The Same Squeeze, Three Different Rooms
Three stories logged on this beat in recent days look unrelated: an online campaign to unmask a Cornell student who filed a lawsuit, a refurbished console selling above its sticker price, and a shift in how investors judge artificial intelligence companies. They share one mechanism. In each case a scarce resource has been rationed, and the party controlling the bottleneck has converted that scarcity into leverage without owning the consequences. For US technology companies, the pattern matters because the leverage is now being tested in public, in courtrooms, in retail listings and in private markets at the same time.
Identity as the Scarcest Asset
Start with the doxxing story. The alleged victim in a lawsuit against seven fraternity members at Cornell has been the target of online vigilantes trying to expose her, and their efforts have instead produced abuse directed at several other women. Her lawyers say three women have been falsely identified and harassed, per The Verge. The real person remains unidentified. The mechanism is familiar to anyone who has watched a platform moderation debate: a scarce piece of information, here a name, attracts enormous demand, and the platforms where the hunt unfolds profit from the engagement without absorbing the cost of getting it wrong. What makes this case sharper than a typical harassment story is the multiplier. A single failed identification does not merely ruin one person's week; it creates a second and third victim who had no part in the underlying dispute. US platforms have spent a decade building tools to verify identity and to remove targeted abuse, and those tools are plainly insufficient against a crowd that treats a wrong guess as a rounding error. The larger meaning for Big Tech is that the same infrastructure used to scale a business also scales a mistake, and the harm lands on people who never opted in.
Scarcity as Pricing Power
Now the console. GameStop is selling used PS5 Pros for $1,399, roughly 50 percent more than a new one, according to Tom's Hardware. The increase arrives while the console is out of stock at list price at various retailers, including directly from Sony. Best Buy and Walmart have new units at around $1,500 each. This is a textbook case of a supply gap being monetized by whoever holds inventory, and it shows how quickly a premium consumer product becomes a speculative asset. The US consumer does not get a discount for accepting used hardware; they pay a markup for the privilege of not waiting. Sony, the manufacturer, collects none of that spread, and the retailer captures it on the resale, which is a curious inversion of the usual relationship between platform owner and channel. It also quietly changes what a console generation means. When hardware costs more on the secondary market than at retail, the install base grows more slowly, and the services revenue that Big Tech counts on from a console ecosystem arrives later and thinner. Every month a unit sits unsold at list price is a month a subscription, a storefront purchase or an advertising impression does not happen.
Investors Re-price the AI Trade
Then there is AI, where the scarcity is not silicon or shelf space but credibility. As AI initial public offerings bring greater scrutiny, guest author Maor Farid, founder and CEO of Leo AI, argues in Crunchbase News that investors will increasingly prioritize customer spending growth, sustainable margins and deployment efficiency over rapid revenue growth alone. That is a meaningful shift in what counts as a good number. For most of the current cycle, the market rewarded the appearance of demand, and companies were priced on the size of the opportunity they described. The framing in Crunchbase News suggests the bar is moving toward evidence that customers actually keep paying, that the unit economics hold and that deployments do not collapse under their own cost. That is not a rejection of AI, it is a change in what investors will accept as proof. For US technology companies preparing to list, the implication is concrete. Investment in AI capacity made sense when capital was cheap and narrative was sufficient; it becomes harder to defend when the same spending has to show a margin.
