What your parent poster said is nonetheless true, regardless of how it feels to you. Getting text from an LLM is a process of iteratively attempting to find a likely next token given the preceding ones.
If you give an LLM "The rain in Spain falls" the single most likely next token is "mainly", and you'll see that one proportionately more than any other.
If you give an LLM "Find an unorthodox completion for the sentence 'The rain in Spain falls'", the most likely next token is something other than "mainly" because the tokens in "unorthodox" are more likely to appear before text that otherwise bucks statistical trends.
If you give the LLM "blarghl unorthodox babble The rain in Spain" it's likely the results are similar to the second one but less likely to be coherent (because text obeying grammatical rules is more likely to follow other text also obeying those same rules).
In any of the three cases, the LLM is predicting text, not "parsing" or "understanding" a prompt. The fact it will respond similarly to a well-formed and unreasonably-formed prompt is evidence of this.
It's theoretically possible to engineer a string of complete gibberish tokens that will prompt the LLM to recite song lyrics, or answer questions about mathemtical formulae. Those strings of gibberish are just difficult to discover.