A friend recently sent me an AI-generated report for their business. On paper, it ticked all the boxes: thorough, data-driven, polished to a mirror shine. But as we read it together, something felt off. The conclusions were circular, the recommendations generic. The problem? The AI had answered exactly the question it was fed—but not the question my friend actually needed answered.

I see this everywhere now. When every tool automates execution, the bottleneck shifts upstream: defining the real problem in the first place. Machines are brilliant at optimizing steps, but they can’t (yet) reliably sense if we’re climbing the wrong mountain. Framing—the art of asking the sharper question, of stretching past the obvious—has become an underrated superpower.

It’s counterintuitive: As more gets automated, the raw act of outputting becomes less valuable, while upstream skills—reframing, critical questioning, seeing the white space—matter more. The future won’t reward those who crank the handles faster, but those who decide which handles are even worth turning.

So next time you’re tempted to throw a problem straight into ChatGPT, pause. Ask: What am I really trying to solve? Am I even solving the right thing? It’s a habit that can’t be outsourced—yet. Read More