The article explores the significance of llms.txt, a standard that enhances web content accessibility for large language models (LLMs), questioning whether it represents genuine value or mere AI hype. Through examples from companies like Vercel, Google, and Anthropic, the text highlights the real benefits of llms.txt in improving AI retrieval, such as token and time savings, and demonstrates its adoption by major LLM providers. It argues that traditional SEO practices are inadequate for LLM optimization, emphasizing the importance of simplified text files for efficient AI processing. The article also introduces llms-full.txt, a more frequently accessed file that facilitates faster ingestion by LLMs, and underscores the necessity for businesses to adapt to AI-first workflows to remain competitive. Looking ahead, it anticipates evolving standards in AI optimization, with efforts like the Model Context Protocol (MCP) aiming to enable LLMs to interact directly with products.