How to approach prompt engineering (experimentation)

Approaching prompt engineering involves a systematic and iterative process of experimentation to achieve the desired output from an LLM. The key is to refine and adapt your prompt based on the model’s responses, continually improving its effectiveness. Here are the steps to approach prompt engineering through experimentation:

1. Define the objective: Clearly outline the goal of the interaction with the LLM. Determine the specific information, format, and context required for the desired output.
2. Craft the initial prompt: Using the components of a prompt, such as context, instruction, role prompting, examples, and output pattern, create a clear and concise prompt that communicates your expectations and requirements to the LLM.
3. Adjust LLM parameters: Set the initial values for LLM parameters, such as temperature, top-k, and max tokens, based on your output preferences, such as creativity, determinism, and response...