The post discusses the Clever Hans effect in relation to large language models (LLMs) and their prompting techniques, drawing a parallel to Socratic questioning. It indicates that LLMs often produce responses not based on true intelligence but rather on pattern recognition, similar to how a Ouija board might provide misleading answers. The commentary highlights that while iterative prompting reveals an emergent form of intelligence shaped by context, the understanding of 'true intelligence' is also contested, as some believe it remains unique to humans. Moreover, concerns are raised about the evolving capabilities of LLMs without extensive prompting, suggesting that the public perception might be more about human ownership of intelligence than about the mechanisms of LLM operation. Additionally, it is recommended that LLMs could enhance their performance by incorporating more context from users' inquiries before formulating responses.