Google's 9 Hour AI Prompt Engineering Course In 20 Minutes

Key Concepts

Prompting, Task, Context, References, Evaluate, Iterate, Persona, Output Format, Multimodality, Hallucinations, Biases, Human-in-the-Loop, Prompt Chaining, Chain of Thought, Tree of Thought, Meta Prompting, AI Agents, Agent Sim, Agent X.

Module 1: Prompting Essentials - Fundamentals

Defining Prompting

Prompting is providing specific instructions to a generative AI tool to get new information or achieve a desired outcome (text, images, video, sound, code).

Five-Step Prompt Design Framework: "Tiny Crabs Ride Enormous Iguanas"

The course introduces a five-step framework for prompt design:

1. Task: Define what you want the AI to do. Example: "Suggest an anime gift for my friend's birthday." Adding a Persona (e.g., "Act as an anime expert") and specifying the Output Format (e.g., "Organize that data into a table") can improve results.
2. Context: Provide as much relevant background information as possible. Example: "Your friend is turning 29 years old. Her favorite animes are Shangula Frontier, Solo Leveling, and Naruto."
3. References: Include examples to clarify your request. This is especially useful when describing what you want is difficult.
4. Evaluate: Assess whether the output meets your expectations.
5. Iterate: Refine the prompt based on the evaluation to improve the results. "Always Be Iterating" (ABI).

Iteration Methods: "Rahen Saves Tragic Idiots"

Beyond the core framework, four iteration methods can further refine prompts:

1. Revisit the Prompting Framework: Add more references, context, or a Persona.
2. Separate into Shorter Sentences: Break down complex prompts into simpler sentences for better AI comprehension.
3. Switch to an Analogous Task: Reframe the task using a related concept. Example: Instead of asking for a "marketing plan," ask for "a story about how this product fits into the lives of our target customer demographics."
4. Introduce Constraints: Narrow the focus by adding limitations. Example: For a road trip playlist, specify a region, tempo, or theme (e.g., heartbreak).

Multimodality Prompting

AI models like Gemini can interact with various modalities (pictures, audio, video, code) as input and output. The core prompting framework remains the same, but careful specification of input/output types and context is crucial. Example: "Write a social media post featuring this image" (attaching a nail art collection).

Addressing Hallucinations and Biases

Two major issues with AI tools are:

• Hallucinations: AI generates inconsistent, incorrect, or nonsensical outputs. Example: Incorrectly stating the number of "R"s in "Strawberry."
• Biases: AI trained on human content can reflect gender and racial biases.

The course recommends a Human-in-the-Loop approach: always check and verify AI outputs to ensure accuracy and responsible use.

Module 2: Design Prompts for Everyday Work Tasks

This module provides examples of applying the prompting framework to common tasks, particularly content generation.

Email Writing Example

Prompt: "I'm a gym manager and we have a new gym schedule. Write an email informing our staff the new schedule. Highlight the fact that the MWF Monday Wednesday Friday Cardio Blast class changed from 7:00 a.m. to 6:00 a.m. Make the email professional and friendly and short so that the reader can skim it quickly. Here's the new schedule," and you can actually attach the link that contains the new schedule.

Improving Tone and Word Choice

Use specific phrases to define the desired tone (e.g., "write a summary in a friendly, easy-to-understand tone, like explaining to a curious friend"). Provide references (past emails, articles) for the AI to match.

Module 3: AI for Data Analysis and Presentations

This module focuses on using AI for data analysis (spreadsheets) and presentation creation.

Data Analysis Example

Prompt: "Attached is a Google sheet of store data. How can I create a new column in sheets that calculates the average sales per customer for each store?" Then, "give me insights into the relationship between daily customer count, items available, and sales based on the given data."

Caution: Be careful about inputting sensitive or private data into AI models.

Module 4: Use AI as a Creative or Expert Partner

This module covers advanced prompting techniques and AI agents.

Prompt Chaining

Guide AI through a series of interconnected prompts, adding complexity at each step. Example: Generating summaries of a novel manuscript, then creating a tagline based on those summaries, and finally developing a six-week promotional plan.

Chain of Thought Prompting

Ask the AI to explain its reasoning step-by-step. Add "explain your thought process" to the prompt. This helps understand the AI's logic and improve its decision-making.

Tree of Thought Prompting

Explore multiple reasoning paths simultaneously, like branches of a tree. Useful for complex problems like developing novel plots or drafting lengthy documents. Example: Brainstorming different image options for an online course landing page.

Meta Prompting

Use AI to help you come up with a prompt if you're stuck.

AI Agents

An AI agent is an expert designed to help with tasks and answer questions.

• Agent Sim: A simulation agent that can simulate scenarios like interviews or role-playing. Focus on Persona and Context. Example: A career development training simulator for interns.
• Agent X: An agent for expert feedback on any topic. Example: A potential client (VP of advertising) providing feedback on a pitch.

Guidelines for Creating AI Agents

1. Assign a Persona (e.g., "act like a successful personal fitness trainer and talented nutritionist").
2. Provide context and detail about the scenario (e.g., "I'm looking to improve my overall fitness and adopt a healthier lifestyle").
3. Specify the type of conversations or interactions (e.g., "ask me about my workout routines and meal planning and give me feedback").
4. Provide a stop phrase (e.g., "no pain no gain").
5. Ask the agent to provide feedback or areas of improvement at the end of the conversation.

Synthesis/Conclusion

The Google Prompt Engineering Course emphasizes a structured approach to prompting, using frameworks like "Tiny Crabs Ride Enormous Iguanas" and "Rahen Saves Tragic Idiots" to guide prompt design and iteration. It highlights the importance of context, references, and a human-in-the-loop approach to mitigate hallucinations and biases. The course also introduces advanced techniques like prompt chaining, chain of thought, tree of thought, and AI agents, showcasing the potential of AI as a creative and expert partner. The key takeaway is that effective prompting is an iterative process that requires careful planning, evaluation, and refinement to achieve desired outcomes.