Course Overview

M1: Prompt Engineering for Generative AI

1. What is prompt?

Definition: A prompt is any input you provide to a generative model to produce a desired output, acting as an instruction.

Importance: Writing effective prompts is crucial for guiding AI models to generate relevant and accurate results.

Elements of a well-structured prompt:

• Instructions: Clear guidelines for the task.
• Context: Background information that sets the stage for the output.
• Input Data: Specific information that the model can reference.
• Output Indicators: Criteria for evaluating the output, such as tone and length.

2. Prompt engineering

Definition: Prompt engineering is the process of designing effective prompts to guide generative AI models in producing relevant responses.

Importance: It is crucial for optimizing model efficiency, boosting performance for specific tasks, understanding model constraints, and enhancing model security.

Well-structured iterative process

The process involves several steps:

1. Define the goal: Clearly establish what you want the model to generate.
2. Craft initial prompt: Create a prompt that reflects your goal.
3. Test the prompt: Analyze the response to see if it meets your expectations.
4. Analyze the response: Review the output and identify areas for improvement.
5. Refine the prompt: Modify the prompt based on your analysis.
6. Iterate: Repeat the testing and refining process until satisfied with the response.

• Example: A ship captain needing a precise weather forecast must provide detailed context in the prompt to get accurate results.

Importance of prompt engineering

• Optimizing model efficiency