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Michael Saylor accidentally reveals that MicroStrategy’s “STRC Perpetual Preferred Stock” was entirely designed by ChatGPT: the AI determined it was fully compliant, and I honestly couldn’t have come up with it myself.
According to foreign media "Crypto Briefing" and community messages, Strategy (MicroStrategy) Executive Chairman Michael Saylor recently admitted that the company's $8.5 billion market value STRC perpetual preferred stock was actually designed with the help of AI tool ChatGPT. However, as the recent STRC price fell below its face value of $100 and dipped to $86, the market is beginning to worry whether this unprecedented "buy-the-dip flywheel" will face systemic risk due to discount pressure.
(Background: MicroStrategy founder Michael Saylor points out the "Four Major Ideologies" of Bitcoin: Only by integrating four forces can the ultimate currency be achieved)
(Additional background: Standard Chartered Bank: MicroStrategy selling Bitcoin marks a turning point for gold! Predicts ETH will start surpassing BTC from now on, aiming for $4,000 by year-end)
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The world's largest Bitcoin corporate holder Strategy has long been the focus of market attention due to its complex financial operations. According to a report by "Crypto Briefing" on June 18, 2026, the company's Executive Chairman Michael Saylor shockingly revealed that the company's $8.5 billion market value "STRC perpetual preferred stock" was actually designed with the assistance of OpenAI's ChatGPT.
ChatGPT Certified Legitimate "Buy-the-Dip Flywheel"
This nickname "Stretch" STRC perpetual preferred stock was first launched in July 2025, featuring no maturity date and continuous high dividend payments, with a priority claim on repayment if the company encounters issues. The current annualized dividend rate is as high as 11.5%, and the company is considering semi-monthly payments to attract income-focused investors who prefer stable cash flow.
On social platform X, well-known user @_FORAB shared a clip of Saylor's speech, pointing out that Saylor himself admitted he couldn't come up with this model. At that time, AI responded that although no one in the world had ever done this before, it was completely compliant with the law. The brilliance of this mechanism lies in that the raised funds do not need to be collateralized with Bitcoin but are directly used to buy more Bitcoin. Investors earn interest, while the company can risk-free continue "stacking" Bitcoin reserves, forming what the community calls the strongest financing flywheel in history.
STRC Falls Below Face Value, Market Worries About Selling Crisis
However, this AI-designed flywheel has recently shown cracks. STRC's price has not only failed to rise steadily; it has recently sharply dropped from the official guidance of $100, with the lowest touching the $86 to $90 range, expanding the discount to 14%.
For preferred stocks, falling below face value is undoubtedly a serious warning signal. Although Saylor has come forward to defend, emphasizing that the product's Sharpe ratio once exceeded 3, demonstrating excellent risk-adjusted returns, and expressing willingness to stabilize investor confidence through share sales or dividend adjustments, market doubts remain. The community speculates whether, if the discount continues to worsen, the company will trigger specific mechanisms to push the price back to $100, potentially forcing the sale of its Bitcoin reserves.
High-Yield Promises Face Bull and Bear Tests
STRC is essentially a hybrid financial product combining "bullish Bitcoin and stable income," with a principal target maintained around $100, allowing investors to indirectly benefit from Bitcoin's long-term appreciation. The high annualized yield of 11.5% is very attractive in the current environment, but analysis indicates that Strategy's entire business model still heavily depends on Bitcoin's long-term appreciation. If Bitcoin enters a prolonged bear market, maintaining the $8.5 billion in high-dividend payments will face severe challenges, which is clearly a market reality that ChatGPT found difficult to fully simulate during its initial design.