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AI Prompt Engineering: Designing Precise Requests Starting with Templates

Learn the core principles of writing prompts to get the desired results from AI. Increase the accuracy of your requests through template-based structuring, and master a repeatable prompt design process through step-by-step verification and Git storage. Compare good and bad examples directly to develop request-writing skills that can be applied immediately in real-world work.

1 learners are taking this course

Level Beginner

Course period Unlimited

Git
Git
Atomic Design
Atomic Design
agents
agents
prompt engineering
prompt engineering
Fine-Tuning
Fine-Tuning
Git
Git
Atomic Design
Atomic Design
agents
agents
prompt engineering
prompt engineering
Fine-Tuning
Fine-Tuning

What you will gain after the course

  • Clear and Reproducible AI Prompt Design Using Template Structures

  • Prompt Iterative Improvement Process Through Step-by-Step Validation and Git Saving

  • Practical criteria for distinguishing good requests from bad requests

Course Introduction

I’m sure everyone has experienced asking AI for something and receiving an irrelevant answer. Usually, we think, “This AI must not be very good. Should I try something else?”

However, the cause usually lies elsewhere. The AI knows nothing about my situation. It doesn’t know what computer I’m using, what I’m currently creating, or how much I already know. So the parts I haven’t told it, the AI decides on its own. There’s not a high chance that those choices will align with my thinking.

This lecture covers how to eliminate those blanks. You will organize the context into four categories, learn three ways to narrow the scope of your request, and practice breaking a large goal down into steps. It also covers how to revise and resubmit your request when the result differs from your expectations, rather than starting over from scratch. Few lectures cover this part, but in practice, it is where the most time is spent.

At the end of the course, you’ll take away a six-part request template. You’ll continue using this template from Lesson 6 onward. Don’t write it from scratch each time—save it and just change the content as needed.

Let me clarify one thing in advance: this course is not about writing lengthy prompts. It’s about filling in the missing elements. Once you get used to it, your prompts will actually become shorter.


It is especially helpful for those who:

- Those who often receive answers from AI that differ from what they wanted when asking for help

- Those who open a new chat and ask again from the beginning when they’re not satisfied with the answer

- Those who have asked AI to create everything at once and ended up with code they couldn’t handle

- People who rethink the wording from scratch every time they make a request

- Those who feel uncomfortable when AI keeps creating things they didn’t ask for.

Recommended for
these people

Who is this course right for?

  • Practitioners who use AI tools for work but struggle because they cannot achieve the desired results

  • An AI beginner who wants to learn prompt writing systematically

  • A leader who needs to guide team members on how to make effective AI requests

Need to know before starting?

  • Basic experience using AI chatbot tools such as ChatGPT and Claude

  • Ability to create documents using a text editor

  • Experience asking AI to help with your work or learning goals

Hello
This is jjangkbg7719

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Hello, I'm Frank.

I am an infrastructure engineer who has been wrestling with servers for over 20 years. Starting with Linux server operations, I am now in charge of the cloud infrastructure for a large-scale payment service. My daily life involves migrating from data centers to AWS, managing hundreds of instances, and tracing the causes of failures in the early hours of the morning.

The reason I created this course is simple.

I often received questions like these from those around me: "I managed to connect to the server, but I don't know what to do next." "There are so many instance types; which one should I choose?" These are the exact same points where I got stuck at first. However, when I looked for resources, I found that most of them were written for people who already knew what they were doing.

So I decided to create the course I wish I had when I first started learning.

My lectures are based on three principles.

First, I help you understand rather than memorize. Instead of just listing commands, I explain why we use them in the first place.

Second, I boldly omit unnecessary content. I do not increase the volume by including information that is useless to beginners right now.

Third, I also talk about what doesn't work. Instead of just listing the pros, I clearly point out cases where it might not be a good fit. For someone who has to make decisions in the field, that is more important.

If you feel a sense of "Ah, I should start from here" after listening to the lecture, then my goal has been achieved.

Please feel free to leave any questions you may have at any time.

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18 lectures ∙ (23min)

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