673 points on Hacker News: “AI makes you boring.”
The argument goes like this. Pre-AI Show HN meant talking to someone who’d thought about a problem for way longer than you had. You learned something. You got a different perspective.
Now? Vibe-coded projects, shallow ideas, nothing to discuss.
But the kicker isn’t just that AI output is boring. It’s that the human doesn’t compensate.
The Fatal Flaw
Some argue: “you need a human in the loop to steer the work and do the high-level thinking.”
That’s fundamentally flawed.
Original ideas are the result of the very work you’re offloading to LLMs. Having a human in the loop doesn’t make the AI think more like people. It makes the human think more like AI output.
The way humans have original ideas is to immerse in a problem for a long period of time. That struggle, that grinding, that’s where insight comes from.
That flat out doesn’t happen when LLMs do the thinking.
The Articulation Problem
Ideas are refined when you try to articulate them. This is why we make students write essays. This is why professors teach undergraduates.
Prompting an AI model is not articulating an idea. You get output, but in terms of ideation, the output is discardable.
It’s the work that matters.
You don’t build muscle using an excavator to lift weights. You don’t produce interesting thoughts using a GPU to think.
The Real Cost
The cost of AI assistance isn’t just that you might be wrong. It’s that you stop developing the muscle that would make you right.
The struggle is the point.
If AI does the thinking, you get surface-level ideas. And surface-level ideas make you boring to talk to, boring to work with, boring to read.
The future belongs to people who still struggle with hard problems. Not because they’re stubborn, but because that’s where the interesting stuff comes from.