Current LLM outputs often mimic logical steps without actually employing a reasoning process. This gap between performance and internal logic suggests models rely on pattern matching over true cognition. Researchers now struggle to prove if these systems solve problems or simply recall similar examples. This distinction limits the reliability of AI in high-stakes technical domains.