He'd been a data scientist for 13 years. The problem was straightforward: clustering sensor data by location. Because errors in latitude and longitude tend to be random, you get elliptical clouds of points. K-means was the right tool for the job.
His boss had a different idea.
"My boss picked up his laptop, turned it around, and said, 'But Copilot says that we should use DBSCAN,'" he recalled.
He researched DBSCAN thoroughly and found what any experienced data scientist would — it would be very slow for this use case and would do the wrong thing in a worse way. He presented his findings. His boss didn't agree.
A few weeks later, he was laid off. Along with the rest of the data team.
The punchline came two months after that: his boss was also laid off.
Now the company has an open position posted for an "AI Scientist." In India.
The story, posted to Reddit under the username u/Utkonos91, received over 11,000 upvotes and became one of the most shared accounts of what happens when management prioritizes AI tool output over human expertise. It struck a nerve because it captured a growing pattern: executives treating AI recommendations as authoritative, even when they contradict the judgment of experienced professionals.
"This isn't about whether AI is good or bad," one commenter wrote. "It's about whether the person in charge has enough technical literacy to tell the difference between a recommendation and a command."
For the data scientist at the center of it all, the lesson was simpler: when your boss values an AI's answer more than yours, it's time to update your resume.