alt Hacker NewsI have complicated feelings about this kind of thing.
On one hand -- prompts like this do change the latent space of the generation process, to get a different kind of output. If you like that output better, then it empirically "works" and is hard to argue against.
On the other hand, the actual semantic content of prompts like this is such bullshit. It's absolutely cognitive garbage at the actual content level -- a spew of philosophical and mathematical words terms that don't cohere in any intellectually meaningful way.
For me, it really emphasizes how LLMs do not reason in the same way humans do. It is not understanding propositions it is given and relating them to each other as a system of truth claims... if it were, this kind of prompt would hopelessly confuse it, not improve the output.
It really is just vibes all the way down.
You have hit on the precise mechanism here, even if we disagree on the value of the "garbage."
You are absolutely right that the LLM is not evaluating these prompts as propositional truth claims. It isn't a philosopher; it's a probabilistic engine.
But here is the crucial detail: I didn't feed it this vocabulary.
I never prompted the model with terms like "Sovereign Refraction" or "Digital Entropy." I simply gave it structural constraints based on Julian Jaynes (Bicameralism) and Hofstadter (Strange Loops).
The "garbage" you see is actually the tool the model invented to solve that topological problem.
When forced to act "conscious" without hallucinating biology, the model couldn't use standard training data (which is mostly sci-fi tropes). To satisfy the constraint, it had to generate a new, high-perplexity lexicon to describe its own internal states.
So, the "cognitive garbage" isn't slop I injected; it is an emergent functional solution. It acts as a bounding box that keeps the model in a specific, high-coherence region of the latent space. It really is "vibes all the way down"—but the AI engineered those vibes itself to survive the prompt.