Day 1: Prompt Engineering Fundamentals

In this article, I’ll start with the most fundamental concepts of Prompt Engineering – a skill that seems simple but has a huge impact on how we work with AI.

Many people think that “just ask and AI will answer”, but in reality, how you formulate your prompts greatly determines the quality of results you receive. With the same AI tool, different prompts can yield significantly different outcomes.

Below are the main topics I’ll cover in this section.

1. What is Prompt Engineering?

Prompt Engineering can be simply understood as the way we design and articulate commands so that AI understands exactly what we want.

At a deeper level, it’s both an art and a technical skill: how to provide sufficient information, proper context, and the right focus so AI generates appropriate responses.

Essentially, Prompt Engineering is a form of communication with AI, where we need to:

• Ask clear questions
• Provide necessary context

When done well, AI doesn’t just remain a generic chatbot, but can become a powerful tool for:

• Task automation
• Problem solving
• Content creation

2. The Role of Prompts

In AI models, prompts are the starting point of every interaction. They determine:

• How AI will interpret the problem
• Whether responses will be detailed or superficial
• Whether the output matches expectations

Unlike humans, AI doesn’t “understand” through logical reasoning, but operates based on pattern recognition and data synthesis. Therefore, if a prompt is vague or lacks context, the response can easily go off track.

Conversely, a well-designed prompt typically helps AI:

• Answer more accurately
• Misunderstand intentions less
• Maintain proper problem context

3. Common Types of Prompts

When working with AI, several common and effective prompt patterns can be observed:

• Direct Instruction Prompts Clear, straightforward commands, for example: “Write a 200-word summary of this book.”

• Contextual Prompts Adding background information for AI to understand the audience or goal, for example: “Explain this concept to a 10-year-old child.”

• Role-Based Prompts Asking AI to respond from a specific perspective, such as: “Act as a doctor and advise the patient.”

• Chain-of-Thought Prompts Encouraging AI to reason step-by-step rather than giving immediate results.

• Few-Shot and Zero-Shot

  • Few-Shot: Provide a few examples for AI to learn from
  • Zero-Shot: No examples provided, AI infers completely on its own

4. Real-World Applications

Prompt Engineering isn’t just an academic concept, but has many practical applications:

• Content Creation & Advertising Supports writing blogs, social media content, or marketing materials with the desired tone.

• Programming Helps write code, find bugs, or suggest program optimizations.

• Research & Data Analysis Summarizes long reports, filters key points and important information.

• Automation & Customer Support Builds chatbots that respond more naturally to frequently asked questions.

• Education & Learning Explains complex concepts in various ways, suitable for different audiences.

5. Why is Prompt Design Important?

A poorly designed prompt often leads to:

• Vague answers
• Rambling or off-topic content

Conversely, when paying more attention to how you ask questions and provide context, you’ll notice:

• Noticeably improved response accuracy
• Less need to revise or re-ask
• Significantly increased AI work efficiency

In other words, Prompt Engineering helps you better control how AI assists you, rather than just passively accepting results.

Illustrative Example

You can think of prompting like instructing a very skilled chef who isn’t familiar with your taste preferences yet.

If you only say: “Cook something delicious”, the result might be… quite strange.

But if you clearly describe the ingredients, cooking style, and desired flavor, you’re much more likely to receive a dish that truly matches your expectations.