Thinking Tech Stocks

Microsoft Up, CoreWeave Down: The Market Just Decided Who Pays for the Data Centre Backlash

Thinking Tech Stocks — Wed, 04 Nov 2026 20:38:09 GMT

The tidy read of today’s tape is “money rotating out of speculative AI into quality AI”. That’s half right. The trigger was the election. A Democratic Congress, plus a pile of local votes against data centres, makes new AI capacity slower and harder to build. Traders worked out within hours who that hurts: the companies whose whole equity story is building that capacity with borrowed money. Microsoft has the customers, the backlog and the cash, so it can wait. Meta, usually lumped into the same “quality” bucket, is the awkward exception.

The tape

The Dow was up about 1,500 points, roughly 2.9%, on course for its best day since April 2025, after Democrats took both the House and the Senate. Big tech led. Microsoft and Amazon were up 6-7%, Apple about 6%, Alphabet 4-5%. Meta managed about 2% and Nvidia slipped.

The neoclouds went the other way. By midday CoreWeave was down 9%, IREN 11% and Nebius about 6%. CNBC put it down to Democratic wins in Texas and data centre rejections on ballots around the country. CoreWeave’s five-year credit default swaps widened to about 1,140bp, which is the bond market saying the same thing more quietly.

None of this came out of nowhere. Ballotpedia’s tally put 41 local data centre measures on Tuesday’s ballots across ten states, 17 of them calling for outright bans. All six decided earlier in the year went against development.

Why the same news splits the trade

A neocloud’s model is simple. Borrow, buy Nvidia GPUs, secure power and land, then rent the capacity to hyperscalers on long contracts. The equity is a bet on the next gigawatt, not the last one. Anything that slows permits or grid connections pushes revenue to the right while the interest keeps running. One analyst puts CoreWeave’s net debt at roughly $30bn. Musk, never one for understatement, said late last month that more than 200 neoclouds will collapse as debt markets shut them out.

Microsoft sits on the other side of those contracts. It is the customer, and last week it showed what delays look like from the buyer’s chair. Quarterly capex came in at $45.2bn against a consensus near $50.7bn because, in CFO Amy Hood’s words, “some third party capacity deliveries we expected in Q1 were delayed.” Calendar-2026 capex was trimmed to about $170bn. The neoclouds sold off after hours that night. Microsoft rose.

That is the asymmetry the market priced today. When building gets harder, the builder eats the cost. The tenant with a signed order book just spends less this quarter.

The quarter

Operating cash flow was about $58bn, so the capex bill is still mostly covered from the till.

One detail the bulls skip. Commercial RPO was $678bn at the end of June, so the backlog was flat on the quarter. The 73% is mostly last winter’s mega-deals, when it jumped from $392bn to $625bn in three months. Microsoft expects to recognise about 30% within a year, so call it $200bn of near-term revenue already signed. Still enormous. Just not still accelerating.

“Quality AI” is not one trade

Amazon belongs in the conversation. AWS grew 39% to $46bn, its fastest in nearly five years, and is on a $184bn run rate. But trailing free cash flow is negative $42.4bn, capex is about $220bn this year, and Jassy says 2027 will be “meaningfully more”. The stock fell more than 6% after results last week. Today’s bid looks political, not fundamental.

Meta is the harder fit. Revenue rose 26% to $64.6bn, but capex of $34.9bn exceeded $32.8bn of operating cash flow, leaving free cash flow negative for the quarter. It hasn’t bought back a share this year. Most of that spending serves Meta’s own ad machine, so there is no external backlog to point to. A 2% gain on a day like this suggests the market knows the difference.

Of the three, Microsoft is the cleanest version of the thesis: outside customers, a contracted backlog and positive free cash flow.

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Disclaimer: All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

I may hold, or have held, positions in any mentioned securities. Opinions herein are subject to change without notice. This material reflects my personal views and does not represent those of any employer or affiliated organization. Please conduct your own research and consult a licensed professional before making any investment decisions.

Partner or Predator? What Musk’s Terafab Really Means for Intel

Thinking Tech Stocks — Tue, 03 Nov 2026 15:39:10 GMT

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The bull case treats Terafab as a customer for Intel. I think the bigger story is that Terafab is buying something else from Intel: its people. To build a leading-edge fab from scratch, Musk needs the small group of engineers and managers who have done it before, and in America more of them work for Intel than anywhere else. If Terafab gets them, Intel keeps a licence fee and loses the capability behind it. The stock is still priced for the partner.

The deal Intel thought it signed

Musk launched Terafab on 21 March as a joint venture between Tesla, SpaceX and xAI. In April Intel joined, promising to design, fabricate and package Terafab’s chips at scale, and Musk later said the fab would run on Intel’s 14A process. That was the partner story, and it helped carry Intel to an all-time high of $142.35 on 30 June.

Then the scope shrank. Musk now says Tesla and SpaceX will build and run the fab themselves. That turns Intel from operator into process licensor. And it raises the obvious question: if you license the recipe, who does the cooking? The answer is whoever you can hire.

The first hire tells you the plan

In June, Tesla hired Gary Jiang as “Director, Terafab” in Austin, the project’s first named leadership hire. Jiang spent nearly 18 years at Intel. Since December 2024 he had been the factory manager responsible for moving 18A from Intel’s development fab in Oregon to high-volume production in Arizona: construction, tool installation, startup. Before that he ran ramps for Intel’s 22nm, 14nm and 10nm-class nodes.

Electrek summed it up neatly: Tesla is “acquiring fab competence one Intel veteran at a time.”

One name isn’t an exodus, and some analysts read the hire as good news for Intel. A licensee staffed by people who know Intel’s process is a more competent licensee. Fair enough. But look at what surrounds the hire.

The machine behind it

Tesla’s job postings are running roughly 50% above their 2025 average, and Musk has made a public call for chip engineers. Listings include lithography process engineers and programme managers for capital projects worth over $100m. Tesla is also recruiting in Taiwan for sub-7nm process experience, with reports of offers up to triple local pay. A Korean engineer has made similar, unconfirmed claims about recruiting at Samsung.

So Terafab is fishing in every leading-edge pond. But for a 14A fab in Texas, the most valuable catch is obvious. An Intel engineer in Oregon or Arizona already knows the process, needs no visa and doesn’t have to leave the country. A TSMC engineer in Hsinchu has to learn a new process and move continents. Intel’s workforce is the cheapest, fastest hire Terafab can make.

Why licensing makes it worse

A process licence is only partly a document. The rest is tacit knowledge: tool recipes, yield-learning habits, the playbook for what to do when a ramp goes sideways. That knowledge lives in people. Each time one of them moves to Terafab, the know-how moves too, and Intel’s leverage in the next negotiation falls.

The timing is ugly. Intel is trying to get 14A into risk production next year, and 14A is the node it needs outside customers for. It is also the node Terafab plans to license. The engineers who would ramp 14A for Intel are exactly the ones Terafab needs to ramp 14A for itself. In effect, Intel risks training its customer’s workforce on its own payroll.

Pay makes it harder still. Intel is competing for senior staff against Tesla and SpaceX equity, with a far higher ceiling and a founder who doesn’t lose bidding wars gracefully.

The national question

Intel is one of only three companies in the world producing 2nm-class logic, and the only American one. Washington has put CHIPS Act money into it and taken an equity stake, on the theory that the US needs a domestic leading-edge champion.

The generous reading of Terafab is that competition spreads know-how. Taiwan’s cluster works partly because engineers move between TSMC, its suppliers and its customers. The less generous reading is that the pool of people who can bring up a sub-2nm node is tiny, and splitting it between two American projects leaves neither fully staffed. Over the next three years, I lean towards the second.

The numbers

Q3 was decent on the top line: revenue of $16.5bn, up 21%, with data centre and AI up 78%. But Intel Foundry lost $1.9bn, and only $411m of its $6.7bn in revenue came from outside customers. In mid-October the stock still traded near 60 times forward earnings.

That multiple assumes the foundry becomes a real external business. A foundry is worth its process and its people. If the process is licensed out and the people follow it, what’s left is a very good CPU company priced like an AI platform.

The AI Trade Is Cracking From the Bottom Up. Here’s Who’s Next

Thinking Tech Stocks — Sat, 31 Oct 2026 19:39:08 GMT

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The weakest, most indebted part of the AI trade has cracked. This week, the hyperscalers’ own cash flow turned negative too. Selling like this tends to start with the most fragile names and then move to the expensive ones. Right now that means Dell, the analog chipmakers and the cybersecurity stocks priced for perfection.

1. The canary

The neoclouds borrow to buy GPUs and rent them out, so they are where the AI trade carries the most debt. CoreWeave lost more than a third of its value in October. Its worst day was a 15.5% drop on the 14th. The share price is the noisy part. The credit market tells you more. In mid-October, five-year default swaps on CoreWeave hit a record of roughly 1,195 basis points, which works out to about a 60% implied chance of default. Some of its bonds yield 15–16%. Equity holders don’t set the price when the bond market is pricing distress.

Nebius matters more, because it had no bad news of its own. It peaked near $300 in June and was below $160 by October 22. That’s a 47% drawdown, even though the stock is still up about 90% on the year. Its debt load looks nothing like CoreWeave’s, but the market sold it anyway. That’s contagion: the market stops telling companies apart. On October 14, Gartner added to the gloom with a forecast that more than 80% of neoclouds will stop operating independently by 2030.

2. The customers just blinked

This is new since the first draft, and it matters most. The whole AI supply chain depends on one group of customers: Amazon, Alphabet, Microsoft and Meta, which together plan roughly $735 billion of capex this year, up almost 80%. This week, three of the four reported negative free cash flow. Amazon’s outflow was about $42 billion. Alphabet’s was $9 billion, and the stock had its worst day ever. Meta’s was $2 billion, its first negative quarter since 2012, and it has since said it plans to raise up to $95 billion in stock. Microsoft was the only one still generating cash.

AI demand is still strong, so that isn’t the issue. The question is whether customers can keep spending at this rate without investors pushing back, and this week investors pushed back. Every chip, switch and server sold into this build-out depends on it continuing.

3. The Intel tell

Intel had a good quarter on October 29. Adjusted EPS was $0.52 against $0.38 guided, and gross margin was 44.1% against 42%. Then it guided Q4 revenue to $15–16 billion versus about $17 billion expected, partly because of a deadly incident at its Israeli fab. The stock fell about 21% after hours, to around $73. This is a stock that tripled from $36 to $128 in the first half. When a beat triggers a 20% drop, the stock was priced for something much better than good.

4. Macro isn’t helping

September CPI ran at 3.7% year on year. On October 28 the Fed held at 3.75–4.00% in a 10–2 vote, and both dissenters wanted a hike. Prediction markets now give a December hike roughly 70% odds. Long-duration growth stocks don’t hold up well when the Fed is debating hikes.

5. Who’s next

Dell. It more than quadrupled this year on AI servers, and neoclouds have been among its biggest buyers. Barclays downgraded it on October 14 and it fell 11% that day. Between late September and October 21 it slid from about $538 to $486, and its forward multiple compressed from 22x to 17x while earnings estimates held steady. So the earnings outlook didn’t change. Investors just stopped paying as much for it. There’s also a cost risk: Michael Dell has said the memory shortage could last four years, and Dell buys a lot of memory.

Analog (TXN, ADI). A cyclical recovery being valued like structural AI growth. Texas Instruments nearly doubled in the first half and peaked at about 40x forward earnings in June, its richest level in more than a decade. Then it posted a clean beat-and-raise, with revenue up 28%, and still sits 14% below the high at around 28x. Analog Devices trades north of 40x trailing earnings and doesn’t report until late November. It hasn’t been tested yet.

Arista. The strongest fundamentals in the group. It raised 2026 guidance three times to $12.6 billion, about 40% growth, and has more than 100 AI networking customers, up from a handful in 2024. It reports Tuesday, with consensus near $3.3 billion. The risk here is mostly about the multiple. A perfectly fine quarter that doesn’t raise guidance again could hit it the way Intel just got hit.

Broadcom, the exception. It already had its hangover. It fell almost 30% between June and mid-September and is roughly flat over twelve months. The thing to watch is that it has agreed to provide up to $42 billion of financing to Anthropic. Vendor financing is what’s hurting CoreWeave, though Broadcom is far stronger. It reports in December.

Cyber and cloud software. CrowdStrike rose almost 150% between late January and early October, while consensus revenue forecasts for the next five years moved less than 4%. Nearly all of that gain came from a higher multiple, not higher earnings forecasts. It then dropped 7% in a day as rates rose. Palo Alto ran above $430 in early October, fell to the mid-$300s and has bounced to about $388. It has also sold off after every report this year, even when results cleared the bar. Cloudflare trades at around 34x forward sales and 210x forward earnings ahead of its November 5 report. Snowflake is up about 55% this year, and its guidance moves the stock more than its beats do.

6. What I’m watching

Arista (Nov 3), Cloudflare (Nov 5), Nebius (around Nov 10). For Nebius, watch how much 2027 capacity customers are paying for upfront. Without those prepayments, it has to issue stock at depressed prices.

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Intel Loses $100 Billion in a Day: The Market Wants a Business, Not a Research Lab

Thinking Tech Stocks — Fri, 30 Oct 2026 16:58:25 GMT

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Q4 guidance was not. Data center revenue grew 78% and Intel still can’t build enough server chips to sell. Three days before results, it agreed to pay a reported $2.3bn for a quantum software start-up its chief executive had once backed personally. The market has started pricing Intel as a policy instrument rather than a chipmaker, and that discount may last.

On Friday Intel had its worst day in more than half a century. The shares fell close to 29 per cent from Thursday’s close of $92.07, taking more than $100bn of market value with them. The only comparable session in the company’s history is 5 July 1974, when the stock dropped 29.9 per cent.

The odd thing is that the quarter was fine. Revenue rose 21 per cent to $16.5bn, and adjusted earnings of 52 cents a share comfortably beat the 40 cents analysts expected. The guidance did the damage. Intel forecast fourth-quarter revenue of $15bn to $16bn against roughly $17bn expected, adjusted EPS of 25 cents against about 43 cents, and a 38 per cent gross margin where the Street had penciled in 42.

The bull case has arrived, and it is sold out

Data center and AI revenue reached $7.3bn, up 78 per cent on the year. That is the division’s fastest growth in 15 years, and it brought in about $3bn of operating profit. Management says its immediate priority is unlocking supply for its Xeon server processors, for which it calls demand “extraordinary”. So Intel is guiding revenue down while its best product is rationed.

Some of the shortfall is beyond Intel’s control. It expects client computing revenue to fall more than 20 per cent quarter on quarter, and management warned the PC slowdown will last through at least the first half of 2027. An accident at Fab 28 in Israel will take roughly $300m off the quarter. Most of Friday’s broker notes lead with the PC numbers, and that is fair: they are the immediate cause.

They are not the whole explanation. A stock that rose 278 per cent in the first half of the year was not priced on laptop shipments. It was priced on the belief that Intel would turn AI infrastructure demand into earnings. Friday’s guidance said the factory still limits that, so investors started asking where management’s attention is going.

Then came the quantum detour

On 26 October Intel signed a definitive agreement to buy Classiq, a Tel Aviv company that writes software for quantum computers. Intel kept the price to itself. Calcalist reported about $2.3bn in cash and stock, which would be the largest quantum acquisition yet, for a company of roughly 150 people that was valued at well under $1bn in its last funding round.

Two details got less attention than they should have. Lip-Bu Tan invested personally in Classiq before he ran Intel, joining its 2022 Series B. Calcalist says he recused himself from the talks, but Intel’s announcement did not mention his stake. Nobody at Intel claims the deal pays off soon, either. Tan calls quantum part of the company’s strategy for the next five to 10 years, and its chief technology officer admitted it won’t be a high-margin business from day one. Tan has also said quantum could be ten times bigger than AI.

He may be right, and $2.3bn is small next to a $16bn quarter. What matters is the signal. A chief executive who can’t meet demand for his server chips is spending capital, and scarcer management time, on a market that doesn’t exist yet, and he is buying a company he once backed with his own money. Shareholders don’t have to give that the benefit of the doubt. On Friday they didn’t.

Washington on the share register

The US government owns about a tenth of Intel. In August 2025 the administration converted $11.1bn of Chips Act grants and pledges into 433.3m shares at $20.47 apiece. With the stock down roughly $26 on Friday, my arithmetic puts the taxpayer’s one-day paper loss at around $11bn. There’s an accounting twist too. Benzinga estimates that because of how part of the government deal is structured, Friday’s fall could give Intel a pre-tax gain of about $3.4bn. When a company’s reported profit goes up as its shares go down, you are not looking at an ordinary equity.

Here is the thesis. A sovereign shareholder changes what management gets rewarded for. National champions are expected to build fabs at home, keep leading-edge manufacturing onshore and stake claims in strategic technologies such as quantum. Those are reasonable national goals, but they are different from earning a return on capital this decade. When the two conflict, a chief executive with Washington on the register has every incentive to choose the first. Friday’s selling looks like investors adjusting for that, valuing Intel less as a cash-flow business and more as a listed research institution with a state backstop.

Jensen’s Robot Duck Runs on a Chinese Chip: Inside the Microduck Supply Chain

Thinking Tech Stocks — Thu, 29 Oct 2026 02:49:38 GMT

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Jensen Huang ended his GTC Berlin keynote on October 21 not with a new chip but with four 25-centimeter robot ducks. At the Tempodrom, he asked them to walk, sit, nap and somersault. Most obeyed; one wandered off facing the wrong way, and Huang told it to stay focused. Business Insider called the finale charming “but not entirely obedient.”

The clip went viral. Two days later, Hugging Face CEO Clem Delangue posted that total Microduck preorders were about to cross 20,000, possibly making it the best-selling robot of 2026. That is on top of the more than 10,000 units sold in the first week after preorders opened on August 27.

In a corporate sense, the duck now belongs to Jensen. NVIDIA agreed in September to buy Hugging Face for $12.9 billion, and Hugging Face owns Pollen Robotics, the Bordeaux startup that designed Microduck. NVIDIA says the stage ducks were trained with AI agents on its RTX Spark laptops and cloud. Yet almost nothing inside the duck is NVIDIA’s. Its brain is a Chinese chip, its muscles are Korean, most of its senses are European, and it is put together in Shenzhen. And the part most likely to decide when buyers get one is not the chip at all.

The parts list

Pollen has not published a bill of materials, and its hardware design files are closed. But its robot software is open, and the code names the chips it talks to. The table below comes from that code, which describes Seeed’s production board as the “custom board’s first spin”, so later units could still change. Where the code is silent, it says so.

The brain: a budget Rockchip

Microduck thinks with a Rockchip RK3566, a quad-core Arm Cortex-A55 chip clocked up to 1.8 GHz, paired with 1 GB of RAM and 32 GB of storage. Rockchip trades on Shanghai’s A-share market, and the chip’s cores are licensed from Britain’s Arm. Pollen says it chose the part for its onboard neural processing unit, which it rates at 1 TOPS; CNX Software lists 0.8 TOPS.

Rockchip’s footprint is bigger than one chip. The development ducks ran on a Radxa Zero 3W, a cheap single-board computer from Shenzhen’s Radxa. Production units move to a custom RK3566 board from Seeed Studio, and Pollen’s code shows that board using Rockchip’s RK809 power-management chip to drive the speaker as well. Rockchip, based in Fuzhou, reported first-half 2026 revenue of 2.88 billion yuan, up about 41 percent.

This is modest silicon, the kind found in budget single-board computers. It doesn’t need to be more. On the robot, a handful of Rust daemons run a 50 Hz loop that drives the servos straight from small neural policies. The expensive part, training those policies, happens off the duck, in simulation on a PC or in the cloud. That is where NVIDIA sits in the stack: its Isaac Sim and Isaac Lab tools and RTX hardware. Pollen’s own workflow also runs the MuJoCo physics engine in a browser.

The arrangement matches what Huang promised when he bought Hugging Face: that NVIDIA compute would not be required to build on or deploy through the platform. Microduck is that promise with legs.

Rockchip’s investors noticed. After the August launch, its shares surged 10 percent one day and closed another 4.6 percent higher the next. Omdia chief analyst Lian Jye Su calls Rockchip a key edge-AI supplier, but notes its chips lack the computing headroom for complex edge AI devices. For a duck running compact walking policies, that ceiling may not matter yet. It could matter once owners start training ambitious new tricks.

The muscles: Korean servos, and the real bottleneck

The most expensive part of the duck is not Chinese. Each Microduck walks on 15 Dynamixel XL330 servos made by ROBOTIS, a KOSDAQ-listed company in Seoul. Pollen’s control code is written for the XL330 throughout, and its training stack models that servo’s friction and delay so policies learned in simulation work on the real joints. A sixteenth device on the same serial bus is a small Pollen board carrying the body’s motion sensor.

The choice is a loyal one. Pollen co-founder Matthieu Lapeyre says Dynamixel “has been used for a long time” and has proven reliable in small robots, and Pollen has put ROBOTIS motors in almost all of its products. Retail, an XL330 sells for about $27, which would put 15 of them above the duck’s $399 price. Pollen pays far less. Korea Investment & Securities valued 50,000 ducks’ worth of servos at about 15 billion won; other Korean reports put the deal near 20 billion won. That implies roughly $14 to $19 per servo, or somewhere around $210 to $285 per duck.

That is why Seeed founder Eric Pan says “there isn’t much margin in this duck.” It is also where production hits a wall. On October 26, Lapeyre visited ROBOTIS’s Seoul headquarters to sign for 750,000 actuators, enough for 50,000 ducks, and said Pollen expects to need about 1 million next year.

ROBOTIS cannot build them yet. Its annual capacity is about 500,000 units, according to Hanwha Investment & Securities, and its order backlog already topped 500,000 in September. Chief executive Kim Byoung-soo says the Seoul plant is “running at maximum capacity” and that serving Pollen means reshuffling other customers’ orders. He expects to fully handle the new demand from the second quarter of 2027. A new ROBOTIS factory in Uzbekistan is due to start in the first half of 2027, but Newspim reports it will prioritize larger actuators for humanoid robots, not the tiny XL330.

The senses: mostly European

The sensors are where Europe shows up. Four chips come from STMicroelectronics, the Franco-Italian group headquartered in Geneva.

• Depth: a VL53L8CX, the 8×8 time-of-flight sensor Pollen markets as LiDAR. It fires infrared pulses and times their return across 64 zones. ST says its FlightSense sensors are made at its 300mm wafer fab in Crolles, France.

• Balance: two LSM6DSV16X IMUs, one on a face board in the head and one on the body board. The chip fuses its own orientation readings, which spares the RK3566 that work.

• Touch: an ST25R100 NFC reader, launched in 2024 as a low-cost part, drives the antennas in the head and beak that read NFC tags.

Prototype ducks used other parts: a Bosch BMI088 motion sensor and Sony’s IMX219 camera sensor, the one in Raspberry Pi’s v2 camera. Production swapped the Sony part for a GC2093 from GalaxyCore, a fabless Shanghai firm that ranked second worldwide in image-sensor shipments in 2019. The GC2093 is a 2-megapixel, 1080p sensor with 2.8-micron pixels, the kind sold in low-cost USB webcams. Pollen’s code notes the camera tuning comes from Seeed.

Power, radio and the rest

The remaining parts are commodities, and Pollen names none of their makers.

• Battery: a removable two-cell lithium-ion pack in the NP-F550 format, 2,600 mAh, good for about an hour. Sony created the NP-F shape for camcorders, and dozens of firms now make compatible packs. That makes it one of the easiest parts to source, and lets owners swap in spares.

• Wireless: still unnamed. The prototypes used an AIC8800 Wi-Fi and Bluetooth chip from China’s AICSemi, but Pollen’s own setup scripts say that radio “is not what ships.”

• Audio: prototypes used a Texas Instruments codec. Production ducks play sound through the Rockchip RK809 and record through a microphone on the face board.

• Body: neither company has said who makes the molded shell, brackets, cables or the gamepad in the box.

Made in Shenzhen

The duck is built by Seeed Studio, the Shenzhen hardware house that has made boards and kits for makers since 2008. Bloomberg reported the arrangement at launch. Seeed founder Eric Pan later told GeekPark that Microduck’s prototype was built on Seeed’s own open-source hardware, and that Pollen had been a Seeed customer for years before Hugging Face bought it.

Seeed also builds Reachy Mini, Pollen’s desktop robot. Pan describes the split simply: Pollen focuses on “their design, their knowhow, their software,” and Seeed runs what he calls a “curated supply chain for robotics.” Going through Seeed, he says, was “probably a good deal more efficient” than Hugging Face sourcing parts itself. To hit $399, Seeed used its volume to negotiate with upstream suppliers and engineered costs out of the design. But its pitch is agile manufacturing, which it advertises as running from a single unit to more than 10,000. Microduck’s order book is already past twice that top figure.

Put together, the map is global but lopsided. The duck is designed in Bordeaux and owned, via Hugging Face, by a California chip giant. Its brain and camera come from mainland China, its sensors mostly from a Franco-Italian chipmaker, and its 15 motors from Seoul. Final assembly happens in southern China. A supply chain spread that wide is cheap and well tested. It also means the slowest supplier sets the pace.

The Christmas math

For most buyers, the answer is already in: no. Pollen launched with a promise to ship before Christmas 2026 in North America and Europe. As of October 28, the Microduck store page carries a new banner. It says production is ramping up, but current preorders should expect to ship after April 2027, first ordered, first shipped.

That leaves the before-Christmas target for the earliest August buyers, and even that depends on a first run that has not shipped yet. Some details, including camera resolution, LiDAR range and SDK languages, were still listed as provisional in Pollen’s press kit. Delangue has also posted that Pollen and Hugging Face need to hire across every function to keep up with Microduck and Reachy Mini.

The new date is not a mystery once you follow the parts. Rockchip chips and ST sensors are high-volume catalog items, and Seeed has a production line ready. The tight link is Seoul. ROBOTIS says it can fully serve Pollen from the second quarter of 2027, and Pollen’s store now promises shipments “after April 2027.” The two timelines match. Until then, every duck Pollen ships depends on how many servos ROBOTIS can shift away from its other customers.

For NVIDIA, the delay barely dents the win. Huang got a viral keynote moment for physical AI, and every duck that ships will be trained on NVIDIA’s tools. It will just do its waddling on a Chinese chip and Korean motors, probably sometime next spring.

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From 8,700 to 60,000: Microsoft Is Buying Out Its Workforce to Pay for the AI Race

Thinking Tech Stocks — Tue, 27 Oct 2026 15:55:23 GMT

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The offer

Microsoft has a new way to shrink: ask first, then cut. On October 26 it offered voluntary exit packages to about 60,000 employees, roughly 27% of a global workforce of about 223,000, according to CNBC. It is the company’s second buyout program of 2026, and seven times the size of the first.

The offer covers staff at vice president level and below in the United States, Canada, India and the United Kingdom. Not every team qualifies. Tech Insider reports that some sales, marketing, engineering, corporate-function and data center groups are excluded. Employees get standard, location-based severance plus career-planning help. They have until early December to decide, and those who accept leave at the end of the year.

One number matters more than the headline, and nobody has it yet: how many say yes. Sixty thousand is the pool, not the exit count. At a 10% take-up, about 6,000 people leave. At the one-third rate Microsoft saw in the spring, about 20,000 do, more than the roughly 15,000 jobs it cut across two layoff rounds in 2025.

The test run

Microsoft has run this play once already. In April it announced the first voluntary buyout in its 51-year history, a retirement offer to about 8,750 U.S. employees at senior director level and below whose age plus years of service reached 70. Staff on sales incentive plans were left out.

The result came in July. In a blog post, chief people officer Amy Coleman said about 30% of eligible employees chose to retire. The same post announced 4,800 job cuts, about 2.1% of the global workforce, across sales, consulting and Xbox.

The order is the tell. Business Insider reported that the July layoffs were smaller than they would have been because the retirement program had already thinned the ranks. HR Executive read the sequence as Microsoft using the buyout to measure acceptance, working out the remaining headcount gap, then cutting to close it. Buyouts first, layoffs second.

Two ways to pay

Every hyperscaler has the same problem: AI data centers cost more than operating cash flow covers. They are choosing different answers.

Oracle went to the capital markets. In February it became the first hyperscaler to raise money on the public equity side, selling a $5 billion mandatory convertible preferred and filing for a $20 billion at-the-market stock program, alongside a $25 billion bond deal. IFR reported that the package funds about $50 billion of planned capex while protecting Oracle’s investment-grade rating. The cost lands on shareholders as dilution and on the balance sheet as debt. Oracle has cut staff too, but its signature move was financial.

Microsoft is taking the opposite route. Its capital spending is running far higher, with the company expecting roughly $190 billion in calendar 2026. Rather than follow Oracle to the equity market, it is leaning on cost. CFO Amy Hood told investors in April that headcount had fallen year over year and would fall again in fiscal 2027. Payroll is a software company’s largest operating cost, and Microsoft is turning it into data center budget.

Why the race costs so much

Both companies are chasing Amazon and Google, and the gap is partly silicon. Google has spent years on its Tensor Processing Units and has begun selling them directly. Amazon’s Trainium chips are winning large customers; Anthropic alone has deals for about one million Trainium and TPU accelerators. Owning the chip lets a cloud provider control the cost of every AI query instead of paying Nvidia’s margins.

Oracle has no in-house AI chip. Microsoft does, but it started late. Its Maia line is widely seen as less mature than Trainium or TPU. The third-generation Maia 300 is slated for deployment in 2027, Microsoft is seeking TSMC capacity for more than 300,000 of them, and unlike its rivals’ chips, outside customers cannot rent it. Until it scales, Microsoft keeps buying Nvidia and AMD hardware at full price. That is the bill the buyouts help pay.

Are layoffs next?

If the spring pattern holds, yes, and the size depends on the take-up. Microsoft has a headcount target for fiscal 2027. The December deadline will tell it how much of that target volunteers cover. Whatever gap remains is the likely size of the next involuntary round, plausibly early in 2027.

There is a risk in letting staff choose. People with the best outside offers are the most likely to leave, which is why Microsoft fenced off data center and some engineering teams. Watch three things: any acceptance figure Microsoft discloses, a restructuring charge in coming earnings (the spring program cost about $900 million, per GeekWire), and whether new WARN notices appear in Washington state after January.

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Why Meta Is Selling $95B of Stock Instead of Issuing Bonds

Thinking Tech Stocks — Tue, 27 Oct 2026 03:17:00 GMT

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Meta just launched one of the largest stock sales in corporate history, and it is paying for AI with shares instead of borrowed money.

On Monday the company opened about $35 billion of underwritten common stock and mandatory convertible preferred offerings. It also plans to sell up to $60 billion more of a new non-voting Class C stock through an at-the-market program starting in 2027. That brings the total to as much as $95 billion.

For a company that spent years buying back its own stock, this is a sharp reversal. So why stock and not bonds? Here are eight reasons, starting with one theory you probably won’t hear on CNBC.

1. The talent-war theory (my take)

The same morning Meta announced its raise, Anthropic publicly filed for its IPO. Its shares could start trading on Nasdaq before Thanksgiving, and there is speculation it could raise around $100 billion at roughly a $2 trillion valuation.

That matters for the AI talent market. Once Anthropic employees can sell their shares, some will cash out and leave. Meanwhile, researchers being recruited today may hesitate to take equity priced at a valuation that already looks stretched.

Here is where Meta comes in. Heavy spending plus a steady supply of new shares tends to keep a stock price in check. A lower share price means a fixed-dollar stock grant buys more shares, which leaves new hires more room to profit if the stock rises later. Meta’s CFO has even said the new Class C stock is usable for employee compensation.

To be clear, Meta has never said recruiting is a reason for the raise. This is speculation. But the timing is hard to ignore.

2. Debt is getting expensive

Meta is not short of borrowing options. It sold a record $30 billion bond deal last year and another $25 billion of notes in May. But borrowing costs have climbed. Meta still carries an AA credit rating, yet its 30-year bonds reportedly yield above 7%, which makes selling stock look comparatively cheap.

3. Protecting the credit rating

More debt could also put that AA rating at risk. According to reporting on the deal, a Meta special committee acknowledged that borrowing on this scale could hurt its credit ratings. A downgrade would raise the cost of every future bond Meta sells.

4. Cash flow turned negative

This is the number that changes the story. In Q3, Meta reportedly spent $34.91 billion on capital expenditures against $32.79 billion of operating cash flow. That would be its first negative free-cash-flow quarter in over a decade, and buybacks have dropped to zero in 2026. With capex guidance as high as $145 billion this year, the cash has to come from somewhere.

5. Zuckerberg keeps control

Selling tens of billions in stock normally dilutes the founder’s vote. Meta solved that by creating a new non-voting Class C share, effective in January 2027. The entire $60 billion at-the-market program will use those shares, and Meta’s committee reportedly said Zuckerberg would not back a raise that diluted his control. Investors get the economics; Zuckerberg keeps the votes.

6. The chip suppliers are buying in

Nvidia, AMD and Broadcom have expressed interest in buying up to $5 billion of the new Meta shares. It is a circular arrangement: the companies selling Meta its AI chips help fund the purchases, and Meta keeps buying their hardware.

7. Selling while the price is high

Equity is cheapest to raise when your stock is richly valued. Investor Craig Shapiro argues that issuing shares at Meta’s current valuation beats piling on more high-interest debt. Meta also gets flexibility: it can settle the forward sales of its common stock on dates it chooses, as late as November 2027.

8. Getting ahead of the line

Investor capital is finite, and the queue is long. Google, SpaceX and soon Anthropic are all tapping the markets for money. Alphabet already raised about $85 billion in stock this summer. By moving now, Meta grabs its share of investor demand before a record-sized Anthropic IPO soaks up attention and cash.

The bottom line

Most of Meta’s reasons are plain corporate finance: debt is pricey, the credit rating is worth protecting, cash flow has gone negative, and the stock is valued well enough to sell. The non-voting shares keep Zuckerberg in charge, and the chipmakers’ participation keeps the hardware flowing.

But the timing invites a bigger question. On the same day Anthropic opened its books to public investors, Meta lined up nearly $100 billion to stay in the AI race, and a new class of stock it can hand to employees. Whether that’s coincidence or strategy, the fight for AI talent and capital just moved to Wall Street.

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AI Sell-Off Rocks Asia as Money Rotates to Robots: Unitree Leads the Physical AI Rebound

Thinking Tech Stocks — Sat, 24 Oct 2026 15:52:49 GMT

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Asia’s AI trade cracked again this week, but not every AI stock went down with it. On Thursday, chipmakers dragged Seoul, Hong Kong and Tokyo sharply lower. In Shanghai, humanoid-robot maker Unitree Robotics finished the week up more than 46%, capped by its first 20% limit-up since listing.

The split suggests investors are not abandoning AI so much as moving down the stack: from the chips that train models to the machines meant to put them to work.

Chips take another hit

Thursday’s selling started in Asia. Korea’s Kospi fell 3.52% to 5,533.77, with Samsung Electronics down 4.03% and SK Hynix down 5.49%. Hong Kong’s Hang Seng dropped about 3%, and Japan’s Nikkei 225 lost 2.6% to 62,907.84.

The trigger was a fresh round of doubt about AI spending. Mixed results from US tech giants, Meta’s in particular, revived the question of whether data-center budgets will pay off. The selling reached Wall Street later that day, where the Nasdaq fell 2.6%.

This was an aftershock, not the main quake. The week before, from October 12 to 15, the 20 most valuable AI and semiconductor stocks lost more than $1 trillion in market value as rate-hike fears, AI debt and Chinese memory competition hit at once. By October 15, the Kospi sat about 21% below its September high.

Unitree leads the robot rebound

Robotics moved the other way, and Beijing gave it the push. On Monday, October 19, China’s Ministry of Commerce and eight other departments called for more supply of smart goods, robots included, and for embodied AI in home services and commercial logistics. Traders read it as the first-time embodied AI had appeared in national commerce policy.

Unitree jumped 16.15% to ¥495.92 that day, its best session since its August 19 debut, excluding the first day of trading. Its market value climbed back above ¥200 billion.

The rally kept building. At a partner conference in Hangzhou on Thursday, chairman Wang Xingxing laid out plans to scale up manufacturing, build AI models for Unitree’s own hardware and invest in computing clusters. The company also unveiled the H2-X, a humanoid pitched as a personal bodyguard. On Friday the stock hit its 20% daily limit at ¥624, valuing Unitree at ¥252.4 billion (about $37.9 billion). The wider sector rose with it: the Wind Humanoid Robot Index gained 6.16%.

The joint makers split

The money did not flow evenly down the supply chain. Harmonic Drive Systems, the Tokyo-listed maker of the strain-wave gears that act as robot joints, fell about 9.6% on Thursday to ¥4,875. It sold off with the chip stocks, not with the robot makers.

Part of the reason is who buys its gears. Harmonic’s reducers go into industrial robots but also semiconductor equipment, so the stock tends to trade with the chip cycle. It now sits about 47% below its July high of ¥9,150, yet still trades at roughly 160 times trailing earnings.

Its biggest Chinese rival had a very different Friday. Suzhou Leader Harmonious Drive Systems, known as Leaderdrive, jumped 12.05% to ¥290 as the humanoid rally spread to suppliers. J.P. Morgan estimates it holds 30% to 40% of China’s harmonic-reducer market, with humanoid makers UBTech and Agibot among its customers. Investors are treating Leaderdrive as a domestic humanoid play. For now, they are not treating Harmonic that way.

Safe haven or the next bubble?

The bull case is that robotics has what the chip trade lacks right now: direct policy support and earlier-stage growth. China built 794,781 industrial robots in the first nine months of 2026, up 29.1% from a year earlier. Unitree’s first-half revenue rose 48.54% to ¥1.152 billion, and unlike loss-making rival UBTech, it turns a profit.

The bear case is valuation and volatility. Unitree’s net profit excluding one-off items fell 19.34% to ¥244 million in the first half. Bank of America rates the stock Underperform with a ¥350 target, and the average analyst target of about ¥486 sits well below Friday’s close. The shares already went from a ¥150.80 IPO price to a peak near ¥1,100, then slid to ¥404 before this rebound. Leaderdrive and Harmonic both trade at triple-digit earnings multiples too.

So robots are not a safe haven in the way bonds are. They are a different bet on AI, and just as exposed to swings in sentiment.

Earnings will start to answer it

Three reports over the next three weeks will test whether the robot rotation rests on sales or on sentiment.

For Harmonic Drive, the slide has opened a wide gap to analysts’ average target of ¥7,597, about 55% above Friday’s ¥4,895 close. That is the buy-the-dip case. It holds only if the November numbers show robot demand reaching Japan’s joint maker, not just China’s.

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Disclaimer:All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

Smoke and Thrusters: Why Tesla’s Roadster Stunt Is Really a Merger Pitch

Thinking Tech Stocks — Fri, 23 Oct 2026 11:31:46 GMT

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Tesla’s new Roadster is a merger advertisement with a steering wheel, and its timing says more about Tesla’s valuation than about its engineering.

Last Thursday, at SpaceX’s test site in McGregor, Texas, Tesla finally showed the car it first promised in 2017. It drove upside down along a ramp using suction, launched itself, barrel-rolled in midair and landed on ten cold-gas thrusters fed by roughly 250 kilograms of compressed air. Later it hopped a line of six vehicles, including a Semi cab. The “Thrust” edition takes a $250,000 deposit. Production is promised for 2028.

It was a spectacular show, but the product barely mattered. The real message was in the hardware: SpaceX parts in a Tesla body, at a SpaceX site, with a mannequin in a SpaceX suit at the wheel. Deepwater’s Gene Munster read the night the same way, as fresh evidence that Musk is impatient to combine the two companies. The question is why now.

A valuation built on two bets

Tesla is not priced as a carmaker. By various analyst counts it trades at around 200 times expected 2026 earnings, while net income has been falling. Bank of America’s sum-of-the-parts model attributes about 45% of Tesla’s value to Robotaxi and 19% to Optimus. Strip those out and the multiple has nothing to stand on.

The first bet, autonomy, is suffering from its own success. Back in 2020, Tesla’s former Autopilot hardware chief Jim Keller argued on Lex Fridman’s podcast that driving is closer to a ballistics problem than skeptics assume: track objects, predict their paths, act. Fridman pushed back on the messy human element, but the industry has since moved toward Keller’s view.

That is good news for riders and bad news for Tesla’s moat. Tesla’s big bet was an “end-to-end” system. Instead of engineers hand-writing rules for every situation, one neural network watches millions of hours of human driving and learns to turn camera images straight into steering and braking. Once the world knows that works, it stops being a secret. Anyone with enough driving data and computing power can follow the same recipe, and the engineers who built Tesla’s version have spread across Silicon Valley. Tesla’s unsupervised robotaxis in Austin, Dallas and Houston prove the approach works. They also prove it can be copied. A solved problem becomes a commodity, and commodities do not earn 200-times multiples.

Optimus has company

The second bet, Optimus, faces rivals who are already shipping. On the April earnings call, Musk said Fremont would begin Optimus production in late July or August. By mid-July, an industry review found it had not started.

Meanwhile, Figure’s robots are on BMW’s Spartanburg line, billed by the operating hour, and its BotQ plant turns out a new unit roughly every 90 minutes. In China, Unitree shipped more than 5,500 humanoids in 2025, about a third of the global market by units, and lists its G1 on Amazon for under $18,000.

Unitree’s robots doing kung fu and backflips at this year’s Spring Festival gala looked like a stunt. Its business is still mostly sales to universities and labs, and its first-quarter profit fell by half. But stunts are how this category starts. Unitree sits inside the world’s densest supply chain for motors, actuators and batteries, backed by a deep engineering bench and state support. When the next generation of physical-AI models makes humanoid software broadly available, the winner may be whoever builds the cheapest reliable body. That race does not obviously favor Tesla.

Why merge before the repricing

If both bets are losing their edge, Tesla’s premium is worth most today. That is where SpaceX comes in. SpaceX absorbed xAI in February, then raised a record $75 billion in a June IPO that valued it at $1.77 trillion. Starlink gives it something Tesla’s story lacks: a cash-generating near-monopoly, with $1.66 billion of connectivity operating income in the second quarter alone.

Musk has stopped dismissing the idea. On Tesla’s July earnings call he cited growing overlap with SpaceX and said any combination would need a proper process. On October 14, Barclays analyst Dan Levy suggested a deal could be announced before Tesla’s annual meeting, due by December 6. Barclays sees an all-stock acquisition of Tesla by SpaceX as the likeliest structure, with an illustrative ratio of about 0.7 SpaceX shares per Tesla share.

The math explains the urgency. In an all-stock deal, Tesla’s share of the combined company depends on Tesla’s price at signing. Merge at today’s multiple and Tesla holders get a large slice of a company anchored by rockets and satellites. Wait until the market reprices autonomy and robotics, and that slice shrinks. Musk, who holds far more voting control at SpaceX than at Tesla, would also tighten his grip on the whole. The flying Roadster is the pitch to the shareholders who would have to approve it.

What would prove this wrong

This is an argument about motive, and Musk may simply love rocket cars. The thesis weakens if Tesla’s robotaxi fleets hit the 50%-plus gross margins management promises, or if Optimus reaches paying outside customers in 2027 ahead of Figure and Unitree. It also weakens if December passes without a deal.

Until then, watch the proxy filings more closely than the deposit page. No merger agreement has been confirmed. But the Roadster’s thrusters were never really pointed at the road. They were pointed at Tesla’s shareholders, and the clock they are racing is the one on Tesla’s multiple.

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Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

Meta’s Earnings Pop Fizzles as AI Selloff Drags Stock Lower Despite Blowout Quarter

Thu, 22 Oct 2026 20:37:33 GMT

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Meta Platforms just delivered one of the strongest quarters in its history, and Wall Street still sold the stock. After reporting third-quarter 2026 results after the bell on Wednesday, October 21, Meta shares surged nearly 8% to just below $749 in after-hours trading. By Thursday morning, that rally had evaporated. As Nasdaq 100 futures fell and Asian chip stocks slid, Meta stock dropped to around $676 in premarket trading, almost 10% below its after-hours peak and beneath Wednesday’s closing level.

The reversal shows how the market is now judging Big Tech: a revenue beat is no longer enough when the price tag on artificial intelligence keeps climbing.

A Blowout Quarter by Almost Any Measure

On paper, Meta’s Q3 2026 earnings were hard to fault. Revenue jumped 26% year over year to a record $64.6 billion, well ahead of the roughly $63.3 billion analysts expected. Advertising did the heavy lifting: ad impressions across Meta’s Family of Apps rose 10%, while the average price per ad climbed 14%, a sign that AI-driven ad targeting is helping advertisers get more for their money.

Earnings beat too. Diluted EPS came in at $3.83 against estimates near $3.57, and the company issued upbeat guidance for the current quarter. Losses at Reality Labs, Meta’s metaverse and hardware unit, also narrowed.

So why did the stock fall?

AI Spending Fears Hit the Whole Tech Sector

The biggest factor was the cost of Meta’s AI ambitions. The company expects 2026 capital expenditures of $135 billion to $145 billion as it pours money into data centers and computing power, while infrastructure and third-party AI token costs are rising fast. Full-year 2026 expenses are now forecast at $175 billion to $179 billion, up from a prior range of $165 billion to $169 billion.

The cash impact is now visible. Meta reported negative free cash flow of about $2.12 billion for the quarter, the first time it has burned cash on that basis since 2012.

That worry wasn’t unique to Meta. Overnight, investors grew more skeptical of the broader AI trade, dragging down Nasdaq futures and chipmakers across Asia. Tesla also gave back an initial post-earnings gain, and Netflix had disappointed earlier in the week. Rising oil prices and jitters in European bond markets added to the risk-off tone.

A $9.9 Billion Legal Charge Clouds the Profit Picture

Meta’s headline profit was also weighed down by a one-time legal charge of $9.89 billion, tied to an agreement reached in August with a coalition of U.S. state attorneys general. The charge, which also accounts for most of the increase in the full-year expense outlook, pushed quarterly costs up 68% to $51.6 billion and cut operating income 37% to about $13 billion. Operating margin fell to 20% from 40% a year earlier.

Excluding the charge, the picture looks very different: operating income would have risen 11% to $22.88 billion, and EPS would have been $7.40. Still, a charge equal to roughly 15% of quarterly revenue is a reminder that legal and regulatory risk, especially around youth safety, remains a real cost for the company.

Meta’s New Non-Voting Share Class

Meta also surprised investors with plans for a new class of non-voting Class C stock. Every shareholder will receive one Class C share for each share they own, effectively a 2-for-1 stock split, with trading expected to begin in late January 2027.

The structure gives Meta a new currency that could help fund its AI buildout without diluting CEO Mark Zuckerberg’s voting control. Filings also indicate Zuckerberg may sell up to 20% of the non-voting shares he receives. For some investors, that raised fresh governance questions at a company where minority shareholders already have limited say, and market reports pointed to the plan as one more reason traders turned cautious.

What Investors Are Watching Next

Technical traders are focused on support near $673 to $675. A sustained break below that zone could deepen the selloff, while reclaiming the $694 to $698 area, roughly where the stock closed before earnings, would suggest buyers are stepping back in.

The next big test for the AI trade comes soon. Microsoft and Alphabet report on October 28, followed by Amazon on October 29. Their numbers on cloud growth and AI spending will show whether Meta’s reversal was a one-off or part of a broader shift in investor sentiment.

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The Bottom Line

Meta’s core business is firing on all cylinders, with record revenue, rising ad prices and a stronger outlook. But the market wants proof that the company’s massive AI spending will pay off. Until investors see clearer returns, even blowout quarters may not be enough to keep Meta stock moving higher.

Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

Hyperliquid and Lighter Go Mainstream: Trump’s Nod and Robinhood’s Bet Bring On-Chain Perps to the Masses

Thinking Tech Stocks — Wed, 21 Oct 2026 23:05:24 GMT

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For most of their short history, on-chain perpetual futures were a playground for crypto power users: airdrop hunters, high-leverage traders and anyone willing to bridge funds onto an unfamiliar chain. In 2026, that changed fast.

A presidential shout-out for Hyperliquid at the White House and Robinhood’s decision to plug Lighter directly into its wallet have pulled decentralized perps out of the crypto niche. They are now part of conversations at the highest levels of US policy and inside one of the best-known retail trading brands in the world.

What are on-chain perpetual futures?

Perpetual futures, or “perps,” are leveraged derivatives with no expiry date. Traders can hold a long or short position indefinitely, while a periodic funding rate keeps the contract price anchored to the underlying asset.

Perps are the most liquid product in crypto, but almost all of that trading has historically happened offshore. On-chain perp exchanges like Hyperliquid and Lighter run their order books on their own blockchains. Users trade from a self-custody wallet instead of handing funds to a centralized exchange, and every trade settles transparently on-chain.

Trump puts Hyperliquid on the map

On August 19, 2026, at a White House meeting with crypto and tech executives, President Trump said CFTC Chairman Michael Selig was working to bring Hyperliquid into the US “in a fully compliant and legal fashion.” SEC Chair Paul Atkins and White House crypto adviser Patrick Witt were also in the room.

Markets reacted within hours. Hyperliquid’s HYPE token jumped more than 20% that day, and shares of Nasdaq-listed Hyperliquid Strategies (PURR), a company built around holding HYPE, rose as much as 31%. The same day, Coinbase’s Base App launched Hyperliquid perpetual trading. HYPE went on to set an all-time high near $98 on September 23.

The remarks did not amount to regulatory approval, and US residents still cannot trade on Hyperliquid. But they landed on prepared ground. On May 29, the CFTC approved the first US-listed bitcoin perpetual contract on Kalshi and cleared Coinbase to offer perps through its offshore arm. Selig has argued that the lack of a domestic pathway pushed perps liquidity overseas, and he has made onshoring it a priority.

Hyperliquid is the obvious prize. It handled roughly $203 billion in 30-day volume in early October, per DefiLlama data cited by Delphi Digital, and held about 58% of on-chain perp open interest in the third quarter. Analysts see a licensed market built on its HIP-3 builder-deployed framework as one likely route into the US.

Robinhood’s bet on Lighter

If Hyperliquid got the political spotlight, Lighter got distribution. On July 1, 2026, Robinhood launched Robinhood Chain, an Ethereum layer-2 network built on Arbitrum, and a revamped Robinhood Wallet that routes perpetual futures to Lighter for eligible users in selected markets.

The setup is simple for the user. They deposit the USDG stablecoin from Robinhood Wallet as margin and trade Lighter’s markets without leaving the app. Robinhood and Lighter reportedly split the revenue 50/50, and Lighter set aside $11 million in LIT tokens as incentives, with double points for trades placed through Robinhood Wallet.

The relationship runs deeper than a routing deal. Robinhood Ventures backed Lighter’s $68 million raise in November 2025. Founded in 2022 by Vladimir Novakovski and live on mainnet since October 2025, Lighter runs an order book whose matching is verified with zero-knowledge proofs. It charges ordinary accounts no trading fees and lists stocks, commodities and FX alongside crypto.

Lighter calls the Robinhood integration its first “Domain”: rather than winning users one by one, it becomes the engine beneath someone else’s front end. The model appears to be working. Lighter posted about $56 billion in 30-day volume in early October, a figure Delphi Digital notes likely includes Robinhood Chain flow.

There is one major catch. Lighter perps in Robinhood Wallet are not available to residents of the US, UK, Canada, Switzerland, the UAE or Singapore. That could change. Reports on October 21 said Lighter plans to apply for a US license in November and may pursue an integration with Robinhood’s US platform if approved. Lighter has not confirmed the reports, but LIT climbed about 20% on the news.

Two paths to the same destination

Hyperliquid and Lighter are taking different roads toward mainstream adoption. Hyperliquid is the liquidity leader, and its path runs top-down through Washington: regulators building a compliant on-ramp for a platform that already dominates the market. Lighter is going bottom-up, borrowing Robinhood’s brand, app and user base to reach traders who would never seek out a standalone DEX.

Both stories point the same way. Perps are no longer something US policymakers want to push offshore, and on-chain venues are no longer just for crypto natives. The infrastructure, the political will and the retail distribution are lining up at the same time.

The risks haven’t gone away

Mainstream access does not make perps any less dangerous. They are leveraged products, and liquidations are automatic. When bitcoin jumped 7.1% intraday on August 19, nearly $2.7 billion in short positions were wiped out.

On-chain venues also carry smart contract risk, and the US rulebook is still being written. CME Group CEO Terry Duffy has opposed treating perpetual contracts as futures, and broader market structure legislation is still pending in Congress. For now, a presidential comment is a signal, not a license.

What to watch next

• CFTC action on Hyperliquid: any formal pathway, such as a licensed HIP-3 market, would turn Trump’s words into access for US traders.

• Lighter’s US license bid: a November filing would be the first concrete step toward Robinhood perps for American users.

• More approved US perps: each new CFTC-cleared contract widens the lane that on-chain venues hope to join.

• Retail volume: whether Robinhood Wallet flow keeps lifting Lighter’s share against Hyperliquid.

The bottom line

A year ago, on-chain perpetual futures were a niche product for crypto insiders. Today, Hyperliquid has been named by the president, Lighter is running inside Robinhood’s wallet, and US regulators have approved domestic perps for the first time. The masses are not fully on board yet, especially in the US, but the doors are opening faster than almost anyone expected.

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Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

Meta Earnings October 21: What Q3 2026 Results Mean for the AI Spending Boom

Thinking Tech Stocks — Mon, 19 Oct 2026 14:24:54 GMT

Meta Platforms reports third-quarter results this Wednesday, and the number that matters most may not be revenue or earnings. It’s capital spending. The company will release results after the market close on Wednesday, October 21, with a conference call at 1:30 p.m. PT / 4:30 p.m. ET. For investors trying to judge whether the AI infrastructure build-out is still accelerating, few reports carry more weight.

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The ad business is the easy part

Meta’s core business has been strong. The company guided third-quarter revenue to between $61 billion and $64 billion, assuming roughly a 1% currency headwind. Analysts expect about $63.3 billion. Bank of America is more bullish, projecting $62.2 billion in advertising revenue, which would be 24% year-over-year growth, and says its checks show AI-powered targeting is helping advertisers get better returns.

Earnings will look messier. Meta expects to book roughly $10 billion in legal expenses in the quarter, tied to a multistate youth-safety settlement, and that charge was not included in the expense outlook Meta gave investors in July. Expect a headline EPS miss that has little to do with the underlying business.

Capex is the real story

Meta has raised its spending plans repeatedly this year. In January it guided 2026 capex to $115–135 billion. In April it lifted that to $125–145 billion, citing higher component pricing and data center costs for future capacity. In July it narrowed the range to $130–145 billion.

The strain is showing in cash flow. Second-quarter capex hit $31.1 billion, nearly double the $17.0 billion spent a year earlier, while free cash flow fell to just $784 million. Shares dropped roughly 8–10% after hours on that report. Morningstar notes that the full-year guide implies about $40–47 billion of capex per quarter in the second half, which likely pushes free cash flow negative.

The 2027 question

The biggest swing factor is next year. Meta gave no 2027 capex guidance last quarter, and the October report is historically where the company has introduced the following year’s spending plan, with the market often selling the capex number before reacting to revenue. Last year’s precedent is sobering: the stock fell 11.3% on October 30, 2025, after a one-time tax charge and a bigger capex plan.

Expectations are already high. Consensus for 2027 capex sits around $185.6 billion, and Bank of America recently raised its 2027 forecast to $205 billion. Options traders are bracing for volatility, pricing in a roughly 6% move in the stock.

Why the whole market is watching

Meta’s guidance is effectively a demand signal for the entire AI supply chain. Its spending outlook tends to move chip and data center stocks the next morning. A 2027 figure at or above $200 billion would suggest the AI build-out is still gaining speed. A number closer to consensus, or more talk of “flexibility,” could be read as the first sign of a plateau.

Investors will also listen for new ways to pay for it all. Morningstar is watching whether Meta announces a signed deal to sell compute to an outside customer, which would give the infrastructure spend a revenue line beyond advertising.

The bottom line

A revenue beat looks likely. The real verdict on Wednesday will come from the capex guide: how big 2027 gets, and how convincingly Meta explains the return on it.

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Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

The Neocloud Debt Treadmill Hits a Wall

Thinking Tech Stocks — Sat, 17 Oct 2026 19:51:34 GMT

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The week the bond market blinked

For most of 2026, credit markets lent CoreWeave whatever it asked for. This week they stopped. On Wednesday, October 14, the company’s unsecured bonds fell to prices that usually signal distress, pushing yields past 15%.

Thursday was worse. The 9.75% notes due 2031 yielded 15.78%, some bonds traded near 79 cents on the dollar, and five-year credit default swaps hit a record 1,194.5 basis points. At that level, swaps price in better than a 60% chance of default within five years.

The stock followed the bonds. CoreWeave closed Wednesday at $65.78, down 15.5%, its worst day since going public. It bounced Thursday, then fell about 11% more on Friday. Chamath Palihapitiya flagged the yields online; Elon Musk replied “yikes.”

CEO Mike Intrator told staff in an internal memo that the market was behaving irrationally and that CoreWeave’s contract backlog more than covers its debt. He may be right about the backlog. But the bond market isn’t pricing demand. It is pricing the treadmill: the need for CoreWeave, and every neocloud built on its model, to borrow ever more, ever faster, at whatever rate the market sets that week.

How the treadmill works

The neocloud model is easy to state. Sign a multi-year capacity contract with a hyperscaler or AI lab. Borrow against that contract and the Nvidia GPUs it will run on, typically at 60–70% of the hardware’s value. Build the data center, then repay the loan from the rent.

The catch is that growth means running the loop faster than it pays down. CoreWeave guides 2026 capital spending of $35–39 billion against revenue of $12.4–13.2 billion. Its debt and lease obligations reached about $52 billion at the end of June, up from roughly $15 billion of debt a year earlier. It held about $5.5 billion in cash. Roughly $4.4 billion comes due by the end of this year and $6.2 billion in 2027.

The collateral makes the loop tighter than it looks. GPUs lose value as each new Nvidia generation ships, so a lender’s security shrinks while the loan is outstanding. Rental rates for older chips have fallen as supply caught up with the 2023–24 shortage. A neocloud therefore has to keep refinancing on good terms. That works only while rates hold still and investors stay keen. In the past month, neither has.

Why rates broke the rhythm

The Federal Reserve raised its benchmark rate a quarter point on September 16, to 3.75–4.00%. It was the first hike since July 2023 and the first move under Chair Kevin Warsh, and most officials pencilled in one more before year end. Long yields had already climbed: the 10-year Treasury touched about 5.17% in late September, its highest since 2007.

Higher base rates are not CoreWeave’s main problem on their own. Its filings put the cost of a one-point rise on its floating-rate debt at roughly $30 million a year. The damage comes from how much it has already borrowed, and from the price of everything it still needs to borrow.

Interest expense has risen every quarter, and the third-quarter guide is roughly four times guided adjusted operating income. CoreWeave lost $626 million in the second quarter on record revenue, close to what it paid its lenders.

New money now costs more too. The 2031 notes carry a 9.75% coupon but trade to yield nearly 16%, and any fresh unsecured issue would have to pay something similar. The treadmill is speeding up just as each step gets more expensive.

It isn’t just CoreWeave

The rout landed in a week already primed for doubt. Five days earlier, on October 9, the Nvidia-backed Australian neocloud Firmus pulled its planned ASX listing, which had aimed to raise about $5 billion. Investors balked at a balance sheet expected to carry roughly $30 billion of debt against a 2028 operating-earnings forecast of $5 billion. Firmus is now exploring a $2–3 billion private round. Days later, Blackstone-backed AirTrunk delayed its own Singapore IPO.

Then on October 14, the same day CoreWeave’s bonds broke, Gartner published a blunt forecast. It expects AI providers to spend nearly $1 trillion on infrastructure in 2026 and another $6 trillion from 2027 to 2030. It sees AI revenue attributable to those data centers reaching only about $3.6 trillion by 2030, against roughly $8.5 trillion needed to justify the spending. More than $3.5 trillion of assets could face write-downs. Its headline for this industry: by 2030, more than 80% of neocloud providers will cease to operate independently.

The spillover showed up fast. Nebius, IREN and Dell sold off. Oracle fell nearly 9%, with its 2032 notes yielding about 7.24%. By Friday, Bloomberg was reporting that junk-bond buyers were increasingly shutting out tech startups seeking financing. That matters more than any one company’s share price. High-yield debt is the fuel the smaller neoclouds run on.

CoreWeave’s case, and why it spooked bondholders

The bull case is not imaginary. Second-quarter revenue was $2.6 billion, up 112% from a year earlier. The contracted backlog reached $104.2 billion, before more than $25 billion of new commitments signed early in the third quarter. Co-founder Brannin McBee says nearly all of CoreWeave’s 2027 capacity is already sold. Even skeptical analysts concede that demand for the compute is real.

Management’s answer to the financing problem is to borrow against its customers’ credit rather than its own. In March, CoreWeave closed an $8.5 billion loan secured by GPUs and a Meta contract that Moody’s rated A3. It was the first loan of its kind to reach investment grade. In a Financial Times interview published October 14, McBee said the goal is to make more chip-backed debt investment grade, and eventually the company itself. That would open the door to insurance-company money, a pool he described as “unlimited.”

Bondholders heard something else. The plan meant still more borrowing. And if the best contracts and newest chips are pledged to ring-fenced, investment-grade vehicles, less is left for unsecured creditors at the parent. Bloomberg tied Thursday’s record swap spreads directly to the insurer talk. The strategy may well lower CoreWeave’s average cost of capital. It does so by putting the unsecured bonds further back in line.

Independent landlords, or tenants’ subsidiaries?

The likeliest answer is that most neoclouds will keep their own names while ceding the economics to someone bigger. There are three ways that happens, and they are already under way.

Owned by the tenant’s credit. The cheapest neocloud money is now priced off the customer, not the neocloud. On October 1, Lambda closed a $1 billion GPU-backed loan at a 6.78% fixed rate, rated investment grade and tied to a Microsoft leasing deal. CoreWeave’s own unsecured paper yields more than twice that. The gap is the market’s price for the neocloud’s name. When the tenant’s balance sheet sets the cost of capital, the landlord keeps a thin operating spread, and the tenant holds the leverage at renewal. Microsoft alone accounted for roughly two-thirds of CoreWeave’s 2025 revenue.

Owned by the supplier. On July 1, Nvidia launched what it calls the AI Compute Partnership. It agrees to rent back a neocloud’s unused GPUs at a fixed rate, and in return takes a share of the cloud revenue on that capacity. Firmus and Sharon AI were among the first takers. Nvidia already holds roughly 9.3% of Nebius and has a $6.3 billion capacity agreement with CoreWeave. The backstop makes clusters bankable. It also makes Nvidia supplier, guarantor, customer of last resort and equity holder at once, which looks less like independence than a franchise.

Owned outright. Gartner’s “cease independent operations” explicitly includes being acquired. Hyperscalers are the obvious buyers: Alphabet, Amazon, Meta and Oracle had issued more than $228 billion of bonds this year at investment-grade rates. But they rent from neoclouds partly to move fast and keep capital spending off their own books. Buying a heavily indebted landlord would undo both benefits. A distressed sale of data centers, power contracts and GPU fleets at a discount is the more plausible path, along with neoclouds buying each other, as Nscale did when it agreed to acquire Anyscale.

CoreWeave itself is an unlikely takeover target, though not because it is too big to buy. A buyer would inherit its liabilities and its contracts with rivals like Meta, who would not want their compute owned by a competitor. Its realistic future is to borrow against its tenants’ credit: independent on paper, but increasingly a financing conduit for its customers’ contracts. The smaller operators, running on junk debt and IPO hopes, are the ones more likely to end up leaning on Nvidia’s backstop or sold off in pieces.

What to watch

The bear case is not that AI demand disappears. It is that the cost of financing it reprices faster than contracts can absorb. A few markers will show which way this goes:

• The Fed, October 27–28. A second hike would raise the floor under every refinancing; a pause would buy time.

• CoreWeave’s year-end maturities. About $4.4 billion falls due by December 31. Whether it rolls that debt, and at what price, is the cleanest test of market access.

• Its next earnings report. Watch interest expense against operating income, and whether capital spending guidance holds or gets cut.

• Credit spreads. Five-year swaps near 1,200 basis points and unsecured yields near 16% need to stabilize before cheap funding returns. Any widening in investment-grade hyperscaler spreads would mean the worry is spreading up the ladder.

• The pipeline of neocloud deals. Firmus’s private round, the IPO plans of Lambda and Nscale, and take-up of Nvidia’s backstop will show who can still raise money on their own name.

If those markers turn, CoreWeave’s bonds will look like the buying opportunity of the cycle. If they don’t, Gartner’s 80% may prove conservative, and the AI-compute landlords will end up working for the companies that pay their rent.

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Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

Everyone Is Building Roblox Now

Thinking Tech Stocks — Fri, 16 Oct 2026 02:53:41 GMT

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Roblox got the model right

Roblox got the business model of modern gaming right, and the rest of the industry is now converging on it. The bet was simple: games would stop being finished products shipped by studios and become worlds hosted on a platform, then built, remixed and modded by the people who play them.

The formula has five parts: one portal, one persistent identity and avatar, user-made games, a virtual currency, and a revenue share. Together they form a flywheel. Creators attract players, players buy Robux, and Robux pay creators to build more. Roblox never has to fund the next hit; it just hosts it, and the next hit can come from anyone. In Q3 2025, seven experiences passed 10 million daily users at some point, and five of them were less than a year old.

The numbers show the flywheel spinning. Creators earned more than $1.5 billion through the Developer Exchange in 2025, and Roblox estimates its share of global gaming spending rose from 2.3% to 3.2% in a year. The model is also aging up: daily users over 18 grew 32% year over year in Q2 2026, and Roblox now pays creators 42% more on spending by verified U.S. adults to keep them.

The rivals are copying it

Epic has built the most faithful copy. Since launching Unreal Editor for Fortnite (UEFN) in 2023, it has paid creators over $1 billion. Creator-made islands now draw 47% of Fortnite playtime, up from 38% a year earlier, and more than 75% of in-game transactions happen outside battle royale. In January, Epic added in-island purchases, Roblox’s other revenue stream, and more than 3,000 islands now earn more from them than from engagement payouts. Unreal Engine 6 will fold UEFN into the professional engine, so a hobbyist’s island and a studio’s game will share one toolchain. Fortnite is no longer a game. It is a portal.

Microsoft is turning its catalog into raw material. Its Muse model, trained on seven years of Bleeding Edge play, generates gameplay and controller input, and Microsoft has released its weights to developers. On October 13, Xbox CEO Asha Sharma launched Xbox Labs, a small team led by CTO Scott Van Vliet, after fans used AI to decompile classic games and run them in browsers and on new hardware. Her stated goals are to make games easier to reach, give old ones new life, and let more players become creators. That is the Roblox pitch applied to the Xbox back catalog. What Microsoft still lacks is a single portal to host it.

Google is building the creation layer. DeepMind’s Genie models went from 2D worlds in March 2024 to Genie 3, which generates explorable 3D worlds at 720p and 24 frames per second. Project Genie, opened in January to U.S. subscribers of Google’s $250-a-month AI Ultra plan, lets anyone sketch a world from a prompt or photo and walk through it. Sessions last only 60 seconds, and Google says it is not a game engine. It is a creation engine still looking for a portal, an economy and creators to pay.

Sony is the holdout, still betting on the finished blockbuster. Its 2026 business report dropped its pledge to bring first-party games to PC, and Ghost of Yotei, Saros and Marvel’s Wolverine are reportedly staying on PlayStation. But the community is converging without Sony: modders have built a fan PC “remaster” of Demon’s Souls, a game Sony never released on PC. Its catalog is becoming remix material whether Sony blesses it or not.

AI makes the model inevitable

Fans already use AI to decompile and rebuild classics: the original Halo has been recompiled to run 128-player matches, and other projects mash franchises together into new games. Roblox’s Cube model has produced 1.8 million 3D assets since March 2025, and its 4D tool lets players conjure drivable cars and flyable planes inside a game. Epic now lets AI agents operate the UEFN editor directly.

This is why AI strengthens the Roblox model rather than threatening it. When making a game gets cheap, games become abundant, and value moves to what stays scarce: an audience, discovery, a shared identity, and a way to get paid. A platform owns all four. Every AI breakthrough adds supply to platforms like Roblox; none of them replaces the platform.

The open questions are real. Generated worlds remain short and glitchy, and 52% of developers in GDC’s 2026 survey say generative AI is hurting the industry. Nobody has settled whether original developers consented to their games becoming training data, or who gets paid when a remix borrows their assets. Reverse-engineering sits in a legal gray zone, and Microsoft has so far promised only to treat IP responsibly.

The three-way race

If everyone is building the same model, the winner will be decided on three fronts.

• Infrastructure: a persistent world for tens of millions of players at once is a hosting problem first. Roblox is adding server authority and custom matchmaking so competitive shooters and racers can run on it. Epic already runs one of the largest live games on earth. Microsoft and Google own hyperscale clouds but no portal to fill them.

• Tools: the winner needs a ladder from prompt to professional engine. Roblox Studio plus Cube covers the bottom rungs. Epic’s UE6 covers the top, built on its Verse language and open to outside AI models. Google has the most impressive world generator but nothing to ship it into.

• Creator economics: payouts decide where talent goes. Epic routes about 40% of Fortnite’s shop revenue into a pool split by engagement. Roblox raised its cash-out rate 8.5% in September 2025 and adds 42% on adult spending. Both economies are lopsided: the median Roblox DevEx creator earned $1,440 in the year to June 2025. Whoever spreads the money wider wins the middle class of creators.

The verdict

Roblox was right about the model, and the scale gap proves it: Roblox paid creators $1.5 billion in 2025 alone, while Epic has paid $1 billion across three years of UEFN. But being right doesn’t guarantee winning.

My bet is Epic, the only copycat strong on all three fronts: servers proven by a global hit, a path from Fortnite islands to a professional engine, payouts already past $1 billion, and licensed worlds like Star Wars for creators to build in. Microsoft has the catalog without the portal, Google has the AI without the platform, and Sony is building walls. Whoever wins, gaming’s future will run on Roblox’s blueprint, and it will belong to whoever makes creators richest.

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Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

Bending Spoons Is Not Berkshire Hathaway: Buying Moats vs. Milking Melting Ice Cubes

Thinking Tech Stocks — Wed, 14 Oct 2026 19:41:05 GMT

Luca Ferrari likes the comparison. Around its July Nasdaq listing, he told Forbes that Bending Spoons (BSP) is “the best of both worlds” of Berkshire Hathaway and a technology company. Public investors now have to price that claim. It does not hold.

Ferrari has himself conceded the key difference: Berkshire buys businesses it likes as they are and lets their managers run them (Milano Finanza). Bending Spoons does close to the opposite.

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Moats versus lock-in

A moat is a durable advantage, such as a brand customers love or a rail network no rival can copy, that protects profits for decades. Berkshire buys those at See’s Candies or BNSF, keeps the managers and lets the business compound.

Buffett’s test goes further. A great business is one so strong that it needs only competent management, not brilliant management: in his words, businesses “so wonderful that an idiot can run them” (Fortune). Bending Spoons inverts that. Its returns depend on exceptional operators, and on paying the right price for the right target, deal after deal. Ferrari says the magic is “almost completely operating” (Sequoia). That is closer to venture capital than to Berkshire: a string of bets, each of which must be won. And the formula is young. Its buying spree began in earnest only in 2023 (Forbes); Berkshire’s has been tested for six decades.

Bending Spoons buys users who find it costly to leave. Meetup is the playbook in miniature. Bought in January 2024, its US team was cut and operations moved to Europe (Silicon Republic). Organiser prices then rose. Appfigures estimates Meetup’s mobile revenue climbed from about $55,000 a month to $291,000 by January 2026, while downloads barely moved. A beloved but stagnant community, harvested rather than grown.

The pattern repeats. Evernote’s annual personal plan nearly doubled and its free tier was capped at 50 notes (Carly). WeTransfer lost 75% of its staff weeks after the deal. Vimeo, bought for $1.38bn, shed a large part of its workforce within months of closing.

The arithmetic of a melting ice cube

Pay $100m for an app that yields $20m a year after the cuts. If price rises cannot fully offset churn and cash flow shrinks 10% a year, the deal pays back in year seven and returns $200m in total, undiscounted. At a 20% annual decline it never quite pays back; at 25% it returns only $80m. Pricing power built on lock-in is not a moat. It is a countdown, and churn sets the clock.

The treadmill also speeds up. Second-quarter revenue rose 126% to $704m, but organic growth, meaning growth from the same businesses year on year, was just 3%, down from 13% in 2025 (Q2 results, prospectus). To move the needle BSP must buy ever bigger: AOL for $1.5bn, Tractive for $759m, Airtable for $1.29bn and, pending, Miro for $1.36bn. Net debt reached $4.09bn at June. Quarterly interest expense roughly tripled to $109m, against $240m of operating income.

Can it grow what the founders couldn’t?

That is the real test. These products were sold because their builders had stopped growing them, mostly for market reasons rather than cost. Vimeo spent years struggling against YouTube (TechCrunch); Evernote had struggled for years before its sale (TechCrunch). Leaner teams do not fix lost markets. And BSP lays off the people who knew each product best, then claims it can grow it better.

So far the evidence leans towards extraction. Remini grew on more monthly users, which is real organic growth. But in Q2, Remini and Splice shrank. Appfigures estimates Evernote’s revenue rose 39% while its downloads fell 64%. Fewer users paying more is not growth in Berkshire’s sense.

The counterargument is serious. BSP does rebuild: it rewrote Evernote’s ageing software (IBTimes) and cut Vimeo’s stability incidents by about 90%. It has never sold a material business, and revenue per employee reached $2.57m in 2025. Some of these apps might otherwise have died. Constellation Software, a permanent owner of niche software, is the fair comparison, not Berkshire.

The verdict: for now, Bending Spoons is a superb harvester, not yet a compounder. Airtable, which Ferrari says is still growing, is its first real test.

What to watch

Investors who want to know which story is true should watch five numbers. The first is organic growth split into more users versus higher prices: BSP reported 3% organic growth in Q2 but does not disclose the split. The second is churn and retention by product, which set how long each ice cube lasts and are also undisclosed.

The third is leverage. Net debt was 2.4 times adjusted EBITDA, a measure that counts cost savings BSP still expects to make. The fourth is interest cover: Q2 operating income covered interest expense only about 2.2 times. The fifth is the price paid against cash flow on each deal. Airtable cost about 2.7 times its revenue, and bigger targets mean fewer bargains.

Figures are from BSP’s Q2 2026 results unless linked. Appfigures data are mobile-only estimates. The size of the Meetup layoff and Meetup’s purchase price have not been disclosed.

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Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

SaaSpocalypse 2.0: The Moat Was Never the Code (ADBE, MSFT, INTU)

Thinking Tech Stocks — Sun, 11 Oct 2026 17:14:51 GMT

Round one priced in fewer seats. Round two prices in the product being copyable. When an AI can rebuild your flagship app from the user manual, your multiple stops being a “software” multiple and starts being a “stuff anyone can make” multiple. The survivors own things you can’t prompt: users, data centers and physical hardware.

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1. Recap for the apes who just got here

Jefferies’ Jeffrey Favuzza named it. Anthropic’s Claude Cowork launched on 12 January 2026, and the S&P Software & Services Index lost roughly 25% by late February. The thesis was arithmetic: agents do the work, companies buy fewer per-seat licenses, revenue compresses. Painful, but survivable. You can reprice from seats to usage. Everyone wrote that memo.

2. Why round two is structurally worse

Round one attacked the pricing model. Round two attacks the product. The market has spent 20 years paying 10x revenue for software because writing it was expensive and switching was painful. Both assumptions just broke in the same week.

Exhibit A: ADBE

Brandon Thomas and his company ArtCraft released seven open-source programs replicating Adobe’s suite, built with Claude Opus 5.5 in Rust, free under MIT and Apache 2.0 licenses, running on Windows, Linux and macOS. PhotoCraft, the Photoshop clone, passed 23,000 GitHub stars within about a week.

The bull will tell you it’s junk, and he’s not wrong today: Thomas walked back his promise of full parity in a month, current parity is estimated at 25–35%, and users report problems with basic editing, shortcuts and performance. But you don’t price the alpha build. You price the slope. The apps shipped multiple new releases within days of launch. Adobe ships annually. This thing ships daily.

Exhibit B: MSFT

Same playbook, bigger target. WordCraft claims 87% coverage of Word’s ribbon commands and about 62% real feature parity, while GridCraft covers about 93% of Excel’s worksheet functions. Office’s moat was never Word’s code. It was .docx compatibility and 30 years of muscle memory, and a model trained on public specs reproduces both. Meanwhile Microsoft’s response to pressure was raising commercial Office prices by up to 33% in July. Raising prices while a free clone closes the gap is a fascinating choice.

The nuance: MSFT is not ADBE. Azure, enterprise identity and procurement inertia mean Office could lose consumers and still keep the Fortune 500 for years. This is a multiple story, not a death story.

Exhibit C: Games (SONY)

Hundreds of AI-decompiled game ports have appeared in a matter of weeks, because Opus 5.5 turns out to be extremely good at decompiling, rebuilding source in record time. Today it’s older titles. But look at the timing: Sony just cut its pledge to bring first-party titles to PC from its SEC annual report, to protect PS5 hardware. If recompilation scales to modern games, exclusivity becomes a legal moat, not a technical one, and legal moats are slower and more expensive to defend.

Exhibit D: INTU

Tax software is rules plus forms, which is precisely what models are best at. As of June, Intuit was the worst performer in the major indices, down 58% year to date, and it had laid off about 17% of its workforce.

3. Who survives

Ask one question: can this be rebuilt from public documentation? If yes, it’s getting rerated.

What can’t be prompted: network effects, physical infrastructure, atoms. You can clone Instagram’s UI over a weekend; you cannot clone three billion users or the data centers that serve them. And META is moving into hardware: Zuckerberg unveiled the Muse Charm, a palm-sized device for Meta’s Muse AI agent, at Connect in September, then launched Muse Gadgets, an open-source project for building hardware that connects to Muse. Note the irony: Meta open-sources the cheap layer (software) to sell the scarce layer (users plus devices).

4. What’s priced in

More than the bears admit. In June, Adobe traded at 8.3x forward earnings versus a five-year average of 25, and Intuit at 11.6x versus 34. Revenue is still growing double digits, with Intuit at 12% and Adobe at 10%, even as the stocks have been cut in half or worse. So the question isn’t “is AI a threat,” it’s whether the market has priced zero switching costs, not just fewer seats. My view: round one priced the first, not the second.

5. What would make me wrong

Patent lawyers. Adobe holds thousands of patents on software features and mechanics, and a few injunctions could chill the clone ecosystem.

Pros don’t switch. Enterprise workflows, plugins, color management and compliance are the last 30% of parity, and the last 30% is where the real work lives.

Incumbents eat the tech. Adobe and Microsoft have the same models available. If they cut prices and ship faster, the clones become a pricing ceiling, not an extinction event.

Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

ADBE: On the Erosion of Moats, or Why the Smart Money Is Holding the Bag

Thinking Tech Stocks — Thu, 08 Oct 2026 21:46:30 GMT

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In one week Adobe had its green-card pipeline frozen by Washington, watched one developer clone seven of its flagship apps with AI, and remained a top holding of an investor whose other contrarian longs have cratered. The moat is not breached. It is merely shallower than the share price once assumed.

I. Washington discovers PERM

On 8 October, Labor Secretary Keith Sonderling suspended eight companies from the PERM green-card programme: six IT outsourcers (Cognizant, Infosys, TCS, Wipro, HCL, Capgemini) plus Microsoft and Adobe, the latter pair “due to multiple active federal investigations.” New applications will not be accepted, and pending ones will not be processed. Subpoenas have been served; no end date has been given.

For Adobe, that means H-1B engineers stuck in a frozen queue during an AI hiring war, and an open-ended risk factor. It also stacks neatly on a $75m DOJ settlement over hidden cancellation fees, a UK CMA probe and a revived US class action.

II. One man, many agents, seven clones

Developer Brandon Thomas says he “vibe coded” open-source Rust replacements for Photoshop, Illustrator, Premiere, Lightroom, After Effects, InDesign and Acrobat. His motive: Adobe’s cancellation fee. Corporate karma rarely arrives so neatly.

The flagship, PhotoCraft, reads PSD files and exposes 500+ commands to AI agents. It is also early alpha, reportedly under 50% Photoshop-compatible, its one-month parity promise already walked back, and a plausible trade-dress target. Nobody cancels Creative Cloud on Monday.

The point is the cost curve. What once took a funded team years took one person weeks. Good enough at zero is awkward for a subscription priced like a gym membership, and AI agents have neither muscle memory nor brand loyalty. Goldman and Oppenheimer downgraded on similar logic earlier this year.

III. Beats that no longer matter

Fiscal Q3 (Jun–Aug): revenue up 13% to $6.76bn, ARR of $27.5bn, a beat and a raise. The shares fell almost 4% to about $239, far below a 52-week high of $370.86, on marginally soft Q4 guidance. When a beat-and-raise sells off, the market is pricing terminal value. Add a CEO succession and $6.82bn of buybacks in nine months, which flatter EPS without deepening the moat. On the forum: the company buying its own bags.

IV. The Burry problem

Burry’s Adobe stake, made public in April near $227, has gone roughly nowhere. Elsewhere, Lululemon, his largest holding, is down more than 50% this year; he calls it the “trickster” of his book. Flutter, bought in July, fell 11% on a guidance cut and CEO exit before he sold the lot. By his own test, a stock falling on fear is a buy and one falling on fundamentals is not. A federal freeze plus collapsing clone costs looks like fundamentals.

Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

Could Oracle's Tencent Deal Pop the Neocloud Bubble?

Thinking Tech Stocks — Wed, 07 Oct 2026 01:55:12 GMT

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A single rental contract may have just told investors what an AI chip is really worth, and the answer is not flattering for the neoclouds. Oracle has reportedly agreed to rent Tencent roughly 100,000 AI chips for about $1.60 per GPU-hour. Neoclouds like Nebius and CoreWeave are valued on the belief that GPU-hours stay scarce and expensive. A hyperscaler-scale deal at that price challenges the premise just as prominent investors are warning the AI trade has run too far.

A $1.60 price tag

According to the Financial Times, as summarized by Tom’s Hardware, Tencent signed a five-year, roughly $7 billion lease for chips in Oracle’s Southeast Asian data centers, paying about 30% upfront. Spread over five years, that works out to about $1.60 per chip-hour. That is roughly 43% below Semi Analysis’s ~$2.80 one-year H100 rate and about 48% below a $3.09 three-year B200 contract Data section disclosed in 2025.

Neither company has named the chips, and Tom’s Hardware argues the math fits older Hopper-class hardware. But that is cold comfort for neoclouds. Their fleets were largely debt-financed on the assumption that rents would hold well above that level. If the market-clearing price for a 100,000-GPU, five-year commitment is $1.60, those assumptions look generous. Oracle has its own reasons to discount: its free cash flow was deeply negative last fiscal year, and upfront cash helps. A cash-hungry hyperscaler willing to undercut on price is exactly the competitor neoclouds cannot match.

Venture veterans see a bubble

The deal lands as some of venture capital’s most experienced investors are sounding alarms. Doug Leone, who led Sequoia Capital for nearly three decades, has said plainly that we are in an AI bubble.

Insight Partners co-founder Jerry Murdock went further on the 20VC podcast, as reported by BigGo Finance. He predicted that, if the Iran conflict keeps festering, a credit dislocation could burst the bubble between late October 2026 and March 2027. Murdock’s point is that the infrastructure is real but the debt funding it is fragile. Hyperscalers, he argued, are best placed to survive a shock. Neoclouds are not: he expects at least half of them to disappear within 36 months.

Burry doubles down

Michael Burry is putting money behind the same view. He disclosed a short on Nebius in August and, after its earnings, questioned the pricing of its compute contracts and its move to stretch server depreciation from four years to five. On September 28 he swapped his Nebius short for June put options with double-digit strikes, far below the roughly $240 share price. He said he was moving his timelines up and wanted more leverage, a bet that only pays on a steep fall.

The Oracle-Tencent price is exactly the kind of evidence Burry’s thesis needs. If rental rates fall faster than neoclouds depreciate their chips, the profits on paper never turn into cash.

Nebius’s COO cashes out

Then came Nebius’s own insiders. On October 5, Chief Operating Officer Ophir Nave sold 500,000 Class A shares at roughly $231 to $244 each, about $118 million in total, according to his Form 4 filing. That cut his directly held stake from about 955,000 shares to 454,685, more than half.

The filing offers context. The sale ran under a Rule 10b5-1 plan adopted May 22, and Nave says it equals about 17% of his total granted equity. Pre-scheduled plans weaken the signal. Still, timing is hard to ignore: the sale landed days after Burry’s bigger bet and the same week the Oracle-Tencent price became public.

What to watch

None of this proves the bubble is popping. Demand is still strong: Oracle reported 97.9% GPU utilization in September, and BNP Paribas recently upgraded Nebius with a $399 target. But the bear case now has a price point, a timeline and an insider sale attached to it.

The next test comes fast. Oracle holds its Investor Day on October 28, where it could reveal which chips Tencent is renting. That lands inside Murdock’s October-to-March window. If the hardware turns out to be newer than Hopper, $1.60 an hour stops being a discount on old chips and becomes the new market rate. For neoclouds priced for scarcity, that would be the pin.

Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

$TCEHY: Tencent's Meta moment, and the Oracle lease investors have overlooked

Thinking Tech Stocks — Tue, 06 Oct 2026 15:45:21 GMT

$TCEHY

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• Thesis. Tencent’s established businesses are growing operating profit at 19% on a 42% margin. Reported growth is 9% because roughly RMB 10.5 billion a quarter is being spent on new AI products.

• Valuation. At HK$421 the shares trade at about 13 times forward earnings, against a consensus target near HK$664. Investors are capitalising the cost of the AI programme and assigning little value to its output.

• Catalyst. A reported five-year, $7 billion lease of 100,000 chips from Oracle addresses the group’s binding constraint, compute supply, at an implied cost of about $1.60 per chip-hour.

• Precedent. Meta in October 2025: a highly profitable core, a sharp rise in capital spending, and an abrupt de-rating.

The setup

When Meta told investors last October that its spending on artificial intelligence would keep rising, its shares lost roughly 11% in a single session. Tencent is experiencing a slower version of the same repricing. The stock closed at HK$421.20 on October 2. In March it stood at HK$515, itself the result of a 6% fall on the day management said AI investment would double. Morgan Stanley lowered its target to HK$550 in August while keeping an overweight rating, and Citi’s target is HK$765. Analysts, in other words, remain constructive. It is the market that has lost patience.

The numbers

Second-quarter revenue rose 11% to RMB 204.8 billion. Operating capital expenditure reached RMB 51.8 billion, up 190% on the year and 66% on the quarter, and research spending rose 35%. Free cash flow was negative RMB 13.8 billion, though it would have been a positive RMB 37.6 billion before prepayments for compute. Net cash fell from RMB 146.9 billion to RMB 58.2 billion in three months.

Management now presents the group as two businesses, and the distinction is useful. The established franchises in games, advertising and payments earned RMB 86.1 billion of operating profit, up 19%. New AI products lost RMB 10.5 billion, compared with about RMB 8.8 billion in the first quarter. The equity is therefore a high-margin compounder attached to a large venture investment, and the share price reflects mainly the second.

On the second-quarter call, president Martin Lau argued that the spending carries “clear downside protection”: should Tencent’s own products disappoint, the capacity can be leased to others through Tencent Cloud. He said compute ordered only months earlier could already be sold at a premium of more than 30% and described the AI outlay as a two-year commitment and not a permanently rising budget. It is this last claim that skeptical investors doubt.

The catalyst: Oracle

The Financial Times reported on September 30 that Tencent had agreed to lease roughly 100,000 advanced AI chips housed in Oracle data centers across Southeast Asia. The contract runs for five years and is valued at about $7 billion, with around 30% paid in advance. It is the group’s largest overseas lease. The shares have fallen since, which suggests the market has not given the agreement much weight.

The arithmetic is favorable. Spread across 100,000 chips and five years, $7 billion equates to $14,000 per chip per year, or about $1.60 per chip-hour. The entire contract costs roughly what Tencent spent on capital expenditure in a single quarter. It also secures hardware the group cannot purchase at home: US export controls prohibit the sale of such chips to Chinese buyers but, for now, do not prevent them from renting capacity abroad.

The timing matters as much as the price. Tencent’s cloud revenue growth accelerated to the low 20s in percentage terms last quarter even as management acknowledged it was short of capacity. Where supply is the limiting factor, a five-year contract for supply is itself a strategic asset.

The risk is real. Neither company has confirmed the terms, and the leasing route remains open only for as long as Washington allows it. Were that to change, about $2 billion of prepayment would be held offshore by an American counterparty.

The moat

Leased compute is valuable only to a company with products to run on it, and here Tencent is well placed. Hunyuan 3, its foundation model, is in production, with daily token usage about six times that of the preview version. A larger successor, Hunyuan 4, is due before the end of the year. WorkBuddy and CodeBuddy are the most heavily used AI productivity tools in China by monthly interactions, and management says gross margins on paying users are already comparable to those of Tencent Cloud as a whole. Xiaowei, an agent being built into Weixin, draws on the app’s payments, mini programs and 1.4 billion users, a distribution advantage no domestic rival can match. The least glamorous application is already contributing AI-driven ad targeting helped lift marketing revenue 22%.

Demand check: the peer read-across

The obvious question is whether the demand is real. Alibaba offers the clearest evidence. Its cloud unit’s external revenue grew 45% in the June quarter, the fastest pace in 22 quarters, on RMB 67.7 billion of capital expenditure. Chief executive Eddie Wu told investors that growth would accelerate further as supply increased. Both groups are describing the same condition: demand that exceeds what they can power. On current cloud demand, Alibaba ranks first and Tencent second. Alibaba’s advantage is its in-house chips. Tencent’s is distribution, and the Oracle lease is its means of closing the supply gap.

Bear case

• Spending persists. The two-year commitment becomes a standing one. Morgan Stanley already forecasts RMB 200 billion of capital expenditure in both 2026 and 2027, with earnings broadly flat through 2027.
• The model falls short. Hunyuan fails to reach the frontier, and token pricing is commoditized.
• Policy shifts. Washington closes the overseas leasing route.
• The economy weighs. Chinese consumer and advertising demand remain uneven, as management itself has noted.
• The balance sheet thins. Net cash continues to decline and the buyback is cut.

Bottom line

This is the Meta trade with a China discount applied. A highly cash-generative core is funding an expensive build, and the market is pricing the whole of the cost and little of the return. Third-quarter results in November are the next test. Three figures will matter most: the loss on new AI products, the rate of cloud growth, and whether capital expenditure eases from RMB 51.8 billion or continues to rise.

Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.

Unreal Engine 6 Just Validated the Roblox Playbook

Thinking Tech Stocks — Mon, 14 Sep 2026 18:06:09 GMT

Roblox has spent the past year absorbing bad headlines: safety scrutiny, regulatory pressure, and skepticism about whether a platform built on user-generated content can sustain premium gaming. Then Epic Games took the stage at Unreal Fest and, without saying so, endorsed the entire Roblox thesis.

Strip away the branding and UE6 is a Roblox-shaped bet. Epic is merging its AAA engine with Unreal Editor for Fortnite into one product, so developers build once and ship live into an ecosystem of 80 million monthly users. That is Roblox’s core loop: one toolchain, one player base, instant publication. Tim Sweeney described a future where players travel from game to game, carrying their items with them, and where independent developers can host their own worlds. Roblox has run that model for nearly two decades.

The economics converge too. Sweeney acknowledged the market has shifted from buying games to buying things inside games, and that established ecosystems with huge player bases have a structural advantage over standalone launches. Epic’s answer is portable cosmetics and “smart assets” that work across titles, backed by a Verse language designed for persistent worlds and automatic global save state. Roblox’s Luau scripting, avatar economy, and cloud persistence were built on the same assumption’s years earlier.

UEFN games now capture 47 percent of Fortnite playtime, and Epic has paid developers over a billion dollars. Meanwhile 3,000-plus islands earn more from in-game transactions than engagement payouts. That is a UGC economy, and it looks a lot like the one Roblox pioneered.

Sweeney framed his vision as an open alternative to a centralized gatekeeper taking 70 percent of revenue. Fair critique. But the dispute is over terms, not direction. When the industry’s most influential engine maker reorganizes its next decade around live platforms, persistent identity, and creator-driven content, Roblox’s critics should notice: the path is no longer in question. Only who walks it best.

Disclaimer:
All views expressed are my own and are provided solely for informational and educational purposes. This is not investment, legal, tax, or accounting advice, nor a recommendation to buy or sell any security. While I aim for accuracy, I cannot guarantee completeness or timeliness of information. The strategies and securities discussed may not suit every investor; past performance does not predict future results, and all investments carry risk, including loss of principal.