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Thursday, November 5, 2026

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AppLovin 3Q26 Business Update: No Notes

AppLovin’s Q3 revenue rose 55% year over year as AXON model gains expanded margins, while ad take-rate compression remains the key competitive risk.

APP $118B
Speedwell Research 3 clicks

From X

@ActAccordingly

PAA Research on X

"That would be PRESUMPTIOUS!" I'm listening to the $ORCL investor day and I found the response to the question about potential vendor/partner financing and whether or not the company has committed/signed deals quite interesting. The tone was defensive and I started to immediately think of Jimmy Cayne. In late 2007, a few months before Bear Stearns blew up they hosted an investor event in NYC to calm the markets following the blow up of 2 hedge funds. I was in the room. An analyst asked about how Bear Stearns planned to manage risk going forward in light of the "unprecedented" events in the capital markets (hedge funds blowing up, subprime defaults, credit spreads widening etc.). Jimmy Cayne responded: "You cannot create a risk model for something that is by definition UNPRECEDENTED". The tone was what I remember most. Defiant, condescending, angry. That's what I heard today with "PRESUMPTIOUS". No $ORCL is not Bear Stearns, but it's obvious to anyone that can read a balance sheet or track CDS, the financial risks for the company are growing rapidly. Negative variance on funding could have massive implications for the company. Assuming they have their financing needs secured from vendor financing or partners would be PRESUMPTIOUS.
@convequity 1 click

Convequity on X

Circular AI financing keeps getting bigger. A record $63 billion vehicle, partly supported by Broadcom ($AVGO), will buy Broadcom chips for Anthropic, and it only pays off if enterprises adopt AI beyond coding. The vehicle borrows, buys Broadcom XPU accelerators (custom AI chips) and networking gear, and leases them to Anthropic. Deliveries are expected from 2027. Broadcom guarantees a residual value of $40B+. This is the latest example of the banks, hyperscalers, model labs and chipmakers are frontrunning AI demand they expect to be insatiable. Without faster enterprise adoption, that demand may not arrive, and the financing stays circular. AI has to spread from coding into the rest of the enterprise. Coding can be checked, because code has to compile and pass tests. Other domains need the same verifiability, which means codifying context that lives in employees' heads, or at best across email, Slack, WhatsApp and work-management platforms. Vendors that can codify that context should extract immense value. Palantir ($PLTR) is the closest so far. Palantir's ontology, a structured account of an enterprise's objects, relationships and rules that software can use to check a result, is critical because it is instrumental to verifiability. We think it can make an average Nemotron model state of the art for that enterprise's own work. If the result is good enough, enterprises will use it and achieve sovereign AI. Once that context is codified, enterprises will not want to blindly run closed frontier models on it and give their know-how away. Broader adoption depends on data sovereignty. The shift has been visible since Palantir's Alex Karp warned earlier this year that handing closed frontier labs their data, models and institutional know-how means losing control of the value. The path is intelligence sovereignty plus more verifiability, then greater enterprise adoption, which would justify this frontrunning. It would also benefit Nvidia ($NVDA), which needs enterprise adoption because hyperscalers and model labs are leaning toward custom chips.
@convequity 1 click

Convequity on X

We think AI power users are overestimating how far enterprise adoption has progressed. Anthropic’s S-1 says over half the Fortune 500 were $100k+ annual customers as of September. Among those publicly traded customers, Anthropic spending averaged under 0.1% of total expenses in Q3 2026. That measures spending on one provider, so it cannot establish whether their AI deployments are succeeding. But the expectation gap is familiar. When you spend all day using the best models, it is easy to assume the rest of the economy is close behind. Building and running an enterprise’s own AI applications is a much harder undertaking. In Part 2 of our recent $NVDA report, we argued that successful adoption remains concentrated in a few exceptionally capable organisations, with Palantir ($PLTR) and coding agents the clearest examples. For Nvidia, adoption through clouds and model providers still leaves compute demand concentrated in intermediaries with the scale and incentive to develop their own chips. It needs more enterprises buying its compute directly. This is why we continue to see Palantir as a strategic enabler. The ability to help enterprises put AI into production remains scarce, even as access to capable models spreads. From Convequity’s “Nvidia at 16x Earnings: Bargain or Value Trap?” (Pt.2), 20 Oct 2026.

Investor Letters

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Intel: The CPU Comeback, Discounted

Intel's Q3 2026 results were hit by memory costs and an Israel shutdown, but enterprise AI inference could lift CPU demand as server…

INTC $287B
Monte Independent Investment Research 2 clicks

Thursday Tailwinds #13: Nov 5, 2026

Florida marinas are 92% full as boat counts rise and permits constrain new supply, creating pricing power for existing operators such as…

SUI $14B
Trade Ideas Flow 6 clicks

New Ideas From The Road

Aurelion Research increased healthcare exposure and sees opportunities in banking and defense, alongside research on Alcoa, Nike, ONON and…

AA $10BNKE $60B
Aurelion Research 4 clicks

Oracle: The Party Is Almost Over

Oracle’s CDS spreads exceed 320 basis points as debt approaches $135 billion and fiscal 2027 capex targets $95 billion, amid heavy reliance…

ORCL $363B
David Desjardins 1 click

Coupang: 3Q26 Business Recap

Coupang’s product-commerce growth rose 9% as data-leak effects fade, while management expects margins to return to pre-incident levels by…

CPNG $27B
Speedwell Memos 3 clicks

update on Gartner

Gartner’s growth has stalled after federal contract losses and cautious commercial spending, raising questions about its competitive…

IT $13B
scuttleblurb 1 click

Recycle Bin

Used aircraft engines can be repurposed as gas turbines, easing data center power constraints while tightening aviation supply.

EQT $33BRRC $12B
Doomberg 8 clicks

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