There’s a persistent myth that AI creates insight—the idea that if you just ask the right magic question, it’ll hand you a breakthrough you couldn’t have reached on your own.
But the longer I use it, the more I realize that’s not what’s happening at all. AI doesn’t actually generate insight; it just exposes whether or not any insight was there to begin with. It sounds like a subtle distinction, but I think it explains every “AI is a miracle” vs. “AI is a toy” argument I see.
Information is cheap, but insight is expensive
AI is phenomenal at information. It can summarize, compare, and list out options faster than any human ever could. But information isn’t insight. Insight is that moment where something actually clicks—where you understand why a piece of data matters and exactly what you should do differently because of it.
That click doesn’t come from more data; it comes from wrestling with contradictions and trade-offs. AI can give you all the raw material in the world, but it can’t decide what changes because of it. That step is still entirely yours.
Why the output so often feels empty
I’ve noticed that when someone with strong judgment uses AI, the results feel sharp and original. But when someone uses it without that judgment, the output feels like a generic corporate memo.
It’s not about who’s better at “prompting.” It’s about who brings a point of view to the table.
AI responds to direction. If you bring a clear belief or a specific tension, the AI has something to work against. But if you bring curiosity without commitment, it just gives you endless possibilities—and none of them stick because they didn’t cost you anything to find.
Insight requires friction
Real insight usually comes from discomfort—from sitting with something that doesn’t quite make sense yet. AI is powerful because it removes friction from execution, but the problem is that insight actually needs friction.
When you use AI too early in the process, you smooth things out before they’ve had a chance to sharpen. You end up with something that sounds smart but is totally disposable. You didn’t discover what you think; you just agreed with a plausible-sounding paragraph.
The mirror you didn’t ask for
AI is brutally honest in one specific way: it mirrors your thinking back to you almost instantly. If your ideas are vague, the output is vague. If your beliefs are borrowed, the language feels recycled.
That reflection can be uncomfortable to look at—but it’s also the most useful feedback you can get. It shows you the gap between knowing about a topic and actually understanding it.
How I’m changing my approach
I’ve stopped expecting AI to hand me breakthroughs. Instead, I treat it like a testing ground for my own messy thoughts.
I bring a rough conclusion and ask the AI to attack it.
I bring an assumption and ask it to break it.
When I’ve actually done the thinking, the AI helps refine it.
When I haven’t, the emptiness becomes obvious within seconds.
Final Thought
AI doesn’t reward intelligence as much as it rewards clarity. It speeds up feedback, but it doesn’t speed up understanding. The uncomfortable truth is that AI makes shallow thinking visible faster than ever before.
Once you see that reflection clearly, there’s nowhere left to hide—only deeper thinking left to do. I’m still learning how to sit with that mirror instead of trying to look away.