Cliff Notes: Google's Prompt Engineering Course

Objective

Summarize and extract core concepts from Google’s Prompt Engineering course, presenting the key frameworks, techniques, and practical advice for effective AI prompting.

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Course Structure

1. Module 1: Start Writing Prompts Like a Pro

   • Introduces key frameworks for prompt crafting.

2. Module 2: Design Prompts for Everyday Work Tasks

   • Covers prompts for emails, brainstorming, tables, summarization, etc.

3. Module 3: Use AI for Data Analysis and Presentations

   • Focuses on using AI for analyzing data and building presentations.

4. Module 4: Use AI as a Creative or Expert Partner

   • Advanced prompting techniques and creating AI agents.

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Module 1: Prompting Fundamentals

What is Prompting?

• Giving specific instructions to generative tools (AI) to receive new information or achieve desired outcomes.
• Applies to text, images, video, sound, code, etc.

Five-Step Framework (Mnemonic: "Tiny Crabs Ride Enormous Iguanas")

1. Task: What do you want the AI to do?
   • Enhance with Persona (the AI’s role) and Format (desired output structure).
2. Context: The more context provided, the better the output.
3. References: Give concrete examples to clarify expectations.
4. Evaluate: Assess if the output meets your needs.
5. Iterate: Refine the prompt based on evaluation—prompting is a cyclical process.

Four Methods for Refining Prompts (“Rahen Saves Tragic Idiots”)

1. Revisit the framework—add more detail or examples.
2. Separate prompts into shorter, simpler sentences.
3. Try different phrasing or switch to an analogous task.
4. Introduce constraints to focus the AI.

Multimodal Prompting

• AI models can take various inputs (text, images, audio, video, code).
• Specify input/output types and required context to match the modality.

Responsible AI Use

• Be aware of hallucinations (incorrect/out-of-context outputs) and biases.
• Keep a “human in the loop” to check outputs for accuracy and fairness.
• Checklist for Responsible AI Use:
  • Always review outputs
  • Check for bias and hallucination
  • Verify sensitive or important information

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Module 2: Everyday Task Prompts

• Examples: Writing emails, summaries, brainstorming, creating tables.
• Improve prompts with:
  • Specific tasks (“write an email to staff about new gym schedule…”)
  • Tone and voice instructions (“write in a friendly, easy-to-understand tone”)
  • Providing references for style

Tip: Build and store your own prompt library for recurring use cases.

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Module 3: Data Analysis & Presentations

• Example Use Cases:
  • Instructing AI to manipulate data in a spreadsheet (e.g., calculate averages)
  • Asking AI for trend analysis and insights
  • Prompting for the creation of presentation slides

Caution: Do not input sensitive or private data into AI tools.

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Module 4: AI as Creative or Expert Partner

Advanced Prompting Techniques

1. Prompt Chaining

• Series of interconnected prompts to add complexity/depth to tasks.
• Ex: Generate summary → create tagline → develop promo plan.

2. Chain of Thought Prompting

• Ask AI to show step-by-step reasoning process.
• Useful for complex or multi-step problems.

3. Tree of Thought Prompting

• Explore multiple reasoning paths in parallel (like branches on a tree).
• Helpful for brainstorming, abstract, or creative tasks.

4. Meta Prompting

• Use AI to help generate or refine prompts if you’re stuck.

Creating AI Agents

What is an AI Agent?

• An AI persona designed to help with specific tasks and answer questions.

Two Agent Types:

1. Simulation Agent (Agent Sim):

   • Simulates scenarios for practice (e.g., mock interviews).
   • Focus on Persona, Context, Task, and a stop phrase (“jazz hands” to end simulation).

2. Expert Feedback Agent (Agent X):

   • Provides feedback/consultation as an expert.
   • Specify Persona, Context, Task, References, and stop phrase.

Steps to Build an AI Agent

1. Assign Persona (“act like a fitness trainer…”)
2. Give detailed Context (“I want to improve lifestyle…”)
3. Specify desired Conversation/Interaction
4. Provide a Stop Phrase (“no pain, no gain”)
5. End with Feedback/Summary of advice or improvement areas

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Key Reminders & Best Practices

• Always provide as much task clarity and context as possible.
• Use examples/references for clearer results.
• Iteratively refine your prompt for improved outputs.
• Stay aware of AI limitations; check for hallucinations/biases.
• Develop and use a personal prompt library for efficiency.

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Assessment (Retain What You Learned)

• Review and reflect on:
  1. The five-step prompting framework
  2. Four prompt iteration methods
  3. Difference between prompt chaining, chain of thought, and tree of thought
  4. Key elements to use when creating an AI agent
  5. Considerations for responsible AI use

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Tip: Say or write your answers to these questions for memory retention!