The market sell-off in cybersecurity stocks like CrowdStrike and Okta wasn't about Anthropic's new tool's direct features. It reflects a broader, rational repricing of all software valuations as investors grapple with the existential risk that AI could render any business model obsolete with terrifying speed.

The "Citrini" essay caused a market sell-off not because it was more technically sound than other AI analyses, but because it framed abstract AI risk in the concrete language of finance (SaaS multiples, credit risk), making it resonate powerfully with a Wall Street audience.

Today's massive AI company valuations are based on market sentiment ("vibes") and debt-fueled speculation, not fundamentals, just like the 1999 internet bubble. The market will likely crash when confidence breaks, long before AI's full potential is realized, wiping out many companies but creating immense wealth for those holding the survivors.

The notable aspect of the Citrini Research piece isn't its dystopian predictions, but its widespread acceptance among investors. Unlike previous 'AI doomer sci-fi,' it's acting as confirmation bias for a market already grappling with AI's disruptive potential. The report's success signals a major shift in 'common knowledge' about AI's socioeconomic risks.

Leopold Aschenbrenner's technical "AI 2027" paper had similar dire conclusions as the Citrini essay but didn't impact markets. Citrini's piece caused a sell-off because it was framed for a financial audience, demonstrating that the packaging and language of an idea are critical for it to influence different domains.

The $830 billion sell-off in software stocks wasn't a reaction to AI's current capabilities, but to a shift in investor perception. New AI agents made a future "software apocalypse" plausible enough to alter present-day company valuations.

The most immediate systemic risk from AI may not be mass unemployment but an unsustainable financial market bubble. Sky-high valuations of AI-related companies pose a more significant short-term threat to economic stability than the still-developing impact of AI on the job market.

The recent software stock wipeout wasn't driven by bubble fears, but by a growing conviction that AI can disintermediate traditional SaaS products. A single Anthropic legal plugin triggered a massive sell-off, showing tangible AI applications are now seen as direct threats to established companies, not just hype.

Historical bubbles, like the dot-com era, occur only when everyone capitulates and believes prices can only go up. According to Ben Horowitz, the constant debate and anxiety about a potential AI bubble is paradoxically the strongest evidence that the market has not yet reached the required state of collective delusion.