I UPDATED MY SPACEX REVENUE ESTIMATES FOLLOWING THE NEW GOOGLE DEAL THAT WAS JUST ANNOUNCED
SPACEX REVENUE
2024 -> $13.1 BILLION
2025 -> $18.7 BILLION
2026E -> $37.5 BILLION
2027E -> $58.9 BILLION
HERE IS MY FULL BREAKDOWN
$SPCX
🚨 SPACEX MAY BE THE BIGGEST INSIDER CASHOUT IN MARKET HISTORY!!!
SpaceX is expected to go public on June 12 at a valuation of $1.75-$2 TRILLION.
That would instantly make it larger than Microsoft and second only to Apple and Nvidia in the US market.
Yet the company lost $4.28 BILLION in Q1 2026 alone and has accumulated deficits of $41.3 BILLION since founding.
The real story is what happens after the IPO.
Insiders currently own 95% of all shares.
The public float is only 5%.
And insiders are sitting on $1.66 TRILLION of paper wealth that cannot currently be sold.
Most IPOs lock insiders up for 180 days.
SpaceX isn't doing that.
Just 60 days after listing, 20% of eligible insider shares can unlock.
If the stock rises 30% above the IPO price, another 10% unlocks.
Then five separate 7% unlocks hit between days 70 and 135.
By November 2026, 93% of early-release insider shares could already be free to sell.
This isn't just an IPO.
It's one of the biggest liquidity grab events Wall Street has ever seen.
> la IA contaba mal el inventario en Starbucks
> Microsoft bloqueó claude code para sus propios ingenieros
> Uber no encuentra el ROI después de gastar miles de millones en IA
3 derrotas de la IA esta semana en el sector laboral.
WE ARE SO BACK
🚨La IA está costando MÁS que los empleados a los que reemplazó.
Y las grandes empresas ya lo admiten en público:
→ Uber desplegó IA entre sus 5.000 ingenieros. En 4 meses agotaron TODO el presupuesto anual. Su COO reconoce que no puede justificar el gasto.
→ Microsoft ha retirado licencias de IA a sus propios desarrolladores para frenar costes.
→ Starbucks eliminó su sistema de inventario con IA tras 9 meses. Funcionaba peor que un empleado.
→ El vicepresidente de NVIDIA dijo recientemente que “La IA está costando más que los trabajadores humanos”
Nos vendieron que la IA iba a ahorrar millones.
La realidad → los costes se disparan, los resultados no llegan y las empresas están dando marcha atrás.
Estamos ante el principio del fin de la burbuja de la IA?
Microsoft just banned its own engineers from using AI.
The tool was literally costing MORE than the humans it was supposed to replace.
They lied to you about AI adoption and now the whole narrative is blowing up:
Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it.
Engineers loved it and adoption exploded. But then the invoices arrived.
Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead.
The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much.
Uber's story is even worse...
Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April.
Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems.
Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session.
The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money.
Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote:
"For my team, the cost of compute is far beyond the costs of the employees."
This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans.
Think about what this means for the entire AI narrative.
Every CEO on every earnings call for the past two years has said the same thing:
AI will make us more efficient, reduce headcount, and cut costs.
The stock market rewarded every company that said it.
Fired workers, stock goes up. Announced AI adoption, stock goes up.
But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill.
Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools.
Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible.
Both companies are spending hundreds of billions on AI infrastructure this year alone.
And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control.
The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP.
This is the gap nobody on Wall Street is pricing in.
$725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work.
What do you think?
At age 25, you give your hedge fund manager $100K to manage, and he produces an annual return of 8%.
Assuming a 1.5% management and 20% performance fee, by the time you retire at 65, you will have $764K
But the manager will have $1.24M (at zero initial investment!)
@NateSilver538 He’s made approximately 10,000x + the wealth his parents had and you don’t need to guess about his returns, they are public.
But you sound like you’re mega butt-hurt by something he said in one of his tweets, so now you’re just speculating with blind resentment.
Full list of business executives joining President Trump on trip to China:
• Jane Fraser (Citi)
• Tim Cook (Apple)
• Elon Musk (Tesla)
• Brian Sikes (Cargill)
• Larry Fink (Blackrock)
• Kelly Ortberg (Boeing)
• Ryan McInerney (Visa)
• Chuck Robbins (Cisco)
• Jacob Thaysen (Illumina)
• Jim Anderson (Coherent)
• Sanjay Mehrotra (Micron)
• Christiano Amon (Qualcomm)
• Michael Miebach (Mastercard)
• Dina Powell McCormick (Meta)
• David Solomon (Goldman Sachs)
• H Lawrence Culp (GE Aerospace)
• Stephen Schwarzman (Blackstone)
The biggest cheat code on the planet is the ability to be in a good mood regardless of what's going on in your life. Not letting external events dictate how you feel is a skill we can learn. If you can train yourself to be in a bad mood you can train yourself to be in a good one.
Instead of looking for a needle in a haystack, just buy the entire AI haystack.
Compute: $NVDA, $AMD, $MU, $ASML, $TSM
Networking: $ANET
Power and cooling: $CEG, $BE, $VRT
Data: $MDB, $ORCL
Control layer: $PLTR
Security: $CRWD
Observation: $DDOG
Cloud infrastructure: $GOOG, $AMZN, $MSFT, $ORCL
Q1 earnings are in: 2026 is off to a terrific start.
Our AI investments and full stack approach are lighting up every part of the business: Search queries are at an all-time high with AI continuing to drive usage. Google Cloud revenue grew 63%, Gemini models have incredible momentum, and it was our strongest quarter ever for consumer AI subs, driven by @GeminiApp.
Thanks to our partners + employees around the world. Much more to share on our earnings call in 20 minutes… and at Google I/O in 20 days!
After listening to Google, Amazon, Microsoft and Meta earnings call:
The AI buildout just got bigger. Combined 2026 capex now tracking $700B+
- $GOOGL: raised to $180-190B (from $175-185B). Cloud +63%, backlog doubled to $460B
- $META: raised to $125-145B (from $115-135B). Pure internal spend, no cloud resale
- $AMZN: $200B maintained. AWS +28%, fastest in 15 quarters. TTM FCF collapsed to $1.2B
- $MSFT: $31.9B in Q (below $34.9B est). Demand still > supply. AI run-rate $37B (+123%)
Theme: Every CEO said the same thing - capacity constrained, not demand constrained.
Winners downstream:
GPUs/Accelerators: $NVDA, $AMD, $AVGO, $MRVL, $ARM
Custom ASIC/Silicon: $AVGO, $MRVL,
Foundry/Equipment: $TSM, $ASML, $AMAT, $LRCX, $KLAC, $ICHR, $UCTT
Memory/HBM: $MU, $HBM (SK Hynix), $WDC, $STX
Connectivity/Interconnect: $CRDO, $ALAB, $MRVL, $AVGO
Networking/Switching: $ANET, $CSCO
Optical/Transceivers: $COHR, $LITE, $CIEN, $FN, $AAOI
Power Generation: $CEG, $VST, $NRG, $TLN, $OKLO
Power Equipment/Grid: $VRT, $GEV, $ETN, $PWR, $HUBB, $NVT, $BE, $FPS
Cooling/Thermal: $VRT, $MOD
Cabling/Components: $APH, $GLW
My take: demand is still accelerating, supply is still catching up - this cycle likely runs longer than most expect.