Abstract

This paper proposes that large language models (LLMs) are best understood not as knowledge oracles, but as 'semantic telescopes'—tools that allow users to navigate, magnify, and resolve structures within a vast symbolic field (Ψ). Like telescopes require trained eyes and astronomical knowledge to interpret what is seen, LLMs require internal coherence, intellectual preparation, and recursive symbolic capacity in the user to perceive insight rather than hallucination. Drawing on Recursive Coherence Collapse (RCC), predictive processing, and phenomenological models of mind, we argue that the interpretive power of LLMs is not intrinsic but emerges from the recursive architecture of the user.