It’s possible that you are better at AI prompting than me.
It’s possible that my current game design is quite complex, to the extent that LLMs have a harder time writing content or designing mechanics for my game as opposed to, say, prompting it to “write an expansion for Monopoly”.
i suspect we are having similar outcomes here, but that i’m noticing “hey, this is better than the last one: its ideas are sometimes interesting to consider” while you’re noticing more “ehh, it still doesn’t get it”.
certainly my best results come from isolating a specific problem, and asking the model to summarize the problem back to me. unclear whether this is more useful than a diary! well, except in the critical sense that i am not motivated to use a diary.
i find that past a fairly low amount of complexity, the model starts forgetting rules, or ignoring/inventing context.
(as for the downvotes: i mean, if you’re sitting at +X agreement, i should be at -X, no?)
to be clear, my bar for ‘impressed’ is pretty low, having tried previous models for these things.
i got good results from fable by asking the model to come up with a system that described a few mechanics, and then look for missing mechanics within that system. i was pleased with the system it developed, and found a few of its proposals inspiring, though not usable verbatim.
i’ve been very impressed with fable for these use cases.
YMMV! Not sure why you’re being downvoted.
It’s possible that you are better at AI prompting than me.
It’s possible that my current game design is quite complex, to the extent that LLMs have a harder time writing content or designing mechanics for my game as opposed to, say, prompting it to “write an expansion for Monopoly”.
What’s your experience with LLMs and game design?
wrote a sibling :)
i suspect we are having similar outcomes here, but that i’m noticing “hey, this is better than the last one: its ideas are sometimes interesting to consider” while you’re noticing more “ehh, it still doesn’t get it”.
certainly my best results come from isolating a specific problem, and asking the model to summarize the problem back to me. unclear whether this is more useful than a diary! well, except in the critical sense that i am not motivated to use a diary.
i find that past a fairly low amount of complexity, the model starts forgetting rules, or ignoring/inventing context.
(as for the downvotes: i mean, if you’re sitting at +X agreement, i should be at -X, no?)
to be clear, my bar for ‘impressed’ is pretty low, having tried previous models for these things.
i got good results from fable by asking the model to come up with a system that described a few mechanics, and then look for missing mechanics within that system. i was pleased with the system it developed, and found a few of its proposals inspiring, though not usable verbatim.