Generative AI Myths, Busted: An Engineer’s Quick Guide

Generative AI, particularly Large Language Models (LLMs), functions by predicting subsequent text tokens based on probabilities rather than true comprehension. These models learn through self-supervised methods on vast datasets, making them especially adept with structured information like programming code. The content debunks several myths, explaining that AI generates new content instead of copying data and that prompts are guidance tools, not hacks. While AI is a powerful assistant for engineers, it is not a replacement, as it lacks the ability to handle system architecture, weigh trade-offs, or understand business goals. AI hallucinations are a natural consequence of its probabilistic design, occurring when the model lacks sufficient context to generate a factually correct response.