According to God of Prompt on Twitter, instructing large language models like Claude, GPT-4, and Gemini to simply "act as an expert" results in lower quality outputs compared to using highly specific persona prompts. Based on tests of 47 persona configurations, generic expert prompts produced only 60% quality, while tailored, detailed personas achieved 94% quality. This analysis highlights that specificity in prompt engineering is critical for extracting expert-level performance from leading LLMs, offering clear guidance for businesses and developers looking to maximize the value of advanced AI models.