Your AI is lying to you. It just sounds really good doing it.
I ran an experiment that changed how I use AI forever. I took the SAME prompt and sent it to ChatGPT, Claude, and Gemini at the same time. Not to see which one was "best." I wanted to see where they DISAGREED. Here's what blew my mind: → ChatGPT gave me a confident, detailed plan. Sounded great. → Claude flagged two risks that ChatGPT completely ignored. → Gemini agreed with ChatGPT's plan... but used completely different reasoning to get there. So who was right? They all were. And they were all wrong. Each one had blind spots that the others caught. That's when it hit me — asking ONE model is like hiring ONE consultant and hoping they don't have blind spots. They always do. So I started doing this with every important decision. Three models. Compare the disagreements. The answer is always in the friction between them. A few things I've noticed after months of doing this: → When all three agree, you can trust the answer. When they don't, that's where the gold is. → ChatGPT is the most confident. Claude is the most cautious. Gemini is the fastest to spot patterns in large data. None of them will tell you they're wrong. → The biggest risk in AI isn't a wrong answer. It's a wrong answer that SOUNDS right and you have no way to know. Curious — is anyone else cross-checking between models, or am I the only one doing this the hard way?