When interacting with transformer-based models like large language models (LLMs) and vision-language models (VLMs), the structure of the input shapes the model’s output. But prompts are often more than a simple user query. In practice, they optimize the response by dynamically assembling data from various sources such as system instructions, context data, and user input.