The Enron Question is not an allegation that today’s AI leaders are committing fraud, nor is it an attempt to force a historical scandal onto a new industry. Our objective is more disciplined: to examine whether the extraordinary financing architecture behind the AI infrastructure boom—special-purpose vehicles, project finance, long-term capacity commitments, private credit, leasing structures, off-balance-sheet obligations, asset transfers, and increasingly interdependent capital relationships—may be creating some of the same economic dependencies that made Enron fragile, even where the individual transactions themselves are lawful, disclosed, and conventional. We are engaging this question because the scale and speed of AI capital formation now extend far beyond ordinary corporate balance sheets, and because system-level risk can become difficult to see when leverage, obligations, and counterparties are distributed across many separate entities. This report will therefore reconstruct the mechanics that mattered most in Enron, compare those mechanics transaction-by-transaction with the modern AI capital stack, identify where the similarities end and where they may become meaningful, and ask the question that matters most to AGORA: if the assumptions supporting this system—demand, valuations, credit availability, asset values, and contractual commitments—begin to fail, where does the economic risk actually land? Every factual claim will be sourced; every inference, assumption, and thesis will be labeled as such.