I would argue that Markov chains were a better tool for comedic purposes. Notice that in all of the examples of using Markov chains, the person would see a pot

I would argue that Markov chains were a better tool for comedic purposes. Notice that in all of the examples of using Markov chains, the person would see a potential, come up with a purpose, exercise the setup, and then fill the setup with generated text. Likewise in a random generation examples, the person would asses the results, then find what parts were actually funny, and choose to spread this parts. LLMs output has less potentially funny results, it has less potential for unexpectedly change realistic-sounding output to absurdist output, and so as a tool it is less fit for comedic purposes.