The four foundational layers of conversational assistants are world knowledge, company-specific knowledge bases, dialog managers with goals and actions, and saved customer conversation context, which work together to provide a more effective and human-like experience for users. LLMs can fill the gap in general world knowledge but need to be filtered through the company's context to prevent misinformation. The combination of these layers enables assistants to capture user goals and context, providing a better interaction that is dynamic and satisfying, rather than rigid or dead-end. However, building one's own LLM may not be realistic for most companies due to the large amount of data required and the complexity of training it, making pre-existing LLM technology a viable option.