The Verge reporter Elizabeth Lopatto: Anthropic's near-trillion-dollar compute contract makes recursive self-improvement a survival condition
Lopatto aggregates the dispersed compute commitments in Anthropic's S-1 filing into at least $850 billion, potentially nearing $1 trillion, in fixed costs over 20 years. She argues this capital structure forces the company to rely on recursive self-improvement to avoid bankruptcy—a financial necessity rather than a technological vision.
Anthropic's S-1 filing discloses compute procurement commitments across multiple sections. The Verge reporter Elizabeth Lopatto sums up these figures: $265.6 billion in non-cancelable purchase commitments, $321.4 billion in lease agreements that have not yet commenced, approximately $245 billion in newly signed compute and infrastructure agreements, and an estimated $125 billion to $150 billion in transactions that have not yet been finalized. She derives a rough lower bound of at least approximately $850 billion over the next 20 years, which would approach $1 trillion if the unsettled transactions are included at their current estimates. She explicitly acknowledges that she may have missed certain items.
PitchBook analyst Harrison Rolfes models these future commitments as an expenditure pace of approximately $90 billion per year from 2027 to 2030. This implies that to maintain the current ratio of costs to revenue, Anthropic requires approximately $188 billion in annual revenue. Rolfes concludes that growth is not optional for this company; the contracts themselves assume growth.
From this, Lopatto draws her core argument: Anthropic's capital structure transforms recursive self-improvement from a technological vision into a financial necessity. In its S-1, the company states that more capable models help researchers discover improvements faster, while more powerful compute multipliers enable more efficient training and deployment of even more capable models—a positive feedback loop. Claude is already building Claude under human guidance. The risk factors section acknowledges that using AI to develop more AI may cause model capabilities to advance more rapidly than the company's ability to develop, validate, and implement corresponding safety alignment measures. Lopatto interprets this as meaning that Anthropic's business model relies on rapidly building new models in ways it may not fully understand, effectively forcing it, for business reasons, to do things that pose risks to everyone.