Layoffs and Survival Cases¶

Are Tech Giants making a pivot by shifting their budget from traditional cloud maintenance and support into high-cost AI chips (like NVIDIA GPUs) and specialized AI talent? In this section, you will find some concrete episodes of workforce reduction and how people and organizations navigated them.

Layoffs Are "Not Due to AI"¶

There is a narrative that 2025-26 layoffs in Tech are not due to AI, but to previous over-hire or other management mistakes, and an AI is just an excuse.

Authors of such narratives, however, often combine this vision with the view that AI is a great tool boosting a productivity. That pulls us back to the question of these docs:

Question-02 of 17: What will some Humans do to other Humans' work, income, safety and well being by growing and utilizing AI?

In this context: will fired people be re-hired by someone? And if not - why? Is it because AI allows CEOs have 10 "10xProductive" developers instead of 100 while paying them the old salary (10 times down in costs)? Will CEOs want 100 "10xProductive" developers to provide 100xValue to the World? Or will they just want more revenue?

And even more precise question: do these CEOs, their investors care about people who cannot find the job and pay their bills? Does "over-hire" map 100% into the idea of "over-population"? Are those going towards the "new economy" while being financially secure suggesting that "extra people" should die along with their families for the "new order to arrive?"

Jevons Paradox - AI's Application¶

The economic theories can feel like gaslighting when applied to real human lives. The Jevons Paradox is frequently cited by AI optimists to say "Don't worry, efficiency creates more work!"

In the 1800s, Jevons noticed that when steam engines became more efficient (used less coal), people didn't save coal. Instead, they built millions more steam engines because it was now so cheap to run them. Total coal use went up.

By analogy, AI optimists suggest that AI will create a huge (scaled up) amount of entirely new roles (e.g., AI product managers, safety engineers) and expand "long-tail" services like personalized healthcare and niche legal analysis that were previously too expensive - while routine, "low-discretion" roles may decrease, there will be a higher demand for "high-context" roles that require a human-in-the-loop, such as:

• AI supervision and governance.
• Problem framing and goal setting.
• Customer-facing roles requiring emotional intelligence.
• Cross-functional coordination.

Doubt

How exactly erasing of 5M taxi drivers with Tesla FSD will create "more demand" for taxi drivers?

It doesn't. Jevons Paradox does not create more demand for taxi drivers—it creates more demand for rides. In the coal case, "Coal" is the resource. In the taxi case, "The Driver" is not the resource—"Transportation" is.

• Reality: If Tesla FSD makes a ride cost $0.20 per mile instead of $2.00, demand for rides will skyrocket. People will send their cars to pick up groceries, kids, or even just circle the block to avoid parking.
• Result: We use more "Driving," but we need zero "Drivers." Jevons Paradox explains why we will have more autonomous cars on the road than we ever had human taxis, but it offers no protection for the human worker.
• Time Gap and Skill Gap: You cannot turn 5 million taxi drivers (or thousands of software developers) into "Customer-facing roles requiring emotional intelligence" overnight.
• Amount Gap: will we need 6 million "Customer-facing roles requiring emotional intelligence"?