Firstly, I want to address some things before diving into my analysis. I am not someone who is against the idea of generative artificial intelligence. I have personally used Claude every day, and feel that Anthropic is making an outstanding product. As someone who started a company myself, I learned my lesson early in my career, when I made precisely the same mistakes that Anthropic is doing currently. Leveraging fixed expenses to fuel early-stage hypergrowth, which resulted in reality adding financial constraints. Luckily enough, my mistake wasn’t nearly as bad as this one because I could simply reduce my variable costs to survive. However, after reading the S-1 in depth, I found myself noticing that not only are they beyond their ability to leverage more debt and financing, but they have created a situation where the company literally does not have a choice but to expand exponentially.
When you only skim the top 25 pages of the S-1, everything about this offering looks perfect:
The company grew revenues from $1.16b in h1 2025 to $16.3b in h1 2026, posted a $1.03 billion in GAAP operating profit for Q2 2026, and holds a whopping $131.7b worth of cash and near-cash investments. However, delving deeper into the numbers, the accounting treatment, working capital loops, and footnote 9 reveals a hidden structure designed specifically to look like high-margin software stocks while masking a balance sheet equivalent to that of a highly leveraged utility firm.
Here are the red flags I have found:
Training Costs: There is No Gross Margin Line Item
If you were to open virtually any SaaS S-1 you would find revenue lines, followed immediately below by COGS/Gross Profit, then operating expenses including R&D. Anthropic removed gross margins completely, bundling cost of goods served (customer inference computing power) AND model training expenses into a single line item labeled “Compute and infrastructure”. The cost came out to be $8.95 billion during h1 2026.
Two primary reasons for doing so:
Without separating them, either the company has extremely low marginal profitability per unit provided, OR the multi-billion-dollar training campaigns which occur routinely for model development are essential recurring capex, not optional discretionary R&D expenditure.
Convertible note subsidy:
Take a glance towards the bottom of the income statement. You can see a mind-numbing number of losses reported in Q2 2026 totaling $72.4b in changes to the fair value of convertible notes. Now this number is waved away by the Wall Street crowd as an innocuous non-cash accounting adjustment since their valuation increased significantly during their last private funding rounds. Allow me to clarify why this isn’t the case at all: These tens of billions of dollars of highly subsidized convertible notes issued by the company between 2023–2025 were solely done to cover massive training compute expenditures, paid directly by subsidizing cheap equity shares to Google & Amazon (cloud providers). So yes, that economic $72.4 billion worth of training expense remains hidden in footnotes below operating line items.
Off-Balance-Sheet Tsunami – The $587 billion take-or-pay obligation trap (Footnote 9):
Total off-balance-sheet liabilities increased to almost 6x what it was just one year ago, reaching $587 billion by the end of Q2 2026.
Breaking this number down:
$265.6 billion worth of irrevocable minimum fixed purchase agreements: Which include at least $114.5b owed to Google Cloud (through 2033), and $110b to AWS services through 2036. With roughly 80% representing non-discretionary commitments.
“Uncommenced leases”:
Due to ASC 842 guidelines allowing these contracts to be deferred indefinitely until the official occupancy date, this category of leases alone totals $321.4b off balance sheets, despite representing actual financial liability. Broadcom 9% debt loop: Within those leases, you have