Often they can't figure out how to test the thing, so "does this attempted solution even work at all?" is its guess from reading the source code, and sometimes I've even caught them writing "tests" which are a regex on the source code, not functionality.
They know almost nothing about "is this solving the right problem?", they're trained to assume the user is right, not to frame-challenge.
My general experience both in game and non-game projects is that it will be lazy by default rather than solving things correctly. Sometimes I spot this from their responses, other times I only notice with manual testing.
The point is that AI is aware of constraints and can manage a round it. You've got to keep in mind the size of a typical software project and plan. Most people aren't writing a kernel. They're writing some backend tool and need a project that fits into a couple of quarters with a handful of people at most involved.
Only if you instruct it with constraints. Otherwise, it's happy to implement whatever workaround it needs. But it still takes a dev to know what those constraints are and why they're needed.
Human test passed. AIs make giant flashy mistakes. They don't fuck up basic grammar.
write a comment about how to use ChatGPT to write a game like you're a barely literate reddit user, short answer, maximum incoherency
Not perfect, gptzero.me still knew it was AI generated (tayo42 is human by the same measure), but if for some reason someone was using an LLM prompted with that pattern, I suspect it would fool me in a Turing test unless I found the keyword to force the agent to change the role it was playing.
Conveying the errors typical in a Raise The Colours group on Facebook, that's the hard stuff.