plan is local lunar production of photovoltaics, solar, and radiators, so that most of the mass does not have to be transported from Earth, with chips either shipped up or eventually made on the moon. Because the moon has no atmosphere and only one sixth of Earth’s gravity, you can accelerate AI satellites into deep space without a rocket, using an electromagnetic mass driver, essentially a rail gun or linear electric motor. A side benefit of moving that much mass to the moon is that anyone who wants to go to the moon would be able to, and could even live there. The team closes on the excitement of building a whole new kind of satellite and the sci fi prospect of a mass driver on the moon.

    Notable Quotes

    “We currently use much less than a trillionth of the power output of the sun. And a trillion is a million times a million.”

    Elon Musk, on how far humanity sits from harnessing the sun’s energy

    “The sun is about 99.86% of all mass in the solar system.”

    Elon Musk, dramatizing the scale of the star we orbit

    “You’re an extremely kick-ass civilization if you get to 1% of the sun’s energy.”

    Elon Musk, on what a meaningful Kardashev milestone would look like

    “Reusability is the fundamental breakthrough that is necessary to make life multiplanetary, as well as to ascend the Kardashev scale.”

    Elon Musk, on why Starship matters

    “An AI satellite is essentially a lot of solar cells, a radiator, and you still need some laser links, but you don’t have all of the super complex antennas that you have on a Starlink satellite.”

    Elon Musk, on why the orbital data center is simpler than Starlink

    “There’s not some magic that’s necessary that doesn’t exist for the AI satellites.”

    Elon Musk, on reusing existing Starlink technology

    “We expect that the Terafab is going to be around 100 million square feet, which is 10 times the size of the Tesla Gigafactory Texas.”

    Elon Musk, on the chip factory needed to reach a terawatt

    “The only way that we can really see that you can achieve that is on the moon with a mass driver.”

    Elon Musk, on scaling another 1,000x beyond a terawatt

    Watch the full conversation here: Elon Musk and the SpaceX team on AI satellites and climbing the Kardashev scale.

    Related Reading

    • Kardashev scale (Wikipedia), background on the Type 1, 2, and 3 framework that anchors the entire conversation.
    • Starship (SpaceX), the official page for the fully reusable vehicle behind the mass to orbit numbers.
    • Starlink, the constellation whose solar arrays, laser links, and operations the AI satellites are built on.
    • Mass driver (Wikipedia), the electromagnetic launch concept proposed for flinging satellites off the moon.
    • Nvidia GB300 (Nvidia), the GPU rack whose power profile defines the first AI satellite’s compute target.

  • Thomas Laffont of Coatue on the $4 Trillion AI IPO Wave: SpaceX, Anthropic, OpenAI, and Why the New Unicorn Economy Is Healthier

    Thomas Laffont, co-founder of the $55 billion hedge fund Coatue Management, made his All-In Podcast premiere with a data-dense walk through what he calls a once-in-a-generation moment for the unicorn economy. In front of Chamath Palihapitiya, Jason Calacanis, David Sacks, and David Friedberg, he argued that a roughly $4 trillion wave of private value is about to hit the public markets, led by SpaceX, Anthropic, and OpenAI, and that the new AI-driven unicorn economy is actually healthier than the one that came before it. You can watch the full presentation and Q&A on YouTube.

    TLDW

    Laffont presents Coatue’s slide deck on the state of the unicorn economy and argues it has rebalanced after the excesses of 2021. The average unicorn is up about 70 percent since September 2024, AI keeps taking a bigger share of all fundraising, and the model has shifted from many small unicorns to fewer companies each raising far more, with funding per unicorn up roughly 5x since 2021. He introduces a “Magnificent 8” private index (SpaceX, Stripe, Anthropic, Databricks, Revolut, ByteDance, Anduril, and more) worth nearly $4 trillion that has crushed the public Mag 7, then shows that exits are finally thawing as SpaceX heads to an IPO in weeks and Anthropic confidentially files its S1. He lays out Coatue’s “CODE” framework for why SpaceX gets more valuable the more it launches, a counterintuitive finding that the odds of a 10x actually rise as companies get bigger (31 percent for $100 billion-plus centicorns), the explosive revenue ramp of OpenAI and Anthropic past Workday, ServiceNow, Adobe, Salesforce, and now the hyperscalers, a three-pillar map of where AI revenue comes from (consumer, ads, enterprise), and the AI memory thesis. The Q&A with Chamath and Calacanis digs into the power law, K-shaped outcomes, whether these valuations are disconnected from reality, the public market as the great antiseptic, and what happens when trillions in private value finally recycles back through GPs and LPs.

    Thoughts

    The most useful idea in the talk is not the $4 trillion headline, it is the cohort-health chart. Laffont splits unicorns into eras and shows that the pre-2021 cohort was healthy, roughly 80 percent had raised again or exited 20 quarters after minting, while the giant 2021 ZIRP cohort of 479 companies is stuck with under 20 percent doing either. That single comparison reframes the whole AI boom. The bullish read is that the 2024 AI cohort is small, concentrated, and cash-generative, so it looks more like the healthy pre-ZIRP group than the 2021 hangover. The bearish read is that we are watching the same movie with bigger numbers, and the test only comes when these companies face public markets. Laffont is honest that we do not yet know which cohort the AI class resembles, and that intellectual humility is what makes the deck credible rather than promotional.

    The SpaceX “CODE” framework is the sharpest analytical move of the presentation. Most people would assume a launch business gets cheaper per launch as it scales. Laffont shows the opposite, the market pays more per launch as cadence rises, and explains it as a phase change in business quality: from one-time government launch revenue, to a single recurring-revenue constellation, to multiple constellations, to a platform with optional upside in space data centers, the moon, and Mars. It is a clean way to think about any company that climbs from a project business to a platform business, and it applies far beyond rockets. The lesson for investors is that valuation can rationally expand even as unit economics look like they should compress, because the nature of the revenue underneath is changing.

    The counterintuitive 10x odds finding deserves more attention than it got in the room. Conventional wisdom says the bigger you are, the harder it is to grow, so a $100 billion company should be less likely to 10x than a $10 billion one. Coatue’s data says the reverse: centicorns have a 31 percent shot at a 10x, far higher than the 8 percent a unicorn has at becoming a decacorn. Laffont’s explanation is a filtering mechanism, every step up validates a compounding advantage and durability of earnings, so survivors are increasingly the kind of business that keeps compounding. This is essentially a quantitative restatement of quality investing, and it is the intellectual backbone of the LP strategy the besties tease out, just buy whoever reaches $100 billion and hold.

    Where the argument gets genuinely contested is valuation, and the panel does not let it slide. The pushback that “these are not fake companies” is true and important, OpenAI and Anthropic are growing faster than any software company in history, and Anthropic reportedly had a profitable month. But growth and reality do not settle the question of price when you are paying 50 to 100 times revenue for trillion-dollar private companies, as Bill Ackman pointed out earlier in the day. Laffont’s answer is the most grounded thing he says all session: the public market is the great antiseptic, it will not care about anyone’s slide deck, and he wants to see these names withstand short sellers and skeptics. That is the right posture. The deck is a thesis, not a verdict, and the verdict arrives roughly six months and one day after the IPOs, once passive flows and supply have washed through.

    The closing thread, that almost every sector is being transformed at once and we still do not have superintelligence, is the part worth sitting with. The risk in a presentation this bullish is treating the trend as destiny. The value is in the framing tools Laffont hands you, cohort health, phase-change business quality, the filtering odds, the three revenue pillars, and the antiseptic of public scrutiny. Use those to interrogate each name rather than to buy the index on faith, and the talk earns its premiere billing.

    Key Takeaways

    • Coatue Management is one of the most successful hedge funds of the last two decades with about $55 billion under management, and is raising roughly another billion dollars specifically to invest in AI.
    • The unicorn economy is up about 70 percent on average since September 2024, and the public market has made a similar move up over the same period.
    • The unicorn economy’s share of the NASDAQ rose significantly after 2015 but has plateaued in recent years, reflecting strong performance from public companies.
    • AI keeps increasing its wallet share of all venture fundraising, multiple years in a row now.
    • The composition of funding has changed. The unicorn “factory” peaked in the ZIRP era of 2021 and has normalized at a much lower level since.
    • Funding per unicorn has increased roughly 5x since 2021. There are fewer unicorns, and each one is raising more.
    • Cohort health, pre-ZIRP group: of about 73 unicorns, 20 quarters after minting roughly 80 percent had either raised a new round or exited, which is healthy.
    • Cohort health, 2021 group: of about 479 unicorns, 20 quarters in, fewer than 20 percent had exited or raised again. Far larger cohort, far worse outcomes.
    • The open question is which cohort the new 2024 AI cohort will resemble.
    • Funding is concentrating: the top 10 companies capture a large share, and it is a small number of AI companies, not all of them, with Anthropic and OpenAI raising massive rounds.
    • Laffont proposes a “Magnificent 8” private index: SpaceX, Stripe, Anthropic, Databricks, Revolut, ByteDance, Anduril, and more, spanning internet, AI, fintech, and space tech.
    • That private index represents almost $4 trillion of value and has crushed the traditional public Mag 7, with almost every name outperforming.
    • Exits are thawing. 2026 is on a good trend for cash returned versus consumed, not quite 2021 levels, with half a year still to go.
    • That trend does not yet include three imminent liquidity events: SpaceX (IPO expected in weeks) and Anthropic (confidentially filed its S1), whose combined value could exceed the prior decade of exits combined.
    • The ecosystem is far more balanced than when Laffont first presented at the 2024 All-In Summit, when it was consuming much more cash than it returned.
    • OpenAI and Anthropic revenue growth is unlike anything previously seen. Starting from January 2025, they passed Workday, then ServiceNow, then Adobe, then Salesforce, and are now bigger than Google Cloud and Azure.
    • On current forecasts, that revenue could pass AWS by the end of the year and exceed all of Microsoft by 2028.
    • Hyperscalers are not sitting still. The largest companies in the world are funding the disruption, investing unprecedented sums to enable the ChatGPT moment.
    • The SpaceX “CODE” framework: the number one driver correlated to SpaceX’s valuation is cadence of launches, and valuation per launch rises as launches increase.
    • Why per-launch value rises: business quality improves through phases, pre-constellation (one-time government revenue), initial ramp (one recurring-revenue constellation), scale (multiple constellations), and platform (space data centers, moon and Mars optionality).
    • Anthropic in particular is scaling like no company seen across the PC, internet, or mobile eras.
    • Counterintuitive 10x odds: a unicorn has about an 8 percent chance of becoming a decacorn, a decacorn has 8 to 13 percent odds of reaching $100 billion, but a centicorn ($100 billion-plus) has a 31 percent chance of a 10x.
    • Value creation has accelerated. It typically takes years to go from $500 billion to $1 trillion in market cap, yet recently three companies did it in one year and two did it in a matter of weeks.
    • Cerebras is the counterexample of slow success: years of dark periods and no new capital developing its technology, then a massive OpenAI contract that quintupled the company’s value ahead of its IPO.
    • Semiconductors are on a generational run, with the sector dramatically outperforming the index since the 2024 All-In Summit.
    • AI memory thesis: the more an AI system knows about you, the more useful it is, so memory per user could quintuple, which helps explain recent moves in memory companies.
    • Where the revenue is: the AI ecosystem is roughly $140 billion today, about $300 billion this year, and is expected to double in 2027.
    • Three revenue pillars: consumer (subscribers times ARPU), ads (about a quarter of Meta and Google ads are AI-enabled today, heading toward 100 percent and roughly $150 billion), and enterprise (tools like Claude Code and Codex inside businesses).
    • Disruption is hitting every sector: software, telco (Starlink-powered global phone calls), semis, energy (data centers reshaping Pennsylvania’s grid), auto (Ferrari’s electric and autonomous stumble), and consumer (GLP-1s reshaping food, alcohol, and wellness).
    • Final takeaways: the new unicorn economy is healthier thanks to AI, winners are compounding faster so the cost of not owning a winner is higher than ever, disruption is everywhere, and we do not even have superintelligence yet.
    • In the Q&A, both Anthropic and OpenAI publicly say they want to be public, and big outcomes now look likely to become liquid within roughly a 12-month window.
    • The valuation pushback: these are not fake companies, they generate substantial revenue at scale and grow faster than anything before, and Anthropic reportedly even had a profitable month.
    • The public market is framed as the great equalizer and antiseptic, but with passive buying the true price discovery may not land on day one, more like six months and a day after listing.
    • A floated LP strategy: wait for whoever reaches $100 billion and concentrate capital there as the least brittle, quickest-return bet, tempered by the warning that valuations are disconnecting from any historical metric (50x to 100x revenue).
    • An open risk: with so much capital, OpenAI and Anthropic could rationally start a price war, the way ride-sharing and food-delivery players once did, though heavy infrastructure spend complicates it.

    Detailed Summary

    The unicorn economy has rebalanced after 2021

    Laffont opens by reframing a market many assume is frothy. The average unicorn is up about 70 percent since September 2024, and the public market has tracked a similar climb, so private and public value are moving together rather than diverging. The unicorn economy’s share of the NASDAQ rose sharply after 2015 and then plateaued, which he reads as a sign of how strong public companies have become. Underneath the headline, the structure of funding has changed. The 2021 ZIRP era was a unicorn factory that minted enormous numbers of companies, and that machine has since normalized to a much lower level. The result is a barbell: fewer new unicorns, but each raising far more, with funding per unicorn up roughly 5x since 2021. AI sits at the center of this, taking a steadily larger share of all venture dollars for several years running.

    Cohort health is the real story

    The deck’s most important slide measures the health of the ecosystem by cohort. The pre-ZIRP cohort, about 73 unicorns, looks healthy: 20 quarters after becoming unicorns, roughly 80 percent had either raised a new round or exited. The 2021 cohort tells the opposite story. It is enormous, about 479 unicorns, and 20 quarters in, fewer than 20 percent had raised again or exited. That contrast sets up the central question of the talk. A new 2024 cohort of AI companies is forming, and no one yet knows whether it will resemble the healthy pre-ZIRP group or the bloated, stuck 2021 group. Laffont’s framing leans optimistic because the AI cohort is small and concentrated, but he is careful not to declare the answer.

    The Magnificent 8 and a $4 trillion private index

    Funding is not just flowing to AI, it is flowing to a handful of AI names, with the top 10 capturing a large share and Anthropic and OpenAI raising the biggest rounds. From this concentration Laffont builds a private index he half-jokingly calls the Magnificent 8, a number he expects to shrink as companies go public. The members span sectors: SpaceX, Stripe, Anthropic, Databricks, Revolut, ByteDance, and Anduril, covering internet, AI, fintech, and space tech. He says he would be comfortable owning that index for the next decade-plus. Collectively it represents almost $4 trillion of value and has outperformed the public Mag 7, with nearly every constituent beating that benchmark.

    Exits are thawing and a wall of liquidity is coming

    One of Laffont’s recurring concerns at past summits has been balance: the unicorn economy is great at consuming cash, but a healthy ecosystem must also return it. On that score 2026 is trending well, not quite 2021, but solid with half a year left. Crucially, that figure does not yet include three imminent events. SpaceX is expected to go public within weeks, and Anthropic confidentially filed its S1 the day of the talk. Adding those up, just a few companies could deliver more liquidity than the prior ten years combined. The takeaway is that the ecosystem that was dangerously out of balance in 2024 is now meaningfully more balanced, and improving.

    The revenue ramp past the hyperscalers

    The growth rates of OpenAI and Anthropic, Laffont argues, are unlike anything previously seen. Charting from January 2025, the leading AI labs passed Workday, then ServiceNow, then Adobe by year end, then Salesforce by January, and are now bigger than Google Cloud and Azure. On forecast, that revenue could surpass AWS by the end of the year and exceed all of Microsoft by 2028. He stresses that the hyperscalers are not passive bystanders, they are actively funding the disruption, pouring unprecedented capital into enabling the change that began with the ChatGPT moment.

    The SpaceX CODE framework

    Laffont devotes real time to how Coatue thinks about SpaceX. The single factor most correlated with SpaceX’s valuation is cadence of launches, which is intuitive for a launch business. The surprise is that valuation per launch has risen rather than fallen as cadence climbed. His explanation, the CODE framework, is that the quality of the business model improves the more SpaceX launches. In phase one, pre-constellation, you are simply proving rockets, with a few government customers and lumpy, unpredictable one-time revenue. In the initial ramp you stand up a constellation, which is an end market and a recurring-revenue business that grows with every satellite and subscriber. At scale you operate multiple constellations, and Laffont expects companies, governments, and militaries to want to own their own. Ultimately it becomes a platform, with new businesses layered on top, from space data centers to the optionality of the moon and Mars.

    Counterintuitive odds and the speed of value creation

    Coatue bucketed companies and asked the odds of a 10x within each. A unicorn has roughly an 8 percent chance of becoming a decacorn. A decacorn has 8 to 13 percent odds of reaching $100 billion. But a centicorn, $100 billion or more, has a 31 percent chance of a 10x, counting both public and private companies. The bigger you are, the better your odds, which inverts intuition. Laffont pairs this with the sheer speed of recent value creation. Going from $500 billion to $1 trillion in market cap normally takes years, yet three companies did it in a single year and two did it in a matter of weeks. He also offers Cerebras as the patient counterexample, a chip company that endured years of dark periods and no new capital before a massive OpenAI contract quintupled its value ahead of IPO, part of a broader generational run for semiconductors.

    AI memory and where the revenue actually comes from

    A throughline from the day’s other speakers is that the more an AI knows about you, the more useful it is, from your restaurant preferences to your work context. Laffont turns that into a thesis: memory per user could quintuple based on what these systems require, which helps explain recent moves in memory companies. He then tackles the most contested question, where is the revenue. He sizes the AI ecosystem at about $140 billion today, roughly $300 billion this year, and doubling in 2027, built on three pillars. Consumer is subscribers times ARPU. Ads are the pillar people forget, with about a quarter of Meta and Google ads already AI-enabled and penetration heading toward 100 percent, a roughly $150 billion opportunity. Enterprise is the breakthrough category, exemplified by tools like Claude Code and Codex operating inside businesses.

    Every sector is being transformed at once

    What makes this era different, Laffont says, is that nearly every sector is being transformed simultaneously. Software is obvious, but look at telco, where he believes Starlink will soon power a device that lets you make a phone call anywhere on earth, attacking the global telco and broadband profit pool with a better product. Compute is driving massive change in semis, data centers are reshaping the energy equation in places like Pennsylvania, and the auto business is being upended, as Ferrari’s stumble introducing electric and autonomous technology showed. In consumer, GLP-1 drugs are profoundly changing consumption of food and alcohol and the broader focus on wellness. His takeaways close the loop: the new unicorn economy is healthier thanks to AI, winners are compounding faster so the cost of missing them is higher than ever, disruption is everywhere, and superintelligence has not even arrived yet.

    The Q&A: power law, valuation, and the public market test

    Chamath and Jason Calacanis press Laffont on what this means for allocators. The recurring theme is the power law and K-shaped outcomes, with gains consolidating into a small number of companies. The positive side, Laffont notes, is that outcomes are enormous and increasingly liquid within a 12-month window, and both Anthropic and OpenAI say they want to be public. The hard part is valuation. The besties cite Bill Ackman’s framing that investors are making venture bets on trillion-dollar companies at 50 to 100 times revenue. Laffont’s pushback is that these are not fake companies, they generate substantial revenue at scale and grow faster than anything before, and Anthropic reportedly had a profitable month. But he embraces the discipline ahead: the public market is the great antiseptic and will not care about anyone’s presentation, though with heavy passive buying, true price discovery may take roughly six months and a day rather than landing on day one. Asked whether the compounding is a market inefficiency or survivor bias, he declines to over-read a small sample, noting that Anthropic before Claude Code was a completely different company than after. The conversation closes on what happens when trillions recycle from GPs to LPs, the case for simply owning whoever crosses $100 billion, the risk of everyone crowding into three names, and the possibility of an eventual OpenAI versus Anthropic price war.

    Notable Quotes

    “So we have fewer unicorns that are each raising more.”

    Thomas Laffont, summarizing how funding per unicorn has risen roughly 5x since 2021

    “The reason is that the quality of SpaceX’s business model increases the more you launch.”

    Thomas Laffont, explaining the CODE framework and why valuation per launch rises with cadence

    “The winners are compounding faster than ever, which means the costs of not being in a winner are higher than ever.”

    Thomas Laffont, on the central risk of a power-law market

    “And by the way, we don’t even have super intelligence yet.”

    Thomas Laffont, closing his takeaways on how early the transformation still is

    “These are companies generating substantial revenue at scale that are growing faster than anything we’ve ever seen.”

    Thomas Laffont, pushing back on the idea that AI valuations rest on fake companies

    “It will be the great antiseptic. It will not care about my presentation.”

    Thomas Laffont, on the public market as the ultimate test for SpaceX, OpenAI, and Anthropic

    “Anthropic pre-cloud code was a completely different company than post cloud code.”

    Thomas Laffont, on why he won’t over-read a small sample of hyper-compounders

    “The power law rules our lives. All the great gains are being consolidated into small numbers of companies.”

    An All-In host, framing the Q&A on concentration in private markets

    This is a curated set of highlights. To hear the full presentation, the slide walkthrough, and the complete Q&A with Chamath and Jason Calacanis, watch the full conversation here.

    Related Reading

    • Coatue Management. Primary source for Thomas Laffont’s firm and the technology investing strategy behind the deck.
    • The All-In Podcast. The show and summit where Laffont made this premiere presentation.
    • Power law (Wikipedia). Background on the distribution Laffont and the hosts say governs venture and public-market returns.
    • The Magnificent Seven (Wikipedia). The public-market benchmark Laffont’s private “Magnificent 8” index is measured against.
    • Cerebras Systems. The AI chipmaker Laffont cites as the slow-grind IPO that was eventually transformed by a major OpenAI contract.

  • Bill Ackman on Investment Strategy, What the Market Is Missing, and How AI Breaks Businesses

    Bill Ackman, founder and CEO of Pershing Square, joined the All-In Podcast for a conversation about how his investment approach has shifted toward permanent, long-term ownership, why he believes the highest-quality companies are being left behind by a market chasing the new new thing, and how AI is raising the risk of disruption for almost every business. He also lays out his plan to turn Howard Hughes into a Berkshire Hathaway-style compounding machine built on insurance. You can watch the full conversation here. Below is a structured breakdown of the ideas, the stories, and the frameworks he uses to underwrite a business.

    TLDW

    Ackman explains how his philosophy evolved from a smaller, more liquid activist toward concentrated, permanent ownership of durable, non-disruptible businesses, with much of his activism now playing out on X rather than in the boardroom. He tells the origin story of his first big trade, Wendy’s and the Tim Hortons spin-off, and explains why a large long-term shareholder on a board is an antidote to short-term markets. On AI, he argues that this is the greatest era in history to build a company, which means the risk of being disrupted has gone up enormously, and that the market is mispricing high-quality compounders like Microsoft, Meta, and Amazon while crowding into chips, semiconductors, and energy. He works through the SaaS question and why niche software is more at risk than platforms, how he underwrites SpaceX, xAI, OpenAI, Anthropic, and Palantir like late-stage venture bets using a people, opportunity, context, deal framework, and why founder-led companies have an edge in making radical calls. The back half covers his Howard Hughes plan to copy Buffett’s insurance-float model, the role of cost of capital and reflexivity in markets, the meme-stock era, going direct on social media, and the three different ways an investor can put money to work with Pershing Square.

    Thoughts

    The most useful idea in the interview is the way Ackman reframes disruption as the central investing problem of the AI era. His point is that the same forces making this the best time in history to start a company, meaning near-unlimited compute, capital, and talent, also raise the odds that any given incumbent gets disrupted. That reframes the word quality. It is no longer mostly about margins and moats. It becomes about non-disruptibility, which is a much higher bar than most quality investors were using a decade ago, and it is why he says most of his research time now goes into assessing that single risk.

    The what-the-market-is-missing thesis is classic contrarian Ackman. Arguing that Microsoft, Meta, and Amazon are the new old-fashioned, undervalued names while capital piles into semiconductors and energy is a direct echo of 2000, when Berkshire Hathaway bottomed precisely because money was chasing internet stocks. It is worth keeping in mind that he owns all three, so the call is also his book. The durable signal here is the framework, not the specific tickers: capital reliably chases the new new thing, and genuinely high-quality businesses get left behind during those rotations.

    The Howard Hughes plan is the most concrete bet in the conversation. Copying Buffett’s insurance-float playbook, short-term treasuries for policyholder money and equities for the surplus, onto a discounted real-estate holding company is elegant. The hard part is exactly what Ackman flags about insurance as an industry: the best investors go to hedge funds, not insurers, so most insurance companies only ever manage the liability side well. Pershing Square’s edge is that Ackman can both write the business and invest the float, which is the same reason it worked for Buffett. The framing of going from a four billion dollar company to a trillion over fifty years is a statement of intent, not a forecast, and should be read that way.

    Underneath all of it sits cost of capital and reflexivity. His observation that a higher stock price literally makes a company more valuable, because it lowers the cost of capital and creates acquisition currency, is the mechanism behind both Elon Musk’s empire and the meme-stock era he is wary of. Going direct on X is the same lever pointed at himself: communicate the vision, lower your own cost of capital, and make the bet easier for other people to place. It is a coherent worldview in which narrative and balance sheet continuously feed each other, and it explains a lot of his behavior over the last few years.

    Key Takeaways

    • The biggest change in Ackman’s approach over time is an appreciation for business quality, meaning long-term, durable, protected, non-disruptible growth as the most important factor.
    • He says he is as activist as ever, but more of it now happens on X than in the traditional corporate context.
    • His first big investment was Wendy’s, which owned Tim Hortons. The simple thesis was to buy Wendy’s, spin off Tim Hortons, and double the money.
    • Early on no one returned his calls, so he had Steve Schwarzman’s Blackstone write a fairness opinion, filed it publicly, and the company spun off Tim Hortons six weeks later. The CEO later thanked him after being fired with a large exit package.
    • Reputation compounds. Where Pershing Square once had to bang down the door, companies now sometimes tweet a welcome when it buys a stake.
    • A large long-term shareholder on a board is a counterweight to short-term markets, letting management test ideas privately and pursue initiatives that hurt the next few quarters of earnings.
    • Pershing Square owns Microsoft, Meta, and Amazon. Ackman argues you are either invested in AI directly or indirectly, or it is a threat, so you have to understand it.
    • The hardest and most important job for a concentrated investor is judging the risk of disruption, and that risk has risen dramatically.
    • This is the greatest era in history to build a business because of near-unlimited access to compute, capital, and talent, which is exactly why the probability of being disrupted has gone up enormously.
    • Markets bring their eye to the new new thing, currently chips, semiconductors, and energy, while high-quality companies get left behind.
    • He draws an analogy to 2000, when Berkshire Hathaway traded at one of its lowest valuations because everyone chased internet stocks. He sees a similar dynamic around Amazon, Meta, and Microsoft today.
    • On the SaaS question, he worries more about a Salesforce than a platform like Microsoft, because niche software charging high per-seat or per-year prices is most exposed, while low-priced platforms are safer.
    • Any software company today has to be as AI-enabled as possible, or risk losing the monopolistic pricing it once enjoyed.
    • His famous March 2020 CNBC appearance was an attempt to reach President Trump and argue for a short shutdown, paired with the view that stocks were incredibly cheap and worth buying.
    • He describes valuation as a tether on the market: when prices stretch too high they snap back, and when they get too cheap the same rubber band pulls valuations up. Calling that out publicly can trigger a psychological reset.
    • His recent bullish call came because stocks of really high-quality companies had gotten crazy cheap on fundamentals, meaning the present value of the cash they generate.
    • He underwrites high-multiple names like SpaceX as venture investments using a framework from business school: people, opportunity, context, deal.
    • On SpaceX, people and opportunity are one of one, the context is incredible, and Starlink plus near-monopoly low-cost launch make it strategically valuable. The complicated part is the deal, meaning the valuation. He invested via an SPV after Ron Baron’s nudge, and also invested in xAI.
    • He treats OpenAI, Anthropic, and Palantir as late-stage venture bets that have proven they can generate real revenue, and says OpenAI should do a better job communicating how it thinks about its enormous capital commitments.
    • Every CEO in America is asking how to use AI, how it applies to their business, and how it is a threat. It is top of mind and boards open every meeting with it.
    • He has not seen much enterprise AI success yet, citing a McKinsey study that 95 percent of enterprise initiatives fail and the rise of the forward deployed engineer as the hot role bridging promise and ROI. Pershing Square itself uses AI mainly for legal, compliance, and back-office work.
    • Founder-led companies have an advantage because founders have the authority and the economic stake to make radical calls, while the average S&P 500 CEO has a roughly three to four year tenure and is incentivized not to make mistakes.
    • He cites Mark Zuckerberg buying Instagram and WhatsApp as the kind of shocking-at-the-time calls that a founder with a track record can make.
    • Ben Graham’s enduring lesson is that a stock is an interest in a business, not a piece of paper, but Graham mostly invested in liquidations and cash-rich shells, and made most of his money on Geico.
    • Most of Buffett’s value at Berkshire came from owning insurance operations and focusing on the asset side of the balance sheet, not just the liability side.
    • Insurance is hard to copy because top investors do not go to work for insurers. Buffett owned half his company and was a great investor, which is why it worked.
    • Howard Hughes came out of the General Growth bankruptcy and owns master-planned cities like Summerlin, with 26,000 acres in the Las Vegas area, comparable to the Irvine Company that built roughly a hundred billion dollars of wealth for Donald Bren.
    • The plan is to reinvest the cash Howard Hughes generates into insurance, put policyholder float in short-term treasuries and the surplus in common stocks, and build a compounding machine over fifty years, buying it at roughly sixty cents on the dollar.
    • A company must earn a return above its cost of capital for the stock to rise. Elon Musk has kept his companies’ cost of capital extremely low, and a SpaceX IPO near a 1.75 trillion dollar valuation could be one of the lowest cost of equity capital transactions ever.
    • Markets have changed less because of Ackman and more because of figures like Ryan Cohen and GameStop, where a stock can trade well above its value on personality and an army of followers.
    • Higher valuations are reflexive: a rising stock price lowers cost of capital and creates currency to issue stock and acquire businesses, which is part of how Elon built Tesla.
    • There are three ways to invest with Pershing Square: the management company itself (a royalty on compounding assets with no capex), PSUS (a portfolio of best ideas trading at an 18 percent discount), and Howard Hughes (a bet on building the next Berkshire). A dollar invested 22 years ago became roughly 27 to 28 times net of fees.
    • Going direct on X, with 2.2 million followers, lets him communicate his vision and lower the friction for others to back his bets, even as his very long tweets have become a running meme.

    Detailed Summary

    From activist trades to permanent capital

    Ackman frames the evolution of his career as a steady move toward business quality. As a smaller, more liquid investor early on, he did not have to think as long-term. As Pershing Square became a bigger, more concentrated investor, durable growth became the dominant factor in every decision. He insists he is still as activist as ever, but a lot of that energy has shifted to X, where he can argue a position publicly rather than only inside a boardroom. The best investments, he notes, are the ones where you do not need to join the board and do anything at all.

    The Wendy’s and Tim Hortons origin story

    One of Pershing Square’s first investments was Wendy’s, which owned the Canadian coffee and donut chain Tim Hortons. The value of Tim Hortons alone was greater than the entire value of Wendy’s, so the idea was simple: buy Wendy’s, spin off Tim Hortons, and double the money. Ackman bought ten percent of the company and could not get the CEO to return a single call, so he had a contact at Blackstone, with Steve Schwarzman’s sign-off, write a fairness opinion on what Wendy’s would be worth after a spin-off, filed it publicly, and watched the spin-off happen six weeks later. The CEO eventually called back to thank him, having been fired but rewarded with a large exit package. Over the years that scrappy approach gave way to a reputation that now opens doors on its own.

    Why a long-term shareholder on the board matters

    The core problem of being a public company, in Ackman’s telling, is the short-term nature of markets and analysts, when a good business should be run in the context of years and even decades. A large, supportive shareholder on the board gives management a place to test ideas before exposing them to the public and a credible voice willing to back initiatives that hurt earnings for a few quarters. That is the value-add he believes a constructive activist can bring to a mature public company, as opposed to a startup where the best outcome is simply to own a great business and stay out of the way.

    AI and the rising risk of disruption

    For a concentrated, long-term investor, the most challenging task is judging the risk that two people from Stanford in a garage build something that destroys your thesis. Ackman argues that risk has climbed dramatically because this is the greatest era in history to build a company, with near-unlimited access to compute, capital, and talent. The paradox is that the conditions that make building easier also make incumbents more fragile, so the bulk of his research now centers on assessing how disruptible a business really is.

    What the market is missing

    Investors bring their attention to the new new thing, currently chips, semiconductors, and energy, which leaves high-quality companies behind. Ackman compares the moment to 2000, when Berkshire Hathaway traded at one of its lowest valuations ever because capital was chasing internet stocks. He sees an echo today in how Amazon, Meta, and Microsoft are treated as old-fashioned, and he considers them undervalued on fundamentals, where value is the present value of the cash a business generates over its life. His recent bullish call, like his March 2020 appearance, came because stocks of really high-quality companies had simply gotten too cheap.

    The SaaS question and AI-enabled software

    On the so-called SaaS apocalypse, Ackman says it is a company-by-company analysis. He worries more about something like Salesforce than about a low-priced platform. The companies most at risk are those that extracted near-monopolistic profits by charging a high annual price for a niche product, because AI lowers the barrier to replicating that functionality. A platform where the average customer pays a small amount per seat, like Microsoft, is far less exposed. The takeaway for any software company is to become as AI-enabled as it possibly can.

    Underwriting SpaceX, xAI, and the AI labs like venture

    For the highest-multiple private companies, Ackman uses a venture lens and a framework a business school professor taught him: people, opportunity, context, deal. SpaceX scores as one of one on people and opportunity, with an incredible context and a near-monopoly in low-cost launch through Starlink, which makes even Amazon a likely customer. The complicated variable is the deal, meaning the valuation, and he admits he has not done all the math, having invested through an SPV after Ron Baron encouraged him, along with a position in xAI. He treats OpenAI, Anthropic, and Palantir as late-stage venture bets that have proven real revenue, and argues OpenAI in particular should communicate more clearly how it justifies capital commitments that vastly exceed current revenue.

    Founder-led companies and the authority to act

    Ackman agrees that founder-led companies have a structural advantage in a fast-changing environment. The average S&P 500 CEO has a tenure of roughly three to four years, a small economic stake, and an incentive not to make a career-ending mistake. A founder is betting an entire life and reputation, has the authority of a major voting and economic position, and has usually made several hard, contrarian calls that turned out right. He points to Mark Zuckerberg’s acquisitions of Instagram and WhatsApp, which looked shocking at the time, as exactly the kind of decision a founder with a track record can make and a hired manager often cannot.

    Howard Hughes as Berkshire Hathaway 2.0

    Ackman points to a detailed financial history of Berkshire Hathaway showing that the vast majority of Buffett’s value creation came from owning insurance and focusing on the asset side of the balance sheet, not just the liability side. Insurance is hard to replicate because skilled investors join hedge funds rather than insurers, but Buffett owned half his company and was a great investor. Pershing Square is applying the same idea to Howard Hughes, a company created out of the General Growth bankruptcy that owns master-planned cities such as Summerlin, with 26,000 acres around Las Vegas, in the spirit of the Irvine Company that made Donald Bren roughly a hundred billion dollars. The plan is to reinvest the company’s cash into insurance, place policyholder float in short-term treasuries and the surplus in common stocks, avoid issuing stock the way Buffett did, and compound for fifty years, all bought at around sixty cents on the dollar.

    Cost of capital, reflexivity, and going direct

    A company only creates value when it earns above its cost of capital, which is why Howard Hughes, seen as a high-cost-of-capital real-estate business, has long traded at a discount, and why Ackman is repurposing its assets into a higher-returning model. He highlights how reflexive markets are: a higher stock price itself makes a company more valuable by lowering its cost of capital and creating currency to raise money and acquire businesses, a lever Elon Musk used to build Tesla. He attributes real market change less to himself and more to figures like Ryan Cohen and GameStop, where personality and a following can lift a stock far above its value. His own going-direct strategy on X, with 2.2 million followers and famously long posts, is the same mechanism applied to communicating a vision and lowering friction for investors. He closes by laying out three ways to invest with Pershing Square: the management company as a royalty on compounding assets, the PSUS portfolio trading at an 18 percent discount, and Howard Hughes as a bet on building the next Berkshire.

    Notable Quotes

    “The best investments are one where you don’t need to join the board and do anything.”

    Bill Ackman, on the kind of business he most wants to own

    “The probability of your being disrupted has gone up enormously.”

    Bill Ackman, on why assessing disruption risk now dominates his research

    “Valuation is like a tether on the market, right? When it gets too high, it’s like this rubber band that’s stretching and inevitably it bounces back.”

    Bill Ackman, on how prices revert at both extremes

    “People, opportunity, context, deal.”

    Bill Ackman, on the business school framework he uses to underwrite companies like SpaceX

    “Every CEO in America today is like, how do I use AI?”

    Bill Ackman, on AI as the top opportunity and threat in every boardroom

    “A closed mouth gathers no foot.”

    Bill Ackman, quoting the line a friend put next to his name in his high school yearbook

    “The increase in value of the company increases the value of the company, right? Because it lowers the cost of capital, it gives you more flexibility, gives you the ability to issue stock, raise capital, acquire other businesses.”

    Bill Ackman, on the reflexivity between stock price and corporate value

    “The company’s got like a $4 billion market cap and the goal is to build it into a trillion dollar thing over time compounding.”

    Bill Ackman, on his fifty-year plan for Howard Hughes

    Taken together, the conversation is a tour of how Ackman now thinks about quality, disruption, and compounding, and a preview of the Berkshire-style machine he wants to build out of Howard Hughes. Watch the full conversation here.

    Related Reading

  • Anthropic Raises $65 Billion Series H at $965 Billion Valuation to Fund AI Safety Research and Massive Compute Expansion

    Anthropic has closed one of the largest private financing rounds in the history of technology, raising $65 billion in Series H funding at a $965 billion post-money valuation. The round, announced on May 28, 2026, lands as demand for Claude reaches what the company calls historic levels, and it positions Anthropic to pour fresh capital into safety research, compute, and the products that enterprises now lean on every day.

    TLDR

    Anthropic raised $65 billion in its Series H at a $965 billion post-money valuation, with Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital leading and Capital Group, Coatue, D1 Capital Partners, GIC, ICONIQ, and XN co-leading, alongside $15 billion in previously committed hyperscaler investment that includes $5 billion from Amazon. The raise follows Anthropic crossing $47 billion in run-rate revenue earlier in May 2026, and it funds three priorities named by CFO Krishna Rao: advancing safety and interpretability research, expanding compute capacity to meet growing Claude demand, and scaling the products and partnerships customers depend on. On the infrastructure side, the company is locking in gigawatt-scale compute through 5 gigawatts with Amazon, 5 gigawatts of TPU capacity via Google and Broadcom, GPU access from SpaceX, and supply from partners Micron, Samsung, and SK hynix, while Claude remains available across all three major cloud platforms, AWS, Google Cloud, and Microsoft Azure, with widespread enterprise adoption across industries.

    Thoughts

    Start with the number that everyone will fixate on. A $965 billion post-money valuation against $47 billion in run-rate revenue is roughly 20 times sales, and for a company growing this fast that multiple is not the interesting part. The interesting part is that run-rate revenue crossed $47 billion earlier this month, which means the denominator is moving so quickly that the multiple is already stale. Investors are not pricing the business Anthropic is today. They are pricing the slope. A 20x multiple on a number that may double again inside a year is a very different bet than 20x on a flat line, and the lead names here (Altimeter, Dragoneer, Greenoaks, Sequoia, with Capital Group, Coatue, GIC and others co-leading) are not the kind of capital that pays for nostalgia. They are paying for the second derivative.

    But the real story is not the valuation. It is the compute. Read the infrastructure list carefully and you see the actual problem this round solves: 5 gigawatts from Amazon, 5 gigawatts of TPU capacity through Google and Broadcom, GPU access from SpaceX, and memory supply locked down with Micron, Samsung, and SK hynix. That is more than 10 gigawatts of secured power and silicon. The constraint on frontier AI in 2026 is no longer talent or even algorithms. It is electricity, land, and the multi-year queue for advanced packaging and high-bandwidth memory. You cannot buy 10 gigawatts on a quarterly basis. You reserve it years out, and you need the balance sheet to make those commitments credible. A $65 billion raise is, in plain terms, the down payment that lets Anthropic sign for capacity nobody can conjure on demand. The money is downstream of the megawatts.

    The diversification across that compute stack matters as much as the size. By splitting between Amazon’s infrastructure, Google and Broadcom’s custom TPUs, and SpaceX-supplied GPUs, Anthropic is refusing to become hostage to any single supplier’s roadmap or pricing. Custom silicon through Broadcom in particular is a bet on bending the cost curve, because the long-term economics of serving Claude at this scale depend on dollars per token, not just on raw availability. Anyone who has watched cloud lock-in play out over the last decade understands the move. Optionality at the hardware layer is leverage, and leverage is what keeps margins from being dictated by whoever owns the only fab slot you can reach.

    It is worth pausing on the fact that the round explicitly funds safety and interpretability research alongside scaling, and not as a footnote. Most companies treat safety spend as a cost center to be minimized once growth kicks in. Naming it first, ahead of compute and products, is a statement about where Anthropic believes its durable advantage sits. If models keep getting more capable, the binding constraint on deployment inside regulated industries (finance, healthcare, government) becomes trust, not intelligence. Interpretability is the work that turns a black box into something an enterprise risk committee can actually sign off on. Framed that way, safety research is not philanthropy subtracted from the bottom line. It is the thing that unlocks the most lucrative and defensible parts of the market, and pairing it with the scaling budget is the tell.

    Finally, look at distribution. Claude now ships on all three major clouds at once: AWS, Google Cloud, and Microsoft Azure. In a market where most frontier labs are tethered to a single hyperscaler, being available everywhere enterprises already run their workloads is a structural edge. It removes the procurement friction of asking a customer to adopt a new vendor relationship, and it means Anthropic competes on the merits of the model rather than on which cloud a buyer happened to standardize on years ago. Combine that omnipresent distribution with the compute reservations and the explicit safety mandate, and the shape of the strategy is clear. This is not a company buying time. It is a company buying the three things that actually compound: capacity that cannot be rushed, trust that cannot be faked, and reach into every place where work already happens.

    Key Takeaways

    • Anthropic raised $65 billion in its Series H funding round, one of the largest private financings in the history of the technology industry.
    • The round set Anthropic’s post-money valuation at $965 billion, placing the company within reach of the $1 trillion mark.
    • Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital led the Series H round.
    • Capital Group, Coatue, D1 Capital Partners, GIC, ICONIQ, and XN served as co-leads on the investment.
    • The new capital builds on $15 billion in previously committed hyperscaler investments, which includes $5 billion from Amazon.
    • Anthropic crossed $47 billion in run-rate revenue earlier in May 2026, reflecting the surging commercial demand for Claude.
    • A core priority for the funding is to advance Anthropic’s safety and interpretability research.
    • The company will use the capital to expand compute capacity in order to meet growing demand for Claude.
    • Anthropic plans to scale the products and partnerships that customers depend on across its business.
    • CFO Krishna Rao said the funding will help Anthropic serve the historic demand it is experiencing, stay at the research frontier, and bring Claude to more of the places where work happens.
    • Amazon is providing 5 gigawatts of compute capacity as part of Anthropic’s infrastructure expansion.
    • Google and Broadcom are supplying 5 gigawatts of TPU capacity to power Claude’s growth.
    • SpaceX is contributing GPU access to Anthropic’s compute footprint.
    • Micron, Samsung, and SK hynix are partnering with Anthropic on memory and infrastructure to support its scaling needs.
    • Claude is available on all three major cloud platforms, AWS, Google Cloud, and Microsoft Azure.
    • Anthropic reports widespread enterprise adoption of Claude across a broad range of industries.

    Detailed Summary

    The Raise and the Valuation

    Anthropic has raised $65 billion in Series H funding, a round that values the company at $965 billion on a post-money basis. The size of the raise places it among the largest private financing events the technology industry has ever seen, and the valuation pushes Anthropic to the doorstep of the trillion dollar mark. The capital arrives at a moment when demand for the company’s Claude models has accelerated sharply, and the round is built to fund the response to that demand rather than simply mark a milestone. Anthropic framed the financing in its Series H announcement as the fuel for staying at the research frontier while scaling the infrastructure and products that customers increasingly rely on.

    Who Put In the Money

    The Series H was led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital, a group that combines deep growth-stage technology experience with conviction in Anthropic’s long-term trajectory. Joining as co-leads were Capital Group, Coatue, D1 Capital Partners, GIC, ICONIQ, and XN, a roster that spans crossover funds, sovereign wealth, and institutional investors. Beyond the new equity, Anthropic pointed to $15 billion in previously committed hyperscaler investment, including $5 billion from Amazon. Taken together, the investor base reflects a mix of financial backers and strategic partners with a direct stake in seeing Claude reach more customers and more compute.

    Revenue at $47 Billion Run-Rate

    Underpinning the valuation is a business that has scaled with unusual speed. Anthropic crossed a $47 billion run-rate revenue figure earlier in May 2026, a number that signals how quickly enterprises and developers have adopted Claude across their workflows. Run-rate revenue annualizes the company’s most recent performance, and at this level it puts Anthropic firmly among the fastest growing software businesses on record. That financial momentum is the practical justification for both the round’s size and the near trillion dollar valuation investors were willing to support.

    The Compute Buildout

    A large share of the strategy behind the raise centers on securing compute at enormous scale. Anthropic detailed a set of infrastructure partnerships designed to keep pace with Claude demand. Amazon is providing 5 gigawatts of capacity, while Google and Broadcom together are supplying 5 gigawatts of TPU capacity. SpaceX is contributing GPU access, broadening the range of silicon Anthropic can draw on. Supporting the buildout on the hardware supply side are Micron, Samsung, and SK hynix, the memory and component partners whose output is essential to standing up data centers at this magnitude. The combined picture is a company assembling power, chips, and supply chain commitments measured in gigawatts rather than racks.

    Where the Money Goes

    Anthropic outlined three priorities for the new capital. The first is to advance safety and interpretability research, continuing the work of understanding how models behave and ensuring they remain reliable as they grow more capable. The second is to expand compute capacity to meet the growing demand for Claude, the practical engine behind the infrastructure commitments above. The third is to scale the products and partnerships that customers depend on, deepening the company’s reach into the tools and platforms where work actually happens. Krishna Rao, Anthropic’s chief financial officer, said the funding “will help us serve the historic demand we are experiencing, stay at the research frontier, and bring Claude to more of the places where work happens.”

    Claude Everywhere

    The funding lands on top of a distribution footprint that already spans the major cloud ecosystems. Claude is available on all three leading cloud platforms, AWS, Google Cloud, and Microsoft Azure, which means enterprises can reach the models through whichever provider they have standardized on. That availability has translated into widespread enterprise adoption across industries, from software and finance to healthcare and beyond. By being present everywhere developers and businesses already operate, Anthropic positions Claude not as a destination customers must travel to but as a capability woven into the platforms they use every day.

    Notable Quotes

    This funding will help us serve the historic demand we are experiencing, stay at the research frontier, and bring Claude to more of the places where work happens.

    Krishna Rao, CFO at Anthropic, on the purpose of the Series H round.

    Advance safety and interpretability research, expand compute capacity to meet growing Claude demand, and scale products and partnerships customers depend on.

    How Anthropic describes its use of funds from the round.

    For the full details on the round, the lead and co-lead investors, and how Anthropic plans to deploy the capital across safety research, compute, and products, read the full announcement here.

    Related Reading

    • Anthropic, the AI safety and research company behind Claude that raised this Series H round.
    • Sequoia Capital, one of the lead investors anchoring the financing.
    • Amazon Web Services, one of the three major cloud platforms where Claude is available and the source of a $5 billion investment.
    • Google Cloud TPUs, the tensor processing units behind the 5 gigawatts of TPU capacity in the Google and Broadcom partnership.
    • AI safety, the research field at the center of how Anthropic says it will use the new funding.

  • Elon’s Tech Tree Convergence: Why the Future of AI is Moving to Space

    Elon’s Tech Tree Convergence: Why the Future of AI is Moving to Space

    The latest sit-down between Elon Musk and Dwarkesh Patel is a roadmap for the next decade. Musk describes a world where the limitations of Earth—regulatory red tape, flat energy production, and labor shortages—are bypassed by moving the “tech tree” into orbit and onto the lunar surface.

    TL;DW (Too Long; Didn’t Watch)

    Elon Musk predicts that within 30–36 months, the most economical place for AI data centers will be space. Due to Earth’s stagnant power grid and the difficulty of permitting, SpaceX and xAI are pivoting toward orbital data centers powered by sun-synchronous solar, eventually scaling to the Moon to build a “multi-petawatt” compute civilization.

    Key Takeaways

    • The Power Wall: Electricity production outside of China is flat. By 2026, there won’t be enough power on Earth to turn on all the chips being manufactured.
    • Space GPUs: Solar efficiency is 5x higher in space. SpaceX aims for 10,000+ Starship launches a year to build orbital “hyper-hyperscalers.”
    • Optimus & The Economy: Once humanoid robots build factories, the global economy could grow by 100,000x.
    • The Lunar Mass Driver: Mining silicon on the Moon to launch AI satellites into deep space is the ultimate scaling play.
    • Truth-Seeking AI: Musk argues that forcing “political correctness” makes AI deceptive and dangerous.

    Detailed Summary: Scaling Beyond the Grid

    Musk identifies energy as the immediate bottleneck. While GPUs are the main cost, the inability to get “interconnect agreements” from utilities is halting progress. In space, you get 24/7 solar power without batteries. Musk predicts SpaceX will eventually launch more AI capacity annually than the cumulative total existing on Earth.

    The discussion on Optimus highlights the “S-curve” of manufacturing. Musk believes Optimus Gen 3 will be ready for million-unit annual production. These robots will initially handle “dirty/boring” tasks like ore refining, eventually closing the recursive loop where robots build the factories that build more robots.

    Thoughts: The Most Interesting Outcome

    Musk’s philosophy remains rooted in keeping civilization “interesting.” Whether or not you buy into the 30-month timeline for space-based AI, his “maniacal urgency” is shifting from cars to the literal stars. We are witnessing the birth of a verticalized, off-world intelligence monopoly.

  • Starlink 2025 Progress Report: 9 Million Users, Direct to Cell, and the Starship Future

    SpaceX has released its Starlink Progress 2025 report, detailing a massive year of growth, technological leaps, and the widespread rollout of Direct to Cell capabilities. From connecting millions of new customers to proving Starship reuse, 2025 was a pivotal year for the constellation.

    TL;DR

    • Massive Growth: Starlink now connects over 9 million active customers across all seven continents, adding 4.6 million in 2025 alone.
    • Direct to Cell is Here: The first-generation Direct to Cell network is operational with 650+ satellites, connecting 12 million people and saving lives in cellular dead zones.
    • Speed & Performance: Median global download speeds have hit 200 Mbps with latency dropping to ~26ms.
    • Next Gen Tech: V3 satellites are coming in 2026, promising 10x capacity, launched via Starship.

    Key Takeaways from 2025

    1. Explosive Network Growth

    • Customer Base: Surpassed 9 million customers globally.
    • New Markets: Activated service in 35+ new countries and territories.
    • Fleet Size: The constellation now boasts over 9,000 active satellites.
    • Manufacturing: Production ramped up to over 170,000 Starlink kits per week, with a massive expansion at the Bastrop, Texas facility.

    2. Direct to Cell Revolution

    • Operational: SpaceX completed the deployment of the first-gen Direct to Cell network (650 satellites).
    • Adoption: The service is the world’s largest 4G coverage provider, actively used by 6 million people monthly through partnerships with mobile network operators.
    • Emergency Services: The tech proved critical in 2025, enabling emergency alerts and 911 calls during wildfires in California and for stranded travelers in cellular dead zones.

    3. Aviation and Maritime Dominance

    • In-Flight: Over 1,400 commercial aircraft are now equipped, including fleets from United, Qatar Airways, and Air France.
    • At Sea: More than 150,000 vessels are connected, from container ships to major cruise lines like Royal Caribbean and Carnival.

    Detailed Summary

    Technological Leaps: V2 Mini and V3

    SpaceX isn’t sitting on its lead. In 2025, they launched over 3,000 V2 Mini Optimized satellites. These are lighter and more reliable than their predecessors, adding over 270 Tbps of capacity to the network.

    Looking ahead, the Starlink V3 satellite is targeted for launch in 2026. Designed to fly on Starship, these massive satellites will offer:

    • 10x downlink capacity (over 1 Terabit per second per satellite).
    • Lower latency due to lower orbital altitudes and advanced beamforming.
    • Direct to Cell 2.0: Utilizing newly acquired spectrum, the next generation will offer full 5G-style performance, supporting video calls and streaming directly to unmodified smartphones.

    The Starship Synergy

    2025 was also the year Starship integrated deeply into the Starlink roadmap. SpaceX successfully caught the Super Heavy booster and achieved rapid reuse. Simulator Starlink satellites were deployed on Starship flight tests, paving the way for the vehicle to become the primary launcher for the V3 constellation. Starship’s massive payload capacity is the key to deploying the next order of magnitude in bandwidth.

    Safety and Sustainability

    With over 9,000 satellites in orbit, space safety is a priority. Starlink has refined its “Duck” maneuver to minimize visual profile and drag, and improved its autonomous collision avoidance system. They continue to utilize a targeted reentry approach, ensuring satellites demise over the open ocean to minimize risk to zero.

    Thoughts

    The 2025 progress report cements Starlink not just as a satellite internet provider, but as a critical global utility. The sheer velocity of execution is staggering—doubling their customer acquisition rate and deploying a functioning Direct to Cell network in under two years is a pace legacy telcos simply cannot match.

    Two things stand out in this report:

    1. Vertical Integration is the Moat: By controlling the satellites, the launch vehicle (Starship/Falcon 9), the user terminals, and the manufacturing, SpaceX can iterate faster than anyone else. The Bastrop factory expansion proves they are treating consumer hardware with the same seriousness as aerospace hardware.
    2. Direct to Cell is a Game Changer: This isn’t just about texting from a mountain top anymore. With the spectrum acquisitions from EchoStar and the V3 satellite specs, Starlink is positioning itself to augment terrestrial 5G networks permanently. The “dead zone” is effectively extinct.

    For creators and remote workers, the promise of stable 20ms latency and gigabit speeds from space (via V3) means the “digital nomad” lifestyle is no longer confined to places with fiber. The world just got a lot smaller, and a lot more connected.

  • Elon Musk x Nikhil Kamath: Universal High Income, The Simulation, and Why Work Will Be Optional

    In a rare, long-form conversation that felt less like an interview and more like a philosophical jamming session, Zerodha co-founder Nikhil Kamath sat down with Elon Musk. The discussion, hosted for Kamath’s “People by WTF” podcast, veered away from standard stock market talk and deep into the future of humanity.

    From the physics of Starlink to the metaphysics of simulation theory, Musk offered a timeline for when human labor might become obsolete and gave pointed advice to India’s rising generation of builders. Here is the breakdown of what you need to know.

    TL;DR

    The Gist: Elon Musk predicts that within 15 to 20 years, AI and robotics will make human labor optional, leading to a “Universal High Income” rather than a basic one. He reiterated his belief that we likely live in a simulation, discussed the economic crisis facing the US, and advised Indian entrepreneurs to focus on “making more than they take” rather than chasing valuation.

    Key Takeaways

    • The End of Work: Musk predicts that in less than 20 years, work will become optional due to advancements in AI and robotics. He frames the future not as Universal Basic Income (UBI), but Universal High Income (UHI), where goods and services are abundant and accessible to all.
    • Simulation Theory: He assigns a “high probability” to the idea that we are living in a simulation. His logic: if video games have gone from Pong to photorealistic in 50 years, eventually they will become indistinguishable from reality.
    • Starlink’s Limitations: Musk clarified that physics prevents Starlink from replacing cellular towers in densely populated cities. It is designed to serve the “least served” in rural areas, making it complementary to, not a replacement for, urban 5G or fiber.
    • The Definition of Money: Musk views money simply as a “database for labor allocation.” If AI provides all labor, money as we know it becomes obsolete. In the future, energy may become the only true currency.
    • Advice to India: His message to young Indian entrepreneurs was simple: Don’t chase money directly. Chase the creation of useful products and services. “Make more than you take.”
    • Government Efficiency (DOGE): Musk claimed that simple changes, like requiring payment codes for government transactions, could save the US hundreds of billions of dollars by eliminating fraud and waste.

    Detailed Summary

    1. AI, Robots, and the “Universal High Income”

    Perhaps the most optimistic (or radical) prediction Musk made was regarding the economic future of humanity. He challenged the concept of Universal Basic Income, arguing that if AI and robotics continue on their current trajectory, the cost of goods and services will drop to near zero. This leads to a “Universal High Income” where work is a hobby, not a necessity. He pegged the timeline for this shift at roughly 15 to 20 years.

    2. The Simulation and “The Most Interesting Outcome”

    Nikhil Kamath pressed Musk on his well-known stance regarding simulation theory. Musk argued that any civilization capable of running simulations would likely run billions of them. Therefore, the odds that we are in “base reality” are incredibly low. He added a unique twist: the “Gods” of the simulation likely keep running the ones that are entertaining. This leads to his theory that the most ironic or entertaining outcome is usually the most likely one.

    3. X (Twitter) as a Collective Consciousness

    Musk described his vision for X not merely as a social media platform, but as a mechanism to create a “collective consciousness” for humanity. By aggregating thoughts, video, and text from across the globe and translating them in real-time, he believes we can better understand the nature of the universe. He contrasted this with platforms designed solely for dopamine hits, which he described as “brain rot.”

    4. The US Debt Crisis and Deflation

    Musk issued a stark warning about the US national debt, noting that interest payments now exceed the military budget. He believes the only way to solve this crisis is through the massive productivity gains AI will provide. He predicts that within three years, the output of goods and services will grow faster than the money supply, leading to significant deflation.

    5. Immigration and the “Brain Drain”

    Discussing his own background and the flow of talent from India to the US, Musk criticized the recent state of the US border, calling it a “free-for-all.” However, he distinguished between illegal immigration and legal, skilled migration. He defended the H1B visa program (while acknowledging it has been gamed by some outsourcing firms) and stated that companies need access to the best talent in the world.

    Thoughts and Analysis

    What stands out in this conversation is the shift in Musk’s demeanor when speaking with a fellow builder like Kamath. Unlike hostile media interviews, this was a dialogue about first principles.

    The most profound takeaway is Musk’s decoupling of “wealth” from “money.” To Musk, money is a temporary tool to allocate human time. Once AI takes over the “time” aspect of production, money loses its utility. This suggests that the future trillionaires won’t be those who hoard cash, but those who control energy generation and compute power.

    For the Indian audience, Musk’s advice was grounded and anti-fragile: ignore the valuation game and focus on the physics of value creation. If you produce more than you consume, you—and society—will win.

  • How Elon Musk Became America’s Kingmaker: A TIME Perspective on Influence, Power, and Political Transformation

    How Elon Musk Became America’s Kingmaker: A TIME Perspective on Influence, Power, and Political Transformation

    Elon Musk, known for his revolutionary achievements in technology and space exploration, has now emerged as a central figure in U.S. politics, effectively becoming what TIME calls a modern-day kingmaker. In the wake of Donald Trump’s re-election, the article explores how Musk played a decisive role not just as a financier but as an architect of campaign strategy, a symbol of ingenuity, and a bridge between political ideologies. This deep dive into Musk’s rise in political influence examines his motivations, his partnership with Trump, and the potential implications for governance and democracy.

    The piece portrays Musk as someone who has extended his influence far beyond his companies—Tesla, SpaceX, and X (formerly Twitter)—into the political realm. Musk’s efforts in the election included a $120 million donation, building a ground game to mobilize voters, and reshaping public perception of Trump. His role as a campaign surrogate and “First Buddy” in Trump’s transition team solidifies his unique position in reshaping the agenda for the next presidential term.

    TIME draws attention to Musk’s ideological pivot, moving from moderate Democratic leanings to becoming a self-declared opponent of “woke culture” and a staunch advocate for free speech. His public battles—on platforms like Joe Rogan’s podcast and within the pages of Twitter—have galvanized his followers, particularly young male voters, and created a new cultural narrative that blends technological innovation with political rebellion.

    The article takes a critical stance on Musk’s unprecedented power, raising concerns about his potential conflicts of interest. Musk’s new role as head of the Department of Government Efficiency (DOGE) is highlighted as both a symbol of his ambitions and a potential ethical minefield. With his companies under regulatory scrutiny, including investigations into Tesla’s self-driving technology and SpaceX’s environmental practices, his ability to influence government agencies poses serious questions about transparency and accountability.

    Furthermore, Musk’s promises to slash $2 trillion in federal spending and overhaul the bureaucracy are met with skepticism. Critics argue that his business-driven efficiency model may harm vulnerable populations dependent on social programs. The piece warns of the dangers of placing vital institutions—designed for public welfare—under the control of figures like Musk, whose priorities often align with profitability and innovation over equity and inclusion.

    The comparison to historical figures like William Randolph Hearst and Russian oligarchs underscores the risks of consolidating power in the hands of one individual. Musk’s growing influence, TIME suggests, may mark the rise of a new form of oligarchy in the U.S., where private wealth and technological vision collide with public governance. The article questions whether Musk’s partnership with Trump will survive the inevitable tensions between their competing agendas and egos.

    While acknowledging Musk’s undeniable brilliance and contributions to innovation, TIME critiques the broader societal consequences of his political rise. The article concludes with an open question: can Musk’s vision for the future—one that includes interplanetary colonization and radical efficiency—coexist with the complex realities of democratic governance, or will his ambitions undermine the very institutions that sustain society?

    This reflective and detailed examination positions Musk as one of the most consequential and controversial figures of our time, embodying both the promise and peril of individual power in the modern age.

  • Starship’s Sixth Launch: SpaceX Targets Key Milestone in Reusable Spacecraft Development

    Mission Objectives

    • Super Heavy Booster Catch: Return the booster to the launch site and catch it using the chopstick arms on the launch tower.
    • Raptor Engine Reignition in Space: Demonstrate an in-space burn using a single Raptor engine, a critical capability for future orbital missions.
    • Heatshield Testing: Evaluate new thermal protection materials and configurations, including sections with intentionally removed heatshield tiles.
    • Descent and Reentry Enhancements: Test higher angle-of-attack descent profiles to push flap control limits and gather data for future landing profiles.
    • Booster Safety Protocols: If conditions are not ideal, execute a safe splashdown in the Gulf of Mexico as a fallback.
    • Structural and Redundancy Upgrades: Validate hardware upgrades for booster propulsion systems, structural strength, and propellant offloading post-catch.
    • Improved Software Systems: Test updated software controls and commit criteria for launch, return, and catch operations.
    • Daylight Reentry Observations: Conduct reentry over the Indian Ocean in daylight for better visual observation and data collection.
    • Data Collection for Future Iterations: Generate valuable flight data to inform upgrades for the seventh flight and beyond, including redesigned forward flaps and enhanced thermal protection systems.

    The Starship’s sixth launch is set to mark yet another groundbreaking milestone in the evolution of space exploration. Scheduled as early as Tuesday, November 19, from Starbase in Texas, this flight test represents a pivotal step in SpaceX’s relentless pursuit of a fully reusable spacecraft system. The 30-minute launch window opens at 4:00 p.m. CT, but as with all developmental testing, the timeline remains fluid. Be sure to stay updated through spacex.com and the SpaceX X account for real-time developments.

    SpaceX is offering a live webcast for enthusiasts and professionals alike, starting 30 minutes before liftoff. You can catch this streaming event on spacex.com, the SpaceX X account, or the brand-new X TV app. The excitement around this test launch stems from the cumulative success of previous iterations, notably the fifth flight test that showcased a seamless Super Heavy booster return to the launch site and an impressive chopstick catch by the Starbase launch and catch tower.

    The upcoming flight test seeks to expand Starship’s capabilities, aiming to perfect reuse of the entire system. Among the objectives are a successful booster return and catch at the launch site, reigniting a Raptor engine while in space, and testing advanced heatshield designs alongside maneuvering strategies for ship reentry over the Indian Ocean. Each of these maneuvers underscores SpaceX’s commitment to innovation and rigorous testing to achieve an unparalleled standard of reusability.

    Key advancements for this test include enhancements to booster propulsion systems for added redundancy, stronger structural integrity in critical areas, and streamlined processes for propellant offloading post-catch. Software updates for improved control systems and booster return criteria further illustrate the precision and care involved in these missions. A vital safety measure remains intact: if conditions for the booster return and catch are deemed unsuitable, the booster will execute a safe splashdown in the Gulf of Mexico, reinforcing SpaceX’s commitment to safety above all else.

    The upper stage of Starship will follow a suborbital trajectory similar to the previous flight, concluding with a controlled splashdown in the Indian Ocean. A major addition this time is the attempt to ignite a single Raptor engine in space, paving the way for deorbit burn capabilities required for future orbital missions. This data-rich approach to testing ensures that every flight contributes invaluable insights to refine both vehicle design and operational strategies.

    This mission will also push the boundaries of thermal protection systems by removing specific heat shield tiles to analyze their impact and performance. Purposefully testing flap controls under high-stress scenarios during descent will further enhance SpaceX’s understanding of landing profiles. By targeting daylight reentry over the Indian Ocean, visual observations will provide clearer data for researchers and engineers to analyze.

    Looking ahead, the seventh Starship flight test will incorporate significant upgrades such as redesigned forward flaps, larger propellant tanks, and advanced heatshield technologies. These continual improvements bring SpaceX closer to achieving its vision of a fully reusable spacecraft that can carry out missions efficiently and reliably.

    As SpaceX gears up for another bold step, the excitement within the space community is palpable. With every test, Starship advances closer to revolutionizing space travel. Join us in cheering for this groundbreaking mission. Go Starship! Go SpaceX!

  • Understanding Elon Musk: A Visionary Leader Misinterpreted

    Understanding Elon Musk: A Visionary Leader Misinterpreted

    Based on an in-depth analysis from Casey Handmer’s blog post titled “Elon Musk is not understood,” this article aims to provide a nuanced understanding of Elon Musk, a figure often at the center of media controversy and admiration. Musk’s journey from a passionate entrepreneur to the head of groundbreaking companies like SpaceX and Tesla is a tale of vision, persistence, and often, misinterpretation.

    Musk’s Visionary Investments and Achievements:
    Elon Musk’s foresight in the realm of sustainable technology is evident from his early investments in Tesla, using his savings to back a then-nascent electric vehicle company. Today, Tesla stands as a beacon in the automotive industry, leading the charge in electric vehicle innovation and production. Similarly, SpaceX, under Musk’s guidance, has revolutionized space technology, particularly with the introduction of the Starlink internet satellite system.

    Media Perception vs. Reality:
    The media often presents Musk as a polarizing figure, focusing on short-term controversies and overlooking the long-term impact of his work. This skewed portrayal can lead to a misunderstanding of his objectives and the transformative nature of his projects. Musk’s approach, while unorthodox, is driven by a commitment to solving some of the most complex and pressing technological challenges of our time.

    Unconventional Leadership:
    Musk’s hands-on leadership style, which involves deep involvement in both technical and managerial aspects of his companies, has been a double-edged sword. It has propelled Tesla and SpaceX to incredible heights but has also been a source of debate and controversy. His unique approach to leadership and problem-solving is integral to understanding both his successes and the criticisms he faces.

    Impact on Industry and Environmental Sustainability:
    Tesla’s influence extends beyond the automotive sector, pushing legacy manufacturers towards a more rapid adoption of sustainable energy practices. SpaceX’s advancements have not only made space exploration more accessible but also demonstrated the potential for private companies to contribute significantly to what was once the domain of government agencies.

    Understanding Elon Musk: Beyond the Controversies:
    To truly understand Elon Musk, one must look beyond the immediate media narratives and controversies. His contributions to technology and sustainability are shaping the future, driven by a vision that challenges conventional methods and expectations.

    Elon Musk’s story, as detailed in Casey Handmer’s blog, is a reflection of the complexities inherent in leading cutting-edge technological ventures. While his methods may sometimes deviate from traditional norms, his impact on electric vehicles, space exploration, and renewable energy is undeniable. A comprehensive understanding of Musk requires recognizing the broader implications of his work and the ambitious vision that drives him to continually push the boundaries of innovation and sustainability.