I sell data center capacity for a living. The conversation with customers has changed completely in the last eighteen months.
It used to start with price per kW. Now the first question out of everyone’s mouth is when can you actually give me power, and the honest answer in most major metros is later than you want to hear.
Everyone wants to argue about GPU supply. That is not where the wall is. The wall is a transformer you order today that arrives in three years, a permitting process that answers to a county board, and an interconnection queue with roughly 2,000 gigawatts stacked up in it. PJM ran the numbers on projects that came online last year and the average was over seven years from request to live power. Three years to get an agreement, four more years to actually energize after the agreement was signed.
And this is the easy part. We are nowhere near the peak of this demand curve. There is at least another order of magnitude coming, and the grid that is supposed to absorb it operates on utility capital planning cycles that were designed in a world where load growth was flat for twenty years.
Which is why the orbital compute argument stopped sounding exotic to me sometime around last fall. Up there you get uninterrupted sunlight, you dump heat straight into vacuum instead of running chillers, and there is no zoning hearing, no queue position, no substation to wait on.
Plenty of companies have interesting orbital compute concepts. Only one of them owns the rocket, has the scale, and deeply embedded partnership with Nvidia.
SpaceX filed with the FCC in January to launch and operate up to a million compute satellites, and there is exactly one launch provider on Earth with the cadence and the cost structure to make that number anything other than a press release. Starship is the reason this is an infrastructure plan and not a science project.
The constraint on the ground is the grid. The constraint in orbit is mass to LEO. SpaceX is the only company that has solved the second one.
$SPCX
Nvidia today announced that @SpaceXAI will deploy Vera CPUs to accelerate its next generation of agentic AI applications.
"SpaceXAI plans to expand its AI infrastructure behind Grok on Nvidia Vera Rubin, while extending an optimized Vera Rubin NVL72 into space with its first-generation Starmind satellite.
SpaceXAI’s work with Nvidia is moving beyond AI factories on Earth. SpaceXAI is developing AI computing infrastructure for orbit, where power, thermal management, bandwidth, reliability and physical integration impose dramatically different constraints from conventional data centers.
SpaceXAI’s planned first-generation Starmind AI satellite will be based on the optimized Nvidia Vera Rubin NVL72 rack-scale system, extending the same accelerated computing architecture powering next-generation AI factories on Earth into space.
Nvidia and SpaceXAI are working to adapt that foundation to the requirements of orbital computing while preserving a common Nvidia architecture and software ecosystem.
This delivers one computing foundation across a wide range of environments: Vera CPUs accelerating increasingly sophisticated AI agents, Vera Rubin powering the AI infrastructure behind Grok and gigawatt-scale AI factories on Earth, and Nvidia accelerated computing extending into orbital AI infrastructure."
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The Atlanta Fed is now tracking 5.1% real GDP growth for Q3.
5.1%.
For a ~$30 trillion economy.
If that holds anywhere close, the U.S. economy is growing at an incredible pace.
Hard not to be bullish on America. 🚀 🇺🇸
Ok. And 1999 didn’t have AI driving accelerating productivity, explosive earnings growth and one of the largest infrastructure buildouts in history.
Rates can go higher while earnings and equities go higher too.
Round 2. LFG. 🚀 🇺🇸
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The scale + speed + monetization is absurd.
People just don’t understand what’s being built here…
No one is deploying AI compute at this scale, this fast.
And the revenue potential is insane.
Remember what SpaceX CFO said on the last earnings call: the ROI on this infrastructure is approaching one year. When compute pays for itself that quickly and can immediately be reinvested into the next cluster, the economics start to look much closer to COGS than some massive capital investment waiting a decade for a return.
SpaceX is building a compute flywheel at a scale that is difficult to comprehend. And this is before it goes into orbit…… 🤯
Colossus 1 is 150k H100, 50k H200 and 30k GB200.
Colossus 2 is 110k GB200 and 440k GB300.
Another 220k GB300 will be fully operational next week and another 220k in November. If we get lucky, yet another 220k GB300 by late December.
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Ok. And 1999 didn’t have AI driving accelerating productivity, explosive earnings growth and one of the largest infrastructure buildouts in history.
Rates can go higher while earnings and equities go higher too.
Round 2. LFG. 🚀 🇺🇸
Your friendly reminder that the Fed hiked 3 times in 1999 and NDX did +51% *after* the first hike
Oh and the 10-year went from 4.7% to 6.5% that same calendar year
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I think there’s a lot of truth to this.
AI may be materially changing the interest-rate sensitivity of the economy.
If the expected return on intelligence and compute is enormous, does moving the cost of capital from 4% to 5% or 6% actually slow investment meaningfully? NEWS FLASH: No.
The largest companies on Earth will keep spending hundreds of billions on compute, power and data centers because the cost of falling behind dwarfs the incremental cost of capital.
Higher rates will still slow housing, credit and marginal investment. But what if they’re far less effective against the investment boom actually driving incremental demand for power, labor and infrastructure?
If so, the Fed is just applying increasingly restrictive policy to the rate-sensitive economy while barely touching the AI capex cycle.
Wrong move indeed…
The presumption that the Fed raising short-term rates reduces inflation is predicated on the belief that higher rates reduce demand and investment.
But what if higher rates don’t reduce demand and investment because the demand for intelligence and energy is unaffected by higher rates because winning the race for super intelligence has a near infinite ROI and the demand for compute will remain incalculable.
Why won’t higher rates at this unique moment in history therefore lead to more inflation as interest costs are embedded in everything?
And the problem is compounded as the more the Fed raises rates, the more inflation we will have and the more the Fed will need to raise rates further and so on.
But what if the old models don’t apply to the current paradigm and the Fed is wrong?
I think the Fed might have just made a mistake. Am I right or am I wrong?
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People still haven’t learned.
You don’t bet against Elon.
🚀🚀🇺🇸🇺🇸🇺🇸
1. We will keep accelerating. Our AI efforts are only 3 years old, vs 6 and 10 years old for Anthropic and OpenAI. If our second derivative remains strong, SpaceX will reach pole position in about 6 months.
2. Once you far exceed the caliber of intelligence needed for a class of tasks, additional intelligence is pointless. You don’t need (and it would be cruel to put) Newton-level intelligence in your toaster!
3. Hardware is hard. Bringing massive compute online rapidly is incredibly difficult. SpaceX has demonstrated exceptional ability in this regard and will only get better.
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It will be complete when Tesla joins the fun and it all trades under one. $X
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Timbo retweeted
There’s a lot of talk about OpenAI, Anthropic, and SpaceX being worth more than the combined IPO day value of all 3,365 U.S. tech IPOs from 1980-2025.
But they can have very different destinies.
OpenAI and Anthropic can both become $5-10 trillion companies near term and still ultimately become zeros if they don’t create a real moat. SpaceX has spent decades building one.
Incremental model improvements alone will not be enough for the frontier labs.
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True. Hike and the interest bill grows. Cut and prices grow. Either way the Treasury prints. This is why ya hold $BTC.
Plot twist: both of these options worsen the inflation problem in the near term
We are so beyond any Fed-driven solution.
The only solution is to cut spending, which we won't do.
So buckle up, own hard assets, and quit being surprised when things get worse.
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This is the adult take. Pause theater helps no one.
The loudest voices stoking fears about AI dangers have made tremendous headway in the past two weeks. AI technology has not taken some unexpected, dangerous turn, but the hype around it — propelled by what appears to be a well orchestrated PR campaign — has drummed up considerable fear. I worry that it represents a setback for our field.
I have written frequently that fears of AI are overhyped. AI’s capabilities can be uncannily human-like and unpredictable, and it’s rational to worry when people who are directly involved express concerns. But I see the problems as a sign of the engineering work that ahead, rather than insurmountable barriers or the sky falling. AI technology continues to advance — which is a good thing! — but technical advances, poorly understood by the public, give those who seek to generate hype repeated opportunities to do so.
First, I don’t see any step up in the risk of human extinction from AI compared to a few months ago. The theories about this remain the same fantastical, science fiction scenarios as a few months ago. The biggest change in AI risk is its cybersecurity capabilities — a topic which we should take seriously — but this, too, will not lead to the end of the world.
The most notable recent event leading to increased fear was when an OpenAI team deployed an agent swarm that hacked into Hugging Face. Much of the popular press contained significant hype. For example, some publications reported that a swarm of 1,200 agents carried out the attack. While this was technically accurate, as I write this, I have about 1,300 processes running on my laptop. Yes, the ability to get large swarms of agents to work in parallel on a task is a significant technical advance, And, in computing, many processes run at the same time. So this shouldn’t be seen as some magical capability.
Additionally, OpenAI’s buggy sandboxing and monitoring processes were key to enabling this incident. Fixing these bugs and putting in place improved monitoring would be appropriate fixes, not pausing AI. There are many well known ways to attack software systems. The main advantage of AI agents is that they are relentless. They will tirelessly try many tactics — and have the patience to chain vulnerabilities together — that previously would have taken an infeasible amount of human effort. But in the long term, I believe the advantage will lie with defenders (because they have more information with which to identify bugs, which they can fix), but the cyber-threat landscape has changed significantly. There are still bottlenecks to identifying and exploiting a vulnerability. AI agents still have to try a lot of things to see what works, and taking these actions takes time and might be detected by defenders. This is why, even though it is now easy to obtain versions of leading open weight models that have had their guardrails removed or weakened, so they will not refuse to try to execute cyber attacks, the world has not ended.
I am also concerned about the anthropomorphization of AI in a lot of reporting, where LLMs and agents are unnecessarily treated as if they were people. If I wield a hammer, miss a nail, and accidentally dent the wall, it’s not the fault of the hammer. The problem lies in how I used the hammer. Similarly, if I prompt an agent and it hacks into someone else’s system, the responsibility lies with me, not the agent.
Of course, we want to build systems that are as safe and predictable as possible. (For example, an unsafe hammer would be one whose head randomly flies off under normal use.) Today’s agentic systems are not predictable, but I see no reason why, by applying sound engineering practices, we won’t be able to make them extremely safe to use. One new element in the forecasts of AI-enabled doom is AI companies disclaiming responsibility for their own products. “I didn’t do it; my out-of-control agent did!” There’s a balance to be struck between the responsibility of the tool maker and the tool user, but when something goes wrong, let’s hold the people building and/or using the hammer responsible, rather than the hammer. (By the way, if you’re worried about AI bioweapon risk, David Bellamy has a great post on why this, too, is overhyped. Briefly, the bottleneck in building a bioweapon is not intelligence, but lab work and manufacturing.)
Pausing AI progress will create much more harm than benefit. First, our adversaries will certainly not slow down. Second, engineering requires discovering problems empirically so we can fix them. If we pause AI by a decade, we will also delay finding and implementing safety engineering fixes by about the same duration.
Of course, the incentive to stoke fears — for regulatory capture, to garner attention, or to make one’s technology seem more powerful — remains the same as before. Disclaiming responsibility is a new one. Taking a hard technical look at the actual risks however, I see little factual basis for the degree of fear that’s been stoked up. We still have hard research and engineering work ahead to improve AI safety, but the beneficial applications continue to vastly outweigh the risks, and we should keep building.
[Original text (with links): deeplearning.ai/the-batch/is… ]
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The rate alone doesn't tell you much. A 7% mortgage on a $97K house in 1990 is a different animal than 7% on a $429K house today.
Put the whole payment against income and today is the worst since 1985. Worse than the 2006 bubble. Only the early 80s were worse.
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AI is so 🔥 🔥.. for years my whole financial picture lived in one Excel file. Stocks, BTC, SpaceX and xAI SPV tranches, debt, income.
I uploaded it to Claude and asked it to turn it into a website that runs locally on my Mac. I also asked for a section with sliders so I could test allocation changes.
It created a full console. Net worth, portfolio totals up top. Allocation pie, holdings, private equity positions, debt, income. A prices tab where I update one number and everything downstream recalculates. Save and load to a file so nothing leaves my machine.
The slider section is the part I use quite a bit... Commission check comes in, add to the index, watch the pie shift. It's how I think through buys/sells now.
I tried the off-the-shelf trackers first. None of them handled SPVs with multiple tranches. None had an allocation tool. This took one conversation and I own the code.
Portfolio update.
++ investment plans.
I’ve spent years building concentrated positions in the assets I have the most conviction in. Today the portfolio sits roughly:
40% SpaceX
34% Bitcoin
10% Tesla
12% Cash
2% **RSUs**
2% Index Funds
That last bucket is going to start growing.
I put a small base into index funds and am now buying $2,000 every trading day, allocated like this:
60% Total U.S. Stock Market via direct indexing. Essentially tracking $VTI, while owning the underlying stocks directly to take advantage of tax-loss harvesting and automatic reinvestment.
20% $VXUS for international exposure. I think some geographic rotation is possible over time, although I’ll never bet against the United States. This gives me exposure if international markets have their day.
10% $RSP, the equal-weight S&P 500. The S&P 500 is only about 2% off its highs, while more than 70% of its constituents are over 10% below their individual highs. If market breadth expands over the next few years, equal weight could benefit. It’s a small allocation, but I like the setup.
10% $QQQ. I continue to believe technology will outperform over the long run. I also think we’re somewhere around the second inning of the AI buildout, with a lot of investment, adoption and productivity gains still ahead.
I’m still very comfortable with a concentrated portfolio. $SPCX, $BTC and $TSLA remain my highest-conviction positions. At this stage of the journey, I also want to steadily build a larger diversified base around them.
No selling required. Just using new capital to gradually change the mix.
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Bitcoin ETFs launched January 11, 2024.
If you bought on launch day, your CAGR is roughly 26%. An 85.09% gain (after ETF fees)
That’s a SOLID annualized return. I think returns around that level are a reasonable expectation for Bitcoin going forward, though certainly not a guarantee. (Frankly, I’d be ok with half-that)
What I find ridiculous is using Bitcoin’s trailing ten-year CAGR to project the next ten years. bitcoin:native was a much smaller asset back then. Expecting the same percentage growth from today’s base is wild...
Bitcoiners should stop leaning on those early returns to sell future expectations. The investment case should stand on its own without them.
Compounding at roughly 25% a year would be an exceptional result. There’s no need to oversell it.
US Spot Bitcoin ETFs had about $4.5 billion in trading volume today. Which isn't all that high considering the move in BTC itself. Even this past Friday was a slightly bigger day at $4.6 billion
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Portfolio update.
++ investment plans.
I’ve spent years building concentrated positions in the assets I have the most conviction in. Today the portfolio sits roughly:
40% SpaceX
34% Bitcoin
10% Tesla
12% Cash
2% **RSUs**
2% Index Funds
That last bucket is going to start growing.
I put a small base into index funds and am now buying $2,000 every trading day, allocated like this:
60% Total U.S. Stock Market via direct indexing. Essentially tracking $VTI, while owning the underlying stocks directly to take advantage of tax-loss harvesting and automatic reinvestment.
20% $VXUS for international exposure. I think some geographic rotation is possible over time, although I’ll never bet against the United States. This gives me exposure if international markets have their day.
10% $RSP, the equal-weight S&P 500. The S&P 500 is only about 2% off its highs, while more than 70% of its constituents are over 10% below their individual highs. If market breadth expands over the next few years, equal weight could benefit. It’s a small allocation, but I like the setup.
10% $QQQ. I continue to believe technology will outperform over the long run. I also think we’re somewhere around the second inning of the AI buildout, with a lot of investment, adoption and productivity gains still ahead.
I’m still very comfortable with a concentrated portfolio. $SPCX, $BTC and $TSLA remain my highest-conviction positions. At this stage of the journey, I also want to steadily build a larger diversified base around them.
No selling required. Just using new capital to gradually change the mix.
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My “Elon sleeve” is now 50% of my portfolio.
That’s a lot of concentration in one person’s ability to execute. I’m comfortable with it.
For 20+ years, Elon Musk has repeatedly pursued things that were widely viewed as unrealistic, uneconomic, or outright impossible.
Tesla was supposed to fail. EVs were supposed to remain a niche product. Tesla went from struggling to manufacture cars to proving EVs could be produced at enormous scale, building factories across multiple continents, developing its own charging ecosystem, expanding into grid-scale batteries and pushing further into autonomy, AI and robotics.
SpaceX may be the even crazier story.
Private rockets were dismissed. Landing orbital-class boosters sounded absurd. Reusing them economically sounded even harder.
Falcon 9 became the world’s first orbital-class rocket capable of re-flight. SpaceX became the first commercial company to visit the ISS, then returned American astronauts to orbit from U.S. soil. SpaceX flew 165 Falcon 9 orbital missions in 2025 alone, with 162 successful booster returns.
Now SpaceX is working on Starship, a fully reusable system designed for Earth orbit, the Moon and Mars. Starlink has turned rockets and vertically integrated satellite manufacturing into a global communications network.
Then you have Neuralink pushing brain-computer interfaces into human trials, The Boring Company tackling transportation infrastructure, and the combination of SpaceX and xAI creating exposure to rockets, satellites, global connectivity, AI models, massive compute infrastructure and soon orbital compute.
And Tesla is increasingly a bet on far more than cars: autonomy, Optimus, energy storage, AI, manufacturing and robotics.
Execution risk is enormous.
But after watching the same pattern repeat for two decades, I’ve learned one investing lesson I’m willing to put real money behind:
I don’t bet against @elonmusk.
50% of my portfolio currently reflects that conviction. 🚀 🇺🇸
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Rolled 38 $IBIT contracts out to November for a small credit. Big move up on BTC today.. forced to manage.
Sold 5 $TSLA $420 10/16 covered calls, then closed them for a $497 profit.
Sold 3 $SPCX $175 10/16 covered calls, then closed them for a $233 profit.
+$730 realized today on the SpaceX and Tesla trades. I’ll take it.
Follow Bobby who’s a blast to watch sell options.. Cool journey on a catamaran too
Stopped out. $tsla
Stop placed at 6.95 and filled at 6.965. Not bad. I’ll take that slippage.
+$740 on these 8 contracts.
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