Are We All Artists Now?

Here's something I've been thinking about for a while now — a mental model I keep coming back to whenever I try to understand how anyone actually gets good at something. I think mastering a skill happens in two phases, and I've always just thought of them as the science of something and the art of something.

The science is where you're learning something — a craft, a trade, a discipline, a sport, whatever — and you start by inheriting the rules. Somebody already went through the trial and error. They figured out what works, wrote it down, handed it to you so you don't have to relearn the whole thing from scratch. You follow it, you absorb the pattern, you do it the way it's supposed to be done, because that's what's been laid out for you. And honestly, that's a fine way to get competent fast. Nothing wrong with it.

Then, at some point, if you keep going long enough, something shifts. You stop asking "what's the rule" and start asking "why does this rule even exist, and does it still apply here?" You start bending things, breaking things, going back and reexamining stuff you used to just take for granted. Not randomly — that's important — but with this kind of earned judgment about which parts of the rulebook are actually load-bearing and which parts are just habit nobody's bothered to question in a while. That's the art.

Turns out I didn't come up with this myself, which, fine. Once I started poking at it I found it maps pretty closely onto existing thinking about skill acquisition — the Dreyfus model of skill mastery describes something similar, moving from novice rule-following (the science) toward this expert-level improvisation past the rules (the art). So I'm not being nearly as clever as I thought I was. But I'm going to keep using my own language for it anyway, because I think it's the more useful frame for what I actually want to talk about here: "art" and "science" as names for two tiers of any skill. Not fine art. Not literal science. Just rule-following versus rule-transcending.

So that's the mental model. What I want to spend this piece doing is pushing on it a bit — specifically, why I think generative AI is stuck pretty firmly in the science tier, why that might be making the art tier more valuable rather than less, and where I think that actually leaves people.

The tell

Here's something I'd bet almost everyone reading this has felt: you read something, or look at something, and some part of you just goes — yep, that's AI. You can't always say exactly why. It's a little too smooth. A little too resolved. Technically fine, but somehow thin.

I don't think that reaction is some mystical sixth sense. I actually think it might be a pretty accurate read of what's happening underneath.

Generative models are trained to predict the most statistically likely continuation given everything they've seen. That process pulls outputs toward the center of the training distribution — smoothed, average, safe. Human work, even mediocre human work, tends to carry more irregularity in it: specific choices, small "wrong" decisions that somehow turn out right, texture that comes from one particular person's particular constraints and mood and history on that day. If AI output tends to read like an average and human output tends to read like a point of view, maybe that difference is genuinely detectable — not just something we're imagining.

"But models keep getting better" — sure, but at what, exactly?

The obvious pushback here: models keep improving, constantly. Doesn't that just erode this whole argument over time?

I don't think it does, actually, and I think it's worth walking through why models get better, because as far as I can tell, none of the reasons actually touch the thing I'm talking about:

• Scale — more parameters, more data. This just gives a model a bigger map of the territory it was trained on, and more resolution once it's there.
• Architecture and training method improvements — these make navigating that map more efficient, less wasted effort on noise.
• Post-training and fine-tuning — this one's closer, honestly. It's sculpting which parts of the existing map the model gets pulled toward by default. That's a real form of discernment. But it's discernment done by humans, in advance, on the model — not something the model works out itself, in the moment, for a case nobody already judged.
• Inference-time stuff — longer context, more reasoning steps. This just gives the model more time to search the map it already has before it answers. Bigger map. Better-curated map. More time to search the map. That's basically every lever I can name, and every one of them is about navigating the existing space better. None of them is "redraw the map because this part of it is wrong." Which isn't a knock on the technology, it's just not what any of these methods are built to do. And honestly, I think that absence is the actual evidence here — not just something I'm asserting because it happens to support what I already wanted to believe.

What's actually missing

Here's where I want to push back on my own instinct a bit. The naive version of "art versus science" makes it sound like creativity is just rule-breaking — like the more you depart from convention, the more creative you are. But I don't think that's really true. Randomly ignoring constraints doesn't produce insight, it produces noise. A musician who "breaks" a harmonic rule isn't just playing random notes — they're breaking exactly the one rule that's stopped being load-bearing, while keeping everything else intact enough that the thing still holds together as music.

So maybe the sharper version of the claim is this: creativity isn't measured by distance from the rules, it's measured by how precisely you can tell which constraints are still structural and which ones are just calcified habit. That's a much harder thing to do than either blindly obeying or blindly departing, and I think that's the actual content of "transcending the rules" — not escaping them, but understanding them well enough to know the one case where they don't hold.

I'll be honest about where this leaves me, though: I don't think we actually have a clean theory of what makes human creative cognition tick, so I hold this with real uncertainty, not settled confidence. I lean toward believing there's something happening when a person does this kind of discernment that isn't happening when a model does pattern completion. But I'm genuinely not sure I'm the person qualified to prove that, and I'd rather just say that out loud than pretend I've got it all figured out.

Where does that leave the rest of us

I think this generalizes across pretty much every field, not just software. If the rule-following tier of a field is what's getting commoditized, the valuable skill in that field was probably never really "know the rules" — it was always "know when they stop applying." That's true in law, in medicine, in writing, in management, in the trades, wherever. It's just that AI is making the floor of rule-execution cheap enough and fast enough that the tier above it is the only one left with any real scarcity.

So if you're trying to figure out where to put your own effort right now, I don't think the useful question is "which tasks can AI not do yet." I think it's closer to: which parts of what I do are me applying a rule someone else already worked out, and which parts are me actually deciding whether that rule still holds in this specific case? The first tier is getting automated out from under all of us, in pretty much every field, on a timeline none of us fully control. The second one's the one worth deliberately getting better at.

So — are we all artists now?

Not literally, no. I'm not telling anyone to quit their job and pick up a paintbrush, and I don't think the economics of fine-arts careers are suddenly any different. But I do think the thing "art" was always shorthand for — the rule-transcending, question-asking, "does this concept even still deserve to exist" instinct — is now the scarce, valuable tier in pretty much every field, including plenty of fields that pride themselves on being practical and rule-bound.

I don't know if that means we're all artists now. But I think it means the thing we used to dismiss as "just art" might be the one thing left with no substitute.