Last week AI almost talked me into a wrong answer. And it sounded completely sur
By Mansour Norouzi · June 12, 2026 · Curated by George's Blog
Last week AI almost talked me into a wrong answer. And it sounded completely sure of itself.
I was digging into our Prime Day data. Trying to understand one weird thing in the numbers.
I had AI help me run the analysis.
It came back with a clean, confident explanation. Well written. Logical. Looked right.
I almost moved on.
But something nagged me. So I looked closer.
The conclusion was wrong. Not a little wrong. The whole reasoning was off.
Here's why. On Amazon, when someone clicks an ad and buys a few days later, that sale gets credited back to the day of the click, not the day they bought. The AI didn't know that. So it read the data as if every sale happened the day it showed up.
One missing piece of context. And the entire story it told me fell apart.
The moment I explained the attribution to it, it caught the mistake instantly and fixed it. Then it was genuinely useful again.
That's the part I keep thinking about.
It wasn't dumb. It was confident. And confident plus wrong is harder to catch than obviously wrong.
A beginner would have published that analysis. It looked too clean not to.
So here's where I've landed. AI is incredible when you already know enough to catch where it slips. It's risky exactly where you can't.
The better it gets at sounding right, the more you have to already know.
I use it every day. I just don't trust it on the details of my own field without checking.
Where have you caught AI being confidently wrong in something you actually know well?