PROMPT
Prompt Course: Clearly Explain the Result You Want the First Time
A 12-chapter practical path for complete beginners: from writing one request correctly to using system prompts to develop an AI assistant that works for you over time
Ask the same question in a different way, and the AI answers can be worlds apart. The difference is not the model; it is whether you clearly explained the context, goal, style, and format. This course teaches no mystical incantations and requires no programming background. It first gives you four techniques you can apply directly, then takes apart two high-quality prompts that are actually in use, line by line, and finally uses system prompts to preserve the assumptions you otherwise have to explain repeatedly.
Learning path
These 12 chapters take you through three steps
The course begins with writing individual requests, moves into structural breakdowns of real prompts, and ends with reusable system prompts for long-term use.
- 01First, write one request correctly
Understand why prompts work; master four techniques—CO-STAR, chain of thought, few-shot examples, and constraint lists—and make AI reliably output tables, JSON, or lists.
- 02Then understand the structure of high-quality prompts
Take apart two long prompts that are actually in use—generating Xiaohongshu infographics and transcribing video—line by line, and see the role played by the persona, task, principles, and format.
- 03Finally, turn experience into an asset
Use a system prompt to define "who the AI is," configure it in Claude, ChatGPT, Gemini, and an API, and directly reuse three mature private prompts.
Course learning path
STAGE ONE
Stage One: Write One Request Correctly
Start with why prompts work, master four techniques you can apply directly, understand how strategies and capability boundaries differ between scenarios, and learn to control output formats.
STAGE TWO
Stage Two: Break Down Two High-Quality Prompts That Are Actually in Use
Apply the methods to real examples: take apart the two long prompts for generating Xiaohongshu infographics and transcribing video line by line, and see what problem is solved by the persona definition, task description, execution principles, and output format.
STAGE THREE
Stage Three: Use System Prompts to Build a Dedicated Assistant
From concept to implementation: understand the difference between system prompts and ordinary prompts, write your own version with five modules, configure it on four platforms, and directly reuse three mature private prompts.
What you will be able to do
After completing the course, you will not need to memorize any template, but you should be able to clarify the context, goal, audience, and format before you begin, and preserve repeatedly explained assumptions in a prompt you can reuse over time.
- Explain why prompts affect answer quality, and rewrite a vague need as an instruction that works on the first attempt.
- Choose the right technique for the task: CO-STAR for structured expression, chain of thought for complex reasoning, and few-shot examples for imitating a style.
- Reliably obtain fixed-format output such as tables, JSON, and lists, and correct format drift quickly.
- Understand the structure of a long prompt, determine why it works, and adapt it into your own version.
- Configure a system prompt in Claude, ChatGPT, Gemini, or an API to build a dedicated assistant that does not need the same context explained repeatedly.
- Recognize the limits of prompt capability and know which problems cannot be solved merely by changing the wording.