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While large tech companies are shedding over-hired staff, the broader tech industry and non-tech sectors are aggressively hiring engineers. The net effect is an increase in engineering jobs, though demand has shifted towards full-stack and data-focused roles across a wider range of industries.

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Tech companies are citing AI as the reason for workforce reductions. However, the technology is not yet the primary driver of job replacement. This narrative serves as a convenient, forward-looking excuse to correct for mismanagement and massive over-hiring that occurred during the pandemic.

Contrary to public messaging about cost-cutting, past tech layoffs were often a headcount shuffle. Companies like Google quickly rehired, ending up with larger workforces. They were replacing generalists with specialized, expensive AI talent.

Many recent tech layoffs are attributed to increased efficiency from AI. However, the underlying driver is often a correction for aggressive over-hiring during the pandemic. AI serves as a convenient and forward-looking excuse for what is fundamentally a post-boom workforce reduction.

Expect a massive talent reshuffle in the next 12-24 months. Companies won't just lay off staff; they'll simultaneously rehire for different, "AI-first" roles. A company might cut 30,000 jobs while adding 8,000 new ones with entirely different skill sets, prioritizing builders over information movers.

Contrary to the media narrative, LinkedIn's data reveals that AI is currently a net job creator. The recent wave of layoffs and hiring freezes is primarily driven by macroeconomic pressures like interest rates, not automation.

Current tech layoffs are misattributed to AI. The real causes are the "wild" hiring binges during the zero-interest-rate COVID period and the rapid increase in the cost of capital. Companies are now correcting for that bloat, using AI as a "silver bullet excuse" for cuts that were financially necessary anyway.

Box CEO Aaron Levie argues AI coding tools will democratize software development, enabling non-tech industries (like agriculture and pharma) to hire engineers. This shifts talent from Silicon Valley and expands the overall engineering job market, contrary to popular belief.

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.

Major tech layoffs are not just about cost-cutting or AI efficiency. They represent a strategic talent reshuffle. Companies are clearing out employees with outdated skills to make way for a new, smaller, and more expensive workforce that is fluent in AI and can fundamentally change how work is done.

Mike Cannon-Brookes argues that AI makes developers more efficient, but since the demand for new technology is effectively unlimited, companies will simply build more. This will lead to a net increase in hiring for engineering talent, not a reduction.