The LLMs I have tested have terrible world models and intuitions for how actions change the environment. They're also not great at discerning and pursuing the right goals. They're like an infinitely patient five-year old with amazing vocabulary.
I'm going to ignore all that and tell my developers working in complicated codebases that they have to use AI. I'm sure comprehending side effects in a world building text adventure is completely different that understanding spaghetti code
Great on small snippets of code, passable on larger pieces of code, great at finding vulnerabilities in large pieces of code, terrible in Zork. All-in-all, a jagged frontier that defies a simple sarcastic characterization.
You keep a document going called "state of the world", on every turn, you read this document in (as context), use it to help compute what happens, and based on what happens, create an updated "state of the world" document. You track important details so your LLM is consistent from turn to turn.
If you doing an RPG, which I guess is where this is more obvious, you track the play and enemy positions, their health, their moods and perhaps top thoughts, the state of important inanimate objects. if you break down the door, you update the door's state in the document. This is in contrast to just giving the LLM the previous turns and hoping it realizes the door is broken down later (just by statistical completion).
The LLMs I have tested have terrible world models and intuitions for how actions change the environment. They're also not great at discerning and pursuing the right goals. They're like an infinitely patient five-year old with amazing vocabulary.
[1]: https://entropicthoughts.com/updated-llm-benchmark
(more descriptions available in earlier evaluations referenced from there)