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Wednesday, November 11, 2026

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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.
@SouthernValue95 1 click

SouthernValue on X

Ramp data shows VC-backed companies are spending 10x more per employee/month on AI vs. PE-owned and other companies. A bearish interpretation could be: token spend is being driven by VC-backed companies, making demand vulnerable to swings in capital cycle. Valid! However, on a longer timeframe, I think this is quite interesting as a leading indicator for the direction of software companies (VC-backed companies are mostly software or service-as-software companies). New companies are being built with a larger ratio of tokens vs. humans. Look at Anthropic itself, which pays 1/6 as much on intelligence as its customers (since it sells tokens marked up at 85% GM): Anthropic is spending ~9x more on compute than human salaries despite having access to tokens at cost. Cash payroll is annualizing ~$2B for a company with ~$60B of run-rate revenue in 1H26. Anthropic employs just 5k people. Wild efficiency in human capital. I suspect that the great software companies of the next decade, both new and incumbent, will insert AI into every aspect of their products so that using them feels like magic, and work happens seamlessly. Building a presentation in Claude feels like magic: I tell it what I want to put on a slide, and it appears like magic. As a user of Ramp, their products feel the same way: I make a purchase, take a picture of a receipt, and the expense is logged into my accounting system appropriately without the need for a human to type into a blank box. I think we will see most software become AI-native or be replaced by software that is. This is a significant opportunity for incumbents and startups alike. And I think this is a huge source of future token spend that will go to $AMZN and $GOOG where most software companies are built (on AWS and GCP) and where AMZN and GOOG are building the platforms for software companies to build AI capabilities into their products with choice around compute and model, embedded safety and governance, and unlimited scale. Amazon CEO @ajassy said on a podcast this week that AI spend is currently a "barbell-shape" with insatiable compute appetite of the AI labs on one side, and corporates using AI for cost savings on the other. In the middle is tokens embedded into "core workloads" which he says is growing but small today, but he thinks in 5 years might be the biggest category of token spend.

Investor Letters

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Airbnb 3Q26: Business Update

Airbnb’s 3Q26 revenue rose 19% to $4.9 billion as nights and seats grew 16%, with app bookings up 29% and Reserve Now Pay Later adding…

ABNB $111B
Speedwell Memos 2 clicks

Research update

S&P Global research will assess Platts, Kensho and ratings growth; Benefit Systems’ 72% YTD rally changed its valuation, while Netflix and…

SPGI $136BICE $96B
Global Outperformers 3 clicks

Monte Investments Market Brief Vol. CXXXV

Quanta Services’ backlog rose 63% year over year to $64 billion as shares fell 30%, while AI power and data-center construction demand…

PWR $77B
Monte Independent Investment Research 2 clicks

No title

SpaceX’s $24 billion Starbase power plant, Microsoft’s Oracle capacity cuts, Riot’s $72 billion AI lease and Quanta’s sell-off frame…

PWR $77BORCL $363B
Monte Independent Investment Research 3 clicks

Insider activity October 2026

Asian insider buying reached $2.9 billion in October, the highest since 2018, with South Korea and Thailand leading.

BKRKY $23B
Asian Century Stocks 2 clicks

Quick Value #337 - Dana Inc (DAN)

Dana is combining with Eaton’s Mobility unit via a 1Q27 Reverse Morris Trust after selling a division, delevering and accelerating buybacks.

ETN $141B
Value Don't Lie 3 clicks

Roblox: Capture This Moment

Roblox’s Q3 FY26 DAUs fell year over year for the first time, while bookings declined 12% to $1.7 billion.

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TSOH Investment Research 2 clicks

DoorDash and Google

DoorDash and Google.

DASH $79B
Stratechery by Ben Thompson – On the business, strategy, and impact of technology. 8 clicks

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