AI can now generate a thousand headlines, designs, or drafts in the time it takes you to read this sentence. That's genuinely remarkable — and it quietly changes what's valuable. When generation is free and infinite, making things stops being the bottleneck. The scarce skill becomes the one AI can't do for you: looking at a thousand options and knowing which one is actually good. That's taste — the judgment to tell the great from the merely fine — and as AI floods the world with output, taste is the thing that can't be copied.
Here's why taste rises in value exactly as generation gets cheap, and how to build the skill that AI makes more important, not less.
As AI makes generation free, taste becomes the scarce skill — the judgment to know which output is actually good.
Why taste wins:
Let AI generate; bring the taste that decides what's worth keeping.
The shift AI creates is best understood as a separation of two things that used to be bundled together: producing something and judging whether it's good. For most of history these came as a pair — making a thing was hard, so the people who could make it were also, usually, the ones who could tell good from bad. AI breaks the bundle. It makes production nearly free and infinite, but it doesn't come with judgment attached. It will happily generate a thousand options, and it will tell you nothing reliable about which of them is actually any good.
That's because judgment of quality isn't really a generation problem — it's a taste problem, and taste is grounded in a human sense of what matters, what resonates, what's true, what's right for this audience and this moment. AI can mimic the surface of taste by averaging what's been praised before, but it can't originate the judgment, because it has no genuine stake in whether the result is good. So as generation collapses toward free, the value migrates to the thing that didn't get automated: the discernment to look at the flood of output and pick the one worth keeping. Making is no longer the bottleneck. Choosing is.
This inversion changes which skill is scarce, and therefore which skill is valuable:
| Old world (making was hard) | New world (making is free) |
|---|---|
| Bottleneck: producing the thing | Bottleneck: judging what's good |
| Scarce skill: generation | Scarce skill: taste |
| Few options, all hard-won | Infinite options, all cheap |
| Value in the craft of making | Value in the judgment of choosing |
When you can generate a thousand designs instantly, your problem is no longer "how do I make a design?" — it's "which of these thousand is the one worth shipping?" And that question AI can't answer for you, because answering it well requires taste: the trained judgment to recognize the great option among the merely competent ones, to know why it's better, and to push for it against the gravitational pull of "good enough." The person who can do that becomes more valuable as generation gets cheaper, because they're the scarce input in a world drowning in cheap output. This is the same reason the best work still needs a human in the loop: the machine produces; the human discerns. Infinite options without taste is just infinite noise. Taste is what turns the flood into a choice.
The good news — and the actionable part — is that taste isn't a mystical gift some people are born with. It's built, the same way any judgment is built: through exposure to lots of examples, practice at distinguishing good from bad, and genuinely caring about quality enough to notice the difference. You develop taste by studying great work closely, by making things and getting feedback, by asking why one option is better than another until the answer becomes intuition. It's a skill, which means it's trainable, which means it's worth deliberately investing in — especially now, when it's becoming the scarce input.
This reframes how to work alongside AI. The move isn't to compete with AI at generation, which is a losing game — it generates faster and cheaper than you ever will. The move is to let AI do the generating and bring the taste it can't: use it to produce the thousand options, then apply your trained judgment to find and refine the one that's genuinely good. That's a partnership that plays to both strengths — the machine's infinite cheap production and the human's irreplaceable discernment. As AI handles more of the making, the people who thrive won't be the ones who generate the most; they'll be the ones with the taste to know what's worth keeping. Build that, and you build the one thing AI can't copy.
To develop the judgment that rises in value as generation gets free:
The throughline: as AI makes generation free, taste becomes the scarce skill. AI produces options but can't judge them, because quality judgment is a human taste problem it can only mimic by averaging the past. When making is free, choosing well is the bottleneck — and choosing well requires trained discernment. Taste is built through exposure, practice, and caring about quality, so invest in it deliberately. Let AI generate; bring the taste that decides what's worth keeping.
Q: Why can't AI just learn taste like any other skill? Because taste isn't a generation problem — it's grounded in a human sense of what matters, resonates, and is right for a specific audience and moment. AI can mimic the surface of taste by averaging what's been praised before, but it can't originate the judgment, because it has no genuine stake in whether the result is good. It will generate a thousand options and tell you nothing reliable about which is actually best. That discernment requires a perspective and a care AI doesn't have, which is exactly why it stays scarce — and valuable — as generation gets cheap.
Q: If AI generates everything, what's left for people to do? Judge, choose, and refine — the parts AI can't do. When you can generate a thousand designs instantly, the problem stops being "how do I make one?" and becomes "which of these is worth shipping?" That question requires taste: recognizing the great option among the competent ones, knowing why it's better, and pushing for it. The person who can do that becomes more valuable as generation gets cheaper, because they're the scarce input in a world drowning in cheap output. Don't compete with AI at making; bring the discernment it lacks.
Q: How do I actually build taste? The same way you build any judgment: exposure, practice, and caring about quality. Study great work closely so your eye learns to recognize excellence. Make things and get feedback. Ask why one option is better than another until the answer becomes intuition rather than guesswork. And genuinely mind the difference between good and great — taste only grows if you notice and care. It's a trainable skill, not a mystical gift, which means it's worth investing in deliberately, especially now that it's becoming the scarce input in a world of infinite cheap generation.
Taste is the thing AI can't copy. AI separates two things that used to come bundled — producing something and judging whether it's good — by making production nearly free while leaving judgment untouched. It generates a thousand options and tells you nothing reliable about which is actually worth keeping, because quality judgment is a human taste problem it can only mimic, never originate.
So as generation collapses toward free, the value migrates to discernment: when making is the easy part, choosing well is the bottleneck, and choosing well requires taste. The encouraging part is that taste is built, not given — through exposure, practice, and caring about quality. Don't compete with AI at generation; let it produce the options and bring the judgment to find the one that's genuinely good. In a world drowning in cheap output, the taste to know what's worth keeping is the one skill that can't be automated away.
I went from 200 to 11,000 subscribers without hiring anyone. AI didn't write my newsletter — it did everything around it.
I chased big, audacious goals for years and burned out every time. Then I built my whole life around wins so small they felt like cheating.
One person, output that looks like five. It isn't about working more hours — it's about a kind of leverage teams rarely have.
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