The Forever Layoff

Jackye Clayton and John Baldino dig into what they are calling the forever layoff: a shift away from one big publicized round of cuts toward continuous, quiet trickles of terminations. They walk through why companies structure layoffs in small batches to avoid triggering WARN Act notice requirements, what happens when bias creeps into who gets picked in each round, and why a Facebook AI driven layoff algorithm ended up cutting employees on protected leave. The conversation also covers what constant uncertainty does to loyalty, knowledge sharing, and hiring strategy, plus where the job market is still strong for people looking to pivot.

Key Takeaways:

• The forever layoff describes small, continuous rounds of cuts instead of one large publicized layoff
• Keeping each round under 50 people can help employers avoid triggering federal WARN Act notice requirements
• New York City's mini WARN law requires 90 days notice, which is difficult for businesses facing fast changing conditions like restaurants
• Comparing today's layoff numbers to the 2020 pandemic understates how many people still have not recovered from that period
• When layoffs target individuals instead of roles, bias about who a manager personally likes or dislikes can creep into decisions
• A Facebook AI layoff algorithm reportedly cut employees on protected leave, including someone about to give birth, after learning biased patterns from past human decisions
• EU regulation meant to hold organizations accountable for AI driven employment decisions has been delayed until December 2027
• Constant, low level layoff risk erodes employee loyalty and pushes people to hoard institutional knowledge as leverage
• Being transparent about financial pressure, such as admitting revenue is down, builds more trust than staying silent and letting people guess
• Job seekers open to a pivot have strong options in medical support roles, last mile logistics, and commercial trucking, where demand remains high

Keywords: forever layoff, WARN Act, layoff bias, AI discrimination, trickle layoffs, employee loyalty, workforce trust, reduction in force, knowledge retention, HR strategy