The Computomatix Times

I was talking to a longtime SpaceX employee who struck gold in the IPO. This person told me that they started getting nonstop pitches from financial firms about something called 'tax loss harvesting' as the offering neared.

That took me down the rabbit hole into the bubbling world of tax minimization and avoidance — now known as 'tax alpha' — where advisors pitch aggressive strategies juiced by modern software and analytics to help create losses for clients that offset the taxes from liquidity events like an IPO.

Data I got showed that this type of investing is now the single most popular category for professionally managed portfolios, and continues to rise. My latest this weekend for @theinformation

theinformation.com/articles/tax-alpha-silicon-…

Too aggressive re Anthropic. Base case of $250 B ‘27 exit run rate (same size as MSFT & Meta) seems wild but achievable. $450 B (size of Apple & Google) seems too aggressive given compute & regulatory constraints. Margins also likely lumpy as big compute comes online. 🧐📈

Changes in H-1B regulations have crushed Indian IT services companies (WITCH), who are down -70% from peak, while BigTech remain steady but down from peak, except Meta.

Those lost numbers are not made up by L-1 applications, which is mostly flat.

We are all lucky that people like @benthompson, @GavinSBaker, @altcap, @dsundheim and others so often take the time to explain what’s happening in a detailed and deep way.

I think it’s a huge force for good in markets.

As someone who has personally spent $500k / mo+ on Google Ads for years, I can tell you with certainty:

This revenue growth in Search is artificial & extremely unhealthy for Google’s business long term

Search volumes are declining as legacy search is being increasingly cannibalized by non-monetized LLM queries

Google’s response?

Manufacture revenue growth via short-sighted, highly extractive, customer-hostile tactics. I.e. charge advertisers more for lower quality clicks, including clicks they do not want and explicitly did not approve Google to charge them for

A few examples to illustrate:

For all of its history until recently, Google operated on a 2nd price auction model

I.e. if you bid $5 CPC and the next highest bidder bids $1 CPC, Google charged you $1.01 for the click (one penny more than the 2nd highest bidder) rather than the $5 you bid

This was a genius move by Google early on as it incentivizes advertisers to input their true maximum willingness to pay rather than trying to play the game of bidding low and constantly adjusting to try to stay just ahead of the next highest bidder while still not paying too much

However recently, Google silently deprecated the 2nd price auction and began charging advertisers as much as their bid and budget caps allow, regardless of what anyone else is bidding

It’s a short-sighted cash grab at the expense of the long term health of the advertiser ecosystem

Making thing worse, Google also recently nerfed keyword targeting precision

Google previously had precise keyword targeting settings that allowed advertisers pick individual search phrases to bid on, defined down to the character w/ exact match or phrase match targeting

This was one of the core features that made search advertising magic, enabling advertisers to run extremely precise campaigns based on exactly what their target customer typed

But now, even if you bid on a specific term or phrase using the strictest exact
-match targeting settings, Google will show your ad across 1000’s of unrelated keywords, labeling them as as “exact match (close variant)”

The definition of “close variant” means whatever they want it to and changes constantly. The result is advertisers get billed for clicks that are totally irrelevant to their business and that their targeting settings explicitly forbid Google from targeting. Google does it anyway and there’s no ability to turn this off

So now exact match is broad match, and broad match is just meaningless spam

This is all very bad for advertisers, but for Google, it allows them to show your ad and bill you for clicks across 1000x more searches that were previously going unmonetized (mainly because they’re garbage queries no one wants)

This is how you grow revenue atop declining search volumes

Lastly, and perhaps most egregiously, Google quietly stopped respecting budget caps by a factor of 2x. For example campaigns we’ve been running for years with $1000 daily budget caps suddenly began spending $2000+ per day

And the extra spend is entirely on the garbage keywords Google arbitrarily throws in as “exact match (close variants)” which have no value to our business, but can’t be turned off

Google offers no refunds nor any recourse for overspend or spend on keywords you explicitly did not target

These are not the actions of a healthy business. These are the actions of company whose core business is in decline but desperately needs to pump quarterly earnings so Wall Street will continue to fund insane capex while hopefully looking through their rapidly deteriorating negative free cash flow

Google operated a benevolent monopoly for the better part of 25 yrs

Meaning the value Google captured from Search was but a small fraction of the value it created, and that spread produced a potential energy that justified expectations of high earnings growth far, far into the future

This is now no longer the case

At the alter of AI capex, Google is sacrificing the golden goose

Nebius will be a TRILLION dollar company and here is exactly why (Save this).

Brad Gerstner's Altimeter said on camera that they are invested in ClickHouse, and explained exactly why in one sentence: "If you're in the data infrastructure layer, then token consumption is driving a lot more consumption of your basic services."

The flip side of that point is equally important.

Gerstner added that the closer you are to a point solution, a single use app built on top of AI, "that feels like you're on the front of the conveyor belt heading toward the guillotine."

Models get better, apps get commoditized and the companies that own the foundational infrastructure that every AI application must run through keep compounding.

ClickHouse is exactly that foundational layer.

It is a real time analytical database engine originally built inside Yandex, optimized for the exact query patterns that AI agents, LLM observability pipelines, and machine learning infrastructure generate, massive write volumes, complex aggregations, and sub-second response at scale.

It processes hundreds of billions of rows per second, serves over 2,000 enterprise customers including Cloudflare, Uber and ByteDance, and grew 300% in a single year.

In January 2026, a $400 million Series D valued ClickHouse at $15 billion more than double its $6 billion valuation just eight months prior.

Here is where Nebius comes in.

Nebius holds a 28% stake in ClickHouse, an asset that traces back to its Yandex origins.

At ClickHouse's current $15 billion valuation, that stake is worth approximately $4.2 billion, sitting largely unrecognized on Nebius's balance sheet while most market coverage focuses entirely on the AI cloud business.

A ClickHouse IPO, which the company is actively positioning toward, would force the market to mark that position to full public market value for the first time and could alone reprice Nebius meaningfully.

But that hidden asset is just one layer of the bull case.

The core AI cloud business just printed 684% year over year revenue growth, $399 million in Q1 2026 against $50 million a year prior.

AI specific revenue grew 841% and now represents 98% of total revenue.

The moat underneath those numbers is 3.5 gigawatts of secured power capacity, a $27 billion five year contract with Meta, a $2 billion strategic investment from Nvidia, and a Microsoft partnership ramping to full run rate in 2027, all stacked on top of a ClickHouse stake that the market is still not fully pricing in.

Long Nebius and make sure to follow me @MelvinInvests for more underlooked AI oppurtunities.

UPDATE: President Trump filed a March 2nd purchase of Moderna stock.

On June 18th, the FDA voted to recommend Moderna's mRNA flu vaccine.

$MRNA has now risen 46% since March 2nd.

I will make 12% rent without owning any stocks. Here is how:-

1) I own 0 stocks of AVGO (Broadcom). The stock trades at 370.
2) Fundamentally, this is one of the best businesses in the world to own.
3) Now, I will sell a PUT option at around 280. This is 20%+ Out of the Money.
4) For this, I will be paid roughly 6% yield over 6 months. So 12%+ in 1 year.
5) Now: some of you would say: that cash secured put is a risky strategy. What if the price hits 280$. And, you are forced to buy?
6) I am okay with this. AVGO falling to 280 means, it is down 40%+ from its peak. I am happy to buy 100 stocks here. Therefore, I picked a firm like AVGO to begin with.

If the stock does not fall to this point, cool, I will collect my 12% rent in $ terms.

Most people make losses on options because they don't make it part of their core portfolio. And, neither understand how to manage risks.

If you use it sensibly (especially in good markets like the US), you can make decent cash flows.

It’s not that complicated. WhatsApp may seem like a global product but effectively it’s not. India is WhatsApp’s only “viable” market, with both the numbers and the consumer habits to make it a possible lifeboat for Meta’s otherwise flailing position as a tech company. Kunal himself has commented previously on India being the world’s DAU farm (which is true).

WhatsApp has already maxxed out its business product in India (no other country’s consumer or regulatory bodies would permit or tolerate the level of spam India deals with on WhatsApp) as well as its ads product (there are ads even between stories now, ffs, in a private messaging app).

The only lever that is yet to be maxxed out is its payments product which launched in India a few years back. Considering the growth of India’s digital microtransaction economy and corresponding consumer habits, it’s tempting to consider that WhatsApp has the chance to outdo every payment product in the region.

All of this narrows down the executive search quite a bit. The $900M investment is not only for Kunal, it’s for the intellectual property he brings about India’s fintech (a headache for global executives everywhere) and Indian consumer habits, from the homegrown CRED. It’s actually a small price considering UPI hit ~230B transactions last year, 33% increase y-o-y. I believe the microtransaction economy is projected to reach $600B in less than a decade. If that’s even fractionally true, it’s a small price for a strong hire. About half of that $900M is going to be new fuel for the company (which will certainly buy CRED good runway), the rest helps investors get an exit.

I surmise WhatsApp is planning to become a fullblown payments product. Messaging + microtransactions has anyway been the trend in Indian consumer products. Bad news for the local fintech startup economy. Worse news for the consumer, imho.

It may be time for someone to build the next messaging app for friends and families. It’s been a while.

I have been trading for five decades, primarily using charts. I have found nobody better as a pure Edwards and Magee devotee than Aksel Kibar. He is the chartist I most trust for accurate chart analysis

This Goldman Sachs interview with Steve Cohen teaches you more about the mindset of a great trader than any course on strategy.

The Point72 founder explains how he reads markets - and how he applies it to running the Mets.

24-min with Goldman on what actually separates great traders from the rest.

bookmark & watch - a rare look inside the mind of a trading legend.

The $SPCX IPO prices todays at $1.77 trillion. Brad Gerstner (@altcap) and Gavin Baker (@GavinSBaker) just spent 80 minutes on @BG2Pod making the case for why that's the cheapest it's going to get.

Here are the 10 takeaways worth saving:

1. In 30 days, SpaceX added $29 billion in AI compute revenue from the Anthropic and Google deals and jumped from not being an AI hyperscaler at all to being the #4 hyperscaler globally, passing Oracle. The trailing multiple compressed from ~100x to 39x in the same window. CoreWeave, Nebius, Iron and the 50 other neoclouds VCs are funding in Silicon Valley are now competing for a smaller slice of what's left.

2. xAI's Google deal generates more operating profit per gigawatt than Anthropic, Meta, Google or OpenAI's own infrastructure. Freda at Altimeter calculated a 55% IRR on Colossus 1. Borrow at 7%, invest at 55%, the math maths. Jensen called the build itself an "N of 1": 100,000 GPUs is normally a 3-year planning cycle plus 1-year deployment. xAI did it in 19 days. Speed is literally cost.

3. The premium Google is paying SpaceX for terrestrial compute is partly a call option on orbital. They want first-in-line when space data centres go live, so they're overpaying today to lock in the relationship.

4. Orbital compute costs about $5 billion per gigawatt of capex to put GPUs in space, vs $20-25 billion per gigawatt for the non-silicon half on the ground (land, power, cooling, switchgear). Space, power and cooling are effectively free up there. The unlock is rapid two-stage reusability of Starship, which takes launch from $1,500 per kg on Falcon to $250 per kg and eventually asymptotes to the cost of fuel. Elon says 3 years, Bezos says 6, truth is probably 4-5.

5. Starlink is at less than 1% global household penetration. The forecast going from $10bn to $50bn in connectivity revenue by 2028 is still only 0.3% of the global telecom market. TAM is not the constraint.

6. The most underrated piece of the IPO is the Cursor acquisition. Cursor and Anthropic each hold more proprietary coding tokens than exist on the public internet combined. xAI bought 700-800 people and a frontier-quality coding dataset, dropped it into Colossus 2 for 3 weeks of training, and Composer 2.5 went pareto-dominant on coding 12 days ago. Grok 4.3, a 1.5 trillion parameter model, is also currently on the pareto frontier. There are now four frontier labs, not three: xAI alongside Google (Gemini 3.1 Pro), Anthropic and OpenAI.

7. Anthropic just shipped Fable 5 (Mythos with safety classifiers). Karpathy says it's SOTA on benchmarks but the real unlock is long-running tasks. Stripe refactored a 50 million line Ruby codebase in a day. Used to take many weeks with many engineers. Noam Brown's corollary: snapshot benchmarks are dead. The x-axis now has to be time, tokens or compute, because frontier models can solve most problems if you let them run long enough. Nobody has ever run Mythos for a year continuously. We may never actually know how smart any given generation is.

8. The cleanest framing of the long-running thesis: imagine Albert Einstein, no need to eat, sleep, or age, thinking about one problem in fundamental physics for one straight year. That's the case for spending $1.5 trillion a year on compute.

9. The frontier captures ~90% of AI revenue. Open source captures ~80% of tokens. Both are true. The market priced one and missed the other. The bear case last year was that cheap open-source tokens would close the gap. Six months in, the frontier is extending its lead instead.

10. Capex for the hyperscalers is moving from $1.1T to ~$1.5T by 2027 (Morgan Stanley revised up). Inference revenue is projected at $300B by 2027 with 60-70% gross margins and roughly 35% of capex going to non-revenue training runs. Brad thinks $300B is low and we end this year at $200B+. Meanwhile Nvidia has not been losing share to ASICs. Once you adjust for Anthropic on TPUs, Nvidia has held or expanded against Broadcom, AMD, Cerebras, MTIA and OpenAI's Jalapeno. Tokens-per-watt is revenue-per-watt in a power-constrained world.

Bonus: The MAG 7 added $1 trillion of revenue over the last 7 years and that produced $17 trillion of market cap. The forecast: SpaceX, Anthropic and OpenAI add the next $1 trillion in revenue in 4-5 years. Three companies, half the time.

Okay this is genuinely insane.

SpaceX just unveiled a satellite whose only job is to run AI. Not internet. Not GPS. Just compute, floating in orbit.

It's called AI1, and the reason behind it breaks your brain.

AI data centers on Earth are hitting a wall, not a chip wall, a physics wall.

They need staggering amounts of power and water just to stay cool, and we're running out of grid and land to build them.

So Musk's answer is: stop building them on Earth.

In orbit, the sun never sets. Free power, 24/7. No water for cooling, you just radiate heat into the vacuum of space. The two things choking AI on the ground barely exist up there.

And here's the wild part: Musk says it's easier to build than a Starlink satellite. Strip out the complex antennas and it's "a lot of solar cells, a radiator, and some laser links."

One AI1 carries the compute of an Nvidia GB300 rack, the same hardware data centers fight over down here.

AI1 is just the first one. The plan is a constellation of up to a million of them.

And the timing isn't an accident, SpaceX goes public this week at a ~$1.75 trillion target. This isn't a rocket company anymore. It's positioning itself as the power grid for AI, in space.

The race for AI compute just left the planet. Literally.

@SpaceX

Lloyd Blankfein, former CEO of Goldman Sachs, broke down his entire personal trading setup:

portfolio: 98% risky assets. 75-90% single stocks. mostly big tech hyperscalers plus "second tier" names slightly below blue chip.

"i invest in risky assets. that's what's fun for me."

"do you have a team? oh, just me."

hardware: no computer. an iPad and a phone.

information source: texting and calling people.

"somebody will text me. i'll text them. then i'll get tired of tapping things out because of my fat fingers. so i just call people up."

frequency: trades every single day. multiple times.

"it's taking a lot of discipline not to look at my screen while i'm talking to you right now."

"some people listen to music. to me, the market is like music. it's out there. it's going on."

has he outperformed the market? "yes, i have for a while. it's because of where i focused, tech, energy, and financial services. i know a lot about financial services having been in financial services."

the former CEO of Goldman Sachs. manages his own money. on an iPad. alone. focused on three sectors he actually knows. and beats the market.

sometimes the edge isn't the model. it's 40 years of pattern recognition and a phone full of the right contacts.

$QQQ went from 718 to 705 before closing the day at highs @ 724.

My first post: Avoid buying
My second post: This is where you buy
This post: Happy that I helped.

My third advice: If you're looking at buying, look between 10:15 to 11:30. That window will work more times than not.

Second advice: This is where you buy.

The gap up: traced all the way down, filled.

Stocks you liked 30 mins ago are 5% lower now

If an Anthropic employee got $500k/year in equity over 4 years in 2024, they are now worth $125M.

At $1M/year equity for 4 years, they are worth about $250M.

The scale and speed of wealth creation are incomprehensible.

$500k/year equity is not a lot for an early-stage startup. I don't think the Bay Area has seen this type of wealth creation in history.

Dot com boom probably feels like a speck of dust.

Moral of the story - do NOT chase hot IPOs

Year-1 average drawdown = 55%
Year-1 median drawdown = 54%

Table: Truist

If all you ever did was:

1. Find trending stocks
2. Buy them at daily 21EMA
3. Ride them until it breaks

you'd not have to worry about what others think of a stock.

Study: $SIVE $INTC $MRVL $MU $NOK $SNDK

All trends start at 21EMA.
All of them.

“We spotted nine Polymarket accounts, all connected, who made, collectively,$2.4 million betting almost exclusively on U.S. military operations,” says Nicolas Vaiman, co-founder of the small data analytics firm Bubblemaps.

“And now here's the crazy part: 98% win rate.” cbsn.ws/4wwp0T7

🚨 THIS IS NOT LOOKING GOOD

SpaceX, OpenAI, and Anthropic will go public at the same time.

That will force the market to absorb $200 BILLION of new supply.

When that happens, funds don't find new money out of thin air.

They sell what has already gone up.

NVIDIA, SK HYNIX, Micron, INTEL: those are the bags that will get cut first.

And if the leaders dump, the S&P 500 dumps with them.

We saw the same pattern after COVID.

Hype IPOs flooded the market --> liquidity got tighter --> air came out fast

This time, the AI bottleneck trade looks even more crowded.

Watch the upcoming IPOs closely.

That's where you may first see what the market is forced to sell.

Krishna Rao is the CFO of Anthropic, and this is his first podcast appearance.

He joined the company two years ago when run-rate revenue was about $250M. Today it is $30B. He has helped raise ~$75B and is responsible for the procurement and allocation of compute.

I feel lucky we get to hear what it is like to sit inside a company this consequential at a moment this pivotal.

We discuss:
- The cone of uncertainty
- How he allocates compute across Trainium, TPUs, and GPUs
- What investors misunderstand about model companies
- Why the returns to frontier intelligence keep rising
- Platform vs application and where Anthropic builds its own products
- How Anthropic uses Claude internally

I have asked my closing question about the kindest thing more than 500 times. Krishna's answer is one I have never heard before.

Enjoy!

Timestamps:
0:00 Intro
2:38 The Compute Canvas
6:51 The "Cone of Uncertainty"
11:58 Why the Returns to Frontier Intelligence Are So High
16:45 Recursive Self-Improvement
20:20 Scaling Laws
23:30 Sourcing $100 Billion in Compute
28:05 Platform vs. Application Strategy
32:52 Pricing Dynamics
38:48 How Anthropic’s Finance Team Uses Claude
43:24 Raising Capital & Overcoming Investor Skepticism
52:32 Public Perception, Risks, and Government Regulation
57:25 Mythos Release
1:12:33 What Could Derail the AI Revolution?
1:13:47 Biotech and Healthcare
1:15:31 The Kindest Thing

Agreed, and I can prove that luxury hotels are mathematically literally very bad value

For the amount of "more" money you pay for this luxury, you should be getting way way way more than you actually get (as measured by ratings)

Aman should have an average rating of 9.5 but in reality barely hits an 8 on average, so they simply cannot produce the "luxury" experiences they are trying to market and brand themselves for

It's essentially all smoke and mirrors, and reflects my experiences completely, you pay 10x more and get either 0.5x-1.5x more (eg many times 2x worse, sometimes a bit better) not 10x better!

Other luxury chains are slightly better but none of them even get close to a 9 rating with the famous Ritz-Carlton being especially bad: its average rating is a 7.68 for a median price of $549/night, terrible!

Real value can be found with Okura, Minor, Melia and even Marriott. Okura is interesting because well known as luxurious but median only $143/night

So as I always say, luxury is mostly a scam, it doesn't exist and you're best off spending much less for much better value (and often better experiences too)

Source: my new site stats page hotelist.com/stats

The vibes in SF feel pretty frenetic right now. The divide in outcomes is the worst I've ever seen.

Over the last 5yrs, a group of ~10k people - employees at Anthropic, OpenAI, xAI, Nvidia, Meta TBD, founders - have hit retirement wealth of well above $20M (back of the envelope AI estimation).

Everyone outside that group feels like they can work their well-paying (but <$500k) job for their whole life and never get there.

Worse yet, layoffs are in full swing. Many software engineers feel like their life's skill is no longer useful. The day to day role of most jobs has changed overnight with AI.

As a result,
1. The corporate ladder looks like the wrong building to climb.
Everyone's trying to align with a new set of career "paths": should I be a founder? Is it too late to join Anthropic / OpenAI? should I get into AI? what company stock will 10x next? People are demanding higher salaries and switching jobs more and more.

2. There’s a deep malaise about work (and its future).
Why even work at all for “peanuts”? Will my job even exist in a few years? Many feel helpless. You hear the “permanent underclass” conversation a lot, esp from young people. It's hard to focus on doing good work when you think "man, if I joined Anthropic 2yrs ago, I could retire"

3. The mid to late middle managers feel paralyzed.
Many have families and don't feel like they have the energy or network to just "start a company". They don't particularly have any AI skills. They see the writing on the wall: middle management is being hollowed out in many companies.

4. The rich aren’t particularly happy either.
No one is shedding tears for them (and rightfully so). But those who have "made it" experience a profound lack of purpose too. Some have gone from <$150k to >$50M in a few years with no ramp. It flips your life plans upside down. For some, comparison is the thief of joy. For some, they escape to NYC to "live life". For others still, they start companies "just cuz", often to win status points. They never imagined that by age 30, they'd be set. I once asked a post-economic founder friend why they didn't just sell the co and they said "and do what? right now, everyone wants to talk to me. if i sell, I will only have money."

I understand that many reading this scoff at the champagne problems of the valley. Society is warped in this tech bubble. What is often well-off anywhere else in the world is bang average here.

Unlike many other places, tenure, intelligence and hard work can be loosely correlated with outcomes in the Bay. Living through a societally transformative gold rush in that environment can be paralyzing. "Am I in the right place? Should I move? Is there time still left? Am I gonna make it?" It psychologically torments many who have moved here in search of "success".

Ironically, a frequent side effect of this torment is to spin up the very products making everyone rich in hopes that you too can vibecode your path to economic enlightenment.