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AI news · Sunday, July 5, 2026

Bending Spoons hits $25 billion market cap, doubling down on layoffs

The Italian tech conglomerate Bending Spoons went public on the Nasdaq this week, briefly hitting a $25 billion market cap as investors bought into its aggressive playbook of acquiring aging tech brands and rapidly trimming their headcount. The company, which now owns names like AOL, Vimeo, and Evernote, is using AI to boost productivity and justify cutting thousands of workers. In its IPO filings, Bending Spoons noted that revenue per employee rose significantly between 2023 and 2025, largely by replacing traditional staffing with AI-driven operations.

While the company claims it plans to hold these businesses forever, the human cost is mounting; they openly stated that out of nearly 2,000 new staff acquired via recent deals, only a few hundred will likely remain by the end of 2026. The firm isn't just targeting legacy software; it is actively scanning thousands of acquisition targets, betting that an uncertain economy will keep prices low for future buyouts. This strategy is part of a broader trend where AI-native firms are shrinking their rosters, according to a Harvard Business School study.

These companies are 25% smaller than their non-AI counterparts, prioritizing senior-level talent over entry-level roles. This shift is creating a narrower path for career starters, even as individual workers find ways to use AI for efficiency. For example, one Texas-based healthcare worker is secretly holding two full-time jobs by using AI tools to handle the increased workload, though he admits the pace is exhausting.

Meanwhile, other professionals are using AI to pivot, such as a corporate lawyer who uses voice-to-text AI to draft documents while walking outside, claiming it has automated away the “grunt work” that used to keep him chained to his desk. At the entry level, however, the landscape is becoming a mess of “CVS receipt” style job descriptions. Recruiters are using LLMs to bloat listings with endless, disjointed requirements, making it harder for candidates to find the actual substance of a role.

This verbosity is turning the hiring process into a gauntlet where applicants and recruiters are both relying on AI, creating a cycle of automated noise that often obscures the best fit for the job. While some leaders are pushing back by writing more authentic, narrative-based job posts, the broader market remains overwhelmed by AI-generated clutter.

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