Summary: In the pursuit of customized chatbots or Large Language Models (LLMs) like ChatGPT, companies face a choice: build an LLM from scratch, fine-tune an existing one with their own data, or employ a prompt architecture approach. For most companies, building from scratch is impractical. Prompt architecture, a cost-effective strategy that leverages existing LLMs with well-crafted prompts, can maximize value. Fine-tuning, though an option, is often more expensive due to data preparation. The goal is to automate tasks or answer queries accurately, swiftly, and securely, making prompt architecture an efficient path.