Google Prompt Engineering Course Overview

This course provides an intensive guide to mastering prompt engineering through four comprehensive modules, each focusing on different aspects of prompting and utilizing AI tools effectively.

Course Structure

1. Module 1: Start Writing Prompts Like a Pro
   • Introduction to crafting prompts using helpful frameworks.
2. Module 2: Design Prompts for Everyday Work Tasks
   • Focuses on prompts for emailing, brainstorming, building tables, and document summarization.
3. Module 3: Using AI for Data Analysis and Presentations
   • Emphasizes AI applications in data analysis and creating presentations.
4. Module 4: Use AI as a Creative or Expert Partner
   • Explores advanced prompting techniques and creating AI agents.

Module 1: Prompting Fundamentals

• Definition of Prompting: Process of providing specific instructions to a gen tool to receive desired outcomes.
• Five-Step Framework (Task, Context, References, Evaluate, Iterate):
  • Task: Define what you want the AI to do.
  • Context: More context improves output.
  • References: Providing examples can clarify your needs.
  • Evaluate: Assess the output against your expectations.
  • Iterate: Refine the prompt based on feedback.
• Mnemonics: "Tiny Crabs Ride Enormous Iguanas" for remembering the framework.

Iteration Methods

1. Revisit the framework to add more context or examples.
2. Simplify prompts into shorter sentences.
3. Use different phrasing or analogous tasks.
4. Introduce constraints to narrow focus.

• Mnemonic: "Rahen Saves Tragic Idiots" for iteration methods.

Multimodal Prompting

• Use various modalities (text, audio, video) to provide input and request output.
• Important to specify input/output types and context.

Issues with AI Tools

1. Hallucinations: AI providing incorrect or nonsensical outputs.
2. Biases: AI reflecting human biases.

• Human in the Loop: Always verify AI outputs.

Module 2: Design Prompts for Everyday Work

• Provides use cases and examples for writing effective prompts.
• Encourages building a prompt library for reference.

Examples

• Email writing: Specify details and tone for professional and quick communication.
• Content Creation: Use detailed instructions for tone and style.

Module 3: Data Analysis and Presentations

• Caution on data privacy and inputting sensitive information.
• Examples of prompting for data insights and creating visual presentations.

Module 4: AI as a Creative or Expert Partner

• Advanced Prompting Techniques:
  • Prompt Chaining: Guides AI through interconnected prompts for complexity.
  • Chain of Thought Prompting: AI explains reasoning step-by-step.
  • Tree of Thought Prompting: Explore multiple reasoning paths like branches.
• Meta Prompting: Using AI to help develop prompts when stuck.

Creating AI Agents

1. Agent Simulation (Agent Sim): Simulates scenarios (e.g., interview training).
2. Agent X: Provides expert feedback.

• Guidelines for Creating Agents:
  • Define a Persona.
  • Provide detailed context.
  • Specify interaction types and rules.
  • Set a stop phrase.
  • Request feedback summary at the end.

Conclusion

• Completing this course enhances prompt engineering skills and saves time for practical applications.
• Emphasizes continuous learning and iteration to improve AI interaction.