We finally built something that “thinks.”
LLMs write code, edit essays, and even coach you through hard days.
Here’s the trap: when a tool can think a little, people tend to stop thinking at all.
Last week at 11am I asked an LLM to sketch the architecture for a sync layer in a Next.js + Firestore app. It looked clean, so I went with it. Two hours later I was fighting race conditions and a weird data types the model had confidently created. I tore it down and wrote a simple spec myself. Ten minutes of real thinking gave me the result I wanted ~90% faster.
LLMs are insanely useful, but they’re not great at higher-level reasoning tasks that involve complex contexts. They’re pattern machines with no skin in your game.
The lazy human heuristic is obvious: “Give the problem to the model so I can conserve energy.” But this is a problem. Brains work like muscle—stop lifting and you get weaker.
Even in a world of superintelligence, the quality of your outcomes tracks the quality of your questions. Questions shape answers. Answers shape actions. Actions shape results.
So don’t delegate your thinking. Upgrade it.
Keep the hard problems on your desk. Use the model as a powerful tool, not the final answer.
That’s your edge: a trained mind directing infinite leverage.