Four Thieves at the Louvre Just Taught Us a Masterclass in Building AI Products
A Louvre heist exposed a critical AI blind spot. Unlock 5 "Contextual Verification" micro-SaaS ideas that solve what current tech ignores. Build this now.
I want you to picture this. It’s a sunny Sunday morning in Paris, October 2025. The Louvre. The most surveilled building on the planet.
Four guys walk in. Eight minutes later, they walk out with €88 million in crown jewels.
Did they hack the mainframe? Did they rappel from the ceiling like Tom Cruise? No.
They wore hi-vis vests.
They brought a furniture lift, dressed like construction workers, and just... went to work.
The security guards didn’t stop them because our brains —and the security cameras—are wired to ignore “normal”. In sociology, it’s called the presentation of self. If you look like you belong, you become invisible.
Here is the scary part (and the opportunity for us): Your AI product has the exact same brain damage.
The “Normality” Trap
AI doesn’t actually “see”. It categorizes. It’s a math equation, not an eyeball.
AI is trained to flag outliers.
If a person runs fast in a museum → FLAG.
If a person wears a mask → FLAG.
If a person wears a construction vest and walks slowly → IGNORE.
The thieves hacked the “Ignore” function. They performed a “Contextual Injection Attack” on human reality.
As builders, we rely on these same datasets. We train our models to look for the statistically suspicious. This creates two massive problems (and one massive business idea):
