LLMs are puzzles
The Internet flattened the world into a digital puzzle—a kind of intelligence test to see who can combine the correct symbols in the correct corner of a social swarm; plucking a nerve to some various end, bringing fortune, fame, or cringe. Your conception of the game shapes how you play it. That’s the real limiting framework: your mental model. You can’t understand emerging social systems without flailing around to update those models. It is very easy to stay sidelined with some excuse that prevents you from getting embarrassed.
This same paradigm applies to AI. It’s limiting to anthropomorphize it; instead, think of it as a linguistic puzzle. It has ingested trillions of words and arranged meaning into a multi-dimensional geometric map, a massive mystery that no one yet has fully uncovered. It’s your job to craft and aim language into this hall of mirrors. We can only do this blindly. But nonetheless, it brings back a result, and how we respond to it is revealing. There all sorts of distortions—cliche prose, lying, hallucinations—and if you’re metaphor for AI is an entity, then you’ll naturally get annoyed or offended and stop playing the game. It’s better to think of your result not as a failure of the LLM, but a failure in your probe. You’ve asked a wrong or vague question. By sending multiple probes, you start to build a fuzzy map of the hyperobject you’re prompting into. Since it gives back feasible answers back so instantly, we expect it to be right for immediately, with little exploration, but that lack of patience is where the frustration comes. It’s a more a matter of rotation, to approach something that matters to you from many angles until you crack it.