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Ripple's CEO Criticizes Saylor's Strategy but Remains Optimistic on Bitcoin

Ripple CEO Brad Garlinghouse criticizes Michael Saylor's funding model for bitcoin while maintaining a positive outlook on bitcoin's future.

Mercation Admin
June 27, 2026 1 min read
Ripple's CEO Criticizes Saylor's Strategy but Remains Optimistic on Bitcoin

Ripple's CEO, Brad Garlinghouse, has expressed his concerns over Michael Saylor's funding approach for bitcoin acquisitions, labeling it as "financial engineering" that detracts from the cryptocurrency's market stability. Despite his criticism, Garlinghouse remains bullish on bitcoin itself.

Concerns Over Preferred Shares

In a recent interview, Garlinghouse highlighted the negative impact of Saylor's Strategy's preferred-share funding model, particularly as the price of its STRC stock plummeted. He noted that the shares, which promise an annual dividend of 11.5% and are meant to trade near $100, recently dropped to 25% below that threshold. This downturn was described by Garlinghouse as a "damning indictment" of Saylor's strategy.

As bitcoin's value dipped below $59,000, the pressure on Strategy’s funding model intensified. Garlinghouse pointed out that the current market conditions are a result of misplaced priorities within Saylor's team, stating that "financial engineering doesn't yield sustainable value" and emphasizing the importance of the utility of digital assets.

Declining Stock Performance

On Thursday, STRC shares reached a historic low, falling as much as 26% below par, while Strategy's common stock also experienced significant losses, closing around $82. Analysts suggest that Strategy should reconsider its bitcoin acquisition strategy and focus on rebuilding its cash reserves, as the financial buffer for its dividends has decreased dramatically.

Mark Palmer, an analyst at Benchmark-StoneX, noted that although Strategy's funding mechanism has become "less efficient," it is not entirely broken. He cautioned against comparisons to completely failed assets, suggesting that while challenges exist, the model still has the potential to function effectively.