If AI Built It, It Cannot Be Good
There is a rule a lot of people carry without saying it out loud: if AI made it, it cannot be good.
Not always spoken this way. More often it’s a reflex — a glance at a piece of writing, a product, a piece of code, and a downgrade the moment someone learns how it was made. The judgment moves from the thing itself to the process behind it. Not “is this good,” but “was this earned?”
I want to be fair to that reflex before taking it apart, because for a period of time it was correct.
It Used to Be True
Think back to 2023. You asked a model for code and it confidently imported a library that did not exist — the function name plausible, the arguments sensible, the whole thing invented. You gave it a long file and it lost the thread by the bottom of the page, contradicting what it had written thirty lines earlier. You asked for an argument and got something fluent, well-organised, and hollow — prose with the shape of a case and nothing load-bearing inside it.
Two things were true at once, and it was the combination that mattered. The tools were not there yet. And people did not know how to use them: the instinct was to type a line and accept whatever came back, rather than brief the drafter and judge what came back. The visible examples were mostly the first kind.
Together they produced a flood of bad work — an instrument that couldn’t do the job, in the hands of someone who didn’t know how to hold it.
So the rule wasn’t prejudice. It was pattern-matching. See ten sub-par things made a certain way, and betting the eleventh would also be sub-par was just good statistics.
The Gap That Opened
Then the ground moved and the rule didn’t.
Both halves moved, and they moved together. The tools crossed into actually capable. And a growing number of people learned to direct them instead of just prompting them — to brief the drafter rather than react to it. Neither change was announced. What comes out the other end now spans an enormous range — from the half-baked thing the old rule was built to catch, to a deep, hand-tuned simulation that took months of real iteration.
The rule doesn’t see that range. It was trained on the low end of an old distribution and still fires on the whole thing, because a heuristic is exactly a decision you don’t have to make freshly each time — that’s the entire point of having one. You see the origin, skip the inspection, move on. It’s efficient right up until it’s wrong, and it gives no signal for when that moment arrives. It doesn’t come with an expiration date. It just stops being true, and keeps being used.
Two Different Questions
I posted Polis, my city builder, on r/SimCity, saying upfront that I’d built it with Claude. Most of the thread was what you’d hope for: cars clipping through hills, light rail tiles refusing to place, gridlock no matter how many avenues you laid down. Real problems, found by people who had actually played it.
Then there was the commenter who never once mentioned the game.
Why would he want to play something I “couldn’t be bothered to make” myself? Note what that objection is and isn’t. It isn’t a claim about the game — he hadn’t opened it. It’s a claim about effort. I pushed back: everything in our society is machine-assisted one way or another, and some of it is good and some of it is bad. He didn’t answer. He said he prefers games made by humans. Pressed further, the position came out: there is no ethical use of AI. Full stop.
That exchange clarified something for me, and it isn’t what I thought at the time. We were not disagreeing. We were answering different questions. I was defending the possibility that the game was good. He was explaining why the answer to that wouldn’t change anything for him.
Effort, then preference, then ethics — three real objections, possibly held all along. What none of them ever was, at any point, is a claim about whether the game is any good.
Which is the shift underneath all of this: provenance used to be a decent shortcut for judging quality, and it is becoming a worse one every month. When the shortcut stops predicting reliably, the only thing left is to inspect the work.
The Objection That Deserves Better
One thing needs saying before I finish, because the commenter above stated his objection bluntly and it would be cheap to let the blunt version stand in for the serious one.
There is a serious case against AI that has nothing to do with whether the output is any good. What the models were trained on, and whether the people who made that work agreed to it. What happens to the people whose living was the thing now being generated. What it costs to run. Those arguments are real, and they don’t get weaker when the output gets better — if anything they get sharper.
But notice that none of them are the rule this post is about. Nobody owes my game their time, and declining to play something because of how it was made is a choice anyone is entitled to. That is different from knowing whether it’s any good. “This was made in a way I object to” and “this cannot be good” are different claims, and only one of them is about the artifact. You can hold the first honestly and still owe the second an actual look. What goes wrong is when the first quietly does the work of the second — when a principled objection to how a thing was made gets spent as a verdict on whether the thing is any good.
The Rule Dies From Being Looked At
The convenient version of this rule will keep being right often enough to survive — that’s what makes it so hard to kill with better evidence alone. Somewhere, right now, someone is dismissing something genuinely excellent without opening it, and somewhere else someone is right to dismiss something genuinely bad, and from the outside those two people sound identical. Statistics won’t settle it. Only looking will.
Nobody updates a comfortable rule because the average got better. They update it the one time they actually looked, and were wrong.