Incorporating the Roles aspect in prompts involves explicitly defining and assigning roles to participants in the conversation. As a regular user, you can include this by specifying the role of each participant (e.g., user, assistant) within the prompt text. This helps create a structured conversational context and clarifies the expected behavior or responses from each role. By incorporating the Roles in prompts, users can shape the interaction dynamics and guide the LLM’s behavior to ensure more coherent and contextually appropriate responses.
The capabilities of AI systems are constantly evolving, and new roles can emerge as technology advances. The specific roles and functionalities may vary depending on the AI system and its design. Most systems can adapt and provide responses in different roles. Here are a few examples:
These are just a few examples, often capabilities can extend beyond these roles depending on the user’s needs and the context of the conversation. The selection of a Role for the AI will be based on your own personal requirements. In this context it is useful to construct a pre-prompt intended to ensure the AI’s understanding and ability to comply. The Prompt will often contain either a specific job function, e.g. {SEO Specialist} and level of expertise e.g. {Expert}, {Global Expert}, {Professor of something}.
The syntax is Role:{Storyteller}Prompt: {the detailed request}. The best way to understand Roles is via examples. We provide some best practice tips and Role Prompt examples in further lessons in this module.
Note: The caveat here is that the usefulness may vary depending on the need for real world data to corroborate.