A troubling pattern is emerging within technology organizations deploying AI: team members tasked with building and managing LLM applications lack basic understanding of how these systems function. Recent discussions reveal that even senior developers and team leads struggle to articulate what artificial intelligence fundamentally is, or explain how language models process and generate text. This knowledge gap extends beyond academic curiosity—it directly impacts production systems. Without proper understanding, teams risk deploying models prone to hallucinations, poor performance, or misaligned outputs without adequate safeguards or evaluation mechanisms.