The numbers tell a different story, especially in the context of SE’s tactics history and product development to-date. Monee operating margin fell from 29% in Q1’25 to 20% in Q2’26. Provisions cost 4pts of that. Sales and marketing cost 9pts. The S&M line is twice the size of the “problem” most are looking at.

This has a huge impact on perception of the segment not only the next few quarters but in modeling long term margins. Provisioning problems are a loan book problem, but a sales and marketing problem could well be building distribution, or buying it.

Quick take

Sea is buying a second payments network one voucher at a time, and the cost is showing up in S&M… to the tune of nearly $300mm in Q2’26, up a staggering 140% yoy (just like in Q1) and 27% qoq. These are wild numbers, but that’s typical of SE when they’re spending to win a market. Monee S&M has gone from 12% of segment revenue in Q1’25 to 21% in Q2’26. They then achieved off-Shopee surpassing 20% of the SPayLater portfolio and reached 35% in some markets. Two years ago it was under 10%. Active credit users are over 40MM, up 34% yoy.

We’ll call this the acceptance bill, meaning the cash a credit network pays to get accepted where a platform integration cannot place it. Monee has been paying it in cashback on QRIS scans, in 50%-off SPayLater vouchers at Alfamart and Indomaret, and in promoting a standalone wallet app in four countries.

Two channels cost nothing per merchant. Shopify checkout already carries ShopeePay and SPayLater across six markets, and Stripe begins enabling both across Southeast Asia in Q4’26. These integrations can take the place of ongoing voucher spend in an effort to expand distribution. If they work, the acceptance bill should peak in H2’26 and Monee’s return on book recovers. If they do not, Sea is buying a network retail, forever, and our FY30E Monee number may be too high.

Monee in 60 seconds

Monee is Sea’s financial services arm, rebranded from SeaMoney in May 2025. It runs the ShopeePay wallet, the SPayLater buy-now-pay-later product, cash loans under several local brands, insurance, and digital banks in Singapore, the Philippines and Indonesia. It operates in 8 markets across Southeast Asia plus Taiwan and Brazil.

Monee revenue and operating income are primarily from consumer and SME credit. The book stood at $11.1BN of principal outstanding at Q2’26, up 63% yoy, split $10.0BN on-book and $1.1BN channeled through partner institutions. Revenue yield on the average book runs ~53% annualized. NPL90 was 1.0%. It has held there for five quarters.

Monee delivered $1BN of adjusted EBITDA in FY’25 and is ~24% of our FY’30E group number. That makes it the second-largest profit pool at Sea. It is also the one with the least written about it.

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Moving onto GOOGL… I’ll admit upfront I spent a great deal of time attempting a bottoms-up build. It failed. However, some of the insights do provide value in mapping the path forward for one of the largest CapEx spenders, globally, in history. I found half to 2/3 of the GW they’ve planned depending on the year.

GOOGL does not disclose MW by site, and expansion inside an already-powered campus generates no groundbreaking or press release. The company discloses $85.2BN of leases signed but not yet commenced with no counterparty named. Twelve countries of international buildout publish almost no capacity figures at all.

The verdict. Google Cloud is becoming the majority of Alphabet’s earnings power. This capacity it is being built and deployed into the tightest compute market, and roughly 3/4 of that capacity has no price attached to it yet (best we can tell). You cannot model the outcome with precision. So I created a range of outcomes and mapped them to FCF in 2030. Ultimately, this is what the market cares most about. After the years of massive spend, will investors get FCF back on the balance sheet to do something with.

The TLDR… pay attention to compute contract pricing going forward. If the current path continues, Alphabet could see 25%+ upside to 2030 FCF estimates and trade at the high end of its historical P/FCF range at 30x.

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1. The monster

Start with what has already happened, because the change in this business is easy to miss if you follow the consolidated line.

Revenue growth accelerated significantly and operating margin doubled. Backlog went up 4.8x in twelve months, much faster than revenue growth. Q2’s incremental margin was 54%.

Cloud contributed 5% of operating income in 2024 and 11% in 2025. Our base case models 18% this year, 30% next, and just under half by 2030.

This is the part that matters for the stock. Alphabet spent two decades as an asset light advertising behemoth with a rounding error attached and that will now begin inverting… the compute business is growing at 3-5x the rate of the advertising business.

FCF was -$5.9BN in the second quarter, the first negative quarter Alphabet has ever printed. Capex guidance has been raised three times this year to $195BN to $205BN. Buybacks went to zero for the first time in a decade and the company raised $49.6BN of equity in June.

2. Data center unit economics

A gigawatt of compute capacity behaves like a well with a fixed production profile. You spend the shell cost roughly a year ahead of the servers. You spend the server cost in the year the capacity lights. Then it produces for about six years until the chips are retired and the building is re-racked.

Two years of outflow, six years of inflow. On our base inputs, one gigawatt costs about $39bn for GOOGL and returns about 1.5x that after tax over one server cycle, with a payback in year five.

Now stack them. Build one gigawatt this year, more next year, more the year after.

While the build rate is rising, cash burn accelerates while the model waits for capacity to be fully utilized. The moment the build rate stops rising, the accumulated production overwhelms the current spending.

This is why Alphabet’s cash flow statement looks the way it does, and it is the single most important thing to understand about the name. The burn is not evidence of a problem, at least as far as anyone can reasonably tell today given the demand outlook. The burn is arithmetically what a company looks like when it is adding capacity faster each year than the year before. The question is not whether the flip happens, but how big the number is on the other side, and when.

3. What we could not find

Here is the honest accounting of the mapping exercise.

Take Alphabet’s capex, strip out the ~8% that is offices, split the rest 60/40 between servers and buildings the way management has described it consistently since late 2025, divide by a cost per gigawatt, and phase it into service. That is the top-down count, and it says Alphabet turns on ~1.9 GW this year, 3.8 next year and 5.4 in 2028 after applying a six-month delivery delay.

The register covers 43% of 2027 and 79% of 2028, and roughly half of the five-year total. The single cleanest illustration of why is Anthropic. Broadcom’s filings put roughly 3.5GW of next-generation TPU capacity for Anthropic beginning in 2027, and on the Q2 call Broadcom said Anthropic is on track to become its largest custom accelerator customer next year, ahead of Google itself. Press reporting derived from the Financial Times says Google backstops 10 TPU data center projects totaling 2.4 GW. We have addresses for three of them.

Five things remained unmapped. Expansion inside existing campuses, which could be the largest figure and which generates no public record at all beyond the occasional utility filing. The $85.2BN of leases not yet commenced, which is a disclosed number attached to no disclosed tenant, implying roughly 3.2GW of leased shell. International capacity across twelve countries where megawatts are almost never published. Densification, because an Ironwood rack draws far more per square foot than the rack it replaces. And the unnamed Anthropic sites.

One honest counterweight. Some of the gap is our top-down being generous rather than the bottom-up being sparse. Alphabet’s capex includes turbine deposits, transformer prepayments, land and Broadcom supply commitments that will not light anything for years. Inventory went from $2.4BN to $10.0BN in six months, and TPUs built for sale to third parties are not Google’s own capacity.

And the timing is uncertain even for the buildings we can name.

That is a 3x spread on cumulative named capacity by 2029, using the same set of projects. Texas ordered a full audit of every data center in the ERCOT interconnection queue early August and suspended large load classification, with completion targeted for December. Indianapolis has a moratorium through the end of 2027. St. Charles passed a permanent ban. Pennsylvania removed data centers from fast-track permitting. Gas turbine lead times run 5-7years, and GE Vernova’s book is sold out into 2030. Sightline Climate found that 26% of expected 2025 capacity slipped and projects 30-50% of 2026 capacity will.

We handle this by carrying capex in full in every scenario and pushing half of each year’s newly lit capacity into the following year. If Alphabet delivers on schedule our capacity is too low and our cash flows are too low. If it slips, we have already paid for it.

4. Pricing

I spent much of my effort on the physical build and it was the wrong place to spend it.

Run the model changing one lever at a time and measure the effect on five years of cumulative free cash flow. Delivery timing, the thing the entire site-by-site exercise was built to pin down, is worth +/- $32bn. The price of a gigawatt-year of compute is worth $137bn either way.

Pricing matters 4x more than the construction schedule. So we went and built the pricing comps properly, across every deal with disclosed dollars and disclosed capacity.

The first thing to understand is that there are three different things being sold and they differ by a factor of thirty.

A powered shell lease is a building with electricity and cooling in it and nothing else. The tenant brings the chips. Core Scientific leases to CoreWeave at roughly $1.44mm per megawatt-year. Applied Digital is at $1.67mm to $1.83mm, Cipher at $1.22mm to $1.79mm, TeraWulf at $1.86mm to $2.26mm. Call it $1.2bn to $2.3bn per gigawatt-year for real estate with power.

Full stack compute is the same building with the operator’s chips in it. CoreWeave’s second quarter revenue against 1.5GW of active capacity annualizes to roughly $6.9bn per gigawatt-year blended across its fleet. Microsoft’s contract with IREN is $9.7bn over five years for 200 MW, or $9.7bn per GW year. Microsoft with Nebius is $11.6bn. Nebius disclosed its own baseline entering 2026 at about $12bn.

The gap between those two layers, roughly seven times, is almost entirely the depreciation of operator-supplied silicon.

The second thing is that the price moved in 2026, and it moved a lot.

Nebius disclosed the clearest ladder anyone has published. Its baseline entering 2026 was about $12mm per MW year. Long term contracts signed in the second quarter were struck at $20-25mm. Short-term capacity in the third quarter went at $40-50mm per MW year, and sometimes above. That is $40-50BN per GW year for capacity of six months or less. Its maiden capacity auction cleared 15% above any price it had previously achieved on Blackwell, and payback on new capacity compressed from two to three years down to one year and ten months.

CoreWeave put through a roughly 25% price increase across every SKU in July and told investors near-term capacity is effectively sold out, with contribution margins on new contracts running 5-10pts above those signed in prior quarters. SemiAnalysis’s one year H100 contract index rose about 40% between October 2025 and March 2026, on a chip two generations old. Nvidia’s chief financial officer said H100 rentals were up about 20% year to date. Bernstein put IREN’s newest contracts 20-25%above its earlier ones.

The third thing is where Google sits on that chart, and it is not where you would expect.

The reported Anthropic arrangement, $200bn over five years across roughly five gigawatts, works out to about $8-9bn per GW year at full ramp. That is the largest private compute contract ever signed and it is priced near the bottom of the observable range, because it was negotiated in 2025 at 2025 rates by the largest single buyer in the market.

Published sellside models for Google Cloud imply $11-14BN of incremental revenue per GW in 2027. Morgan Stanley’s own framework models Google at $15 per watt in 2027 rising to $18 in 2028, and notes explicitly that this is below what it calls an industry negotiation level above $20bn per Gw.

So consensus is modelling Google’s compute at roughly half of what the merchant market is currently charging.

And then there is Google’s own price list, which nobody seems to be reading.

Google publishes TPU pricing. Ironwood, the current generation, lists at $12.00 per chip-hour on demand, $8.40 on a one-year commitment and $5.40 on three years. Convert that at roughly 714,000 accelerators per gigawatt, which assumes 1.4 kilowatts all-in per accelerator including networking and cooling overhead.

Google’s own three-year committed list price implies $34bn per GW at full utilization, or $24bn at 70%. Our base case assumption of $18bn sits below every rate Google publishes, including the cheapest one after a 30 percent utilization haircut. SemiAnalysis’s estimate of what Anthropic actually pays, about $1.60 per chip-hour, implies $10bn, which tells you how large the discount is to the single largest customer.

We are not claiming Google will realize list price, nobody realizes list price. We are pointing out that the model assumes Google captures roughly half of its own published three year committed rate on capacity it has not sold yet, and that this is a conservative assumption rather than an aggressive one.

5. The window

Put the two halves together and the setup becomes clearer than either half alone.

8% of Google Cloud’s capacity is unpriced this year. By 2028 it is as much as 55% and by 2030 it is 73%. The legacy book and the Anthropic and Meta contracts are locked at rates struck in 2025 and earlier. Everything lit after, we believe gets priced at whatever the market clears at on the day it is energized. And it is being energized into the tightest compute market anyone has seen. SemiAnalysis counts roughly 20 GW energized industry-wide in 2026 and expects about 30 in 2027, against demand that Morgan Stanley models as a 38 to 49 GW shortfall through 2028. Texas has paused its interconnection queue pending an audit. Half a dozen counties have moratoria.

Every one of those constraints is a reason our delivery timing might be too optimistic. Every one of them is also a reason the price on delivered capacity goes up. If power scarcity delays Alphabet’s buildout, the same scarcity raises the rate it can charge on whatever it does deliver. The two things that make us wrong on timing make us conservative on price. They do not compound in the same direction.

One thing does compound, and it is the actual risk. If demand cracks, then delivery is easy, pricing collapses and utilization falls, all at once. That is the scenario where this does not work, and no amount of construction mapping would have told you about it.

The bear case on pricing deserves a fair hearing because it is real and it is loud. Spot rental rates for H100s have fallen roughly 57% from their early-2024 peak. AWS cut its P5 on-demand list price 44% in June 2025. Inference cost per token is collapsing at something like an order of magnitude a year. TD Cowen’s channel checks found Microsoft cancelling or deferring data center leases, which the firm reads as a potential oversupply signal.

Every one of those is about a different thing than what Google sells on a multi-year contract. Falling spot prices in 2026 coincided with contract prices rising 40% because serious buyers migrated out of spot and into committed capacity as on-demand sold out. Per-token deflation is a model efficiency gain, and Google itself has disclosed cutting Gemini serving costs 78% in a single year, which raises the output a GW can produce rather than lowering what the gigawatt rents for.

6. Why pay Google more

There is a piece of this that does not show up in any comps table.

Alphabet is a company with $155bn of cash, effectively no net debt, an Aa2 rating and a stable outlook, selling a multi-year compute contract. The merchant alternatives are, in several cases, former bitcoin miners financed through SPVs with private credit, residual value guarantees and, in a number of the largest deals, a credit backstop from Google itself. Alphabet discloses $43.8bn of maximum potential payments under credit derivatives backstopping data center payment obligations, plus $7.6bn of guarantees for suppliers buying long-lead power equipment and $24.1bn more agreed but not finalized.

If you are a chief information officer signing a five year commitment for capacity your business now depends on, the identity of the counterparty is part of what you are buying. So is the security posture, where Alphabet has bought Wiz and Mandiant and folded them into the stack. So is distribution, where Google reaches both the consumer surface and the enterprise, and where Thomas Kurian has said nine of the ten largest AI labs are already customers, that customers using AI products consume 1.5 times as many Google Cloud products as those who do not, and that customers who sign commitments routinely over-attain them.

7. The inversion

So I stopped forecasting bottoms-up and asked the only question that can be answered.

Alphabet’s market capitalization at $335 is $4.1tn. Take out $57bn of net cash, the entire securities portfolio at reported value ($101bn of SpaceX stock and $131bn of non-marketable holdings dominated by the Anthropic stake). What remains is a core business priced at $3.8bn.

At 25x 2030 FCF (roughly the 10 year average), you need visibility to ~$150bn of FCF.

Now run the model at every price point in the observable range, changing nothing else.

At $8bn per GW year, which is the reported Anthropic rate and the cheapest price anyone has paid for compute at scale anywhere, Alphabet produces $165bn of FCF in 2030 and the stock trades at 23x.

At consensus pricing of $11bn, it is $191bn and 20 times. At our base case of $18bn, half of Google’s own three year committed list rate, it is $253bn and 15x. At the rate Nebius is signing long-term contracts today, it is $315bn and 12x.

The bear case…. where pricing is low and costs are high and delivery slips and chip life proves to be five years and the installed base was smaller than we thought, produces $50bn of FCF in 2030. That is 77x and it does not clear anything. The bull case produces $612bn, which is 6x.

So the width of the distribution on a five-year view of a company spending $1.56tn is enormous, and anyone quoting a point estimate on this is not being straight with you. What the inversion tells you is narrower and more useful. No single variable breaks this. The variables have to fail together. And the two most likely failure modes, power scarcity and slow permitting, push price up while they push volume down, which is a partial hedge rather than a compounding loss.

For what it is worth, our base case has the hole deeper and a year later than consensus. Minus $65bn in 2027 against consensus at minus $19bn, almost entirely because we carry 2027 capex at $330bn, or as much as 10% above consensus. Run the operating model on consensus and the 2027 gap narrows to about $11bn.

8. Funding

Net debt peaks at $76bn at the end of 2028, which is 0.2x EBITDA, and is gone during 2029. Peak incremental borrowing across the whole program is $37.5bn. Moody’s affirmed Aa2 stable in May and S&P AA+ stable, with S&P forecasting adjusted debt to EBITDA of 0.2-0.3x.

That bridge excludes $101bn of SpaceX stock and $131bn of other securities. Include the SpaceX position at reported value and Alphabet never crosses into net debt at all. The 551 million SpaceX shares carried at $94bn cost roughly $900mm in 2015.

The funding question here is genuinely uninteresting. The $40bn at-the-market program authorized in June is unused. The preferred converts to equity in May 2029. Alphabet could fund the entire remaining burn by selling a third of a position it did not know it needed.

9. What to watch

The value of the site-by-site work is not that it produced a number. It is that it produced a list of things that resolve on dates, which converts an unmodelable company into a monitorable one. Here is a long list of items to watch into Q3 earnings and beyond.

The three that matter most are the 2027 capex guide in February, because it settles whether the spending path is real, any disclosure of external TPU pricing, because it settles the repricing question, and the direction of merchant contract rates, because that is the highest-frequency read on whether the window is open or closing.

10. Conclusion

It is unlikely that anyone outside of perhaps SemiAnalysis can model this business with any precision. And even then, there are human factors that are unquantifiable here. However, it is indisputable that Google Cloud is becoming the majority of Alphabet’s earnings power on a timeline that is short, and the market has not had to price that because it is happening underneath the worst-looking cash flow profile in the company’s history.

The capacity being built is landing in the tightest compute market on record, and roughly three quarters of it has no price on it yet. Contracts struck in 2026 may clear at as high as 2-4x the rate embedded in published models, and Google’s own three year committed list price implies double what the models use. Every observable failure mode on the physical build makes the pricing better.

Furthermore, the full deltas diagram below shows the sensitivity in the model to all of the variables, from bear case to bull case. The market should be more worried about advertising risk downside, however that downside reflects a dramatically different macro environment to be fair.

Alphabet is one of a very small number of counterparties that can credibly sign a 10 year compute commitment, and across a large share of the merchant market it is already the credit standing behind somebody else’s lease.

And when you invert the question rather than forecasting it, the price at $335 requires roughly $153bn of FCF in 2030 against a model that produces $165BN at the cheapest price anyone has ever paid for compute and $253bn at half of Google’s own list rate.

While we should all monitor the construction schedule, we really care most about the moment the market decides the cash flows are coming, because that is when a business growing operating income at this rate, with half of it not yet priced, stops being valued on the burn and starts being valued on the ramp in FCF possible beyond.

Appendix

Four assumptions that matter

Everything in this note reduces to four levers. The rest is noise at five years' distance. Each is shown with the observable evidence rather than a point estimate, so a reader can substitute their own.

Named capacity register

Thirty-three projects. Structure A is an owned shell with Google chips, B is a leased shell with Google chips, C is a third-party site where Google sells TPU systems rather than renting capacity. Megawatt figures for owned campuses are estimates, because Alphabet discloses none. Both tables are downloadable images.

Pricing comps

All figures are total contract value divided by term and by capacity, which is a bookings average and not a steady-state realized rate. Layer matters more than any other adjustment.

What we couldn’t resolve

1. The Anthropic and Meta contract terms are press reports and neither company has confirmed them. We do not know whether either carries an annual escalator, whether they are leases with a rent schedule or minimum spend commitments, or how capacity is measured for billing. We model Anthropic flat at $8.5bn per gigawatt-year and flag that the contract form itself is unknown.

2. The counterparty, megawatts and term of the $5.8Bbn short-term lease commencing in the third quarter of 2026 are undisclosed. We model roughly 0.3 GW of full-stack compute over twelve months.

3. Installed lit capacity at the end of 2025 is not disclosed anywhere. Our 8.5 GW starting point is triangulated from cumulative capex.

4. Segment capex and segment depreciation are not disclosed and are allocated by lit-gigawatt share. This is the largest single judgment in the model.

5. The $707bn purchase commitment figure comes from secondary sources quoting Note 10 of the second-quarter 10-Q rather than from the note text directly.

6. Owned-campus megawatt figures throughout Appendix B are estimates. Only the Structure C sites carry disclosed megawatts.

7. The 2Q26 net income of $112bn includes a $99bn unrealized gain on Anthropic and SpaceX marks. Nothing in this note is built on it.

8. The Koyfin consensus free cash flow line does not equal the same screen’s cash from operations less capex, with a gap of about $39BN in 2029. Both are shown where relevant.

9. The backlog series has a definitional break. The first quarter of 2026 added contracts with an original term of one year or less, worth about $7.3bn. The move from $240bn to $462bn is 97% bookings.

10. Conversions from chip-hour prices to revenue per gigawatt-year assume 714,000 accelerators per gigawatt at 1.4 kilowatts all-in. That assumption drives the result and is stated wherever it is used.

DISCLOSURE

Position: At the time of publication, the author holds a position in GOOGL.

Trading Policy: The author will not materially alter this position within 48 hours of publication. After this period, the author may buy, sell, or otherwise adjust the position without further notice. Changes to the author’s view or position will be reflected in subsequent publications when material.

Conflicts: The author has received no compensation from the issuer or any party with a financial interest in this security.

Forward-Looking Statements: This report contains the author’s opinions, estimates, and projections, including price targets derived from financial models. These are forward-looking statements subject to substantial uncertainty. If these assumptions prove incorrect, the actual value may differ materially, including scenarios of significant loss or total impairment. The price target represents the author’s estimate of fair value under the stated assumptions, not a prediction of where the stock will trade.

This report is provided for informational purposes only and does not constitute investment advice. See the full Terms & Disclosures for additional important information.

Sea Limited (SE) has entered “investment windows” 4 times in 9 years with a predictable impact on the stock. We are now emerging from this cycle with shares ~40% from the September 2025 high, and management has done something it never did in the first three. It has put a date and a dollar figure on the exit.

Pitch in 1 paragraph…

Shopee’s EBITDA margin on GMV troughed at 0.55% in 4Q25 and has risen two quarters running to 0.67%. Management guided FY’26 Shopee adjusted EBITDA to $1BN on the Q2 call, which needs $522MM in 2H26 against $478MM in 1H26, and it reaffirmed a 2% to 3% medium-term margin target with a three-part bridge. Our own bridge says advertising will add 128 of the 194bps between here and FY30, and the ad line is compounding at +90bps of take rate a year. Our base case sees consolidated adjusted EBITDA growing from $3.9BN in FY26 to $11.85BN in FY30. That is 3x in 3 years. The stock trades at 13.6x CY27 EBITDA. And perhaps most importantly, this mix shift away from less certain Free Fire EBITDA should provide long-term support to valuation.

Put more simply… SE spends into a competitive or structural opening, the equity market prices the spend as permanent, and the business exits the window with more share and a higher profit base.

Why the opportunity exists

The market is pricing the current spend as a tax rather than an investment, and it has good reason to be skeptical. The 2% to 3% target has been reaffirmed on every call for two years while the margin fell from 0.92% to 0.55%. Hayden Capital, which runs SE as a top-two position, frames the whole debate as reinvestment versus defense and puts the bear’s terminal margin near 1% of GMV against management’s 2% to 3% [C]. At $119 the stock discounts roughly that bear, and we show the back-solve below.

Two things have changed since the March guide that the price has not caught up with. The margin turned in 1Q26 and confirmed in 2Q26. And the composition of the ad business inverted, from a fixed base of sellers spending more to a broadening base of sellers, which is the only version of the ad story that reaches 5% of GMV without hitting seller economics.

SE in 60 seconds

3 businesses run from of Singapore with local market teams.

• Shopee is the largest marketplace in SEA and Taiwan with $127BN of GMV in FY25 and a profitable and fast-growing Brazil business

  • Revenue is commission on transactions, ads sold to sellers, and logistics fees, FY25 Shopee revenue was $17.0BN and adjusted EBITDA $881MM

• Monee is the consumer credit and payments arm

  • Lends to Shopee buyers and, increasingly, off-platform through SPayLater at physical merchants

  • Loan book $11.1BN at 2Q26, up 62.5% yoy, with 90-day NPL at 1.0% and FY25 adjusted EBITDA of $1.0BN

• Garena publishes Free Fire, a nine-year-old mobile shooter with more than 100MM daily active users

  • Bookings were $2.9BN in FY25 and adjusted EBITDA $1.7BN, it funded the first two windows, and it still carries 46% of segment EBITDA

Evidence

From Dec 2021 to Aug 2023 the stock fell 85%. Over the same 20 months Shopee’s share of the tracked marketplace pair rose in Indonesia (49% to 67%), Malaysia (60% to 69%), Vietnam (31% to 61%), Thailand (24% to 41%), Singapore (42% to 51%) and Taiwan (67% to 71%). The Philippines fell 25pts between Oct 2022 and Mar 2023 as TikTok Shop scaled, and had recovered the entire loss by July 2023.

The 2022 collapse was rising rates and Covid pull forward coupled with strategy reversal. It was never a competitive event (had the data that proved so at prior fund), though the Tik Tok fear at the time was real and growing.

Lazada was supposed to buy share (funded by BABA) as they Lazada raised discount penetration from 23% of orders to 78% between 2019 and 2023 and lost 7pts of regional share. Shopee gained 23pts over the same window while its free-delivery penetration fell from 54% to 51%. Announced competitor spend buys no measurable share.

We provide the above prices as a range of outcomes for the next few years. They are not meant as price targets, rather to help a reader frame the opportunity set under different assumptions. Those assumptions are spelled out in detail below the paywall.

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TLDR… storied history of building businesses over decades with key mentors who helped shape his now empire that expands well beyond MAIR to his own private equity firm. Now a buy-and-hold style investor, it’s no wonder he agreed to inject hundreds of millions to help close MAIR’s recent transformative transaction of ebm-papst. His quiet $9bn stake in MAIR has gone largely undiscovered, it seems, though it stacks up against some of the greatest tech founders of our time…

Ownership

As of 30 June 2026, Larry Gies controlled ~337MM shares of MAIR. They sit across three vehicles. Madison Industries Holdings LLC, Madison Air Co-Investors LLC, and a private placement made at the IPO price. That’s 67% of the economic interest and 95% of the voting rights, worth ~$9BN. For scale, Marc Benioff’s stake in CRM runs ~$6.5BN, Tobi Lutke’s in SHOP $12BN, Brian Chesky’s in ABNB $12BN.

The gap between the two percentages is built on 10 votes per Class B share. The Schedule 13G filed August 10th states the chain plainly, “Larry Gies is the sole manager of Holdings. Holdings is the sole manager of Co-Investors.”

Small town Illinois

Gies grew up in Mendota, Illinois. Population ~7K, 90 miles west of Chicago. His father worked at Conco, a local manufacturer.

Conco was owned by Michael Heisley, a Chicago industrialist who founded Heico Companies, a decentralized holding company assembled from broken manufacturers. Heisley later bought the Vancouver Grizzlies and moved them to Memphis. He’s the single most important figure in this story, and he’s almost entirely absent from coverage of MAIR.

Gies’s first job was at Touche Ross. It ended at 24, after he wrote a memo criticizing how the firm handled its largest client. The story is usually told as a firing over a memo sent to a client’s CEO. His own account is narrower. His words are that “my days in my first job were numbered,” and the memo was internal.

He then went to work for Heisley. By his own description he ran one of Heisley’s manufacturing companies “quite poorly.” The instruction he received, and repeats, was “Go do it, kid.”

That apprenticeship is where the operating model comes from. A decentralized holding company that keeps what it buys. He founded what became Madison Industries in 1994, at 27, on 10 maxed-out credit cards and a $50,000 loan from a high school friend. His wife Beth, a former teacher, worked three jobs.

The eulogy, and when it actually happened

The story Gies tells most often is the eulogy exercise, from his University of Illinois commencement address of 11 May 2019.

“So that day I got our entire management team together and asked them to do something a bit unorthodox. I had them write their eulogy. Not their obituary, but their eulogy... My teammates spoke of family, making a positive impact on the world and doing good. But when they spoke specifically about how they wanted to be remembered for their professional lives, nobody mentioned making a lot of money for our investors.”

“That day we formed Madison Industries. Which meant that our highly successful business of buying and selling companies was headed for the trash heap.”

In a 2018 speech he put a date on it. “I was forty-five before I found my why.” That would place the turn around 2011, not 1994.

Madison Industries was founded in 1994 as Madison Capital Partners, a fundless sponsor. And a 2006 profile in The Deal describes a firm advertising a 90% net internal rate of return across 12 exits and five partial realizations.

So the hold-forever philosophy dates to 2011, not to the founding. Todd Bluedorn, former Vice Chairman of Madison Industries, described the earlier version in May 2026. “Man, the guy can sniff markets. He buys on the cheap, he sells at the peak, and when he buys, it’s from corporations who are running and he sells them to corporations who have more money than they know what to do with.”

Professionalizing the business

Frank Ptak spent ~30 years at Illinois Tool Works (ITW), rising to Vice Chairman, and Madison’s own materials credit him with helping pioneer ITW’s 80/20 model. He then ran Marmon Holdings for 13 years. More than 100 autonomous businesses and $8BN of revenue, sold to Berkshire Hathaway. He reported to Warren Buffett. He also ran Marmon’s acquisition of Duracell in 2014, then joined Madison Industries as Senior Managing Director in January 2019.

He wasn’t the only one. Gies has assembled an unusually senior bench at the private parent.

George Nolen arrived first, in October 2010, as Vice Chair. 27 years at Siemens, the last five as President and CEO of Siemens Corporation. He also chairs Filtration Group, another Madison company, and now sits on MAIR’s board.

Todd Bluedorn joined in April 2022, also as Vice Chair. 15 years at Lennox International, CEO from 2007 and Chairman from 2012, over which market capitalization went from $2.5BN to more than $13BN. Before Lennox he was President of Otis Elevator Americas and President of Carrier North American HVAC at United Technologies, and McKinsey before that, from 1992. West Point, and a US Army Combat Engineer Officer from 1985 to 1990. He’s the man quoted above.

Gies on hiring him. “Todd attracts world-class talent, builds high-performing teams and brings a successful track record of building best in class global businesses.” Bluedorn on why he came, and note what he names first. “The exceptional Madison team and its mission of making the world safer, healthier and more productive attracted me to this opportunity.”

There’s a recruiting channel visible in the dates but stated nowhere. Quan Nguyen, now MAIR’s Group President for Air Quality & Home, was VP and GM of Lennox Industries Residential from 2017 to 2024, under Bluedorn for most of it.

The lineage we can now see… Heisley supplies the shape in the early 1990s. Gies runs it for 15 years as a buy-and-sell operation. The identity changes around 2011 to holding. Ptak arrives in 2019 to professionalize the machine, immediately before the air platform is scaled through the $3.6BN Nortek acquisition.

The acquisition record

Madison Industries has done 80+ acquisitions since 2004, across 20-plus countries. MAIR specifically claims ~$8BN invested and ~$28BN of TAM unlocked since 2021. The air platform itself was assembled in nine years.

Madison publishes margin expansion figures for three deals. That’s the closest thing to a track record on the operating model. +975bps at Therma-Stor in Nov 2017. +1,700bps at Specified Air Solutions in Oct 2018. And +500bps at Broan-NuTone after the Nortek acquisition in Apr 2021. The company states the majority of those gains landed inside the first three years, and more than half above the gross margin line.

The anchor deal was Nortek Air, announced 19 April 2021 and bought from Melrose Industries plc at a reported $3.6BN. It brought ~6,000 employees and the Broan, NuTone, Reznor, StatePoint, Zephyr and Huntair brands. Gies at the time. “The global pandemic has put a spotlight on the importance of indoor air quality.”

Two things about how they buy are worth more attention than they get… they don’t call it integration. Wyant, on the 1Q26 call. “we don’t really call them integrations. We call them transitions... we buy businesses to allow them to continue to do what they do.” For a serial acquirer that’s a real statement of intent. It’s also consistent with a 45-person center that couldn’t run integrations even if it wanted to.

And speed is a stated value. Madison Industries publicly claims it has never changed an acquisition price after agreeing it, and that acquisitions close within 30 days, with one counterparty testimonial citing 15 business days. This is very attractive to sellers.

The green line on that timeline matters too. In October 2024, mid-assembly, Madison sold Nortek Global HVAC to Rheem for $1.15BN and said very little publicly about why. A company that holds forever is still a seller when the asset doesn’t fit. That’s defensible. But it isn’t the story on the slide, and it’s the fact that gives Bluedorn’s quote its edge.

The parent you are not buying

MAIR is one of seven verticals inside Madison Industries. Filtration, medical, safety, energy, industrial solutions, air, and Seakeeper. The parent reported ~$5BN of revenue in 2019 with 10,000 employees and 178 facilities. It has since ~doubled on both counts. Madison Capital Partners, the capital vehicle, is separately described as a registered investment adviser managing ~$4.8BN across 13 funds.

Two things follow for a public-market investor. The governance of the listed company is set by a private organization with considerably more at stake than the listed entity. And a Transition Services Agreement with Madison Industries International keeps supplying services post-IPO. Pre-listing, allocated corporate costs ran $10.0MM and $5.8MM in the periods shown in the 2Q reconciliation.

Decentralization

The prospectus contains the sentence that makes the model concrete.

“We remain lean at the center with approximately 0.5% of total headcount.”

Against ~8,800 employees, that’s ~45 people running a $3.9BN revenue company. Forty-five. A typical industrial of this scale carries several hundred at corporate.

The CFO described the mechanism at the William Blair Growth Stock Conference on 4 June 2026, and it’s the clearest account anyone at the company has given.

“I think about the Nortek Air Solutions business, where it was kind of run as one blob when we first bought the business. Now we’ve broken that out into the air handling and the direct expansion in the clean room, clean room breaks out into life sciences, into semicon. Now we’ve got, instead of a centralized commercial team, we have dedicated teams coming to work every single day thinking about how they serve those customers in that end market.”

That’s 80/20 applied to org design rather than to product lines. Gies described the same instinct in the 2006 profile, long before any of the current messaging existed.

“I think that is why we have a hard time keeping people in the office. They all want to be on the plant floor.”

Where the decisions actually sit, from the filings and calls.

One caution on the branding. The decks name the operating system MAXX, Madison Air Execution Excellence. It appears once in the public record once… a strategy-pillar bullet reading “Madison Air Execution Excellence (MAXX) powered by 80/20.” That’s the entirety of the disclosure.

The nearest thing to observable machinery comes from Wyant’s 1Q remarks. More than 60 leaders put through 80/20 and sales training courses in a few weeks. Immersive AI-enablement sessions. And an enterprise-wide innovation summit she hosts at least twice a year.

The published values are short enough to quote in full, and two of them are testable. Trust, “doing what you say and saying what you do.” Bias for Action, “an organizational reflex to own problems and resolve them quickly.” Entrepreneurial, “operating with an owner’s mindset, emphasizing accountability, humility, and continuous improvement.”

Compensation

The compensation design is what makes a 45-person team possible. Executives are paid in long-dated Equity Appreciation Rights with single-cliff vesting. Jill Wyant held 3.7MM shares at IPO, of which 2.6MM were EAR units. She’s now at 3.5MM after two tax-withholding events. JJ Foley holds 1.7MM including 0.6MM EAR units.

The instrument is defined in Wyant’s Form 3 as “the right to receive one share of the Issuer’s Class A common stock upon vesting.” The cliffs are long. The clearest published example is the new chief accounting officer, hired June 2026. Base salary $355,000, target bonus 50%, and ~$700,000 of EAR units vesting in a single cliff on 15 July 2031. Five years, all or nothing.

It’s also broad. At the IPO, 10,339,435 Class A shares went to company executives and employees, and 146,556 EAR units went to former employees and consultants. They carried alumni. At the private parent, Madison Industries describes ~1,000 “owner managers” and maintains a named corporate function called Vice President, Owner Relations.

This is where an accounting item from the first piece stops being a technicality. The $125.9MM equity-appreciation charge Madison adds back to adjusted EBITDA is the price of running a company with 45 people at the center. It’s a real compensation cost. Excluding it is what takes the reported 2025 margin from an honest 23.0% to the 26.6% that anchors the premium-platform framing.

Board of Directors

One structural fact follows directly from all of the above, and we haven’t seen it written anywhere.

The entire board is four people. Four. Hudson La Force and George Nolen joined on 15 April 2026, the day before the IPO. Gies has chaired since October 2017.

Both directors labeled independent have long-standing Madison relationships. Nolen has been Vice Chair of Madison Industries since October 2010 and chairs Filtration Group, another Madison company. La Force sat on Filtration Group’s board from 2022 to 2026. Independence here is a NYSE definition.

And Gies personally chairs the Compensation and Nominating Committee. The founder holding 95% of the votes also chairs the committee that sets executive pay and nominates directors. La Force chairs Audit, which is the one committee where the rules leave no discretion. Directors are paid in the same instrument as management. Form 4s dated 29 June 2026 show La Force granted 5,711 EAR units and Nolen 5,077.

For a certain kind of investor this is the attraction, not the objection. Owner-operators with real capital at risk and no quarterly-earnings reflex have compounded capital better than committees for a century. Gies has ~$9BN of his own money in the same security, plus $620MM more bought in last week’s placement at the market price. But be clear about what you own. A private holding company that has sold a third of its economics and none of its control.

Ownership figures are from the Schedule 13G filed 10 August 2026 and Form 3 and 4 filings. Quotations are as delivered and dated in the text. The third piece will cover the products, the pricing and the ebm-papst acquisition. Not investment advice.

DISCLOSURE

Position: At the time of publication, the author holds a position in MAIR.

Trading Policy: The author will not materially alter this position within 48 hours of publication. After this period, the author may buy, sell, or otherwise adjust the position without further notice. Changes to the author’s view or position will be reflected in subsequent publications when material.

Conflicts: The author has received no compensation from the issuer or any party with a financial interest in this security.

Forward-Looking Statements: This report contains the author’s opinions, estimates, and projections, including price targets derived from financial models. These are forward-looking statements subject to substantial uncertainty. If these assumptions prove incorrect, the actual value may differ materially, including scenarios of significant loss or total impairment. The price target represents the author’s estimate of fair value under the stated assumptions, not a prediction of where the stock will trade.

This report is provided for informational purposes only and does not constitute investment advice. See the full Terms & Disclosures for additional important information.

Arxis, Inc. (ARXS) is an explicit “Buy-Down Machine.” As CEO Kevin Perhamus puts it, “[we] grow the EBITDA of the acquired business at a higher rate than the base of Arxis in the next three years”, and can it “buy down the multiple to less than 10 times within 36 months”. Thirty-five acquisitions in ~6 years. The two most recent large deals were disclosed together at ~12x forward EBITDA.

And what comes after is even more important… ARXS printed 21% organic growth and a 42% adjusted EBITDA margin in 2Q26, its second quarter as a public company, and the shares have ~doubled from a $28 April IPO. Given it’s market cap of ~$22bn, this business is entering what we believe is a sweet spot of scale in its lifecycle… large enough to do $1-5bn transactions but small enough so that these actually matter. We’ve seen too many large acquirers/compounders suffer from scale, and this is an opportune time to look at one with nice runway ahead.

Overview

ARXS designs and manufactures proprietary electronic and mechanical components for harsh environments. Connectors, RF and microwave devices, sensors, capacitors, self-lubricating bearings, seals, ducting, radar-absorbing materials. To cut to the chase…

• ~90% of revenue is proprietary, sold to >600 platforms for more than 5k customers

• Top 10 customers 36% of revenue, none >7%

• Defense and space 46%, commercial aerospace 22%, industrial technology 31% (includes med devices, surgical robots, semiconductor equipment and factory automation

• Parts typically cost less than 0.01% of the platform… too cheap to fight about, too critical to remove… qualified years before production, usually as the only approved source, on platforms that produce for 20 years and fly for 40

• Platforms are diverse… F-35, DDG-51, Virginia-class, SPY-6 radar, missile-tracking satellites, 737 and Airbus A320, the LEAP, CFM56, PW1000G and PT6 engine families, Gulfstreams G650, G700 and G800, and in medical the contacts are built to survive 15 years inside the human body

So the budget line that matters is R&D, not procurement. A designed-in supplier wins its next positions during platform development, and the Pentagon’s RDT&E request stepped from ~$143BN in FY25 to $179BN in FY26.

In the company’s own words, positions are won because “our engineers meet with our customers’ engineers. They solve a problem which results in a custom product that gets designed into the bill of materials, typically as the only qualified part, and then stays there for decades.” ARXS owns 67 foundational technologies across 48 business units. A good example of this is the KAron bearing liner, which turns a standard bearing into a custom product with “five to ten times the value.” KAron went onto the Gulfstream G650 in 2008, then spread to five more models. It produced “approximately a 965x increase in our revenue from this product line and customer.”

Two structural facts about ARXS that set this business apart from average roll-ups…

First, they have an actual operating system that everything together called Arxis EDGE which also enables a scaled and decentralized model. EDGE is a purchase-order-level system that digests 6k orders / month. ARXS runs 48 decentralized business units across ~70 focus factories under 16 block leaders. That’s why 2026 was guided in a $20MM revenue range and then raised by $100MM a quarter later. By late July, 95% of 2026 revenue sat in firm orders, with “another $150 million or so left to go to book for the year.” More than 450 of the company’s ~5,750 employees are paid on new-business wins, and the EDGE cross-sell pipeline grew from ~50 opportunities in 2021 to more than 2,000 by mid-2025… so they have a large proportion of employees who are highly incentivized to grow volumes (on which they’ll surely take ongoing price) and track every order. This is important as it means management can quickly triage with problems before they become large.

Second, they actually decompose growth… their algorithm is MSD new business, plus MSD price, plus whatever the market gives. They put up 17% organic in 1Q26 and 21% in 2Q26, and the entire acceleration was the market bucket… “new business remains at mid-single digit. The price that we’re gaining remains at mid-single digits. All of the delta that you’re seeing is in the base business.” So the long-term guide is high-single-digit organic growth, converting at ~50% incrementals into low-double-digit EBITDA growth, before any acquisition.

Adjusted EBITDA margins should land near 40% for 2026, up 3pts YoY. High teens FCF margins in 2026 will help reduce net leverage toward 1.3x from 4.2x at IPO. CapEx runs ~3% of sales. This is one of the nicest compounding models I’ve come across at what seems to be a sweetspot… wish had finished the work sooner! Share are almost 15% off their highs.

We provide the following targets as a range of scenarios overtime. These are not meant to be explicit price targets, more so they provide a framework for where the stock could across different sets of outcomes. The details for all of this, and more, are below the paywall. Despite the run-up post IPO and large headline multiple, there remains a nice opportunity ahead, and the 13F scrape suggests this is genuinely underowned the funds that would typically be involved in a name like this.

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The pattern is easy to admire five years after it becomes apparent and when the record is public and the multiple agrees. It is only ever available at a reasonable valuation when something breaks the price without breaking the machine.

Madison Air Solutions (NYSE: MAIR) came public in April at $27 and just broke deal price. (See our prior work on this dynamic here… shouldn’t be entirely surprising is the takeaway link.) Shares peaked in the first few months at 27x NTM EBITDA - expensive by any measure. Add a softening macro on numerous fronts and higher rates and a BIG acquisition with equity to be raised alongside 4.0x net leverage and it’s no wonder why the stock is now ~45% off its highs. Then, add a restatement the market is anxious about was disclosed in the IPO prospectus back in March (balance sheet reclassification of redeemable NCI, restating 2023 and 2024, with no impact on income, revenue or cash flow). We look at the acquisition and path forward and are immediately reminded of acquisition indigestion seen many times before for similar businesses. Taking a view beyond this short-term hiccup yields material upside and an attractive risk:reward.

Overview

MAIR was the largest US industrial IPO in quite some time, and quickly ran to an intraday high of $44.50 creating a multiple problem. Then the tape turned against duration industrials. The Q2 print raised the sales guidance and the stock fell 9% anyway. On August 17th, the company announced a transformative acquisition, at an EV larger than its own public float, with underwritten debt and an equity component whose size and price are still undisclosed.

Looking forward, we should be most focused on whether the compounding algorithm is impaired. The CFO’s own decomposition on the Q1 call speaks to this… of 13% pro forma net sales growth, “volume was about 9 points, price was about 4. Commercial growth was mostly volume driven. That’s typically a backlog-driven business.” Then in Q2 they achieved 11 points of volume and 3 price. The company has outgrown US GDP in 16 of the last 18 years through 2025 (when measured on an if-owned basis).

Over the same four months in which the stock fell 42%, the business raised full-year sales guidance, grew Commercial orders more than 70% (up roughly 50% even excluding data centers), grew Resi through a falling housing market while expanding that segment’s margin by 423bps, and ended June with a record backlog near $2.9bn, more than half of it converting in 2027 and beyond, at 2.8x net leverage.

Today, pro forma for the deal, the stock trades at just under 14x 2027 EBITDA… for a business whose stated algorithm is mid-single-digit revenue growth converting to high-single-digit EBITDA growth before any synergy credit. From 27x to under 14x while guidance went up. We believe they are entering a unique window where EBITDA will compound above stated algorithm and assume no further M&A, nor a buyback, and very modest Resi / housing recovery out to 2030.

This is our first round of diligence, with more to come in the future as we go deeper on the product range and dynamics and refine estimates. For now, below the paywall we tell the high level story, the case for compounding… publishing in a timely manner here as the share price continues to approach levels we believe long-term investors will start to pick away to establish a floor. Math included, as always - matters more than the story (and don’t let people tell you that’s not the case).

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Kri-Kri makes Greek yogurt in one plant in Serres and sells most of it as supermarket own-label across Europe. Revenue grew 28% last year, and we estimate the plant ran near 92% of the milk intake its environmental permit allowed. Management deferred taking on new customers, and reported wasting product by over-running lines. Soon they’ll be able to show investors how much demand really exists in Europe for “authentic” Greek label yogurt (labels matter in the EU) just as GLP1 adoption also ramps.

Across fourteen reported years Kri-Kri compounded revenue at 14% a year. It did that from one site, through an energy war, and a milk inflation cycle. Demand has been solid, and now they need more room to run.

The market has picked up the permit alongside a sell-side note and run with it. We still see nice compounding upside on every time frame. The stock is breaking out and multiple modestly expanding but not demanding given the durability and drivers of growth. We are still looking for a call with management to understand the nuances and shape of the growth to come, but feel it’s reasonable to assume this capacity gets eaten up by end of the decade. The other important driver we’re trying to pin down and refine the range of outcomes for is milk input prices. These can swing and move GMs, but increasingly imported feedstock should also keep a lid on absolute costs (more on that below).

Secular demand growth

Kri-Kri is best analyzed as a manufacturing business, not a consumer brand. While their brand means something in some regions, the growth from here is increasingly exported and private label. Regardless, evidence points to the fact that they’ll be able to sell what they produce for the foreseeable future. There are three stacked demand curves… modest yogurt category growth, strong Greek yogurt share within the category (healthy and protein trends along side GLP1 growth, and now opportunity for them to take incremental share…

• UK Greek yogurt consumption growing 40%, importing some Kri-Kri already

• Authentic Greek, meaning strained yogurt made in Greece, is taking share inside yogurt.

• Europe sits at 2% GLP1 adoption against 12% in the US

• A Cornell basket study finds yogurt is the largest positive category shift among GLP1 users

• Kri-Kri taking share in authentic export private-label manufacture… we estimate it is the largest exporter, with 33.6% of a EUR 559m market that grew 42% in 2025.

So the growing demand of exported Greek yogurt has a very long runway supporting continued expansions. This is the type of long-term runway you want to look for to find multi-baggers. Nothing is guaranteed but it certainly leaves plenty of room to compound for years in a category where healthier eating habits can be driven by broad populations organically changing habits or via regulation or via GLP1 use incentives.

And for Kri-Kri, this is clearly their sweetspot and where they have been focusing the most effort.

Supply

The Serres plant operated under a permit capping milk processing at 299 tonnes /day, roughly 109k tonnes / year. Our intake reconstruction puts 2025 at about 100k tonnes. Management’s own commentary corroborates it. The ministry approved 554 tonnes / day, about 202k tonnes, split 480 dairy and 74 ice cream. The site expands 62%, water rights rise 39%, and a second whey digester doubles the straining bottleneck’s relief. The state co-funds the expansion. About EUR 23m of tax relief becomes available after the project completes at end-2027, so it phases from 2028, and a separate certified relief of roughly EUR 6.5m is already in hand with about EUR 4m usable in 2026.

How fast can the new plant ramp, and what is it worth?

Our base case fills the new ceiling to 87% by 2030, and net income roughly doubles against 2025 by 2029. The build is mechanical with milk intake times revenue / tonne, then margins from the milk work below. Revenue per tonne drifts from EUR 3.3k toward 3.5k on mix. That gives revenue of EUR 396m this year, EUR 497m in 2028 and EUR 604m in 2030. Management frames the current expansion as capacity for about EUR 500m of sales, and was careful to add that it depends on demand. Note that management states the Dynamo doubling against 2024, not 2025. Our plant-defined mid-case at full utilization is EUR 600m. The three anchors agree.

The cadence is the model’s biggest unknown. A doubling that arrives in one step in late 2027 and one that phases across six quarters are different stocks for a year. The company has never disclosed the sequence. Until it does, our 2027 carries the widest error bars in the model.

One broker models EUR 715.8m of revenue in 2029. At the company’s 2025 dairy revenue per tonne of milk, that needs about 263k tonnes of intake, or 130% of the approved ceiling. Their number is only reachable through a large mix shift toward fortified recipes, an unannounced further permit, or both. Perhaps there is further upside in scale or mix, but we would not underwrite this without confirmation from management.

Milk prices and margins

The cost base is roughly 90% Greek liquid milk. Asked directly what share of cost of goods is Greek versus EU milk, management said imports of raw milk are very limited, that they mostly use Greek milk, and that what they import is dairy commodities such as butter and proteins. So the cheaper leg is commodities, not liquid milk, and the premium full-fat cups and the domestic book carry Greek milk throughout. Greek farmgate stands near EUR 56.60 per 100 kilos against an EU average of about 41.84. The spread is above a third, the widest on record, and it helps through the commodity line rather than the milk line. The gross margin expansion of 5.5 points in Q1 is better explained by the price adjustments management took from H2 2025 and by falling dairy commodity prices, which management cited directly when noting the energy surcharge was largely offset.

Greece produces roughly 40% of the cow milk it consumes. Feed is imported and runs 60-75% of production cost. Farm numbers fell 42% in a decade, and 358 farms now deliver nearly three quarters of the pool. A price ~30% above the EU average has produced supply growth under 2%. The 2026 EU price decline is driven by a shrinking herd while the heifer pipeline is the thinnest in decades. EU prices firm into 2027 and 2028, exactly when the new capacity lands. Meanwhile, a growing competitor plans to triple production with a EUR 150 to 160m plant into the same market. Thus, we have tried to prudently give back some margins after a great 2026 for this spread.

However, this remains a key risk to monitor… a double squeeze, EU inputs recovering fast while Greece stays high, produced 2025’s 27.0%. Our bear carries exactly that.

Free cash flow coming

Today’s modest net cash position supports the buildout. Prior years saw lumpy working capital and CapEx leading to minimal FCF. Normal cadence with more scale and similar CapEx as those years will yield a growing net cash balance to nicely support the dividend (current 1.5% yield, or EUR 0.45).

Cumulative free cash flow after dividends from 2026 to 2030 is about EUR 111m. Phase 4, the post-2030 study, is EUR 100 to 150m. The cash the plant generates and the next project management is contemplating are the same size.

Valuation

We value the business on EPS as the going FCF will likely be given back in a few years to support further expansions. Importantly, past EPS declines were largely driven by GM compression resulting in real pullbacks in the stock. However, the underlying demand and volume growth support a nicely growth EPS algorithm when margins are normalized and observed over any multi-year time frame. We use a range of multiples of just 14-18x which result in a very modest PEG ratio. There is a scenario where finding growth stocks, with durable trends, in the EU becomes hard in the coming years as a result of so many secular headwinds… this could see Kri-Kri trade at a multiple of 20x EPS or higher.

The multiple range is not arbitrary. It comes off what buyers actually pay.

The transaction comps below should be viewed as the high end of what is possible.

Risks

UK case law defines Greek yogurt as made in Greece, traditionally strained, without additives. The fastest growing tier is protein-focused recipes lawfully declaring EU dairy inputs. A purist litigant or a front-page investigation into what authentic means could compress the whole category’s premium. Two mitigants are real... the practice is industry-wide, since Greece’s entire 400k tonne yogurt output could not exist on traditional straining from a 640k tonne pool.

Second, the input squeeze. BellRing fell 80%+ when protein inflation and club own-label broke its margins. Kri-Kri buys the same protein complex for its growth tier. However, they are unlevered, have a strong brand position, and pass-through on most UK voluemes.

Third, a competing plant is tripling capacity with state funding and is backed by the country’s most successful food-export builder. It arrives after our ramp fills, which is why it caps the terminal multiple and growth rather than the base case in order to strike a conservative approach. However, they will also begin bidding for the same fixed milk pool, so Greek farmgate drifts up in our base case rather than flat.

Fourth, capital allocation as the cash accrued through 2030 is likely to be redeployed again for expansion, it seems.

Conclusion

Kri-Kri is the manufacturer behind Europe’s fastest-growing food category, and the binding variable was never demand. Expansion is coming which will support multiple years of growth at the same time GLP1 adoption grows. This type of durable demand profile is rare to find in packaged goods, and we believe the market will pay a healthy multiple for it. It has secular, thematic growth, is self-funded, and entering new markets that are rapidly absorbing product. The risk remains input costs which will certainly swing over time, but this should be manageable. The large ~70% family ownership makes an outright acquisition unlikely, but acquisitions of this sort of growth and margin profile have come at multiples well above our underwriting cases. Current valuation is fair and we aim to get a call with management to drill down on the most important drivers.

DISCLOSURE

Position: At the time of publication, the author holds a position in KRI.AT.

Trading Policy: The author will not materially alter this position within 48 hours of publication. After this period, the author may buy, sell, or otherwise adjust the position without further notice. Changes to the author’s view or position will be reflected in subsequent publications when material.

Conflicts: The author has received no compensation from the issuer or any party with a financial interest in this security.

Forward-Looking Statements: This report contains the author’s opinions, estimates, and projections, including price targets derived from financial models. These are forward-looking statements subject to substantial uncertainty. If these assumptions prove incorrect, the actual value may differ materially, including scenarios of significant loss or total impairment. The price target represents the author’s estimate of fair value under the stated assumptions, not a prediction of where the stock will trade.

This report is provided for informational purposes only and does not constitute investment advice. See the full Terms & Disclosures for additional important information.

ADI reported its first quarter as a public company last week. One number changed our targets and most of the rest confirmed the setup. The new CFO put the real GM run rate at 21.35%, about 100 points below the base the July targets were built on. Reported margins had been flattered by tariff pricing and a $20M one-time refund. The targets move from $8, $30 and $58 to $7, $26 and $39, struck the same way as before (1yr downside, 1yr upside, 3yr upside). The bull case, a residential recovery, yields adds $33 and $49 at the same multiples.

The tape has been wild. I do not have good trading color to justify these moves. The stock was added to the Russell 2000 and S&P 600, but REZI was already a part of these. Mechanically, this should mean the index received the spinoff shares so was not a large buyer in the market. We also do not have any insider filings yet. The one-year target now offers 23% and the three-year offers 81%, about 19% a year. Importantly, a long term investor can look out three years to a resi recovery and see a 25% IRR from here. That’s worth doing the work on.

The size of the change deserves a clear statement. Our July numbers had 2028 EBITDA at $429M, but the clean, updated figure is $370M in our base case. This change was driven almost entirely by GMs, falling 100bps (100bps on $5.4B of revenue is $55M of the $59M cut). The demand call was right and the margin base was wrong.

The same arithmetic hits management’s plan. Their bridge ran 22.3% to above 22.7%, a task of 40 to 50bps. From 21.35% the identical target needs 135. At roughly 35bps per point of EB mix, that is four points, 18% to 22%, which is exactly their stated plan. Their target is internally consistent. Their $500M for 2030 also compounds off a lower base now. From this year’s guide it requires 15.1% a year vs. our clean path compounds 12.1%.

https://open.substack.com/pub/banyanlanecapital/p/adi-global-distribution-adig-greenblatt?r=5cm8h&utm_campaign=post-expanded-share&utm_medium=post%20viewer

Results

Four things moved our numbers. First, GM ran 21.3% to 21.4% in both quarters this year, and management called that the run rate of the business. The July targets started from 22.3%. Second, the mix engine stalled, it seems. EB revenue fell almost 3%. Management disclosed that roughly three quarters of the $800M program sits in residential AV, the one market still declining. A clear negative vs. expectations, but also provides cyclical kicker should the housing market thaw. Third, the guide itself of $275M to $295M of standalone EBITDA, below last year’s $295M, and about $265M excluding the refund. In addition, there were 4 analysts on the call asking questions, but all shorter term - good questions and trying to figure out the near term noise in numbers which is not uncommon in spins.

The call also laid bare the cost of the savings program, we’ll call this the The Savings Treadmill… $80M gross cost program nets against merit, inflation and growth spending to roughly zero. EBITDA growth therefore has to come from gross profit. Management said both part aloud. Sixty million of savings are already actioned, and operating expenses next year should not grow “significantly, if at all.” Flat opex is the win. The program costs money though.

The call. Our base case is the clean path below, because the savings are contracted and commercial demand is intact. Security is back to mid-single-digit growth, and management says most of the share lost in the system conversion has returned. The next print confirms it if net operating expenses decline as guided and the newly filed exclusive-brands revenue split holds steady. A residential turn moves us to the bull case. EB mix and GM flat together through mid-2027 ends the thesis.

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The stock has been more challenged than the chart above since covid, despite the underlying moat and strength of the business being unchanged.

The disconnect is due to both pull forward of pet adoption rates during covid, and the fact that Americans have been taking pets to the vet slightly less often for three years. The fear has been this is a broken consumer story. Meanwhile the growth engine re-accelerated from 4.5% to above 10%. Visits now increasingly suggest testing, thus creating incremental growth not tied to visits.

The AI angle is not a chatbot, but a cytology analyzer that replaced the glass slide. It is a $15 cancer screen that finds lymphoma months before symptoms. It is software that writes the medical record while the vet talks. Nine thousand of those analyzers are in clinics eighteen months after launch. Ten thousand clinics order the cancer panel. Next week, at the 13 August investor day, a fifth undisclosed platform may get unveiled.

I did the full workup in late July with the stock at $559, hoping to get a shot 5-10% cheaper. It never quite got there, then earnings hit, and shares rose nicely, again. So the honest title of this note is the one at the top. The turn is visible in the numbers, and I partially missed it. Below the line is the complete work… the business, history, why the acceleration is structural, and what the AI stack is actually worth. Also included are my forecasts and scenarios, and a preview of what I expect at the investor day.

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Elevator pitch

• Probe cards are consumables… they wear out and are rebuilt for every chip design, so revenue tracks wafer starts and design turnover, not capex sentiment

• Every AI path pays the toll so they win with both GPUs or custom ASIC, HBM or DDR, pluggable or co-packaged optics… all of it runs wafers, and every wafer gets tested

• Q2 proved the model with revenue up 32% and GMs 1,500bps in four quarters and EPS tripling

• A second engine is now lighting… co-packaged optics test revenue passes $20M this year… management sizes this market at $400M by 2030

• The stock is up 4x from its April 2025 low on four straight record quarters, but still maintains powerful secular tailwinds that present good multi-year upside

Why this opportunity exists

• The market files FORM under semicap equipment, so it trades on capex sentiment… revenue actually follows unit volume, which capex fear does not dent

• Complexity is good… test intensity per wafer compounds with stacking, pin count, and now optics

• The July selloff was a memory pricing scare and momentum washout… falling memory prices come from rising memory volume, and volume is FORM’s paymaster

The business in 60 seconds

FORM makes probe cards or boards holding thousands of microscopic springs that touch a chip while it is still on the wafer and check it electrically. A defective die caught here costs cents to discard. The same die caught after packaging destroys a $10,000-plus AI package. Cards wear out and are redesigned for every new chip, which makes this a razor-blade business. FORM holds the number one share in advanced probe cards, roughly twice the next competitor [VLSIresearch]. It also sells the probing systems used to characterize chips, which is where the optics story lives.

Free section ends here.

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The pitch

• On August 4, every Resideo (REZI) holder receives shares in North America’s largest security-products distributor.

• ADIG will debut trading with a $261M loss last year and 3.0x leverage, rated BB minus. Index funds and many active managers will punt the stock - a classic Greenblatt-style spinoff.

• Losses and the leverage were both inherited from REZI - they are the result of REZI’s 2018 Honeywell indemnity that it received upon spin. Operating profit grew every year underneath both.

• Management plan calls for EBITDA compounding from 2025 depressed $295M toward $500M as a result of finally getting hold of the strategy with initiatives that have largely been in the works for a year already.

• Even the bear grows EBITDA every year and sweeps debt below $100M by 2030, so the business survives but the multiple wobbles.

Why this setup exists

• Forced sellers: REZI holders own a products story. Index funds must sell what no index includes. Nobody will cover the stock for some time, potentially quite a while.

• Optics: $364M charge, junk ratings, and three different EBITDA figures likely to give many pause.

• Neglect: The business spent 30 years as a segment inside Honeywell, then Resideo, and it has never been managed for its own benefit.

The business in 60 seconds

ADIG is the middleman between roughly 1,000 electronics manufacturers and 100,000 security and AV installers. When a two-truck alarm contractor needs a camera, a panel, and a spool of cable today, on credit, they go to ADI. He also needs someone at the counter who knows which transformer fits. ADI runs 200 counters, 20 distribution centers, and 500,000 products to answer that need. Revenue is $4.8B. Gross margin is 22.3%. EBITDA margin is 6.2% standalone, against 10% to 13% for the best distributors. That gap is the whole investment. Security and fire are 65% of revenue, AV is 30%, data-comm is 5%.

Three straight years of growth through an ERP conversion and a housing trough, then three paths forward. Management’s own 2030 floor sits just below our base case.

The real pitch is the distressed print

To be clear about what we are actually interested in here, when mechanical selling starts on August 4 we believe the trough could bring a very attractive risk:reward. And few will have done the deep work to understand the opportunity they aim to execute against over the years to come. CD&R owns roughly 20% as-converted. Open-market common purchases from management would validate the equity.

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The typical lockup is 180 days after IPO allowing private shareholders, executives the opportunity to monetize. Everyone knows the date, and it sits in the prospectus months ahead. The lead up to these events serve as a well-known opportunity for long and short investors to position ahead of the feared supply that will swamp demand on the days that follow lockup expiry.

So, I went to check whether that actually happens. My last piece, Nine in Ten IPOs Break, found that most of an IPO’s damage lands in the first few months. That is well before the lockup opens. This is the follow-up, and it puts the lockup itself under a microscope.

I pulled 19 of the most recognizable IPOs of the past fifteen years, and ran a study of the period around each one’s 180-day unlock. Every figure here is market-adjusted, meaning the stock’s return minus the S&P 500 over the same days. A falling market

never gets counted as a lockup effect. Day 0 is the first trading day at or after 180 calendar days from listing. Direct listings sit out, since going public without underwriters means there is no lockup at all. Coinbase, Palantir, and Roblox are therefore excluded.

Here is the short version. The dip everyone waits for has already happened by the time the lockup arrives. The unlock day itself is a volume event with a small price notch. The two largest insider floods in the sample did not crater their stocks. They rallied them.

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The fade shows up before the unlock

The dip is mostly over by the time insiders can sell. Stack all 19 names on the same clock and the shape is plain. The average IPO walks into its unlock already down about 15% against the market over the prior 30 trading days. The median is worse, at down 21%. By the time insiders can legally sell, the selling is nearly done.

Some of that slide is ordinary post-IPO drift. These are expensive stocks. The quiet period ends, when the company and its bankers stop promoting the stock, and the first earnings misses land. Some of the slide is the market front-running a date it can see coming. I will not claim the lockup causes the whole 15%. But the direction is clear, and it runs opposite to the folk model. The weakness comes before the event.

Volume is the only thing you can count on

The one dependable feature of an unlock is a jump in volume. On the day itself, volume explodes. The mean is 4.5× normal, and the median is 3×. Every marquee name in the sample lit up. Twitter traded 11×. Uber traded 15×. The float, meaning the shares actually available to trade, multiplies overnight, and the tape shows it at once.

The price move is a different animal. The unlock day is usually a small down-notch. 15 of the 19 names fell against the market. But the average was only −2.7%, and it does not stick. Volume tells you the event happened. It tells you almost nothing about direction.

The reaction is an average, not a rule

The base rate dissolves the moment you look at the names. The 20-day reaction runs from Beyond Meat at −28% to Facebook at +33%. Just over half the sample was negative. The rest rose, some of them sharply. This is not something you can trade blind on any single name. It is a faint tilt buried inside huge dispersion.

The worst-behaved cohort is the one you would guess. The 2019 profitless-unicorn class averaged −5% on the day, on roughly 7× volume. Uber, Lyft, Pinterest, and Peloton led it. The three names that barely flinched arrived at their IPO already profitable, namely Alibaba, Zoom, and Facebook. That is the same fault line my last piece found across the whole asset class.

The biggest single unlocks rallied

The largest single unlocks in the data went up, not down. The cleanest test sits inside two stocks that released their shares in stages.

Facebook spread its release across five dates. The reactions ran the full range. Down 7% on the 90-day tranche. Almost nothing on the 150-day. Then up 14% on the 180-day unlock, which freed 777 million shares. That was the single largest block of the whole schedule. The biggest flood of insider stock in the sample produced a rally.

The +19% pop a few days earlier was Facebook’s Q3 earnings, not a lockup. The two get conflated constantly, and they are not the same thing.

Snap tells it in miniature. Its first unlock freed 400 million shares to early investors. The stock had already bled 22% into the date, and it slipped about 1%. Then came the big one. 782 million employee shares, freed four days after a poor earnings report. That is the exact setup the fear model says should be catastrophic. The stock rose 5.5%.

The mechanism is not mysterious. By the time the flood everyone circled finally arrives, it is the most anticipated seller in the market. The overhang that pressed on the stock for weeks clears. The last buyer of downside protection is done. It is sell the rumor and buy the news, expressed in share count.

The size of the flood is irrelevant

The size of an unlock does not predict the reaction. If the fear model were right, the deals that free the most stock should fall hardest, and they do not. Initial float across the 19 names clustered in a thin band. The median was around 10% of shares outstanding, with none above 20%. So the lockup takes each stock from a sliver of tradeable float to nearly all of it. That is a float expansion of roughly 6× to 16× overnight.

The expansion has no reliable link to the reaction. The rank correlation is near zero over the 20 days after the unlock. On the day itself the faint tilt runs backwards, with bigger expansions posting slightly better days. The two largest single-session releases settle it without a regression. Facebook freed 36% of its shares in one day, and Snap freed 67%. Both rose. What sets the reaction is not how much stock unlocks. It is whether the market saw it coming, and with the date in the prospectus for months, it always does.

Robinhood shows where the cliff went

The clean 180-day cliff is disappearing, and Robinhood is the tell. Its lockup was a patchwork of early releases. A slug of shares became sellable under Rule 144 from the 91st day. Rule 144 is the SEC rule that lets holders sell restricted stock after a set holding period. Price-based triggers freed more, and the nominal 180-day date sat underneath it all.

By the time that date arrived in late January 2022, it was a non-event. Volume ran 1.1× normal. The float had already been let out in pieces, and the stock had already fallen by roughly two-thirds on its own merits. Robinhood’s worst day in the window was not a lockup at all. It was the −10% reaction to Q3 earnings.

More deals now write in these staggered, performance-based releases. The single date you could once circle is turning into a smear. If you still trade the lockup, use the date where the shares actually move. The volume spike will tell you, and often it is nowhere near the 180-day mark.

The folk trade runs backwards

The intuitive lockup trade is backwards. The obvious version is to wait for the lockup and short the flood, and it points the wrong way. The fade is a pre-event, not a post-event. By the day the shares unlock, the crowd has already shorted it, and the overhang is already in the price.

The evidence says the stock is closer to a local bottom than to a fresh leg down. Across the sample, the average name is at its worst the day after the unlock. Then it grinds back to roughly flat against the market within 60 trading days.

If there is an edge near the event, it is the mirror of the folk trade. It is the weakness into the print, not out of it. But the same wall from my last piece applies here, and harder. Borrow on a fresh IPO is scarce and expensive. It gets cheap only once the lockup floods the float, and by then the move is over.

Options are the cleaner vehicle, but implied volatility around these dates is brutal. The pattern is real, but the tradeable version is small. It lives in careful timing and instrument selection. That gap is probably why it survives.

Caveats

This is 19 hand-picked marquee names, not the full universe. They are the famous, heavily analyzed deals with the loudest lockup coverage. That is deliberate. It also bakes in survivorship and selection, and the small-cap tail behaves worse. Returns are market-adjusted with a beta of one, not a fitted factor model.

The 180-day mark is a convention. I use each stock’s first trading day at or after IPO plus 180 calendar days. For the two names with staggered or early-release structures, Snap and Robinhood, that date misses the real unlock. That is why their day-0 volume is flat. The “down 15% into the event” figure blends real pre-positioning with ordinary post-IPO drift, so it should not be read as pure lockup anticipation. LinkedIn belonged in the sample but was dropped, since clean split-adjusted history for it no longer exists after its acquisition.

What I take from this

The lockup is a supply event the market prices in advance. The damage lands in the weeks before, not the day of. If you wait for the unlock to tell you something, you are quite possibly reading yesterday’s news.

Volume is the signal, and price is noise. Every unlock spikes volume. The direction of the day is a small, mostly-down flicker that fades within weeks.

The size of the flood is not the risk. The two largest insider unlocks in the sample both rallied. Across all 19 names, the float-expansion multiple has no bearing on the move. A fully anticipated seller clearing the overhang is a bottoming mechanism, not a crash.

Check the date, not the calendar. Early-release and staggered structures have moved the real unlock off the 180-day mark. Follow the volume, not the six-month rule of thumb.

The lockup is not where IPOs break. It is where the market finishes pricing a break it saw coming months earlier. And often enough, it is where the selling finally ends.

19 marquee US IPOs from 2012 to 2021, with daily prices from Financial Modeling Prep. Event study around each name’s 180-day lockup expiration, defined as the first trading day at or after IPO plus 180 calendar days. Returns are market-adjusted against the S&P 500. Staggered-tranche dates for Facebook and Snap, and the Robinhood early-release timeline, come from contemporaneous reporting and SEC filings. Per-tranche volume uses a trailing 20-day median. Unlock magnitude compares each deal’s base offering size, excluding the greenshoe, to shares outstanding from the quarterly filing nearest each unlock. The greenshoe is the underwriters’ option to sell up to about 15% more shares. Direct listings are excluded. None of this is investment advice. It is a base-rate study. See here for Disclosures & Disclaimers.

So I had Fable build it. Roughly 3,000 US operating company IPOs from 2010 through mid 2026, assembled from Ritter’s IPO database, IPOScoop’s offer price records, and SEC prospectus filings. SPACs, closed end funds, and ETF listings are stripped out. After requiring a valid offer price of at least $4 and a clean daily price history from listing day forward, the core sample is about 1,700 IPOs. Of those, 1,638 also have financial statements from around the time of listing.

The typical IPO loses money

Index every IPO to its offer price, so offer equals 100, and stack all the price paths on top of each other. The median IPO closes day one around 106. It drifts up for a few weeks, tops out, and then bleeds. By the end of year one the median IPO trades below its offer price. By the end of year two it sits around 87 and is still falling.

The mean tells a completely different story. It stays above par and grinds higher the whole time. That gap between mean and median is the entire IPO asset class in one chart. The average gets rescued by a small right tail of enormous winners while the typical name in the group is a losing investment from the first print. Buy every IPO at the day one close and your results depend almost entirely on whether you caught the handful of Airbnbs (priced at $68, peaked at $220, then chopped between $80 and $160 for ~5 years).

A few base rates from the sample are worth having in your head. The median day one pop is 6.5%. The mean is 17%, dragged up by the tail. And about 29% of IPOs close their first day below the offer price. The pop is not a law of nature. It is a coin flip with a mild upward tilt.

The early peak comes fast. Looking at the first 60 trading days, the median IPO tops out around trading day 24, roughly a month after listing. About one in five IPOs peaks within the first three days, meaning the pop was the top.

Then comes the purge. Measured from that early peak, the median maximum drawdown over the following year is 50%. The 25th percentile is 70%. This is not a mega cap thing or a busted small cap thing. It is the base rate for the asset class, and it sits right in the range Truist found on their 30 famous names.

More than 90% trade below their offer price at some point, and the median first breach happens around trading day 31, about six weeks in, after the quiet period ends and well before the lockup opens.

Who comes back

Since breaching the offer price is nearly universal, the interesting question is how long stocks stay under. Most breaches are brief. A stock hovering near its offer dips below and pops back within days. But there is a thick, stubborn tail. I ran the recovery question through survival analysis, treating delistings both as censored observations and as permanent failures, and the two versions barely differ. About 15% of breachers are still below their offer price a full year after first going under. Roughly 10% are still under three years later. Once a name settles into that tail, delisting becomes a common exit. About 40% of the full sample no longer trades today.

Only about six in ten IPOs ever get back to their early peak, and the ones that do often take the better part of a year.

One accounting flag splits the whole market

At the time of listing, only 38% of these companies had positive net income and only 51% had positive EBITDA in their latest fiscal year before the offering. Split every path metric by that one flag and you get two different asset classes.

The EBITDA positive group pulls back a median of 38% from its early peak. Its median price path hovers around par, 103 at one year and 99 at two. Two thirds of these names eventually reclaim their early peak. These stocks mean revert.

The EBITDA negative group pulls back a median of 60%. The median path sits at 88 after one year and 68 after two, still declining. Nearly half are delisted today.

And the part that should bother you. The unprofitable names pop harder on day one, a median of 8.7% versus 5.5% for the profitable ones. The market pays its biggest opening premium to exactly the cohort with the worst subsequent outcomes. Story stocks pop on story. Then the quiet period ends, the lockup expires, the cash burn continues, and gravity does the rest. As far as I can tell, essentially the entire famous long run IPO underperformance result lives inside the unprofitable half of the market.

Two refinements on this.

First, pop size interacts with profitability until it stops mattering. Profitability protects you in every pop bucket except the biggest one. A modestly popping profitable IPO, up 0 to 10% on day one with positive EBITDA, behaves like a normal stock, with a median one year forward return from the day five close of about plus 3%. But IPOs that popped more than 75% were toxic no matter what the financials said. Median one year forward returns were minus 37% for the unprofitable ones and minus 47% for the profitable ones, though that last cell is small. A giant pop is not a quality signal. It is a supply and demand dislocation that gets corrected over the following year, usually violently.

Second, growth partially redeems cash burn. Among the EBITDA negative names, the top quartile of revenue growers, with growth above roughly 80% and a median near 170, showed much better forward returns, roughly minus 12% over the next year versus minus 30 for the slower growers, along with lower delisting rates. The true kill zone is the slow growing money loser. Burning cash while growing less than about 20% carried a median pullback of 64% and about half of those names are gone. Burning cash while hypergrowing is a gamble. Burning cash while growing slowly is a diagnosis. VC backing, for what it is worth, mostly proxies this same split, since 79% of VC backed IPOs came public without positive EBITDA.

The uncomfortable trade

Put the pieces together and a systematic pattern falls out that is almost embarrassing in its simplicity. Short the unprofitable IPOs after the early peak. Entering short at the day 20 close and covering six months later produced a median gain to the short of about 16% with a 63% hit rate across 800 EBITDA negative IPOs. Waiting until day 40 or 60 does slightly better still. Run the same trade on the profitable cohort and you get about 2%, which is no edge at all. The whole anomaly is concentrated in the cash burners.

Before anyone runs off to build this, those numbers are gross of borrow costs, and borrow is exactly where the market defends itself. There is no rule stopping you from shorting a new listing. You can short the moment your broker locates shares. The problem is that shares barely exist to borrow at first. IPO stock has not settled, lendable float is tiny, and fees on fresh deals routinely run to triple digits annualized. In practice, borrow becomes possible within the first week on larger deals, tolerable over the first month, and cheap only after the lockup expiration floods the float about six months in, by which point much of the fade has already happened. Options usually start listing about a week after the IPO and are often the cleaner early vehicle, though implied vol on fresh IPOs is brutal and eats a good share of the expected fade. The edge in the data is real. The implementable edge is smaller and lives in careful instrument selection. That gap, where everyone can see the pattern but few can cheaply trade it, is probably why the pattern survives.

Caveats on base rates

Prices are split adjusted, and I cross checked day one closes against contemporaneous records to catch adjustment mismatches. About a fifth of names needed correction, mostly reverse split casualties. Names with unrecoverable price history, which skew heavily toward fast failures, are missing entirely, so if anything these numbers flatter the asset class. Fundamentals use the fiscal year closest to listing, which for some names is the first post IPO year. Companies that changed tickers along the way, which usually means they were acquired or rebranded, drop out of the sample, and since acquisitions skew toward good outcomes this cuts mildly against the recovery numbers. Offer price records also thin out after 2020, so a handful of famous recent listings like Reddit, Arm, and Cava sit outside the offer price sample even though their price paths check out fine. Direct listings were never in scope since they have no offer price at all. Recent IPOs have not had time to complete their arc. And the 2020 and 2021 vintage, where 60% of IPOs were unprofitable and median pullbacks hit 66%, weighs heavily on the worst cells. The pattern shows up in every era but the magnitudes move with the cycle.

What I take from this

If you like an IPO, plan around a better than 90% chance it trades below its offer price at some point, most likely one to three months after listing. The best time to buy something you believe in is rarely week one. The supply calendar and the data both argue for patience measured in months, not days.

One accounting flag, positive EBITDA at listing, separates stocks that mean revert from stocks that melt. It is the cheapest quality screen in the market and almost nobody applies it to new issues.

And if a deal doubles on day one, that is a reason for caution rather than celebration. The biggest pops had the worst year one outcomes even among profitable companies.

The IPO market is not mysterious. It sells stories at peak enthusiasm into constrained supply, then delivers the shares, and the truth, on a six to twelve month delay.

Data covers roughly 3,000 US operating company IPOs from 2010 to 2026, built from Ritter’s IPO database, IPOScoop, and SEC filings, with daily prices from FMP and Yahoo. The core sample with financials is 1,638 names. None of this is investment advice. It is a base rate study, and base rates are where the bodies are buried.

The verdict, up front

Supply is close to a known quantity. Every project is announced and mapped. The entire 2028 supply band, from announced-only to a fully induced wave, is about 3 to 4 points wide, and the single biggest swing inside it is one company’s tool orders. Undersupply persists through 2028 on the announced path, the base-case 2028 gap is roughly minus 1 point, and 2029 re-tightens because the buildout outruns everything under construction.

Demand is the debate. Morgan Stanley raised its 2027-28 hyperscaler capex forecasts by 9% and 10%, to $1.2 and $1.4 trillion, and now models hyperscaler compute capacity growing roughly 4x from 2025 to 2028 (SemiAnalysis is ahead of even these figures). On top of that curve sits a stack of innovation vectors, each individually worth 2 to 10 points of the 2028 balance, each with a dated gate inside the next 18 months, and each with real companies shipping real products against it today. That stack, not the fabs, decides whether 2028 digests or re-tightens early.

One conditional governs everything. If AI capex enters a bear market, all bets are off, and the point to watch is spot prices cracking while contract prices hold, alongside widening credit spreads on datacenter debt. On the branch where spend keeps pace with expectations, buyers planning in multi-year cycles rationally pay for uninterrupted supply rather than haggle over one year’s balance, and the deposits flooding producer balance sheets say that is exactly what they are doing.

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Price is doing all the work

Korea hosts roughly ~60% of world NAND capacity and publishes its exports monthly in both dollars and kilograms. Divide one by the other and the implied selling price is up three to four times year over year while physical volume sits flat. Volumes stay flat through the coming quarters by construction... no new fab delivers first bits inside 2026, and a wafer already started still needs about a quarter to finish. Every claim in this piece can be checked against that one free dataset, on the first of every month.

The tape behind that chart is worth spelling out, because the individual prints are hard to believe until you line them up. Korea’s NAND exports ran +366% year over year in January, +377% for the first quarter, and +207% in May... on falling kilograms. A one-terabit TLC chip that sold for $4.80 has printed $10.70. First-quarter contract prices settled up 33 to 100% depending on the product, and second-quarter settlements came in up another 70 to 75%. Counterpoint put first-quarter industry revenue at $46 billion, an annualized pace nearing $200 billion against roughly $74 billion for all of 2025. One honesty note belongs here because it applies to every forecast you will ever read on this market, including this one. The suppliers stopped disclosing absolute bit shipments years ago, so every exabyte model in existence, TrendForce’s, the sell side’s, and this one, is constructed by chaining disclosed growth rates off an anchor. The dollars and the kilograms are the only hard numbers in the whole debate, which is exactly why the Korea series is the referee.

Twelve years of deflation, inverted in one

NAND’s natural state is falling prices... cost per gigabyte drops 15 to 25 percent a year, bits compound, and buyers get rescued by physics on schedule. Twelve years of that pattern ended with the 2023 bust pricing bits at cash cost, roughly $0.055 per gigabyte, and producers answering with the deepest cuts in the industry’s history. AI demand arrived in late 2025 into a supply base that had been deliberately shrunk.

Walk the regimes and a base rate falls out. The 2016-18 supercycle was cloud demand landing on the 3D transition, and supply arrival cured it... prices fell roughly 60% in 2019, about two years after the price signal. The covid whipsaw pulled demand forward and then took it back. The 2022-23 collapse was the worst in the industry’s history, the first time bits ever traded at cash cost, and it did something no previous bust had done... it taught the survivors what the bottom actually looks like. Industry revenue went $57 billion in 2018, $39 billion in 2023, $74 billion in 2025, and the 2026 build now points to roughly $320 billion. Read that last jump carefully. Bits are up maybe 10% this year. The rest is price. Every prior shortage in this market was cured by supply within 18 to 30 months of the price signal, and that base rate is the strongest argument the bears have. The counterargument is physical. This time the cure is slower, because stacking toward 1,000-plus layers now requires bonding finished wafers together, every bonding step costs yield, and roughly a fifth of world capacity sits politically frozen at legacy nodes in China under export-control rules. The deflation that always rescued buyers is fading exactly as the biggest buyer the industry has ever seen walks in.

The buyers keep raising their own numbers

Plain and simple, buildout numbers keep going up... at least for now, though the revisions are smaller than early 2026 rounds. Morgan Stanley’s rebuilt bottom-up model puts hyperscaler compute capacity at about 30 gigawatts in 2025 growing to roughly 120 by 2028, four times in three years, and its 2027-28 capex forecasts moved up 9% and 10% in a single week, with Meta up 29% and 22% and Amazon up 15% and 29%. And look at what is driving the cost of a datacenter from $35 billion per gigawatt on GB200 racks to $39 billion on GB300 to $49 billion on Vera Rubin... partly memory inflation itself. Memory prices are now large enough to move the cost of the datacenter, which feeds the capex forecasts, which feed memory demand. Revisions this cycle have run one direction.

Those bars slot into the wider global picture. SemiAnalysis tracks global datacenter capacity outside China near 89 gigawatts in 2026, about 106 by 2027 on grid-connected supply, and as much as roughly 338 by 2030 once converted sites and behind-the-meter generation are counted. Inside that envelope, converting disclosed capex to capacity at $45-55 billion per gigawatt yields gross additions of 25-30 gigawatts in 2026 rising toward 70-77 by 2029, about 60-65 net of equipment refresh, and Morgan Stanley’s hyperscaler-only additions of 21, 29, and 36 gigawatts sit inside it as the floor. Each gross gigawatt carries 16 to 17 exabytes of NAND in the base case, and an independent rack-by-rack build lands within one percent of that arithmetic in every overlapping year.

AI is taking the market

AI is now the marginal buyer of every bit, and it is pushing phones and PCs down the queue. Handset makers are already cutting storage per device to absorb the price shock, resuming their traditional role as the market’s shock absorber, while enterprise and AI bits go from 22% of the market in 2024 to roughly 58% by 2030 in this build. Consumer becomes the residual claimant on wafers, which is why it absorbs the shocks in both directions.

The engine behind that green wedge... when a model works a task, it holds a running memory of the session, the KV cache. The physics of it can be derived on one page. A model writes somewhere between 35 kilobytes of cache per token, for the most aggressively compressed architectures like DeepSeek’s, and 300-plus kilobytes for frontier dense models, which means a single million-token session occupies 35 to 300 gigabytes per conversation. That state used to live in scarce GPU memory and die with the session. Agents broke the arrangement, because an assistant working a multi-day task cannot afford amnesia, and the operators did the arithmetic. Parking the state on flash costs about ten cents a day, while recomputing it burns about two dollars of GPU time every single time, and takes minutes the user will not wait. A 70-billion-parameter Llama model writes about 326 kilobytes of cache per token, which means a terabyte of expensive DRAM holds roughly eight minutes of context before eviction begins and hit rates collapse. Manus, the agent startup Meta bought for $2 billion, calls cache hit rate the single most important metric in agentic AI, and agents generate on the order of 100 times the tokens of a human chat. Moonshot’s Mooncake has pooled these caches across DRAM and SSDs at thousands-of-nodes scale since 2024, with peer-reviewed serving gains of 59% to 498%. Nvidia industrialized the pattern in January... ICMS, a dedicated flash tier for each Rubin pod, sized in Nvidia’s own words at petabytes per pod, shipping with the BlueField-4 processor in the second half of this year.

And the pull on wafers is bigger than the bits. A flash tier written like memory reserves 2 to 3 units of physical capacity per unit of usable capacity to spread the wear, and the AI tier is reviving one-bit-per-cell SLC media, which consumes three times the wafer area of a mainstream TLC bit. Samsung has exited MLC outright, and every low-bit-per-cell tier is reported extremely short. Stacked, the affected volume draws three to four times the wafers per usable exabyte, which is why wafer demand is rising faster than bit demand and why the shortage binds at the wafer, not the exabyte.

Supply... take it as given, inside a defined band

A handful of companies own effectively all the fabs, a greenfield takes 15 to 42 months from decision to first bits, and every project is announced and mapped below. That makes supply the knowable side of this market, and the honest way to treat it is as a given with a band. The band runs like this. 2026 is fully written, about 55,000 wafers per month of additions, 3.6 percent of the installed base, plus or minus a point. 2027 is plus or minus 2 points, set by K2’s ramp cadence and Dalian’s tool installs. 2028 is plus or minus 3 to 4 points, and Samsung is nearly the entire swing... V10 is slated for mass production in late 2026, yet as of May the tool orders had not been placed, and those purchase orders start a 15-to-21-month clock the whole market can read. 2029-30 widens to 8 to 10 points as M17, P5, Singapore, and YMTC’s next fab ramp or slip. Everything else is a 2029 story.

Why so much confidence in the band? Because the machinery only has so many levers, and the fast ones all point the wrong way. A wafer takes about three months and a thousand sequential steps to flow through a fab, so output physically cannot spike inside a quarter... that is the base clock under everything. Above it, the menu is short. Restoring idled utilization is the one fast lever that adds bits, and it is already spent... that is precisely what the flat Korea kilogram data means. Switching wafers into the AI-preferred one-bit mode is instant and subtracts two-thirds of their output. Node conversions are J-curves... output falls during the tool swap, then yield climbs from roughly 60% to 90% over a year. Greenfield is 30 to 42 months of concrete physics. And sitting on top of all of it is the most under-modeled friction in the industry... qualification. An enterprise drive must pass 6 to 12 months of hyperscaler validation per drive per platform, and a new node restarts much of it, so qualified supply structurally lags physical supply by two to four quarters. The net of all this is that supply arrives as datable lumps, the earliest observable event in the longest chain is a tool order, and that is why a single Samsung purchase-order headline carries more information than most quarters of earnings.

One paragraph of history explains why the band is credible rather than hopeful. This market earned its undisciplined reputation honestly... around 2003, roughly a dozen producers expanded into every uptick, and twenty years of losses did the consolidating, down to five groups plus one Chinese entrant, with the top two controlling about 58% of wafers. The 2023 bust finished the education. Now, against the strongest inducement any commodity has ever offered, a $15-20 billion fab paying back in under two years, the incumbents are still holding formation. The Kioxia/SanDisk joint venture funds growth entirely inside existing building shells, with either partner able to veto expansion and any new-fab decision pushed to fiscal 2027-28. Micron’s stated policy is no new NAND wafers beyond its Singapore project. SK hynix waited until this month to announce the cycle’s first true greenfield, and its first bits land in 2029, not 2028. The exception is state-funded YMTC, around 8 percent of wafers heading toward 17 by 2030, indifferent to price by design. Whether formation holds against a decade-long demand wave is a fair question. The tell is public, and it is Samsung’s order book.

The balance, and where the real debate lives

Cross the demand envelope against the two edges of the supply band...

In 2028, the difference between announced-only supply and a fully induced wave is worth about 2 points. The difference between the demand paths is worth up to 9. Supply sets the stage... demand writes the year. That is why the rest of this piece is about demand.

2028... the demand drivers, one at a time

The fair way to handle a feared year is not to argue it away. It is to quantify what would deepen it and what would fill it, each variable alone, with a probability and a date. Do not sum the green bars... several are correlated (the attach dial and the SLC shift overlap in the same racks), and stacking them would manufacture a bull case. Read them as independent answers to one question. How much does this single variable move the 2028 balance if it goes its way?

1. The intensity dial (+7 to +9 points, roughly a 30 percent chance). The base case holds storage per gigawatt flat, and every hardware precedent argues against that... HBM content grew roughly 50 percent per GPU generation, the newest racks carry four times the system memory of the prior ones, and cache-hit economics improve as storage is added, meaning flash converts directly into effective compute. The plumbing for this is shipping, not slideware. Nvidia’s Dynamo scheduler and its NIXL transfer library, riding GPUDirect Storage, let a GPU pull cache straight from flash with microsecond latency, and BlueField-4 fronts the whole tier. The storage industry has piled in behind it. WEKA’s Augmented Memory Grid, already generally available and validated with Supermicro, streams cache between GPU memory and what it calls a token warehouse at roughly 300 gigabytes a second per host, claiming a thousand times the cache capacity of DRAM and a twenty-fold cut in time-to-first-token on 128,000-token contexts. VAST Data open-sourced its equivalent, VUA, showing roughly threefold faster first tokens at 30,000-token contexts. Pliops sells a purpose-built accelerator card, an ASIC that turns a GPU server’s SSDs into a cache tier without touching the cluster architecture. Hammerspace, DDN, Lightbits, ScaleFlux, Peak:AIO, MinIO, Cloudian, and Graid all ship variants, and Quanta builds a server around the concept. If attach compounds the way memory content always has, 2028 swings from minus 1 to plus 8 on this dial alone. The range is measurable... the context tier spans 300 to 2,500 terabytes per rack depending on whose configuration wins, a spread worth roughly $200 billion of 2028 industry revenue, and it converts from assumption to measurement the day someone opens a shipping enclosure with a screwdriver, likely in the first quarter of 2027.

2. The memory transition (+3 to +5 points, roughly even odds). The deeper story practitioners keep telling is flash entering the memory hierarchy itself, and it is a wafer story, not a bit story. High Bandwidth Flash is SanDisk’s invention... sixteen flash dies stacked into a 512-gigabyte device delivering 1.6 terabytes a second, in a footprint that drops into an HBM4 socket, holding about four times the capacity of the HBM it sits beside at comparable cost. SanDisk seated David Patterson, the Berkeley architect behind RISC and RAID, and veteran chip designer Raja Koduri on its technical advisory board to shepherd it, then signed SK hynix last August to co-develop the standard, a competitor-turned-partner arrangement the industry has not seen since the early HBM days. Samsung and Micron are reported to be running their own designs behind it. One rung down, Kioxia’s XL-FLASH answers Nvidia’s explicit specification for a high-IOPS AI drive... single-bit cells read in about five microseconds, an order of magnitude faster than ordinary flash, with samples due this year. Both products run on the same production lines as mainstream flash, so every wafer they win comes out of the common pool, and because single-bit media takes triple the area, each exabyte of this tier effectively withdraws about two more exabytes of ordinary supply. The tier does not need to be huge to matter... it needs to exist.

3. The CPU-server line (+5 to +10 points, genuinely unresolved). Agentic AI turns out to be CPU-hungry... the scaffolding around every model call, the tool calls, retrieval, sandboxing, and scheduling, runs on ordinary cores, whether Intel and AMD sockets or the hyperscalers’ own Graviton, Axion, and Cobalt chips. A JPMorgan and Gartner forecast circulating this spring put server CPU units at 68 million by 2028 versus 26 million in 2025... stress-tested against wafer supply and the more conservative sell-side numbers, the mechanism survives with the magnitude cut by a third, to roughly 44 million. The strongest confirmation on record came from AMD itself, guiding that its server CPU shipments will decline in late 2026 because memory cannot be procured. Every one of those servers carries enterprise flash. The open question, and it deserves to be stated as open rather than assumed... is this buildout already inside the gigawatt envelope, or additive to it? If additive, it is the largest single tightener on the board, and Mercury Research’s late-August unit print will start answering it.

4. SOCAMM returns as flash (+2 to +3 points, roughly even odds). When Nvidia cut the Vera Rubin memory configuration from 192 to 96 gigabytes per module, the displaced context state did not vanish... it moved down the hierarchy toward flash, and the module sockets ship installed and empty either way. Dell, HPE, Supermicro, and Quanta are productizing the flash bays now, and the first wave of buyers is on the record... CoreWeave, Crusoe, Lambda, Nebius, and Oracle Cloud among them. If the deferred state lands in those bays through 2027-28, it is incremental NAND demand that no percentage forecast contains.

5. Samsung slips (+2 to +3 points, maybe one chance in three) is the one supply-side row worth carrying... every quarter of V10 slippage past mid-2027 removes supply from a 2028 that consensus already books.

The looseners get equal weight. A hyperscaler funding shock (minus 20 to 30 points, perhaps a one-in-eight chance) is the only force fast enough to break the balance before the fabs do, and it announces itself... spot cracks while contracts hold, and credit spreads on datacenter debt widen. Model routing (minus 3 to 5 points) is the honest demand-side risk... cheap small models handling more queries could shrink state per query even as queries grow. The compression version of this fear was just answered the other way. DeepSeek’s latest model cut cache size roughly tenfold, and total flash-resident context rose as cache-hit pricing collapsed and usage exploded, the oldest pattern in technology economics. Routing remains open. The full supply wave (minus 2 to 4 points) is smaller than intuition suggests, because even a maximal wave mostly lands in 2029 and later. Deeper consumer cuts (minus 2 to 3 points) are the shock absorber absorbing more.

What the fork does to price

Here is where the volume debate becomes a dollars debate, and where the structure of this cycle diverges hardest from every prior one. While shortages persist, price rises, capped only by what the contracts allow. A correction is not a schedule... it is an event, and the event requires two things to happen together, tool orders that have not yet been placed, and a demand undershoot that the buyers’ own raised forecasts argue against. In the base case, blended pricing grinds to roughly five times late-2025 levels by the end of 2027, gives back about 15% through the 2028 digestion, and firms again into 2029. The revenue arithmetic under that path runs from a peak near $314 billion in 2027 to a trough around $215 billion in 2028 and back to roughly $298 billion by 2030. The bull path, where content compounds and the correction never gets room to happen, grinds toward $936 billion by 2030... which, for calibration, is roughly the world the most evangelical price targets in this sector quietly require. The bear needs everything at once, soft demand and a full supply race and bending floors, and even then it produces $82 billion in 2028, a one-year drawdown harsher than the entire 2023 crash.

Two things on that chart deserve a hard stare. First, 2026 and 2027 barely fork at all. Those years are locked by allocation and contracts, which means the entire investment debate compresses into 2028 and beyond... trade the fork, not the consensus. Second, look at where the downside paths land. Every scenario keeps 2028-30 pricing above the 2023 trough of $0.055 per gigabyte. The base-case floor sits near $0.159, about 2.9 times the trough. The bear floor sits near $0.070, about 1.3 times. That spread, 1.3x versus 2.9x trough, is the single most valuable unknown in the entire model, and it is not a demand question or a supply question. It is a contract question, which is where this piece goes next... after one more stop on the demand side.

The upside has a calendar, and a cap table

What separates this demand stack from a story is that every vector carries a dated gate, a moment when it converts from assumption to measurement, and the whole calendar fits inside 18 months. Two more vectors sit beyond the tornado. Per-user persistent memory is quietly becoming its own funded software category... Mem0, which raised $24 million and became the memory provider inside Amazon’s agent toolkit, processed 186 million memory API calls in a single quarter. Letta grew out of Berkeley’s MemGPT research and pages an agent’s memory between context and disk the way an operating system pages RAM. Zep builds timestamped knowledge graphs so an agent knows what was true and when. Microsoft now ships user-scoped memory inside Azure AI Foundry and Oracle built a memory core into its database. Every fact those layers retain is a write that outlives the session, multiplied by user counts in the hundreds of millions. This is the vector where big and sudden is most likely and least priced, because it changes the demand equation’s very units... inference storage stops being per-query and becomes recurring per-user. Storage turning into a subscription. And behind that sit the video and world-model labs, World Labs, Runway, Luma, Decart, Odyssey, whose persistent interactive worlds hold state that makes text look small... that vector mostly loads 2029 rather than 2028.

The market is pricing 2028 as if the supply is certain and the innovation is hypothetical. The project list says the supply is conditional. The shipping products say the innovation is not.

Look at 2028 from the buyer’s chair

The whole thesis folds into one conditional. If AI capex enters a bear market, all bets are off... the balance breaks through the credit channel faster than any fab can move, and no line on any chart above survives the repricing. That is the honest boundary of this analysis, and the tripwire never changes... spot cracking while contracts hold, credit spreads on datacenter debt widening.

Now walk the other branch, the one Morgan Stanley just marked higher. A hyperscaler planning a multi-year buildout is not studying 2028 balance charts hunting for a year to nitpick price. Memory inside a $49 billion gigawatt is a real cost but a survivable one. A gigawatt of racks sitting idle for want of drives is not. When a single teardown can swing the balance eight points, the rational buyer pays for certainty of supply and treats price as the second-order term. If anything, the move on this branch is to keep signing long-term agreements with flexible terms, locking volume while capping the downside, which is what the producers report the buyers keep asking for... Kioxia’s counterparties are already pushing to extend beyond 2029.

And notice what the buyers are actually doing, because it is stranger than it sounds. The largest, best-informed technology companies on earth are walking into commodity memory suppliers and offering to fund their capital spending, posting billions in cash as security. These are the operators of the biggest AI clusters in existence... nobody sees the next three years of compute demand more clearly than they do. The agreements are untested, and the first soft quarter will test them. But a deposit is a forward view expressed in cash, and the deposits are accelerating.

The floor under 2028 is written in contract law

Here is what that behavior has produced on paper, and it is the genuinely new feature of the cycle... for the first time in memory’s history, the buyers have posted cash. Micron holds 16 strategic customer agreements, five-year take-or-pay, covering roughly a third of its NAND volume, with about $100 billion of cumulative minimum revenue and roughly $22 billion in deposits and letters of credit. SanDisk’s order book runs to about $69 billion, backed by more than $11 billion of enforceable guarantees, across five multi-year agreements covering more than a third of next fiscal year’s output. Kioxia is targeting agreements over roughly half of its 2028 bits, with counterparties asking to extend beyond 2029. If a customer walks, the supplier does not sue for years... it draws on money that already exists.

The deposit design matters more than the headline sums. These are security instruments, held at full value and returned at contract completion rather than drawn down per shipment, so the guarantee’s coverage of what remains owed rises over the contract’s life, from roughly a quarter at signing toward full coverage in the final year. Maximum protection lands exactly where breach risk lives... 2028 and beyond. The collection pace is sitting in the filings, with Micron’s deposit-linked liabilities running from $1.4 billion to $7.1 billion in nine months and SanDisk booking its first $511 million of inflows in April. Customer floors typically sit 10-20% below baseline pricing, which is why the base case’s 2028 digestion prices as roughly a 15% giveback rather than a collapse, why consumer prices crack first while the contracted datacenter tier holds longest, and why the only fast bear runs through the credit channel. Fair warning on the limits... the fixed-versus-floating split inside each contract is largely undisclosed, the floors’ first real test only comes in the first soft quarter, and the same deposits come due for return around 2029-30, a refund cliff timed, by construction, to the arrival of the supply wave. Whether the floors hold on first contact is worth a factor of two on every terminal value in the sector... it is the 1.3x-versus-2.9x-trough spread from the price chart, restated in legal terms.

The balanced close

None of the upside is a promise. Any vector can fail cheaply... a teardown under 400 terabytes per rack halves the biggest demand line, a weak Mercury Research print in late August retires the CPU-server story, HBF sampling as a clever drive rather than a socketed device shrinks the memory-transition prize, and soft demand meeting full supply execution produces a 2028 surplus north of 30 points. But the shape of the debate is now clear. Supply is a band a few points wide with one company holding the pen. Demand is a freshly raised capex curve with an innovation stack on top, and if models keep improving, adoption keeps widening, and use cases keep multiplying, hardware innovation does not stop at the GPU and the CPU... it moves down the memory hierarchy toward wherever state can be held cheaply, because state is what agents accumulate. On the balanced reading, buyers take 2028 as a breather, give back perhaps 15 percent on price against contract floors, and walk into a 2029 demand cohort that nothing currently under construction can meet. The customers with the clearest three-year view are choosing to prepay for supply rather than wait for a better price. Their behavior is a forecast, and it is the one worth weighting.

The scoreboard

The supply is the band. The demand is the debate. The floors are the trade. The calendar settles all of it, one dated event at a time.

What does this mean for Sandisk (SNDK)…?

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This Friday, SpaceX will begins trading… SPCX… $135/share… raise of about $75 billion… valuation of ~$1.75 trillion. The largest IPO ever. Starlink, with $11.3 billion of 2025 revenue and 10.3 million subscribers, is the near term engine of any fundamental valuation.

Buried in the competition language of that S-1 is a company with seven satellites, $70.9 million of trailing revenue: AST SpaceMobile.

This post is about why those two companies, and for broadband purposes only those two, are racing for the same prize: turning every ordinary smartphone on Earth into a satellite phone. No app. No antenna. No new hardware. The phone already in your pocket, connecting to space when towers cannot reach it.

The market understands roughly half of this race, the Starlink half. The other half is one of the more interesting under-examined setups in public markets. Some institutions have shunned the other half because of the “Space Mob” stereotypes thrown around, the pre-revenue nature, or simply for fear of buying an Elon competitor. What follows is the logic, in seven pictures. I have tried to make every chart honest enough that a Starlink bull could read it without objecting to the facts.

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(Disclosure and method notes at the end. Nothing here is investment advice.)

1. The race almost nobody is pricing

D2D service is already real. T-Mobile sells it today for $10 a month, powered by Starlink. Millions of people used it during the 2025 hurricane season. Apple’s Emergency SOS has quietly routed iPhone messages through Globalstar satellites since 2022.

Here is what the headlines miss: everything live today is narrowband. Texting. Location pings. Compressed voice in beta. The real prize is full cellular broadband from space to an unmodified phone, the thing that actually replaces a cell tower. That category has exactly two credible entrants, and as of this morning, zero occupants.

Chart positions D2D players by service class and deployment status, showing Starlink live in narrowband moving toward broadband, AST SpaceMobile in broadband but pre-commercial, and an empty contested quadrant for live broadband service.

Amazon bought its way to a third seat in April, paying $11.6 billion for Globalstar. But its own D2D system starts deploying around 2028, at best, and likely later given its leading peers have shown it can take multiple years to design and engineer the right satellites for proper service. Skylo and Lynk sell texting. China is building a parallel system closed to Western operators anyway. Through at least 2028, broadband from space to your phone is Starlink versus AST SpaceMobile.

One of those names trades at a $1.75 trillion target. The other is a roughly $35 billion company with a devoted retail following, thin institutional coverage, and near-zero recognition among the general public. That awareness gap is not itself a thesis. It is the precondition for one.

2. Two ways to build a cell tower in space

The physics problem is brutal and identical for both companies. A smartphone transmits about 0.2 watts from a tiny antenna that points nowhere in particular. To serve it from orbit, a satellite has to hear that whisper from roughly 500 kilometers up, then whisper back loudly enough to be heard indoors.

The two companies answered with opposite machines.

Drawn to scale. AST’s answer is the largest commercial antenna ever deployed in low Earth orbit. Starlink’s answer is hundreds more satellites, flying closer.

AST builds enormous satellites: about 2,400 square feet of phased array on a 6,100 kg spacecraft, the largest commercial antennas ever flown in low orbit. Antenna size is receive sensitivity. AST’s array is roughly 35 to 40 times the size of Starlink’s per-satellite D2D antenna. That is what lets one AST satellite deliver up to 120 Mbps per cell (per its FCC filing) and close a link through a roof. Management has guided to 150Mbps per cell and some AST sleuths have shown this number could grow by multiples as they release their new ASIC and bundle additional technology. It also opens a second business for large government contracts in defense and otherwise.

Starlink builds compact panels on mass-produced buses and compensates with numbers: more than 600 D2D satellites launched, flying about 170 km lower, replaced often, on rockets it owns. Its Gen-2 satellites claim five times the antenna and roughly 100 times the data density of today’s.

Any cell, terrestrial or orbital, is a shared medium. AST’s 98.9 Mbps demo is a link-budget triumph, not a capacity claim. Within each satellite cell, bandwidth is shared among every active user, and by my math both constellations deliver a tiny fraction of terrestrial capacity density: on the order of 0.1 Mbps per square kilometer averaged across the US. Satellite D2D is a coverage business. Starlink’s path to more capacity is more satellites and tighter frequency reuse. AST’s is wider spectrum slices and beamforming. Neither will ever replace towers where towers exist, and neither is trying to, so far.

And one asymmetry the antenna chart cannot show: the ground. AST’s design routes every call through a gateway station, so a satellite must see one to deliver service. Continuous coverage needs a parallel build-out of earth stations, with all the permitting and fiber that implies. Starlink’s laser links let satellites hand traffic to each other and come down wherever convenient, which is a genuine architectural edge in some ways and downside in others (see prior posts on data sovereignty). AST’s partial answer is baked into its business model: carriers buy the gateways. Gateway hardware is most of AST’s booked revenue today. That shares the cost without erasing the execution risk.

Neither approach is wrong. They are different bets: physics per satellite versus economics per fleet. But for the specific job of broadband to an unmodified phone, indoors, the antenna math favors the big satellite. Which leads to the more interesting question.

3. The spectrum chess game (think of it like sound)

Radio frequency behaves like sound. Bass travels through walls. Treble does not. Low-band spectrum (700/800/850 MHz) penetrates buildings, cars, and forests. Mid-band S-band spectrum near 2 GHz is crisp outdoors and dies at the drywall.

Now look at who holds what.

US D2D spectrum map, to scale. AST borrowed the bass from the carriers and bought the mid-range cheap. SpaceX bought the treble outright, for about $19.6 billion.

AST’s position is the one the market has not absorbed. In April, the FCC authorized up to 248 AST satellites to operate commercially on 700 and 800 MHz low-band: AT&T’s, Verizon’s, and FirstNet’s own frequencies, leased to AST for revenue share, with zero dollars upfront. No other company on Earth holds an indoor-capable D2D authorization. Not SpaceX. Not Amazon. The carriers own that spectrum, and they chose their partner.

The fine print that bulls skip: the authorization comes with leashes. Under the FCC’s Supplemental Coverage from Space rules, satellite service is secondary to terrestrial networks. Transmit power is capped to protect towers, with coordination back-offs near market boundaries and the Canadian and Mexican borders. The bass advantage is engineered for dead zones, the empty fifth of the US landmass that towers do not reach, not for downtowns, which the capacity math rules out anyway. The moat is real. It is also regulated.

On top of the leased low-band, AST locked up 45 MHz of L-band from Ligado for about $550M upfront plus roughly $80M a year for 80-plus years. Pocket change next to what SpaceX paid EchoStar: about $19.6 billion for roughly 65 MHz of S-band. SpaceX’s spectrum is genuinely valuable, owned outright and globally harmonized. It is also treble, outdoor-grade. And it has a second problem that deserves its own chart.

4. The clock inside your phone

A satellite band is only real once phones support it. This is the most underrated fact in the entire race, and it is where the two strategies diverge hardest.

Three paths to your phone. The carriers’ low-band is already in every handset. AST’s L-band has existed in the 3GPP standard since 2022. SpaceX’s band was born in January.

AST’s primary play, riding the carriers’ low-band, requires no new chipset at all. Every phone sold in the last fifteen years already speaks 700 and 800 MHz. That is what “broadband to an unmodified phone” actually means, and AST has demonstrated it: 98.9 Mbps to a standard handset, native video calls included.

AST’s L-band sits inside 3GPP band n255, standardized in Release 17 back in 2022 and already validated on commercial modem silicon. Management guides for L-band support in “most new phones in a big way” from 2027.

SpaceX’s new S-band holdings only partially overlap the existing standard, so the industry had to create a new band: n252, under Release 19, which got its first commercial-silicon demo at CES this January. When Musk said at MWC that broad chipset support is about two years out, that was not pessimism. It is the normal speed of the standards-to-silicon-to-handset pipeline. Until then, SpaceX’s $19.6 billion band waits.

The honest sequencing: AST’s spectrum works in your current phone. Its second band arrives in next year’s phones. SpaceX’s band arrives roughly with the 2028 model cycle.

5. What they have promised, and what we actually expect

Both companies have put specific guidance on the record. The chart below shows it side by side, along with one adjustment of ours, clearly marked.

Dual timeline from June 2026 to 2028. The AST rail shows launches, continuous service guidance, revenue targets of 150 to 200 million in 2026 and about 1 billion in 2027, plus an adjusted base case of about 30 satellites by year-end 2026 with 45 to 60 shifted to Q1 2027. The Starlink rail shows the IPO, Gen-2 deployment, a 25 million user target, and 2028 chipset and Deutsche Telekom milestones.

AST has guided to: 45 to 60 satellites in orbit during 2026 (BlueBirds 8, 9 and 10 are stacked on a Falcon 9 for a mid-June window); continuous US service beginning in H2; $150 to 200M of 2026 revenue with half already contracted; and roughly $1 billion in 2027, split about 50/50 commercial and government, on roughly 90 satellites. It holds about $3.5 billion of cash and says it is fully funded for the build, at $21 to 23M per satellite. Behind the guidance sits a contracted floor: $1.2 billion of take-or-pay commitments, including a $175M prepayment from STC.

Our adjusted base case, shown on the chart: launch cadence rarely forgives. With New Glenn grounded since its May 28 pad explosion and Falcon 9 manifest slots finite, we pencil in roughly 30 satellites by year-end 2026, with the 45 to 60 threshold reached in Q1 2027. What that one-quarter slip means: continuous service and the uncontracted half of the 2026 revenue guide slide toward 2027, since carriers will not bill retail customers for intermittent coverage. Revenue leans on the contracted floor: gateway sales, prepayments, and government milestones, which usefully scale with satellite count rather than the finished constellation. With $3.5 billion of cash this is not a solvency question, but it reopens the dilution question in 2027, from a weaker share price, before carrier revenue proves out if there are issues getting service running as expected. That is the nature of a launch-shaped thesis: the same binary that can re-rate the stock this autumn can push the story out a year.

Starlink and SpaceX have guided to: 650 Gen-2 satellites within 18 months; about 25 million Starlink Mobile users by year-end (their target); T-Satellite voice out of beta and data expanding; a Deutsche Telekom launch across 10 European countries in 2028; and the IPO itself, which makes the war chest effectively unlimited. One strategic read worth a sentence: the $19.6 billion EchoStar purchase bought independence, the option to operate as a global carrier keeping 100% of the revenue per user rather than splitting it as a wholesale partner. SpaceX traded two years of chipset lead time for permanent margin control. The Deutsche Telekom deal shows it will happily run both models at once. However, DT has also publicly stated they may pursue a dual course strategy with other operators, presumably AST.

The asymmetry matters. AST’s promises are binary and near. Rockets fly and satellites work, or they do not, and we will know within quarters. Starlink’s are gradual and far: chipsets, regulatory transfers, Starship cadence. The next two quarters stress AST harder. The next two years stress Starlink.

And the honest ledger requires this paragraph. AST is behind. It has seven satellites and zero paying subscribers. It buys launch from others, currently including its rival’s Falcon 9. It must deploy, then re-prove at constellation scale what it has so far proven in tests. The hardest engineering work is plausibly done: design frozen, factories running, FCC cleared, carriers signed, capital raised. The hardest operational stretch starts now.

6. The quiet customer

Here is the part of the AST story that gets priced last, and where I will be most careful to separate fact from thesis.

Three-tier chart of AST’s defense business: public-record contracts including a 30 million dollar SDA prime award; partially disclosed items like ten government use cases cited by management; and the explicitly labeled bull’s inference of a Palantir-style re-rating, with SpaceX’s Starshield incumbency shown for balance.

On the public record: AST’s defense subsidiary won a $30M prime contract from the Space Development Agency (HALO Europa Track 2) in February, its first as prime. It holds an MDA SHIELD IDIQ that makes it eligible for Golden Dome task orders. It demonstrated tactical communications to US Indo-Pacific Command: TAK over VPN and secure video, on standard phones. FirstNet’s public-safety Band 14 is written into its FCC grant. And it holds experimental authority at 902 to 928 MHz, the foundation of a radar ambition only a giant antenna can attempt.

Disclosed in outline only: management cites roughly ten government use cases and books government revenue at milestone level. It describes this work without detailing it. Government is roughly half of the near-term revenue plan, and it scales with satellite count, not the finished constellation. It monetizes early.

The bull’s inference, mine, clearly labeled: if that outlined government book converts into visible, reported revenue through 2026 and 2027, the market tends to re-rate companies the way it re-rated Palantir. Opaque government traction becomes printed numbers, and the multiple follows. The caveat is real and I will state it plainly: Palantir re-rated on proven software margins. AST must first fly the hardware. The pattern is plausible.

For balance: SpaceX is already a defense giant at far larger scale. Starshield is largely classified, with a reported $1.8B NRO constellation among its work. The difference is that defense is upside on top of SpaceX’s valuation, while for AST it is a second business the current price arguably does not reflect. Both carry political risk, in opposite directions.

7. The honest scoreboard

Score it honestly and Starlink wins the present on nearly every line. AST’s wins are the forward-looking ones. That is not a tie. It is a duopoly forming.

What would break the AST thesis? I keep a live list: launch cadence slipping past even our adjusted base case into mid-2027 (watch New Glenn’s return to flight, and whether the BE-4 investigation touches ULA’s Vulcan, since both are named AST providers); satellites underperforming at scale what seven units demonstrated in tests; consumer willingness-to-pay disappointing (T-Mobile’s CEO has already admitted satellite usage is running lighter than expected, which cuts at both companies’ consumer math); the FCC’s pending Ligado sign-off stalling; a gateway build-out that lags the constellation; or dilution if “fully funded” proves optimistic.

What would break the Starlink-dominance thesis is simpler: nothing breaks it before 2028. It merely gets bounded. Starlink keeps the present: the revenue, the rockets, the subscriber machine. The question the market has not priced is whether AST keeps the blueprint: the physics, the indoor spectrum, the carrier alignment, the standards head start, and a government customer that pays early.

My bottom line: this is a duopoly forming in plain sight, and only one of its members is priced like a member. Starlink owns the present. AST owns the blueprint and potential stronger path to consumers via their less adversarial structure. Neither can take the other’s ground before roughly 2028, and the next two quarters of launches will tell us whether the blueprint becomes a building.

This week alone: SpaceX lists Friday. AST’s next three satellites launch on a Falcon 9 early next Wednesday morning.

DISCLOSURE

Position: At the time of publication, the author holds a position in AST SpaceMobile (ASTS).

Trading Policy: The author will not materially alter this position within 48 hours of publication. After this period, the author may buy, sell, or otherwise adjust the position without further notice. Changes to the author’s view or position will be reflected in subsequent publications when material.

Conflicts: The author has received no compensation from the issuer or any party with a financial interest in this security.

Forward-Looking Statements: This report contains the author’s opinions, estimates, and projections, including price targets derived from financial models. These are forward-looking statements subject to substantial uncertainty. If these assumptions prove incorrect, the actual value may differ materially, including scenarios of significant loss or total impairment. The price target represents the author’s estimate of fair value under the stated assumptions, not a prediction of where the stock will trade.

This report is provided for informational purposes only and does not constitute investment advice. See the full Terms & Disclosures for additional important information.

The rocket belongs to SpaceX, and the satellites belong SpaceX’s toughest competition in direct-to-device, AST SpaceMobile… just days after the SPCX IPO. What a collision of events! The market will spend the week staring at SpaceX, but it should also be watching the payload fairing.

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The Tesla moment was never the demo

People misremember Tesla’s inflection. It wasn’t the Roadster. By its June 2010 IPO, Tesla had built fewer than 2,500 cars, booked about $150 million of lifetime revenue, and carried $290 million of accumulated losses. The Roadster had already answered the only question it existed to answer (can an electric car be real and desirable?) and the market valued that answer at $1.7 billion.

The Tesla moment was everything after from buying the Fremont plant before the volume product existed, the Model S ramp, the first profitable quarter in Q1 2013, and eventually the Model 3 production hell that nearly killed the company on its way to making it the most valuable automaker on Earth. The demo got Tesla credibility. Industrialization got Tesla everything else.

AST has finished its demo phase. The physics question is retired with a standard, unmodified smartphone pulling 98.9 Mbps from a BlueBird over international waters. The FCC has authorized commercial direct-to-device service in the United States and a constellation of up to 248 satellites. AT&T, Verizon, and roughly sixty carriers representing nearly 3 billion subscribers have signed up, with over $1 billion in contracted revenue commitments reported. The FirstNet Authority literally amended its contract with AT&T to authorize AST’s service for first responders.

What hasn’t happened yet is the industrialization. That’s what June 17 starts.

Everyone forgets the explosions

Here is the part of the SpaceX and Tesla stories that gets airbrushed out of the retrospectives: they failed constantly, in public, for years.

SpaceX blew up three of its first four Falcon 1 rockets and was weeks from bankruptcy when flight four reached orbit in 2008. It then spent two solid years crashing boosters into the ocean and onto drone ships before one finally stuck the landing in December 2015. It lost a Falcon 9 and its NASA cargo in flight in 2015, and blew up another — with a customer’s satellite on top — on the pad in 2016. Starship’s development has been a literal highlight reel of fireballs. None of it mattered, because the factory behind the launch pad kept building rockets faster than the test program could destroy them.

Tesla’s version was the tent: Model 3 production began in July 2017 with a 5,000-cars-per-week target for year-end. It hit that number a year late, in June 2018, partly on an assembly line built under a temporary structure in the Fremont parking lot, with Musk describing the company as “single digit weeks” from death.

AST is now living its own chapter of this. BlueBird 7 was lost this spring when a New Glenn upper stage failed to reach its planned orbit, and Blue Origin (one of AST’s named launch providers) suffered a second major setback within weeks.

That’s a real risk and we’ll come back to it. But the lesson from the two greatest hardware-scaling stories of this generation is that lost vehicles are tuition, not necessarily verdicts. The question that actually decides the outcome is the same one it was for Tesla in 2017 and SpaceX in 2014: is the factory winning?

The factory is the story

This is what the market, fixated on launch dates, keeps skating past:

• AST designs and builds ~95% of its technology in-house including its own ASICs across 500,000+ square feet of facilities with a workforce of 2,250+

• BlueBirds 11 through 33 are in advanced stages of production and assembly right now, with phased arrays completed through BlueBird 28

• The company says it can now manufacture up to six fully equipped BlueBirds per month at an average cost of $21–23 million per satellite for the 90+ bird constellation

• The June 17 flight debuts the stackable architecture of composite carbon structures designed specifically so multiple giant satellites can ride one rocket, which is the unlock for monthly launch cadence across multiple providers

Read that list against Tesla circa 2011: factory acquired before the volume product ships, production line loaded, balance sheet stocked (~$3.5 billion in cash, with management saying no further convertible debt in 2026). The satellites stacking up in Midland are the equivalent of Model S bodies moving down the Fremont line for the first time. The hard, boring, unglamorous middle of the story, and the part that creates essentially all of the value.

And what does June 17 specifically unlock? Three more Block 2 satellites designed to nearly double peak data speeds. The first real-world test of the stacked launch system the entire 2026 cadence depends on. Progress toward the 45-satellite threshold that flips service from intermittent to continuous across the U.S., which is the trigger for commercial service gates, carrier monetization, and the FirstNet beta already being field-tested by the Texas Department of Public Safety, U.S. Customs and Border Protection, and county sheriffs on live BlueBirds. The tests that won the MNO contracts now have to hold up at scale, in the wild. That’s the whole ballgame, and it starts at 2:39 in the morning.

One S-curve, four companies

We built the timeline below to make a single point: aligned by phase instead of calendar year, Tesla, SpaceX, Starlink, and AST are the same story told four times — concept, proof, first product, production hell, payoff — and AST is standing at the exact spot on the curve where the other three went vertical.

Look at the right-hand column. The valuations don’t grow through the demo phase. They grow through the industrialization phase - the one AST is entering this month. Tesla went from $3.5B to $30B while shipping its first product, then $30B to $1T through scaling. SpaceX’s private marks went from $46B to $350B to a $1.7T IPO as Starlink went from a $99 beta to $11.4 billion in revenue and $4.4 billion in operating profit in roughly five years.

That last number deserves its own sentence. Starlink, the supposed ASTS killer, is the single best evidence that ASTS’s market exists. It took a satellite connectivity business from zero to eleven billion dollars of revenue in six years, signed up over 10 million broadband subscribers, and put direct-to-device in front of roughly 12 million users across 22+ countries. The demand question is answered by the competitor.

Now plot those right-column valuations as curves, and the whole thesis fits on one chart. On a linear scale, Tesla and SpaceX are essentially flat lines through their first three phases. All of it, the $1 trillion and the $1.7 trillion, shows up in the back half. The inset magnifies phases 1–3: same track, same slope, a decade apart. ASTS’s dot sits at phase 3, at the foot of the wall the other two climbed.

And notice what the shaded zone says: the scenario range we lay out below — $48 billion from the subscriber napkin alone, up to ~$200 billion in a full duopoly outcome — is 1.4x to 6x from today’s price, and it still barely lifts off the x-axis of this chart. The bull case here doesn’t require believing ASTS becomes Tesla or SpaceX. It requires believing it gets a fraction of the way up a wall two companies have now climbed in public.

The math nobody is doing

Here’s where it gets uncomfortable for the “it’s already priced in” crowd. ASTS trades around $89, a market cap in the neighborhood of $35 billion. Big number. Up 148% in a year. Surely the dream is in the price?

Run three simple sums.

1. The spectrum, marked to market. In 2025, EchoStar sold roughly 50 MHz of nationwide spectrum to SpaceX for ~$17 billion and a similar amount to AT&T for ~$23 billion - call it $340–460 million per nationwide MHz. AST controls 45 MHz of L-band spectrum (40 MHz MSS plus 5 MHz at 1670–1675) under an 80+ year arrangement that cost ~$550 million upfront plus ~$80 million a year, alongside FCC authorization to operate on partners’ low-band across up to 248 satellites. Apply even a steep satellite-spectrum discount to the 2025 clearing prices and the L-band position alone plausibly underpins $10 billion or more of value against a sub-$2 billion cost basis. (Caveat honestly: L-band’s device ecosystem is younger than AWS’s, and spectrum comps are directional, not fungible. But the direction is not subtle.)

2. The FirstNet program, with actual numbers. This isn’t a press-release partnership. The First Responder Network Authority is a federal agency that amended its 25-year contract with AT&T to authorize Supplemental Coverage from Space from AST specifically, on Band 14 spectrum that is licensed nationwide. Public-safety agencies are field-testing voice, data, and mission-critical push-to-talk on BlueBirds in orbit today.

Here’s the scale people miss: FirstNet now supports more than 7 million connections across roughly 30,000 public-safety agencies, including 2+ million IoT devices, and AT&T’s FirstNet chief says the true addressable count (command vehicles, deployables, backup links for 911 centers) is much larger than that. Satellite isn’t a nice-to-have for this user base; it’s the killer feature. Towers fail in hurricanes, wildfires, and earthquakes which is exactly when first responders need the network most, and exactly why FirstNet already fields a fleet of 180+ satellite-equipped deployable trucks as a workaround. AST replaces the workaround with the phone in the responder’s pocket.

So run it at a public-safety-grade price point:

7,000,000 connections × $10/month × 12 = $840M revenue × 80% EBITDA margin = $672M EBITDA × 20× = ~$13.4B of value

That’s more than a third of AST’s entire market cap, from one federal program, at full attach. ARPU could actually be much higher. Nobody has put this in a model because it doesn’t have a revenue line yet. It will.

3. The subscriber napkin. This is the one to tattoo somewhere visible:

50 million subscribers × $5/month net to ASTS × 12 months = $3.0B of revenue. At an 80% EBITDA margin (management guides 90%+ at scale, because the carriers bear customer acquisition, billing, and support which AST sells wholesale capacity), that’s $2.4B of EBITDA. At 20×, a very reasonable multiple for scaling high margin infrastructure, that’s $48 billion of value from this leg alone, against a ~$35 billion market cap today. And 50 million subscribers is less than 2% penetration of the ~3 billion subscribers already under AST’s carrier agreements.

Reasonable people can fight about every cell. Starlink’s own ARPU fell 18% to $81/month as it chased scale - pricing gravity is real, which is exactly why we model $3–8 blended satellite-ARPU and not consumer-broadband numbers. Haircut the margin to 60% and the multiple to 15× and the base case is still ~$27B from subscribers alone before the spectrum, before FirstNet, before the U.S. government business that is already generating revenue today.

The point isn’t precision. The point is that none of these three legs requires AST to take a single customer from Starlink. The carriers did the distribution work already. Starlink did the market-education work already. AST just needs satellites in the sky and proof that the tests which won the contracts hold up in the wild. And here’s the asymmetry on top: every satellite launched widens the distribution moat, because continuous coverage activates dormant carrier agreements country by country — meaning scale doesn’t just defend AST’s position, it progressively improves its odds of taking share later, from a starting point of the widest carrier distribution in the industry.

What would break this

We publish bull cases with the bear case attached, so the thesis breaks if they fail to industrialize manufacturing and launch. If “up to six satellites a month” doesn’t translate into launch cadence because Falcon 9 slots stay scarce, New Glenn stays grounded, or the stacked architecture has a teething failure on the 17th, then continuous coverage slides toward 2028, the 2027 revenue inflection slides with it, and a company burning ~$190M a quarter against $14.7M of quarterly revenue gets re-rated the way pre-ramp hardware companies always do. Tesla’s history says slips of 12–24 months are the normal case, not the disaster case; ASTS’s valuation, unlike 2010 Tesla’s $1.7B, does not have infinite patience priced in. Watch the cadence, not the narrative. Satellites delivered to the Cape per quarter is the only KPI that matters this year.

But that cuts both ways. If the cadence holds, if BlueBirds keep arriving at the pad every month or two the way Roadsters once trickled and Model S’s eventually flooded out of Fremont, then the market is currently valuing the exponential part of this S-curve at roughly the price of its first leg.

Tesla’s IPO buyers got the curve for $1.7 billion. SpaceX’s insiders got Starlink’s curve at private marks that look comical against Friday’s IPO. AST is offering its curve in public, at $89, with the satellites already stacked on the rocket.

June 17, 2:39 a.m. EDT we’ll find out more.

DISCLOSURE

Position: At the time of publication, the author holds a position in AST SpaceMobile (ASTS).

Trading Policy: The author will not materially alter this position within 48 hours of publication. After this period, the author may buy, sell, or otherwise adjust the position without further notice. Changes to the author’s view or position will be reflected in subsequent publications when material.

Conflicts: The author has received no compensation from the issuer or any party with a financial interest in this security.

Forward-Looking Statements: This report contains the author’s opinions, estimates, and projections, including price targets derived from financial models. These are forward-looking statements subject to substantial uncertainty. If these assumptions prove incorrect, the actual value may differ materially, including scenarios of significant loss or total impairment. The price target represents the author’s estimate of fair value under the stated assumptions, not a prediction of where the stock will trade.

Risk Warning: Short selling involves unique and potentially infinite risks, as there is no theoretical limit to how high a security’s price can rise. Past performance is not indicative of future results. You should consult with a qualified financial advisor and conduct your own rigorous due diligence before making any investment decisions.

This report is provided for informational purposes only and does not constitute investment advice. See the full Terms & Disclosures for additional important information.

I have been involved, in one seat or another, in something like 100 IPOs over a hedge-fund career. If that experience compressed into a single habit, it is this. Before I form any view on an IPO, I ask one question.

Who is on the other side of this trade, and why are they willing to sell it to me now?

The letter everyone forgets is the “O.” An IPO is an offering. Somebody is offering to sell you something. In the ordinary case, the answer to “why now” is benign enough. A company needs growth capital, and the public market is the cheapest place to get it. That framing has trained two generations of retail investors to treat an IPO as an invitation to get in early on the future.

The SpaceX offering does not fit that frame. And the way it fails to fit is the entire point.

A company that does not need the money

Start with the strangest fact in the prospectus, which is a fact of omission: SpaceX does not need to do this.

This is a company with effectively unlimited access to private capital. It runs regular tender offers that mint liquidity on demand. Its private valuation roughly doubled in under six months, from the $800 billion December 2025 tender to a $1.75 trillion-plus IPO target. When a business with that kind of private access nonetheless chooses to sell $75 to $80 billion of stock to the public, the raise is not solving a balance-sheet problem. It is opening a door.

A door for whom? For everyone already inside.

There is an old line on the buy-side. Companies go public when they can, not when they must. “When they can” is a polite way of saying “when sentiment is hottest.” And the moment sentiment is hottest is, by definition, the moment least favorable to the buyer and most favorable to the seller. That is not cynicism. It is just the arithmetic of who controls the timing. The insiders pick the date. They are not going to pick the date that is bad for them.

So the honest first read of the SpaceX IPO is not “the public finally gets access.” It is “the existing owners have finally found a window large enough, and a bid deep enough, to begin converting paper into cash.” Which raises the obvious next question. Why do they want the cash so badly, and why now?

The distribution drought, and why the whole ecosystem needs this to clear

Here is the part the rocket coverage almost entirely ignores, because it has nothing to do with rockets.

The private-capital ecosystem has spent roughly four years in a liquidity desert. Exits are the events that turn fund marks into distributed cash, the IPOs and the acquisitions. They slowed to a trickle after 2021. The result is a system swollen with unrealized value and starved of realized value. There are on the order of 1,900 venture-backed unicorns still private. They represent something like $7.3 trillion in carrying value and an estimated $3 trillion in unrealized gains, sitting on the balance sheets of venture and growth funds.

That sounds like wealth. To a limited partner, it is a problem.

The people whose money actually fills those funds do not run on paper marks. They run on distributions. These are the university endowments, public pensions, foundations, insurance general accounts, sovereign wealth funds, and large family offices. They have spending obligations, payout ratios, and beneficiaries. Their own internal allocators measure them on DPI, which is cash returned over cash invested. For four years that number has been anemic across the asset class. Allocators have been unable to recycle. And the venture model, stripped to its mechanics, is a recycling machine. You harvest cash from your winners, especially at liquidity events like an IPO, and you redeploy it into the next vintage of private bets which, one hopes, achieve power law-driven success. Starve the harvest and the whole machine seizes.

SpaceX is not a participant in this dynamic. SpaceX is the single largest store of unrealized private value on the planet. It is the biggest, ripest harvest in the entire system.

I want to be precise about what I am and am not saying, because this is exactly where people slide into a conspiracy register that I think is both wrong and unnecessary. I am not saying anyone is doing anything improper. I am saying that the entire institutional capital ecosystem has a powerful, structural, entirely rational interest in this IPO clearing well. That includes the funds that hold SpaceX directly, the SPVs stacked on top of them, and the LPs behind both. The interest is not there because SpaceX is a bad company. It is there because a successful SpaceX listing is the largest single liquidity event available to an asset class that has been gasping for liquidity. It re-opens the recycling cycle. It generates DPI. That is a good thing for capital formation broadly. I genuinely want a healthy liquidity cycle, and so should you, Musk fan or not. But “good for the ecosystem” and “good for the marginal buyer at $1.75 trillion” are not the same statement. And the machine has every incentive to blur them into one.

The onion, and the cliff

Two structural features turn that diffuse incentive into concrete selling pressure on a calendar.

The first is the SPV onion. Exposure to SpaceX has been sold, re-sold, and re-wrapped through layers of special-purpose vehicles for years. There are funds of SPVs, feeders into feeders, and retail-adjacent platforms slicing access into ever-smaller pieces, often at marked-up entry prices carrying their own fee loads. Every layer of that onion is a holder with a cost basis, a fund life, and an LP who may or may not want or require liquidity. Many of these structures were built on the implicit promise of an eventual liquidity event. The IPO is that event. When the wrapper can finally unwrap, it will. And here is the uncomfortable part. The aggregate size of that wrapped supply is essentially unknowable from the filings. You can read the lockup schedule to the day. You cannot see the full notional of stock sitting in SPVs and feeders waiting for those gates to open. A precise calendar set against an unmeasurable quantity. That is the overhang that should worry a buyer most, because it is the one you cannot size in advance no matter how carefully you read.

The second is the lockup cliff, and it interacts with float in a way most buyers do not model. Musk is keeping majority control. The company is floating only a thin slice of itself. The new public float is on the order of a few percent of the fully diluted company, and the founder is selling nothing. A deliberately small float against red-hot demand is precisely the setup that lets a stock trade well above any defensible fair value in its first weeks. Too little supply, too much narrative, and price discovery that is really just demand discovery. Then the lockups roll off. The latent supply behind that thin float gets the right to sell into a price the early scarcity helped inflate. That supply is all those funds and SPVs and early holders sitting on 40x and 100x marks. A very important variable for equity returns for the next twelve months here is relationship between that small initial float and the very large supply waiting behind it.

And here the S-1 hands us something far more revealing than the usual boilerplate, because SpaceX did not use the standard single 180-day cliff. It built a staggered, partly performance-triggered early-release staircase, and the design tells you exactly what the deal is engineered to do. Here is how it works, applied to each insider’s pool of eligible locked-up shares. Up to 20% releases after the first post-IPO earnings report. An additional 10% unlocks only if the stock is up at least 30% over the IPO price, measured on five of ten consecutive days before that report. Then 7% releases at each of days 70, 90, 105, 120, and 135. Then a further 28% releases after the second earnings report. The remainder comes free at day 180. The lawyers’ framing is that it is gentler on the market, that it is “probably better that there will not be one big lock-up cliff.” That is true. It is also the tell. A continuous dribble of supply from roughly day 45 onward does not remove the overhang. It spreads it across nearly the entire first six months. There is no single cliff to brace for, and no clean moment when the pressure is finally behind you. The overhang is simply always there.

Look hard at that performance trigger, because it is the most underappreciated clause in the entire filing. The extra tranche unlocks only if the stock runs early. Sit with what that means. The better the stock performs out of the gate, the more insider stock becomes eligible to sell. I do not read intent into that. It is a reasonable way to tie liquidity to performance. But the mechanical consequence is worth holding onto, because it runs against the intuition most buyers carry. A strong open is usually taken as pure good news. Here, a strong open is also the thing that brings forward supply. The schedule leans on earnings-linked and price-linked releases rather than simple calendar dates, and that dovetails with the next layer. The staircase also serves to build tradeable float quickly enough to qualify for accelerated Nasdaq 100 inclusion under the exchange’s new fast-entry rule. That pulls forward a wave of mechanical, price-insensitive index buying. One thing is not disclosed. The total share count the percentages apply to, and which holders dominate the early-eligible pool, are both redacted. So you know the schedule precisely, but not yet the notional behind it.

It is worth drawing out what that index buying actually is, because it is easy to mistake for durable demand. Inclusion is a one-time event. When the funds that track the index add SPCX, they buy a slug of stock once, mechanically, regardless of price. Then they are done until much smaller impact periodic rebalances occur. That demand gets pulled forward by the fast-entry rule. Meanwhile the lockup staircase pushes supply out across the same window. Set the two against each other and the shape of the first six months comes into focus. A front-loaded burst of price-insensitive buying, and once it is spent, it is not there to absorb the steadily rising supply behind it. The demand is scheduled early. The supply is scheduled to follow. At some point the curves cross. A buyer who reads the early index bid as ongoing support is misreading a one-time event as a standing one.

Ask the question again. Who is on the other side when the lockup expires? Disproportionately, it is a fund that has to sell. It sells because its life is ending, or because its LP demanded the distribution, or because the mandate requires trimming a position that has ballooned to an uncomfortable weight. Forced and semi-forced sellers are the best counterparties to buy from. They are the worst to be standing next to.

Just how much is sitting in named hands

It is worth putting a number on the supply, because the number is larger than most people assume. SpaceX is private, so per-fund share counts are not disclosed. But you can triangulate. Some funds mark the position in their own public filings. Some rounds were disclosed with named leads. Some stakes have been reported by the press. Stitch those anchor points together against the roughly $1.75 trillion valuation, and a clear picture emerges of how much of the company sits in identifiable institutional hands.

Here is the build, grouped by type, expressed as estimated economic ownership of the fully diluted company.

Holder group

Names

Est. economic stake

Strategic corporates

Alphabet/Google (~5.0%), EchoStar (~0.6%), NVIDIA (~1.5%)

~7.1%

Top venture firms

Founders Fund (~2.5%), Valor (~4.0%), Sequoia (~2.0%), a16z (~1.8%), Gigafund (~1.2%), DFJ/Draper (~0.6%), Capricorn (~0.4%)

~12.5%

Crossover / mutual funds

Fidelity (~2.2%), Baillie Gifford (~1.5%), T. Rowe (~1.0%), Baron (~0.9%), Coatue (~0.8%), Mirae (~0.7%)

~7.1%

Sovereign wealth

Saudi PIF (~1.3%), ADIA (~0.9%), Qatar QIA (~1.0%)

~3.2%

Pensions

Ontario Teachers’ (~0.5%)

~0.5%

Named institutions, total

~30%

Round it down for caution and you are still at roughly the low 20s as a percentage of the entire company. That is the part you can actually name. Sit with what that means. Set aside Musk’s roughly 42% and the employee equity. What is left over for the public, the unnamed long tail, and the eventual float is not that large. And close to a third of the whole company is held by exactly the cohort with the strongest, most structural reason to harvest into a liquidity event. There are additional funds who we know have participated at some point along the way but we do not have a clear view into the size and timing. Venture funds at the end of their lives. Crossover funds that mark to market and trim winners. Sovereigns and pensions that recycle. These are not diamond hands. These are professional allocators whose job is to turn a 50x or 100x mark into cash their own investors can spend.

So the supply waiting behind the float is not a vague worry. It is nameable, it is large, and it is concentrated in the holders most likely to sell. The exact figures above are estimates, and I would not defend any single line to the basis point. But the shape is robust. A very large slice of SpaceX is held by people who, by the nature of their funds, are going to want out to some degree at some point in time.

The incentive map

None of the participants below is doing anything wrong. That is the point. You do not need anyone to misbehave for the system to point overwhelmingly in one direction. Just follow the money and the airtime.

Participant

What they get from a successful listing

What that does to the narrative

Underwriting syndicate (21+ banks, Goldman lead-left)

Estimated $800M to $1B+ in fees, reportedly the richest underwriting payday in IPO history

Maximum institutional muscle behind a clean, well-bid deal

Sell-side research (same banks)

A vast, recurring coverage franchise on the most-watched stock on earth

Quiet-period ends, then initiations land, and IPO initiations skew heavily to “buy”

Existing funds, SPVs, LPs

The largest liquidity event available to a distribution-starved asset class

Universal, rational interest in the deal clearing high

Financial media

The biggest story of the decade, endlessly monetizable

Saturation coverage, overwhelmingly framed around scale and inevitability

Index & ETF complex

Anticipated inclusion flows, a marquee holding the products need

Mechanical, price-insensitive demand layered on top of narrative demand

Retail

A genuine first chance to own a generational company

Allocated 20 to 30% of the deal, roughly triple the mega-cap norm

Dwell on that last row, because it is the most revealing and the least discussed. Why allocate three times the usual share to retail? The flattering story is democratization, and there is something to it. The mechanical story is that retail is the most narrative-driven and least price-sensitive buyer cohort in existence. If you are bringing an enormous amount of stock to market, both at the IPO and in the supply waves that follow lockup expiry, you want the broadest, stickiest, most price-insensitive base of demand you can assemble to absorb it. Seating that base early, before the institutional supply unlocks, is not sinister. It is just convenient for whoever eventually needs to sell. And it is worth simply noticing, without making too much of it, that two facts sit next to each other. A large, price-insensitive retail base is what tends to produce an early pop. And an early pop is, per the lockup terms above, one of the things that brings insider supply forward. I will leave the reader to decide how much weight that coincidence deserves. Who is on the other side? Increasingly, by design, it is the household.

Business, stock, valuation, multiple. Four different things.

Now the distinction that the entire bullish chorus collapses and that decades of market history refuses to let you collapse.

The business can be extraordinary. The stock is a claim on that business at a price. The valuation is what that price implies about the future. The multiple is the compression spring between today’s reality and that implied future. You can be unambiguously right about the first and lose money for a decade because of the last three.

Look at what the price implies. A $1.75 trillion valuation sits against roughly $18.7 billion of 2025 revenue. That revenue carries large GAAP losses, and it bundles a cash-burning AI segment and the former Twitter into the number through common-control recasting. So you are paying on the order of ninety times sales. And you are paying it for a company in which the public buyer gets pure economic exposure to the growth and little else. Musk’s control is total and by design, and that is a feature to anyone buying, not a scandal. A valuation like that is not a forecast. It is a demand. A demand that more or less everything go right, for a long time.

History is blunt on this. The largest IPOs have produced no clean verdict at all. One recent survey of the record books put it well. The same record-sized listing has launched a 200% rally in one case and a 40% collapse in another. What separated them was never the deal. It was the cycle the deal landed in. Consider the comparison set.

Issuer (year)

What happened after listing

Saudi Aramco (2019), prior record holder

Floated just 1.5%. Leaned on domestic and Gulf demand after foreign investors balked at the price. Never reached the $2T it sought. Not a good comp in many ways.

Rivian (2021)

Largest EV IPO ever. Subsequently traded about 85% below the offer. Not a great comp.

Facebook / Meta (2012)

Broke below its IPO price for a year. Then compounded about 550% over the following decade.

Uber (2019)

Underwater for years before a multi-year recovery.

Snowflake (2020)

Roughly flat-to-down from its first-day close, for years.

Aramco is the uncomfortable structural twin, but lands as a very poor business comp. It was the prior largest-ever listing, a narrative-and-state-backed crown jewel, floated in a deliberately thin slice, priced on enthusiasm its own sponsors could not fully justify abroad. Meta is the bull’s rebuttal. It broke, then it was vindicated spectacularly. But notice what the Meta case actually proves. Even a generational winner handed early buyers a year of pain, and it rewarded only those who bought the business at a price the stock had to fall to first. Cisco was the best-positioned company of its entire era in 2000, and it was dead money for fifteen years from the peak. The business was never the problem. The entry multiple was.

I lived a gentler version of this with Tesla. I was right on the company and still left a great deal on the table to the volatility and the multiple, holding a wonderful business through drawdowns that had nothing to do with whether the business was wonderful. I would own SpaceX. I would not do anything to own it. The difference between those two sentences is the entire discipline.

The live case study: Palantir. You do not need a 2000-era Cisco story to see this. You can watch it happen in real time. Palantir is, by any reasonable read, an exceptional and accelerating business. Its growth rate has gone up, not down, with expanding margins, which is the rarest of large-cap profiles. It posted 70% revenue growth in Q4 2025 and 85% in Q1 2026, the eleventh consecutive quarter of accelerating growth, beating and raising the whole way. And the stock still got cut by more than a third. It peaked at an all-time high of $207.52 on November 3, 2025, trading around 55 times trailing sales, a multiple essentially unprecedented for a company that size. Then it fell roughly 36% to the high $110s. It has only recently begun clawing back, sitting near $156 in late May 2026. The fundamentals never cracked. The multiple did. Even after that derate it still trades in the mid-to-high 40s on forward sales, with analysts noting the market had priced it for perfection. That is the whole lesson in one ticker. When you buy at the top of the multiple, you have pre-paid yourself the next several years of the company’s success. So the company can execute flawlessly, beat every quarter, and you can still lose a third of your money while you wait for the growth to catch up to the price you paid. SpaceX is coming public at roughly ninety times sales. Palantir got punished from fifty-five while accelerating.

The drivers cut both ways, and that is the trap

Let me be the one to make the bull case sharper than the bulls do, because it’s the honest thing to do and because it sets up the most important point in this entire piece.

I can already see several distinct drivers that could have SpaceX beating numbers in the quarters right after listing. The Anthropic compute deal is the clearest. It is worth roughly $15 billion a year, which is $1.25 billion a month through May 2029, about $45 billion in total. And it was explicitly disclosed as ramping from a discounted rate during the May to June 2026 window up to full billing thereafter. So that revenue line steps up mechanically into the first couple of reported quarters, regardless of anything else. Colossus II carries stated but undated headroom on top of that. Management has flagged a “next phase” bringing at least 220,000 additional next-generation GPUs and 400-plus megawatts online, with no committed date. So a new build or a switched-on tranche could juice 2027 numbers at a time of management’s choosing. Starlink has been pushing through price increases that drop onto a high-incremental-margin subscription base. And the company says it anticipates entering into additional similar services contracts, so more Anthropic-style compute deals could simply appear. Layer on the recurring tender cadence and the brand’s gravitational pull on demand, and the path to a string of headline beats is not hard to draw.

Here is the trap. It is the same mechanism that took a third out of Palantir while it was accelerating. At ninety times sales, the beats are already in the price. A stock valued for perfection does not re-rate up on a beat, because it was already priced for the beat. It re-rates down the moment the beat is merely good instead of spectacular, or the moment the cycle turns, or the moment a lockup tranche meets a market that has run out of fresh narrative. Good news that is already discounted is not a catalyst. It is a coupon you already paid for. The drivers I just listed make a beat more likely. And that makes the valuation more dangerous, not less, because they raise the bar the company must clear just to avoid disappointing a price that already assumes them.

And then there is the opaqueness. SpaceX reports three radically different businesses, Space, Connectivity, and AI, rolled into single consolidated figures. The recast folds in xAI and the former Twitter under common control. Segment detail is not cleanly broken out quarter to quarter. And the filing itself cautions that its installed-compute number “does not represent actual power consumption or utilization.” All of that hands management wide latitude over the timing and framing of when revenue appears. It is worth being concrete about where the slack lives. The AI segment is the clearest case. The Anthropic contract steps up from a discounted rate to full billing, so the first couple of quarters carry a pre-baked ramp that reads as accelerating AI revenue whether or not anything new is signed. The undated Colossus II expansion is capacity management can switch on when it chooses. Launch revenue is lumpy and milestone-driven, which gives discretion over which quarter a number lands in. The recast muddies year-over-year comps. And as a brand-new filer, SpaceX sets its own initial guidance bar. None of that makes a beat fake or the business weak. Starlink is a genuinely excellent, high-margin franchise, and I concede that cleanly. The point is narrower. A new issuer with multi-segment, recast, partly timing-controlled revenue has more room than most to clear an early bar. And the oldest move in the post-IPO playbook is to guide conservatively into the first prints and let the beat-and-raise narrative do the work. So in these specific quarters a beat carries less information than it appears to. At ninety times sales, it may already be in the price. That is precisely the environment in which a priced-for-perfection multiple can be sustained longer than it should be, and then unwind faster than anyone expects.

A note on where the oxygen goes

One last observation, offered carefully, because it’s the one most easily caricatured.

Attention is a finite resource, and so is sell-side coverage, and both flow toward the largest fee pool. I do not believe anyone is conspiring to suppress competing stories. I believe something more mundane and more powerful. When the biggest underwriting payday in history is on the table, the gravitational pull of that fee pool bends coverage, conference airtime, and narrative real estate toward a single name. It bends them away from smaller companies that may be doing genuinely differentiated work. No coordination is required for the distortion to exist. Emergent incentives are quite enough.

The example I happen to know, and here I disclose plainly that I am long the stock, is AST SpaceMobile. Ask a roomful of well-informed technologists at the mega-cap firms whether they have heard of it, and you will mostly get blank looks. That is striking for a company that may well beat StarLink to properly defined direct-to-device satellite connectivity and with a much larger MNO partner subscriber base to sell into while StarLink takes a somewhat adversarial approach. I want to be fair about what that anecdote does and does not prove. It is consistent with “under-covered relative to merit.” It is also consistent with “pre-revenue, satellites not yet fully deployed, genuinely not yet load-bearing.” Both can be true at once. The honest reading is that obscurity is evidence of where the oxygen is going, not proof of what anything is worth. I raise it only as an illustration of the broader mechanic. In the gravitational field of the largest IPO ever, attention is not distributed by merit. It is distributed by fee pool.

The questions I’d want answered first

I do not have a price target, because the honest answer is that several of the variables that determine the trade are not yet knowable. So instead of a verdict, here is the homework. These are the questions a disciplined buyer should be able to answer, or at least price, before committing capital. Many of them will only be resolved in the final S-1 amendment, at pricing, or in the first few earnings cycles.

On the deal itself:

• What is the actual price range, and what fully-diluted share count does it imply? The S-1 left price blank.

• What is the true initial free float, as a percentage of fully-diluted shares?

• How much of the offering is secondary, meaning existing holders cashing out, versus primary new capital? This is the single most important undisclosed number in the whole piece. It tells you directly how much insider selling is happening at the IPO itself, versus how much is deferred to lockup expiry. The preliminary S-1 leaves it blank, so it will not resolve until the pricing amendment. But there is a clean yardstick to hold it against. A healthy growth IPO runs 70 to 90% primary. Once insiders are selling more than about 30% of the deal, you ask why. And there is a deeper version of the question worth sitting with. SpaceX already runs a recurring tender channel that has given employees and early holders liquidity at an $800 billion valuation, with no public listing required. The late-2025 tender existed precisely so the company would not need an IPO to let insiders sell. So why go public at all? Either the tender machine can no longer absorb the scale the cap table now wants to monetize, or the public listing unlocks a far larger and more permanent exit at lockup expiry. Both answers point back at the same spine. This is a liquidity event first.

• What are the exact lockup terms? How many tranches, at what intervals, releasing what share volume at each step?

• Is the 20 to 30% retail allocation a fixed carve-out, or is it demand-dependent?

• Has any major existing holder signaled an intent to sell, or to hold?

On the business beneath the consolidated number, which this piece deliberately does not try to litigate, but which you should:

• The fundamentals deserve their own analysis. That means Starlink’s standalone unit economics, the AI segment’s cash burn and whether it is a temporary drag or a standing claim on Starlink’s cash, and what the company looks like stripped of the xAI and X recast. One note on the supply side, though. SpaceX has strong Starlink cash flow and ample credit access. It already carries some debt and signed a fresh bridge loan in early 2026. So future capital needs are far more likely to be met with leverage than with a flood of new equity. The supply that matters for your trade is the stock that already exists and becomes sellable, not hypothetical new issuance.

On the market it is landing in:

• What cycle does this list into? Per the record books, that single variable separated the +200% mega-IPOs from the negative-40% ones, and it cannot be known in advance, so I will not pretend to call it. What I will note instead is structural and direction-neutral. SpaceX is going first, while the window is open, into a hot tape with a deep pool of retail dollars looking to redeploy gains from elsewhere. That is intelligent issuance timing. It is exactly what you would choose if the priority were a large, cleanly absorbed offering. Smart timing for the seller is not the same as a good entry for the buyer. But it is not a market-top prediction either. It is just worth seeing the deal arriving into strength, by design.

• When does index inclusion hit, and how much price-insensitive buying does it pull forward versus leave as future support?

• How large is the latent SPV supply that becomes sellable at lockup expiry? This is likely unknowable from the filings, and it is the overhang that matters most.

If you cannot answer the secondary-versus-primary question and the lockup-schedule question, you do not yet know who is on the other side of your trade. Which means you are not yet ready to take it.

What this is, and isn’t

So, to be unmistakable. This is not a bear case. I think SpaceX may well be one of the defining enterprises of the century. I would be thrilled to own it, at a valuation that pays me for the cycle I would be buying into, rather than one that demands I supply the upside to the people selling. Or perhaps this is actually a great trade from opening price for a period.

The case is only this. An IPO is a liquidity event before it is anything else. This one arrives carried by an ecosystem that needs it to clear. It is structured to seat price-insensitive demand ahead of a large and patient supply. It is priced at a level that is a demand rather than a forecast. And it is wrapped in a narrative manufactured by everyone who gets paid when it works. None of that makes the business less remarkable. All of it should make you ask the only question that has ever mattered.

When you buy this stock, who is on the other side, and why are they so happy to sell it to you?

Not investment advice. For research and educational discussion only. Please see ABOUT page for additional disclosures and disclaimers. The author holds a position in ASTS and may hold or transact in other names mentioned, subject to a publisher’s-exclusion trading blackout around publication. Figures are drawn from SpaceX’s S-1 (filed 20 May 2026) and contemporaneous reporting. The Anthropic contract terms (about $1.25B per month, about $45B total through May 2029) and the underwriting-fee range (about $800M to over $1B) are as reported. Private valuations, segment detail, and float and lockup terms are subject to change before pricing. Some estimations were made in triangulating capital structure figures.

The consensus on MLCCs is simple and half right. The bull case is that AI servers consume staggering quantities of high-end MLCCs, that Murata and Samsung Electro-Mechanics control that segment, and that the resulting shortage drives pricing power. This piece is about what comes next, and it has four parts that build on each other.

First, I am going to close the door on the most common pushback to the bull case: the claim that the broad MLCC industry can simply redirect automotive capacity into the AI server segment and relieve the shortage. This argument is wrong at the level of physics and manufacturing, and I will show you exactly why using the manufacturers’ own spec sheets.

Second, I will reiterate the greenfield economics, because understanding why new capacity does not arrive is the foundation of the entire thesis. The supply curve in MLCCs does not behave the way most investors assume.

Third, the new analytical contribution: the shift from AI training to AI inference is structurally CPU-intensive, server CPUs draw their MLCCs from the same shared mid-cap pool as automotive and industrial, and that pool is heading for deficit even under conservative assumptions. If the high-end AI segment is already ripping, this is the second act that pulls the commodity end of the market up with it.

Fourth, I will connect this to the names that get hurt: downstream manufacturers with heavy MLCC and memory exposure and weak pricing power, who have told the market the shortage is handled before their customers have agreed to pay for it.

PART 1: Auto MLCCs Cannot Become GPU MLCCs

The Pushback, and Why It Matters

Every time the MLCC bull case comes up, someone makes a version of this argument:

“There are six or more MLCC manufacturers. They all supply the automotive market, which has enormous volume and strict reliability requirements. Auto-grade MLCCs are qualified for harsh conditions, so they are good enough for AI servers. The capacity is more elastic than you think. The shortage will resolve.”

This matters enormously for the thesis. If automotive MLCC capacity can flex into the AI server segment, then the supply curve is elastic, pricing power is temporary, and the whole investment case has a short shelf life. If it cannot, then the bottleneck is structural and the pricing power is durable.

The argument is wrong. Not partially wrong, but wrong at the level of physics and manufacturing process. Here is the proof, working entirely from the manufacturers’ own published technical documentation.

Same Manufacturer, Two Products, Different Worlds

The cleanest single piece of evidence comes from Samsung Electro-Mechanics, which published two technical papers six weeks apart in early 2026, describing the MLCCs it builds for two different markets.

On February 23, 2026, SEMCO published its AI server MLCC strategy. The flagship part, CL05X476MS6N9W#, has these specifications:

• Case size 0402 (1.0 x 0.5 mm)

• Capacitance 47 microfarads

• Rated voltage 2.5 volts

• X6S Class 2 dielectric

• Positioned within millimeters of GPU silicon, decoupling the 0.8V GPU core

On April 15, 2026, SEMCO published its electric vehicle powertrain MLCC paper. The part there, CL32C223JIV3PN#, has these specifications:

• Case size 1210 (3.2 x 2.5 mm)

• Capacitance 22 nanofarads

• Rated voltage 1000 volts

• C0G Class 1 dielectric

• Positioned in the 800V battery bus and inverter snubber circuits

The difference between these two parts is not incremental. The capacitance differs by a factor of 2,136. The voltage rating differs by a factor of 400. The case footprint differs by 16x. The dielectric chemistry is fundamentally different. These are not variations on a theme. They are different products that happen to share a category name.

For the Non-Technical Reader: An Analogy

If the spec sheet language is unfamiliar, here is the intuition.

Think of MLCCs like containers for water. The AI server part is like a thin, wide, shallow tray designed to hold a large volume of water (high capacitance) at very low pressure (low voltage), and to release it instantly when needed. The EV part is like a narrow, thick-walled pipe designed to hold a small volume of water (low capacitance) at extremely high pressure (high voltage) without bursting.

You cannot use a shallow tray as a high-pressure pipe. It would burst. You cannot use a high-pressure pipe as a shallow tray. It holds almost nothing and is far too bulky. The two are engineered for opposite problems. The fact that both are “containers” tells you nothing about whether one can substitute for the other.

That is precisely the relationship between AI server MLCCs and EV MLCCs.

Physical Scale Makes It Concrete

The AI server part is a 0402 case, one millimeter by half a millimeter. The EV part is a 1210 case, more than three times longer and five times wider, with sixteen times the board footprint.

This matters because of density. A single NVIDIA GB200 NVL72 rack contains roughly 440,000 MLCCs, the vast majority in the 0402 size class or smaller, packed tightly around the GPU silicon. You physically cannot fit that many 1210-size parts in the same board area. The geometry forbids it. The space simply does not exist on a GPU module for capacitors that are sixteen times larger.

So even setting aside the electrical specs, the substitution fails on physical packaging alone.

The “800V Is 800V” Confusion

The more sophisticated version of the substitution argument goes like this: “NVIDIA is moving to 800V power architecture. EVs run on 800V battery systems. Both convert high voltage down to roughly one volt. The MLCCs must be similar.”

This conflates the system-level voltage label with where the MLCC actually sits in the power chain.

In NVIDIA’s architecture, 800V is the rack-level distribution voltage. The power is then stepped down through multiple conversion stages: 800V to 48V to 12V to 0.8V at the GPU core. The MLCCs that decouple the GPU sit at the 0.8V end of that chain. They are 2.5V-rated parts. The high-voltage parts in NVIDIA’s power supply units are a completely different component (a Class 1 C0G resonant capacitor, which I will return to).

In an EV, 800V is the battery bus voltage, and the high-voltage MLCC sits right there at 800-1000V in the inverter and on-board charger. The vehicle separately steps down to its own 48V and 12V buses with different parts.

So both systems have “800V” on the label, but in the AI server the GPU-adjacent MLCC is four conversion stages downstream at 0.8V, while in the EV the MLCC is at the 800V bus. Same number, three orders of magnitude apart at the actual component location. They cannot be the same part.

The Physics That Forbids One Part Doing Both Jobs

There is a fundamental engineering tradeoff in MLCC design between capacitance and voltage. An MLCC stores charge in many thin layers of ceramic stacked between electrodes. To handle high voltage, each ceramic layer must be thicker so it does not break down. Thicker layers mean fewer layers fit in a given package, which means less capacitance. On top of that, the high-voltage Class 1 dielectrics have far lower dielectric constants than the high-capacitance Class 2 dielectrics, for fundamental material reasons.

The result: you cannot build a single MLCC that is both high-capacitance and high-voltage. The chart above plots real products on capacitance versus voltage axes. The AI parts cluster in the upper-left (high capacitance, low voltage, small case). The EV parts cluster in the lower-right (low capacitance, high voltage, larger case). The upper-right region, high capacitance and high voltage together, is physically empty. No MLCC exists there because the materials do not permit it.

This is not a manufacturing limitation that engineering will overcome next year. It is the physics of dielectric materials.

A Single AI Server Uses Five Different MLCC Types

There is one more layer to this, and it actually concedes a small point to the substitution argument before taking it back.

“AI server MLCC” is not one part. Per TDK’s December 2025 application note on data center power systems, a single AI server uses at least five distinct MLCC families: Y-caps for EMI filtering, bypass caps rated 630V and above, snubber caps with surge tolerance, LLC resonant caps in Class 1 C0G rated to 1.25kV, and the GPU decoupling caps in X6S/X7T at 2.5V.

Here is the honest concession. The high-voltage Class 1 parts used for snubbers and resonant circuits in AI server power supplies are actually closer to EV powertrain parts than the GPU decoupling caps are. There may be some genuine flexibility there. Murata’s December 2025 launch of a 15nF 1.25kV C0G part explicitly targets both EV chargers and high-end power supplies.

But that is not where the binding constraint sits. The shortage and the pricing power are concentrated in the GPU decoupling segment: the 47µF and 100µF, 2.5V, 0402 and 0603, X6S and X7T parts. That category has no EV equivalent, no automotive equivalent, and no commodity equivalent. It is built by Murata and SEMCO on dedicated lines with bespoke equipment, and nothing in the automotive supply base can substitute into it.

Part 1 Conclusion

The claim that automotive MLCC capacity can relieve the AI server shortage fails on four independent grounds: electrical specs differ by three orders of magnitude, physical packaging is sixteen times different in footprint, the components sit at opposite ends of the power conversion chain, and the capacitance-voltage physics forbids a single part from serving both roles. The manufacturers themselves publish these as entirely different products.

The bottleneck in high-end AI MLCC is structural. It does not resolve through capacity reallocation from autos. That is the foundation everything else rests on.

PART 2: What Greenfield Economics Actually Require

Why New Capacity Does Not Simply Arrive

If the high-end segment is so profitable and so constrained, why does new capacity not flood in? This is the question that determines whether pricing power is durable or fleeting, and the answer is in the capital and time economics of building MLCC capacity.

The hard numbers, from industry sources:

Building new MLCC production capacity takes 18 to 24 months from the moment capacity is committed to first output, per 773 Group and Mordor Intelligence. A full greenfield plant runs three to five years. The capital intensity is $750 million to $1.5 billion per advanced production line, per Mordor Intelligence. And per McKinsey’s capital projects research, the average large capital project of this type runs roughly 60% over schedule and more than 70% over budget.

This is not a fast-response supply curve. Unlike semiconductors, where process node advances drive rapid efficiency gains, MLCC manufacturing improvements are incremental and the equipment is specialized.

The ROIC Hurdle

Here I need to be explicit that the following is my own analytical framework, not a number published by Murata or any sell-side analyst. I am reasoning from Murata’s disclosed capital intensity and return targets to estimate what pricing is required to justify greenfield expansion. Treat it as a directional argument, not a precise figure.

Murata’s emergency capex announcement of ¥80 billion adds roughly 10 to 15% capacity at the high end. From the capacity added relative to the capital spent, I estimate brownfield capital intensity in the range of $200-300 million per billion units of annual AI-grade MLCC capacity. Greenfield is typically two to three times more capital-intensive, because you must build the building, the clean rooms, the utilities, and ramp yield from scratch. That puts greenfield in the range of $500-900 million per billion units of annual capacity.

To clear a 12% post-tax ROIC hurdle on a ten-year asset at those capital intensities, with current AI MLCC gross margins, my math suggests you need annual revenue per billion units of capacity in the range of $130-150 million, which implies an ASP roughly 3 to 5 times current levels.

The point is not the precise multiple. The point is the direction: at current ASPs, greenfield AI-grade MLCC capacity does not clear incumbent return hurdles. The first round of price hikes in March 2026 (15-35% from Murata) is not nearly enough to incentivize the wave of new capacity that would relieve the shortage. The market needs a far stronger and more sustained pricing signal before greenfield supply arrives, and even once the signal comes, the capacity is 18-24 months behind it.

Murata’s Own Capital Discipline Reinforces This

This is supported by Murata’s stated capital allocation framework. Murata’s Medium-Term Direction 2027 switched its primary return metric from pre-tax to post-tax ROIC and made capital efficiency a core KPI. The company’s FY2026 ROIC guidance is 12.3% against a weighted average cost of capital around 7%.

A company managing explicitly to post-tax ROIC, with a disciplined history of under-building in upcycles when peers over-built, does not flood the market with speculative capacity. It builds only when the pricing signal clears the hurdle, and it returns excess cash rather than chasing volume. That discipline is exactly what keeps the supply response slow and the pricing power durable.

Part 2 Conclusion

The supply curve in high-end MLCC is slow (18-24 months minimum), expensive ($750M-$1.5B per line), and gated by return hurdles that current ASPs do not clear. The incumbent with 60% share manages to post-tax ROIC and has every incentive to keep the market tight rather than flood it. New capacity is not coming fast enough to break the shortage in the thesis window. This is why the pricing power is structural rather than cyclical.

PART 3: The CPU Tightening Thesis

What Nobody Is Pricing

Everything to this point has been about the high-end, GPU-adjacent segment, which is a genuine duopoly. Now I want to make a different and, I believe, novel argument about the commodity and mid-tier end of the MLCC market, the segment that everyone currently dismisses as oversupplied.

The thesis in one sentence: the shift from AI training to AI inference is structurally CPU-intensive, server CPUs draw their MLCCs from the same shared mid-cap pool as automotive and industrial electronics, and that pool is heading for deficit even under conservative recovery assumptions for the consumer markets.

If I am right, the commodity end of the MLCC market, which the bears point to as proof there is no real shortage, tightens over the next several years for the first time since 2018. And unlike 2018, the driver this time is structural rather than cyclical.

Let me build this in four logical links, and verify each one.

Link 1: Inference Will Carry Much Higher CPU-to-GPU Ratio Than Training

This is confirmed by primary management commentary, not speculation.

On Intel’s Q1 2026 earnings call, CFO David Zinsner stated that training workloads run at 7 to 8 GPUs per CPU, while inference tightens to 3 to 4 GPUs per CPU. CEO Lip-Bu Tan added that the ratio has already moved from 1:8 to 1:4, and could reach 1:1 in agentic scenarios, or tilt even further toward CPUs. SemiAnalysis corroborates from the architecture side, noting Microsoft’s Fairwater datacenter runs a 1:6 CPU-to-GPU power ratio, and that future generations like Rubin may require an even higher ratio.

The mechanism is intuitive. Training is massively parallel matrix math, which is what GPUs excel at. Inference, especially agentic inference with tool-calling, orchestration, retrieval, and sequential decision-making, leans far more on general-purpose CPU compute. As the workload mix shifts toward inference, the CPU share of the system rises.

Link 2: Inference Is Becoming Dominant, and the CPU Runway Is Enormous

Inference is becoming the dominant share of AI compute. It accounted for roughly one-third of AI compute in 2023, half in 2025, and is projected at two-thirds in 2026, per Introl and Gartner data. Gartner sees inference at 65% or more of AI-optimized infrastructure spending by 2029.

The CPU demand implications are large. Arm estimates that traditional AI data centers require around 30 million CPU cores per gigawatt, but that demand could rise to 120 million cores per gigawatt in the agentic era, a fourfold increase. AMD, on May 6, 2026, raised its server CPU total addressable market outlook to $120 billion by 2030, at a 35%+ CAGR. IDC pegged the x86 server market at $283.9 billion in 2025, up 39.9%, with ARM-based servers growing 70% to reach 21.1% of shipments. Yole projects data center server semiconductor value reaching $500 billion by 2030. TrendForce notes that Google and Microsoft are specifically ramping general-purpose (CPU) server procurement to handle inference traffic from Copilot and Gemini.

The summary: if you are bullish on AI, you are bullish on CPUs. The inference and agentic future is more CPU-intensive than the training era was, and every major research house confirms the runway.

Link 3: Server CPU MLCCs Come From the Same Pool as Auto and Industrial

This is the crux, and it is stronger than mere substitutability. CPU MLCCs are not a separate category that happens to resemble auto MLCCs. They occupy the identical electrical envelope: mid-capacitance (1 to 100 microfarads), mid-voltage (4 to 100 volts), X5R/X6S/X7R dielectrics, case sizes 0402 to 1210.

The clearest proof is the DDR5 memory transition. Per Power Electronics News, DDR4 server memory used 10µF/6.3V MLCCs, while DDR5 requires 22µF/25V MLCCs in the 0805 case size. That 22µF/25V 0805 part is exactly the same specification class used in automotive body electronics, ECUs, and infotainment systems. Yageo’s high-capacitance MLCC series (1 to 220µF, 0201 to 2220 case sizes, 4 to 100V) is explicitly marketed for “Server, AI Server, Industrial, Computing” applications all in the same product family.

So when server CPU demand rises, it does not draw from some dedicated CPU MLCC supply. It pulls from the same production lines that make automotive body electronics capacitors and industrial capacitors. This is competition for shared capacity, which is more direct than substitution.

One important friction to name explicitly, because it actually strengthens the case. “Same electrical envelope” does not mean “same line, flipped overnight.” Automotive-grade MLCCs require AEC-Q200 certification: 1,000-hour high-temperature life testing, extreme thermal shock cycling, extended burn-in, and DC-bias ageing validation that IT-grade parts never undergo. A manufacturer cannot convert an IT-grade server line to an auto-grade line, or vice versa, without dedicated QA processes and a fresh qualification cycle that runs 18 to 24 months. This cuts both ways and both ways favor the thesis. When AI server CPU demand pulls on the IT-grade mid-cap pool, suppliers cannot instantly backfill from auto-grade capacity, and when they do reallocate, the qualification friction slows it to a crawl. The shared pool is therefore even stickier than the raw spec overlap suggests. The capacity is genuinely fungible at the materials and equipment level but genuinely sticky at the qualification level, which means demand shocks translate into shortages faster, not slower.

This distinction is what separates the CPU thesis from the GPU thesis. The GPU decoupling part is bespoke and duopoly-controlled. The CPU mid-cap part is commodity-to-mid-tier, made by everyone, and shared with the largest MLCC end market in the world: automotive. But “made by everyone” comes with a tiering caveat that matters enormously for the supply math, which I turn to next.

Link 4: Shared Pool Flips to Deficit

I built a supply and demand model for the shared mid-cap MLCC pool, breaking out the five demand segments that draw from it (server CPU, automotive, PC, phone, industrial) against the available mid-cap supply.

A critical modeling choice, flagged explicitly: I deliberately modeled only MODEST growth and recovery for the automotive, PC, and phone segments. All three are currently in cyclical down or soft patches. PCs and smartphones are in a demand trough, and automotive production is roughly flat with EV growth decelerating in the West. Rather than assume a sharp recovery, I assumed automotive grows at 7.2% CAGR (driven by EV content mix, not unit volume), PCs at 4.1%, and phones at 3.5% through 2030. These are conservative assumptions. If the consumer markets recover sharply, the pool tightens faster than I show. I would rather understate the case.

Here is the first output, the structural driver in isolation.

Server CPU MLCC demand inflects from roughly 19% CAGR over 2018-2025 to roughly 33% CAGR over 2025-2030E. It rises from about 30 billion units per year in 2025 to roughly 125 billion units per year by 2030. This inflection is driven by two compounding factors: more server CPU units (the inference shift) and more MLCC content per socket (DDR5, higher core counts, more power rails).

Now the shared pool, all five segments stacked against supply.

The shared mid-cap pool runs a comfortable surplus today, roughly +40 billion units in 2025. But under my conservative assumptions, the surplus shrinks every year and the pool flips into deficit around 2028, reaching a deficit of roughly 164 billion units by 2030, which is about 11% of demand. The deficit appears even though I modeled the consumer segments modestly, because the structural CPU driver and steady automotive and industrial growth outpace the slow supply additions.

Here is where the growth comes from, and what the supply response looks like.

Of the roughly 444 billion units of incremental mid-cap demand from 2025 to 2030, automotive contributes the largest absolute share at +195 billion (44%), but server CPU is the fastest-growing segment at 33% CAGR, contributing +95 billion (21%). The key insight is that CPU is the new, structural, accelerating driver layered on top of an automotive base that was already going to grow. It is the marginal demand that tips the balance.

On the supply side, the announced capacity additions are real but slow, and a reader should immediately ask the obvious question: Walsin alone is scaling from 600 billion units per year toward 1.5 trillion by 2028, and Fenghua is adding a $1 billion-plus plant at 540 billion units per year. How does a 164 billion unit deficit survive a Chinese supply wave measured in the trillions?

The answer is the qualification and yield tiering, and it is the single most important nuance in the supply analysis. Raw Chinese MLCC volume is enormous, but it is concentrated in commodity smartphone and consumer parts where it does not compete for the sockets that matter here. Per Mordor Intelligence, Chinese entrants like Fenghua and Sunlord “move aggressively on price in commodity smartphones, underbidding Japanese peers by 15 to 25 percent, but remain excluded from automotive and data-center sockets that demand AEC-Q200 compliance and low-ESL metrics.” That is the crux. The deficit I am modeling is in the AEC-Q200 and server-qualified mid-cap tier, not in the raw commodity tonnage. Walsin’s 1.5 trillion units is a total-capacity figure spanning commodity to mid-tier; only a fraction is qualified for the auto and server sockets that define the shared pool, and Walsin and Yageo are pursuing automotive qualification largely through M and A (Yageo’s KEMET acquisition, Walsin’s facility build-outs) precisely because organic qualification is so slow.

Three things therefore blunt the Chinese supply wave against the specific deficit I am modeling. First, the qualification wall: a large share of announced Chinese capacity targets commodity sockets that do not relieve the AEC-Q200 mid-cap tier, and the parts that do qualify lag in the high-capacitance, low-ESL nodes that server and auto demand. Second, the Japanese and Korean leaders (Murata, SEMCO, Taiyo Yuden) are actively reallocating their own qualified mid-cap capacity OUT of the shared pool and INTO high-end AI, which removes qualified supply even as Chinese commodity volume grows. Third, as established in Part 2, any genuinely qualified new capacity takes 18 to 24 months to arrive and runs over schedule. The trillions of Chinese units are real, but they are mostly the wrong units in the wrong tier, and that is why the deficit math holds.

Why This Is Not 2018

The last MLCC cycle, in 2017-2018, was a broad cyclical tightening driven primarily by the smartphone supercycle (the iPhone X era), early EV adoption, and 5G preparation. The entire market tightened together because demand rose broadly across one connected pool. Then it corrected hard in 2019 when smartphone demand rolled over. The driver was cyclical, so the tightening was cyclical.

This time the structure is different and, for a sustained cycle, better. The high-end AI GPU segment is a separate, duopoly-controlled market ripping on its own. And the mid-cap CPU segment is now layering a second, structural demand driver onto the shared automotive and industrial pool. The CPU driver does not roll over like smartphones did, because it is tied to the secular shift toward inference and agentic AI compute, which is just beginning.

So the bull case is two independent demand surges, the bespoke GPU surge and the shared-pool CPU surge, hitting a supply base that is already reallocating away from commodity and cannot add capacity quickly. If both hold, you get broad MLCC price increases for the first time since 2018, but with a far more durable demand driver underneath.

The Major Assumptions, Stated Plainly

I want to be explicit about what could make this wrong, because the model depends on judgment calls.

The softest assumption is MLCC content per CPU socket. There is no published per-socket MLCC series. I built the ramp from the DDR5 transition, core-count growth, and power-rail trends. If content per socket rises more slowly than I assumed, the inflection pushes out past 2028.

The consumer recovery timing is the biggest cyclical swing factor. I modeled modest recovery for PC, phone, and auto. If those markets stay in trough longer, the pool stays looser longer. If they recover sharply, the pool tightens faster than shown. I chose the conservative path.

The Japanese and Korean reallocation rate is the biggest supply swing factor. How much of Murata’s roughly 1,100 billion units per year of total capacity they point at high-end versus mid-cap is a management decision I modeled as a smooth glide path. It could move either way.

EV penetration drives the slope of the automotive line. I assumed steady EV content-mix growth. A sharper EV slowdown would soften the automotive contribution.

Raw material inflation is absent from the unit model entirely, and it is a tailwind I left out. Nickel, palladium, barium titanate, silver, and copper have all seen double-digit price swings. Rising input costs raise the cost floor on even commodity MLCCs, which supports broad pricing independent of the supply and demand balance. Leaving this out makes the pricing case conservative.

The honest framing of the thesis is therefore not “the pool deterministically flips in 2028.” It is this: the shared mid-cap pool is tightening structurally even while three of its four demand drivers sit in cyclical troughs. The structural driver, AI CPU, is just beginning. When the troughs end and the structural driver compounds, the pool tightens hard. The timing depends on the cyclical recovery, but the direction is not really in question.

Part 3 Conclusion

The inference shift is real and CPU-intensive (confirmed). The CPU runway is enormous (confirmed by AMD, Arm, IDC, Yole, TrendForce). CPU MLCCs are drawn from the same pool as automotive and industrial (confirmed by spec overlap and the DDR5 transition). And the shared pool flips to deficit around 2028 even under conservative consumer assumptions (my model). This is the second act of the MLCC squeeze, and it extends the pricing thesis from the bespoke high end into the broad commodity market.

PART 4: The Shorts That Will Pay for It

Below we’ll discuss names that could suffer greatly from MLCC tightening along with memory shortages in the coming years. I have put this behind the paywall as it is not suitable for most investors. I previously spent 10 years at long/short hedge funds where I spent a substantial portion of my time looking for alpha shorts (as opposed to just hedges). These carry tremendous risk that is not suitable outside of most controlled, defined, institutional settings. I plan to continue to work this theme in the coming months/quarters, along with other thematic short themes given the large and shifting secular trends that are presenting lots of opportunities. Please see disclaimer at end of publication for additional information regarding risks.

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Three months ago I laid out the case for BeWhere as a quiet compounder approaching its most catalyst-dense window in company history. Q1 2026 landed this morning and changes the analytical job in one specific way. Management put public numbers on the multi-year plan for the first time, and those numbers line up with the published base case almost exactly.

The headline numbers

Q1 revenue C$4.7M, up 12% year over year, a record first quarter. Q1 Adjusted EBITDA C$653K, up 96%, also a record first quarter. Q1 gross margin 45.5%, the highest in company history, a 750 basis point jump year over year and a 1,000 basis point jump versus Q4. Adjusted EBITDA margin 14% versus 8% in the prior year, a 600 basis point expansion. ARR C$9.7M, up 16% year over year and up from C$8.9M exiting Q4. Twenty-sixth consecutive quarter of positive Adjusted EBITDA.

The unusual feature of this print is that revenue growth was the slowest in eight quarters while gross profit dollars hit an all-time high. However, this should not be surprising given the product launch-driven nature of growth cycles that has occurred multiple times (see here for original post detailing this dynamic). Operating leverage finally showed up in the financials as a printed number rather than a forecast.

The new disclosure: Vision 20/20 Plus

For the first time, management published a multi-year financial target. Three-year objectives exiting 2028:

1. ARR above C$20M, versus C$9.7M today

2. Adjusted EBITDA margin 20% run-rate, versus 14% in Q1

3. Path driven by organic growth (new products, new geographies, new verticals) plus strategic acquisitions

The original post explicitly modeled a base case of approximately 25% revenue CAGR through 2028 with meaningful margin expansion as recurring revenue mix grew, and 40%-plus EBITDA CAGR through 2028. That base case sat in the post without crediting AST SpaceMobile, Vodafone, or European expansion. Vision 20/20 Plus reads the same way. The satellite and carrier optionality is not in the targets.

How Vision 20/20 Plus compares to the published view

Working through the math, recurring goes from C$9.7M to above C$20M by end of 2028, which implies roughly a 28% recurring CAGR. The original base case implied recurring growth in the 25 to 30% range as DaaS and the product cycle layered in.

Adjusted EBITDA scales from a Q1/26 annualized run-rate near C$2.6M to 20% of a much larger revenue base. If total revenue reaches roughly C$35 to C$40M by 2028 (a reasonable derivation given recurring above C$20M and the historical mix), Adjusted EBITDA at 20% margin is C$7-8M. From the FY2025 print of C$2.25M, that math implies roughly 45 to 55% EBITDA CAGR over three years.

In plain language, management just publicly committed to a financial plan that exceeds the published base case on EBITDA growth and broadly matches it on revenue trajectory. None of this requires the satellite story to work.

What Q1 actually demonstrated

A few KPI movements worth flagging against the original thesis.

Operating leverage is now tangible, yet again. Revenue up 12%, gross profit up 34%, EBITDA up 96%. The thesis required this mechanic. Q1 was the cleanest demonstration of it, including in a quarter where unit shipments were essentially flat year over year. The gross margin jump to 45.5% means the supply chain pivot (CUSMA compliance, Albania manufacturing, plus a second international contract manufacturer onboarded in Q4) is delivering more than tariff neutralization. It is restructuring the unit economics.

The DaaS book continues to scale. Long-term trade receivable grew from C$1.13M at year-end to C$1.45M in one quarter, up 29%. The February raise was sized specifically to support this expansion. The working capital math is starting to look correct.

Moore Installs flipped accretive. Contributed C$439K of revenue and a C$60K net profit in Q1 versus a C$39K net loss in the year-ago stub period. The dilutive-acquisition concern from the FY25 update reversed in one quarter.

Recurring crossed 52% of revenue. New high. The original thesis mapped the rotation from hardware-led to recurring-led. Q1 was the first quarter where recurring is a majority of the revenue mix.

What worsened and what to watch for

Two items moved the wrong direction.

First, revenue growth decelerated to 12% from 19% in Q4 and 21% in Q3. Hardware revenue declined 3% year over year for the first time I can recall, with management language of “relatively flat device shipments year over year.” The benign reading is that customers held back ahead of the BeBatt launch on February 9 (mid-quarter) and the B5-BeSol+ refresh coming in Q2. If Q2 hardware shipments reaccelerate, this is a non-event. If Q2 hardware is still flat or down, the BeBatt cycle is pushing demand out rather than pulling it forward, and the deceleration story becomes harder to dismiss.

Second, recurring revenue growth itself has decelerated from a 51% peak in Q4/24 to 11% in Q4/25 to 14% in Q1/26. The mix is at a new high, dollar growth is record, but the YoY recurring growth curve has compressed. To hit Vision 20/20 Plus organically, recurring needs to compound at roughly 28%. The trailing run-rate is closer to 14%. The math closes only if the BeBatt and B5 cycle pulls device-to-recurring attach materially higher, or carrier and satellite channels add a step-function in 2027-28, or M&A contributes meaningfully. Management explicitly invoked all three. The acquisition lever in particular is now a public part of the plan, which is new.

Where the stock can go

BeWhere has been in the C$0.80 to C$0.90 range. Fully diluted share count post the February raise is approximately 100M, putting the equity at roughly C$85M and enterprise value near C$76M after netting C$9.2M of cash and a small government loan. Against trailing revenue of C$21.5M, that is about 3.5x trailing sales, versus an IoT/SaaS peer average closer to 8x.

The Vision 20/20 Plus targets translate fairly cleanly into a multi-year price framework. By the end of 2028, if management delivers what they just committed to publicly, the company should be running at C$35 to C$40M of revenue with Adjusted EBITDA in the C$7-8M range. Three scenarios are worth laying out.

In a conservative case where the company trades at 5x forward sales (still a discount to peers despite a higher recurring mix and better EBITDA profile), market cap exits 2028 near C$175 to C$200M, or roughly C$1.75 to C$2.00 per share. That is a double from the current C$0.85.

In a base case at 6x to 7x forward sales (compressing the peer discount but not closing it entirely), market cap is C$210 to C$280M, or C$2.10 to C$2.80 per share. That is 2.5x to 3.3x from here.

In a re-rated case where the recurring mix above 60%, the 20% EBITDA margin, and the disclosed three-year plan justify trading closer to the IoT/SaaS peer average of 8x sales, market cap reaches C$280 to C$320M, or C$2.80 to C$3.20 per share, roughly 3.5x to 4x from here.

The 2028 EBITDA exit at C$7 to C$8M cross-checks the framework. At a 20x EBITDA multiple (modest for a company at this growth rate and recurring mix), market cap is C$140 to C$160M. At 25x, C$175 to C$200M. At 30x, C$210 to C$240M. The two methodologies bracket each other in a consistent range of C$1.40 to C$3.20 per share over a three-year horizon, on management’s own publicly committed numbers.

The satellite scenario sits above all of this. The original post laid out a path where European and Middle Eastern expansion via Vodafone / AST SpaceMobile / Satellite Connect commercialization could push revenue toward C$100 to C$150M by 2029-30 with 25 to 35% EBITDA margins. At 8 to 10x forward revenue, that implies an enterprise value in the C$800M to C$1.5B range, or 10x to 20x upside from today. That scenario remains contingent on AST execution and is still optionality rather than a forecast, but the value of that optionality is the same as it was three months ago. Nothing in Q1 changed it for better or worse. The GSMA Foundry whitepaper still names BeWhere as one of two companies rolling out integrated solutions, and the Vodafone board seat still sits where it sat.

Why the thesis is on track

The compounding base is doing exactly what the thesis required. Gross margin re-rated to 45%. EBITDA margin expanded 600 basis points. Recurring crossed 50% of revenue. The DaaS book is recognized on the P&L upfront and funded on the balance sheet via the February raise. Management committed publicly to a three-year financial plan that broadly matches the published base case and exceeds it on EBITDA growth.

What remains is execution on the product cycle. BeBatt launched February 9. B5-BeSol+ is scheduled for Q2, B5-BeWired+ for Q3. Every prior step-function in BeWhere’s revenue trajectory traces back to a product cycle landing in market, and the 2025-26 cycle is the first to combine a new low-cost form factor with a full platform refresh and the embedded satellite-readiness via firmware update. If the BeMini ramp from 2023-24 is the template, the visible financial impact of the current cycle should be most pronounced in the second half of 2026 into 2027. That is when ARR growth re-accelerates from the current 14 to 16% range back toward the 25 to 30% trajectory required by Vision 20/20 Plus.

In short, the operating story has done its work. The valuation story now waits for product cycle revenue to land and for the recurring re-acceleration to begin showing in the prints. Q2 is the first read on that.

What I would ask management

Three questions matter most… 1) What does the Q2 unit shipment cadence look like, and how is BeBatt sell-through tracking against the BeMini ramp pattern from 2023? 2) Of the C$10M-plus ARR uplift implied by Vision 20/20 Plus, what is the organic versus M&A split management is underwriting? 3) And Canadian revenue declined 11% in Q1 after declining for the full year 2025, so what is driving the Canadian market softness given Bell Canada relationships at the board level?

DISCLOSURE

Position: At the time of publication, the author owns BeWhere.

Trading Policy: The author will not materially alter this position within 48 hours of publication. After this period, the author may buy, sell, or otherwise adjust the position without further notice. Changes to the author’s view or position will be reflected in subsequent publications when material.

Conflicts: The author has received no compensation from the issuer or any party with a financial interest in this security.

Forward-Looking Statements: This report contains the author’s opinions, estimates, and projections, including price targets derived from financial models. These are forward-looking statements subject to substantial uncertainty. If these assumptions prove incorrect, the actual value may differ materially, including scenarios of significant loss or total impairment. The price target represents the author’s estimate of fair value under the stated assumptions, not a prediction of where the stock will trade.

This report is provided for informational purposes only and does not constitute investment advice. See the full Terms & Disclosures for additional important information.

Vodafone delivered FY26 at the upper end of guidance and, for the first time in years, put a multi-year target back on the table. The stock fell on German profit guidance - understandable. The market is paying for the quarter and getting the strategic optionality for free. The more important news for Vodafone came from the US, where the three largest carriers agreed to build a neutral, carrier-controlled direct-to-device (D2D) satellite platform whose architecture (predominately low bandwith spectrum) fits AST SpaceMobile and sidelines Starlink. They did so just as Starlink’s exclusivity with T-Mobile runs out and weeks ahead of their SpaceX IPO. That is a preview of the fight heading to Europe in 2027, and Vodafone is increasingly on the right side of it. (They also stand to materially financially benefit from their ASTS investment should this logic hold.) The multi-year thesis holds, and the satellite leg of it is stronger than it was a month ago.

Key points:

• The print was not the problem. FY26 landed at the top of the guided range on both profit and cash. The selloff was about Germany, where management was explicit that profit keeps falling into FY27.

• FY27 consensus falls high single digits. FY27 guidance sits above FY26 on both adjusted profit and adjusted free cash flow, the UK synergy ramp is contracted and visible, and management chose to reinstate a medium-term double-digit free-cash-flow growth ambition. Given the track record of this management team, they should get the benefit of the doubt, for now.

• The satellite optionality barely registered. Not one analyst question and not one management sentence on the call touched AST SpaceMobile or the European JV. In the results deck it appears as a single line on a portfolio timeline. The market is valuing it at roughly zero.

• The US carriers drew the blueprint. AT&T, Verizon and T-Mobile’s new D2D venture pools low-band spectrum into a neutral, multi-provider wholesale platform. Low-band cellular broadband from space is AST’s lane, not Starlink’s.

• Starlink got boxed. Its one-year T-Mobile exclusivity lapses in June. Rather than let Starlink expand to all three networks, the carriers built a layer they control. The same week, the FCC handed Starlink its own exclusive nationwide spectrum, which sharpens the single-point-of-control worry rather than easing it.

• Europe is the main event. Deutsche Telekom’s CEO has said plainly he will not let Starlink become a “kingmaker.” The EU’s 2 GHz satellite-spectrum licenses expire in May 2027, and Brussels wants a sovereign, European-controlled answer. The Vodafone and AST joint venture is built to be exactly that.

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1. The quarter and the guide: what is actually moving

FY26 itself was clean and close to a non-event for the thesis. Group service revenue growth held above 5% in the fourth quarter, profit grew at the top of the guided range, and free cash flow extended the upward trajectory of the past three years. Della Valle opened the call by calling this “a new chapter” and “a simpler and stronger business,” and the framing is fair. The portfolio is now scaled in every market it keeps, the balance sheet is repaired, and the dividend is rising again under a progressive policy.

The print is not what moved the stock. Shares fell roughly 6% on the day, and the reason was entirely forward and entirely German. Management was candid that German profit will decline again in FY27. As Della Valle put it, “we expect EBITDA to remain under pressure in Germany,” with the mobile market “fundamentally unchanged” and the price reset of the past two years still flowing through the base. Germany is the largest single profit pool in the group, so a guided decline there sets the tone regardless of what Africa or the UK do. That is the bear case, and it is real. It is also already known, already guided, and already in the price.

FY27 guidance sits above FY26 on both adjusted profit and adjusted free cash flow. The UK is the visible swing factor: FY27 is the first year of meaningful VodafoneThree synergies, the cost savings are contracted rather than hoped for, and UK capital spending peaks this year and falls thereafter. Africa just posted its strongest service revenue growth in close to two decades, and the emerging-markets businesses are managed for euro growth. Net of the German drag, the group still guides higher.

The more telling signal is what management chose to do with the multi-year outlook. After years of refusing to give one, they reinstated a medium-term ambition of double-digit organic free-cash-flow growth. A reinstated long-range target is a statement about conviction in the floor. Asked directly why now, Della Valle pointed to a fully transformed portfolio operating “only from strong scaled position” in every market. So the risk around the forward numbers is lower than it was a year ago, not higher. The downside, Germany, is identified and bounded. The upside, UK synergies plus Africa plus capital spending rolling off, is contracted or structural. And the satellite optionality is not in any of those numbers at all.

2. The US carriers drew the blueprint, and it is AST’s

On May 14th AT&T, Verizon and T-Mobile, three bitter enemies, announced an agreement in principle to form a joint venture for satellite-based D2D. The stated purpose is to end wireless dead zones by pooling scarce spectrum, building shared ground infrastructure, and writing common industry specifications so satellite operators can plug into terrestrial networks in a standard way. The carriers call it a “technology-neutral innovation platform.” T-Mobile CEO Srini Gopalan framed it as a way to “make it easier for satellite operators to deliver a broader range of direct-to-device experiences.” Both AST SpaceMobile and Skylo welcomed the announcement.

Look past the neutral language and the architecture is specific. The venture is built around pooling low-band cellular spectrum, aggregating traffic to avoid a fragmented market, and routing satellite traffic into each carrier’s own core network so the customer experience never changes. It is a design in which satellite is an extension of the terrestrial network, and the carriers, not the satellite operator, own the standard and the customer.

That is AST SpaceMobile’s design. AST describes its own system as a cell tower in space. The radio access network stays on the ground, the satellite uses the operators’ existing low-band spectrum, and traffic hands straight down into the carrier’s core. It does not impose a proprietary routing layer. Low-band broadband to an unmodified phone is the one thing AST is purpose-built to do, while Starlink’s direct-to-cell service has leaned on dedicated mid-band and, increasingly, its own satellite spectrum. AT&T and Verizon already hold definitive commercial agreements with AST and are strategic investors, and AST shares jumped on the news. The carriers built a platform whose specifications happen to match one provider’s network.

The honest caveat is that the JV is officially technology-neutral and names no provider. It courts multiple operators, and Skylo’s endorsement is a reminder AST is not the only candidate. T-Mobile, importantly, is not an AST customer; its satellite partner is Starlink. The implicit-AST read is an interpretation. But it rests on the physics of low-band spectrum, on the two carrier relationships AST already has, and on the architecture the venture describes, not on hope. And the fact that T-Mobile, Starlink’s own partner, chose to join a neutral multi-provider platform is itself the signal.

3. Starlink, boxed

The timing is the whole point. T-Mobile’s exclusivity on Starlink’s US D2D service runs one year from commercial launch, which means the window that tied Starlink to a single US carrier lapses soon. That was the moment Starlink could, in theory, have expanded to AT&T and Verizon.

Instead the three carriers built a venture they jointly control. T-Mobile, Starlink’s own launch partner, chose a neutral multi-provider platform over deeper dependence on one satellite operator. The practical effect is to push US D2D through a carrier-governed layer in which no single provider sets the terms.

The contrast sharpened the same week. On May 12th, the day of Vodafone’s results, the FCC cleared EchoStar’s spectrum exit and assigned a large block of mobile-satellite spectrum to SpaceX. For the first time Starlink holds a contiguous, exclusive-use nationwide D2D spectrum position of its own. Pair that with Musk’s recurring public musings about a “Starlink phone” and Starlink evolving into a full mobile carrier, and the question every operator now has to answer becomes obvious. Is the satellite layer something you rent, or something you are feeding? The US carriers answered by building their own. That answer travels.

4. Bent pipe versus black box

Strip away the commentary and the entire debate reduces to one engineering choice.

AST’s model is a neutral relay, a bent pipe. The operator keeps its spectrum, its subscribers, its core network and, critically, its data. Traffic originates and terminates inside the operator’s own network and its own jurisdiction. AST sells wholesale capacity that extends coverage without inserting itself between the operator and the customer. Control of the network stays with the operator by design.

Starlink’s model is a vertically integrated proprietary stack. SpaceX builds the satellites, owns the constellation, increasingly owns the spectrum, and runs processing on the satellite itself. For a mobile operator the relationship looks closer to roaming onto, or reselling, someone else’s network. It works, it is first to market, and it is efficient. It also creates a dependency, on a counterparty that has openly mused about becoming a carrier itself.

For a commercial buyer, neutral versus proprietary is a question of pricing power and who owns the customer. For a government or a regulator it is a question of who controls a strategic communications layer and where citizens’ data physically sits. That second framing is the one about to dominate Europe.

5. Europe is the main event

Deutsche Telekom is the cleanest read on where Europe is heading. DT brought Starlink Mobile to Europe, and yet its CEO Tim Höttges has been strikingly blunt about the limits of that relationship. On DT’s most recent earnings call he told investors: “I do not want to throw my destiny into one hand, nor do I want a Starlink which is a kingmaker of the destiny of our businesses.” He has said DT will work with other D2D providers, and has noted that “the Starlink people are very aware about the political role and the power we have as a brand in Europe.” His framing is a network of networks, with satellite as one input and never a single dependency.

That is the trojan-horse concern, stated by a CEO who is himself a Starlink customer. A service sold as a complement can quietly become a dependency, and a US-controlled proprietary stack embedded in a European operator’s coverage map is a strategic exposure no matter how friendly today’s commercial terms look. Höttges is not refusing Starlink. He is refusing to be captured by it, and he is signaling that he wants a credible alternative to exist.

The regulatory clock makes this urgent. The EU’s 2 GHz mobile-satellite-service band, the spectrum best suited to D2D, sits under licenses that expire in May 2027. The European Commission has to decide whether to renew the incumbents or run a fresh selection process, and it has signaled real wariness of a straight auction, on the grounds that the cash-rich bidders are mostly American and an auction risks handing European spectrum to US balance sheets while crowding out European players. Brussels has said it wants to favour European players and weight the outcome toward sovereignty and security.

Two facts about that process belong side by side. AST SpaceMobile has made an explicit pitch for the band, backed by a European constellation plan and a German operations center. Starlink did not respond to the EU consultation at all. A company that did not engage when Brussels asked the question is not well placed to be Brussels’ answer.

This is why the US story is a preview rather than a sideshow. In the US, EchoStar’s spectrum flowed to Starlink and the carriers responded by building a neutral layer they control. In the EU the equivalent decision is still open, and the bloc has both the motive and the mechanism to steer it toward a European-operated, sovereignty-aligned vehicle.

6. Why this is a Vodafone story

Vodafone sits on the right side of both the financial and the strategic ledger.

Financially, Vodafone is one of AST’s largest and earliest backers. On AST’s own account, Vodafone has invested three times and holds over $1bn of AST stock, alongside a commercial framework that runs into the next decade. As AST re-rates, on the US JV, on an FCC authorization clearing commercial US service across a constellation of up to 248 satellites, on a partner roster of nearly 60 operators covering more than 3 billion subscribers, and on a take-or-pay backlog of around $1.2bn, Vodafone’s stake marks up with it. AST is still pre-commercial, with first-quarter revenue of $14.7m against full-year guidance of $150m to $200m, but it is funded through deployment on roughly $3.5bn of cash. The point is that this is real balance-sheet value that no Vodafone model currently carries.

Strategically, the larger asset is the joint venture. Satellite Connect Europe, the 50/50 Vodafone and AST venture once known as SatCo, is now operational. It is headquartered in Luxembourg, run from a control center in Germany, staffed by a dedicated European management team, and building ground stations across Germany, the UK, Spain and France. It is a wholesale vehicle. It sells sovereign D2D capacity to European operators rather than competing with them, and it carries a five-year mutual exclusivity with AST across Europe and Africa. It has already drawn agreements from operators including Orange and Telefónica, signed roughly ten new partners at Mobile World Congress, and, on AST’s disclosure, fielded interest from operators in 21 of the EU’s 27 member states. AST president Scott Wisniewski has been blunt about how far ahead the broadband-first service tier sits relative to earlier text and emergency offerings, calling the gap “apples and aircraft carriers.”

Put the pieces together. Europe needs a satellite connectivity layer. Its regulators and its largest operators have made clear they will not accept a US-controlled proprietary stack as the only option. The EU’s defining spectrum decision lands in 2027. And Vodafone has spent the past year quietly assembling the one vehicle purpose-built to be the European, sovereignty-preserving, neutral-wholesale answer, alongside the technology partner whose architecture the US carriers’ own blueprint implicitly endorses. This is the defensive telco playing offense, in concrete form, and it is currently valued at close to nothing.

7. Thesis holds…

… and on balance it is stronger than it was a month ago.

The multi-year thesis rests on two legs. The first is the restructuring story: a simpler, scaled Vodafone whose cash flow compounds. Management reinstated a multi-year growth target, and the one genuine weak point, Germany, is identified and already in guidance. The second leg is the satellite optionality, and that leg strengthened materially. The US carrier JV validated AST’s architecture, the regulatory and competitive dynamics in both the US and the EU moved AST’s way, and Vodafone’s own vehicle for Europe is up and running.

The risks are still real and worth stating plainly.

AST execution is the largest. The deployment plan is aggressive, around 45 satellites in orbit by year-end, and it depends on a launch cadence split between Blue Origin’s New Glenn, recently grounded after an anomaly, and SpaceX’s Falcon 9. Some independent analysts doubt the year-end target, and first-quarter revenue of $14.7m implies a steep second-half ramp. A material slip pushes the JV’s revenue to the right.

The US JV is genuinely technology-neutral. It names no provider and courts several. If Skylo or others take meaningful share, the implicit-AST read weakens.

The EU outcome is undecided. Brussels has not chosen between renewal, auction and beauty contest, and the process can run past 2027. A sovereignty-weighted outcome favours the Vodafone and AST vehicle, but it is not guaranteed.

Vodafone’s near term is genuinely soft. German profit falls again in FY27, the German mobile market is not yet repaired, and the derate reflects real pressure, not imagined pressure. The optionality does not pay the dividend. The operating business does.

And Starlink is formidable. First to market, but with a superior offering versus what AST’s satellites can support. However, they now own spectrum, and effectively unlimited capital. Boxed in the US is a structural read, not a victory.

None of this breaks the core point, which is asymmetry. The share price already carries the German drag and carries almost none of the satellite optionality. The risks above are reasons the option could be worth less than the bull case. They are not reasons it should be worth zero.

Bottom line

The market spent the last week marking Vodafone down for a German profit decline it had already been told to expect. On the same day the FCC redrew the US satellite-spectrum map. Two days later the three largest US carriers sketched an architecture that fits Vodafone’s satellite partner and sidelines that partner’s main rival. Deutsche Telekom’s CEO has said out loud what every European operator is now thinking, and the EU’s defining spectrum decision is about a year away. Vodafone owns half of the vehicle built for that moment. You are being asked to pay for the quarter. The option comes with it.