You have an Azure subscription. The subscription contains an Azure OpenAI resource that hosts a GPT-3.5 Turbo model named Model1. You configure Model1 to use the following system message: "You are…

Few-shot learning involves providing several examples of input-output pairs in the prompt to teach the model a new task or pattern, which is not what a single system message achieves.

Affordance refers to the perceived properties of an object suggesting how it can be used, a concept from design, not a prompt engineering technique.

Chain of thought prompting guides the model to show its reasoning steps before the final answer, usually by including explicit 'let's think step by step' instructions, which is not present here.

Priming is a prompt engineering technique where a system message or initial instructions are used to establish the large language model's persona, role, or the desired style and constraints for its responses. The instruction 'You are an AI assistant that helps people solve mathematical puzzles. Explain your answers as if the request is by a 4-year-old' directly primes the model's behavior and output format.