Tutorial Prompt Engineering Google untuk Bisnis & Kreator Indonesia l Prompt Engineering 2025

Summary

This tutorial presents essential AI prompting techniques based on a Google course, covering a 5-step framework (Task, Context, References, Evaluate, Authorize) for crafting effective prompts. Key techniques like prompt chaining, chain-of-thought, and three-of-thought help break down tasks, ensuring detailed and creative outputs. The tutorial also explores multimodal prompting, which incorporates text, images, and more. It highlights AI challenges like hallucination and bias, stressing the importance of human verification. The video aims to help viewers improve their prompting skills, making them more efficient in communicating with AI and achieving high-quality results.

Takeaways

• 😀 Prompting is a way of communicating with AI to get the desired output, and it involves a five-step framework: Task, Context, References, Evaluate, and Authorize.
• 😀 To get better results from AI, provide clear and specific context, such as details about your needs (e.g., age, preferences, budget). The more context you provide, the more accurate the AI's response will be.
• 😀 Including references in your prompts can help guide the AI to produce more relevant and focused outputs. For example, mentioning a similar gift from the past helps the AI understand your preferences.
• 😀 Evaluating the results and refining your prompts is important. Continuously improve your prompts based on the initial AI responses to get closer to your ideal output.
• 😀 The five-step prompting process can be improved by breaking it into shorter, simpler sentences, using similar tasks for more creative engagement, and setting boundaries or limitations on the output.
• 😀 In multimodal prompting, AI can handle different types of input like text, images, and even videos, which can be used to generate creative outputs like social media posts or product promotions.
• 😀 AI can sometimes 'hallucinate' or provide wrong, inconsistent, or biased information. It's important to fact-check and verify AI responses before accepting them.
• 😀 Prompts can be broken into manageable steps using techniques like 'prompt chaining,' where you build on each part of the task progressively to guide the AI toward the final output.
• 😀 'Chain of thought' prompting helps make AI's reasoning transparent. By asking AI to explain its thought process step-by-step, you can identify and correct any mistakes it makes.
• 😀 'Three of thought' prompting is a method where you generate multiple ideas or options at once, allowing you to choose the best path to develop further, increasing creativity and efficiency.
• 😀 Continuous learning and improvement are essential. Prompting is an iterative process, and you can keep refining your approach until the AI's output matches your expectations.

Q & A

What is prompting, and why is it important for interacting with AI?

Prompting is the language we use to communicate with AI to get the desired output. It's essential because it allows us to guide AI in producing results that meet our needs, whether that's for generating content, providing ideas, or solving problems.

What are the five key steps in Google's prompting framework?

Google's five-step framework for prompting includes: Task (defining the goal), Context (providing relevant background information), References (giving examples to guide AI), Evaluate (assessing the output), and Authorize (making necessary adjustments to refine results).

How can adding context to a prompt improve the AI's output?

Adding context to a prompt allows the AI to better understand the specifics of the task, leading to more detailed and relevant results. For example, providing details like the recipient's age, interests, and budget when asking for gift ideas will help AI generate more precise suggestions.

What role do references play in the prompting process?

References help guide the AI by providing examples from previous experiences. By giving AI reference points, such as past successful projects or similar tasks, the AI can tailor its output more closely to your needs, avoiding irrelevant or off-target results.

How can you evaluate the results from AI and improve them?

To evaluate AI's output, you should check if it meets your standards and expectations. If the result falls short, you can improve it by refining the prompt, adding more context, or specifying more clearly what is missing in the results.

What are four ways to improve a prompt, according to Google?

The four ways to improve a prompt include: 1) Reviewing the prompting framework to provide better context and references, 2) Breaking the prompt into shorter sentences for clarity, 3) Making the task more engaging or emotional, and 4) Setting boundaries or limitations to narrow the scope.

How can multimodal prompting enhance AI interactions?

Multimodal prompting allows you to use various types of inputs (like images, audio, or text) to interact with AI. This broadens the potential for AI to generate richer, more creative outputs, such as designing promotional content or generating recipes based on ingredients from photos.

What is AI hallucination, and how can it affect the results?

AI hallucination refers to instances where AI generates incorrect or illogical results, often due to the limitations of its training data or flawed processing. This is why human verification is crucial to ensure the accuracy and reliability of the output.

What is the importance of using AI as a creative partner or expert?

Using AI as a creative partner involves treating it as a tool to assist in brainstorming, generating ideas, and refining concepts. It can help augment human creativity, provide new perspectives, and speed up the process of developing content, designs, or strategies.

What is prompt chaining, and how does it work?

Prompt chaining involves breaking down a task into sequential steps, allowing you to guide AI through the process step-by-step. Each block or 'prompt' builds on the previous one, making the final result more coherent and aligned with your goals.

How does the 'chain of thought' prompting technique work?

Chain of thought prompting asks AI to explain its reasoning process step-by-step. This approach allows you to see how AI arrives at an answer, making it easier to identify any errors or adjustments needed, ultimately leading to more accurate and transparent results.

What is the purpose of 'three of thought' prompting, and how does it differ from other techniques?

Three of thought prompting provides multiple ideas or approaches to a problem, offering more creative flexibility. Instead of focusing on just one solution, you explore several options and choose the best one to develop further, fostering creativity and efficiency.