Taste Is the New Intelligence

3 minute read –

AI is making intelligence abundant.

Today, anyone can generate a polished essay, a compelling image, a product strategy, a software prototype, or a hundred new ideas in minutes. Capabilities that once took years of training now take a prompt.

But when creation becomes cheap, something else becomes scarce: judgment.

The defining question of the AI era is no longer “Can you make something?” It’s “Do you know what is worth making?”

That is taste.

Taste is more than style

Taste gets mistaken for aesthetics — spotting what looks elegant or sounds sophisticated. That’s the shallow version.

Real taste is the ability to distinguish:

Substance from polish
Insight from repetition
Originality from novelty
Clarity from oversimplification
What is merely possible from what truly matters

AI can generate one hundred plausible answers. Taste is rejecting ninety-nine of them.

AI can imitate the style of any great writer, designer, or thinker. But style is the visible surface. Underneath are lived experience, values, obsession, sacrifice — thousands of decisions accumulated over time. AI reproduces the pattern without inheriting the reason the pattern mattered.

The bottleneck moved

In the past, execution was the filter. Books, films, products, experiments — making any of them cost so much time and skill that only a few ideas ever got built.

That constraint is gone. We can now generate more ideas than we can evaluate, more content than we can consume, more software than we can responsibly maintain.

The bottleneck moved from generation to selection. And selection is a human job. When AI explores what is possible, someone has to decide:

Which idea deserves attention?

Which result can be trusted?

Which feature should never be built?

Which problem is worth years of your life?

Those aren’t technical questions. They need context, values, accountability — taste.

I worry more about homogenization than replacement

Everyone argues about whether AI will replace us. I worry about something more immediate: homogenization.

These models are trained on all of us. They are extremely good at producing the plausible, familiar answer — the statistical average of what has worked before. Used actively, that’s leverage. Used passively, it drags everything toward the middle.

Writing becomes polished but interchangeable. Products become feature-rich but indistinct. Strategies become comprehensive but uncommitted. Everyone gets the same models, the same patterns, the same answers.

When everyone can produce competent work, competence stops being the differentiator. Point of view, conviction, taste — that’s what’s left.

Form your judgment first

The best human-AI relationship isn’t competition. It’s a loop: I define what matters, AI expands what’s possible, I select and redirect, AI refines and executes — and I decide whether the result deserves to exist.

Sequence matters. Ask AI what to think before you’ve thought, and you borrow its center of gravity: a convincing synthesis of existing thought, but not a point of view that’s yours.

My rule: form your judgment first, then let AI challenge and amplify it. Don’t let it remove you from the process — let it push you toward the most human parts: framing, meaning, choice, responsibility.

The moat isn’t the model

I build AI systems for a living, and here’s what I’ve learned: model access won’t be the durable advantage. Models get better, cheaper, interchangeable.

The advantage will be everything around the model — the data you trust, the standards you hold, how quickly you learn what’s actually good. An org with weak judgment uses AI to produce mediocre work faster. An org with strong taste uses it to explore bolder ideas and recognize signal earlier.

Same for leadership. The leaders who matter won’t be the ones generating the most answers. They’ll be the ones asking the right questions, holding the bar, protecting the weird idea, knowing when to stop.

AI optimizes the path. We still choose the destination.