External commentators on layoffs lack crucial context like severance details or the humanity of the process. The true measure of a company's integrity during downsizing is not public opinion but the sentiment expressed by the actual employees who were let go.

When companies mishandle layoffs, disgruntled employees post negative reviews on sites like Glassdoor. AI-powered search engines and algorithms then aggregate and amplify this content, turning isolated complaints into a dominant and damaging part of the company's public reputation.

The drama at Thinking Machines, where co-founders were fired and immediately rejoined OpenAI, shows the extreme volatility of AI startups. Top talent holds immense leverage, and personal disputes can quickly unravel a company as key players have guaranteed soft landings back at established labs, making retention incredibly difficult.

Instead of fostering long-term talent, some companies deliberately create high-pressure environments to extract maximum value from employees over a short period. They accept high turnover as a cost of business, constantly replacing burnt-out staff with new hires.

While high-profile layoffs make headlines, the more widespread effect of AI is that companies are maintaining or reducing headcount through attrition rather than active firing. They are leveraging AI to grow their business without expanding their workforce, creating a challenging hiring environment for new entrants.

Businesses are increasingly framing necessary, performance-driven layoffs as a proactive AI strategy. This shifts the narrative from business struggles to forward-looking innovation, which is a better look for investors and the public.

According to an ex-employee, Google had an unwritten policy to retain intelligent but underperforming staff. The rationale was that they might become productive again, but more importantly, it prevented competitors from acquiring top talent, effectively treating talent as a scarce resource to be stockpiled.

Layoffs at a leading AI company like Meta are not just a negative signal. They function as a healthy redistribution of talent. Engineers who don't meet Meta's extremely high bar are still elite performers who get quickly absorbed by other companies, accelerating innovation across the broader tech ecosystem.

Companies that over-hired in 2022 are now stuck with expensive employees who won't leave due to a weak job market. This creates a bottleneck, forcing companies to eventually lay off these 'seniors' to make room for new, cheaper 'freshmen' hires, signaling a turn in the labor market.