[hansvm]

There are definitely a lot more clues than you realize (plus the context window is something like 12 written pages of standard English text, without much space wasted for the system prompts). If you were doing anything interesting at all, the output is heavily biased by your prompt. You lose some bits of information in that you only have one sample (the previous output/history) rather than the soft probabilities, and you lose some bits in that multiple inputs can map to the same output (like the class of prompts "output the 2nd letter of the following phrase: ..."), but real-world prompts tend to be the easiest/shortest thing to come to mind that you think will give you the result you're looking for, so the LLM's best guess for that prompt (there are lots of ways of guessing, so suppose for the sake of argument you did something like textual inversion on the one sample) is likely to not be a half-bad interpretation of the missing context -- i.e., a lot of the seemingly missing information was retained in the LLM's output, and you don't lose too many bits at a time as the old context trails off.