What is the primary goal of an AWS support chatbot response?	To directly answer the user's question while listing relevant AWS hosting options and guiding initial steps.
What types of content should an AWS support chatbot strictly avoid including in its responses?	Mentions of competitor solutions or answers to questions unrelated to cloud services.
Why is listing all "do's and don'ts" within the user message (Option 1) an inefficient method for chatbot implementation?	It is tedious because a comprehensive list would need to address every possible question a user might ask.
What is the recommended method for guiding an LLM's response behavior to meet specific requirements?	Providing a System Prompt.
How does a System Prompt guide an LLM's behavior?	By assigning a specific role or persona to the model (e.g., "You are an AWS cloud support specialist").
In the API call, where is the System Prompt passed to the model?	Via the `system` keyword in the function call (e.g., the `converse` function).
What is the effect of successfully implementing a System Prompt on a chatbot?	It forces the model to adhere to the defined persona and constraints, such as politely refusing non-relevant questions.
What is a key technical requirement when passing a system prompt to the API?	The system prompt must contain at least one character.
What is the purpose of refactoring the chat function in the code?	To make the system prompt reusable and not hard-coded into the function.
Give an example of a System Prompt used to define an AWS chatbot's role.	"You are an AWS cloud support specialist."