Prompt engineering is the process of structuring text that can be interpreted and understood by a generative AI tool like ChatGPT, Google Gemini, or Microsoft Copilot. A prompt is natural language text describing the task that an AI tool should perform.

There are many different prompt frameworks. For example, here is a Medium article that lists some with examples of prompts based on the frameworks.

For today's workshop, let's practice with this one: PREP and EDIT

A Prompt Engineer Framework from The AI Classroom: PREP the machine and EDIT the output. PREP and EDIT are all caps reflecting letters that stand for steps.

PREP helps to create the input.

Prompt - Introduce the question or the request with a prompt
Role - Give the AI tool a role or voice.
Explicit - Be explicit in your instructions.
Parameters - Set the parameters of the answer.

NOTE: When you add or upload information, data, or reports to AI tools, do not include any student PII or personally identifiable information (name, date of birth, etc.).

EDIT helps to review the output.

Evaluate - Evaluate your AI output content for language, facts, and structure.
Determine - Determine accuracy and corroborate with sources.
Identify - Identify biases, misinformation, and hallucinations in output.
Transform - Transform content to reflect adjustments and new findings.

(Note: Dan Fitzpatrick has expanded PREP to PREPARE - read about it in this blog post.)

If you are in need of inspiration, a good site to review is the AI for Education / Prompt Library.