• Prompting principles
• Prompt development lifecycle
• Capabilities of prompting

Principle 1 - write clear and specific instructions

• Use delimiters to quote the task and avoid prompt injection to ensure to execute content as a whole, i.e. '', "", ``, <>
• Ask for structured output formats to respond, i.e. JSON, HTML
• Check if the conditions are satisfied
• Few-shot prompting

Principle 2 - give the model time to 'think'

• Specify steps to complete a task
• Instruct model to think before conclude and complete a task

• Idea/ Problem
• Implementation
• Experimental results
• Error analysis

Summarizing

• Summarize a task content based on prompt
• Can be single/ multiple tasks
• For multiple tasks
  • Define a List of all required task contents
  • Define for-loop of List
  • Print( i, response, "\n")

Extracting

• Extracting is part of natural language processing (NLP)
• Can be included in the process of summarizing and inferring

Inferring

• Help provide basic understanding of a task content
• Classify sentiment of a task content (Yes/ No)
• Identify specific sentiments of a task content (What kinds of sentiments)
• Extract keywords as an understanding of a task content
• Can be single/ multiple tasks

Transforming

• Identify language
• Translate from language A to language B
• Tranform to formal and informal tone
• Tranform from format A to format B, i.e. HTML, JSON
• Transform from text A to text B, i.e. re-writing, shortening
• Check gramma and spelling
• Can be single/ multiple tasks

Expanding

• Create a response including all the other functions, i.e. extract and summarize the task content for creating a response

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