Prompt Engineering Masterclass: Beyond "Write a Blog Post"

Prompt Engineering is not just "guessing words". It is a systematic way to program the latent space of a Large Language Model (LLM).

1. Zero-Shot vs Few-Shot Prompting

Zero-Shot: Asking the model to do something without examples.

"Translate this to Spanish: Hello"

Few-Shot: Providing examples to guide the pattern.

"Translate to Spanish. English: Good morning -> Spanish: Buenos días English: How are you? -> Spanish: ¿Cómo estás? English: Hello -> Spanish:"

Few-shot almost always outperforms Zero-shot for complex tasks.

2. Chain-of-Thought (CoT)

LLMs struggle with math and logic. CoT forces the model to "think out loud".

Standard Prompt:

"Roger has 5 tennis balls. He buys 2 more cans of tennis balls. Each can has 3 balls. How many does he have?"

CoT Prompt:

"Roger has 5 tennis balls. He buys 2 more cans of tennis balls. Each can has 3 balls. How many does he have? Let's think step by step."

Model Output:

"Roger started with 5 balls. 2 cans * 3 balls/can = 6 balls. 5 + 6 = 11. The answer is 11."

3. ReAct (Reason + Act)

Used for Agents. It combines reasoning with taking actions.

1. Thought: I need to find the weather in Delhi.
2. Action: Search(Weather in Delhi)
3. Observation: 32°C, Sunny.
4. Thought: I should tell the user.
5. Answer: It is 32°C in Delhi.

Conclusion

Prompt Engineering is the new coding. Master it to bridge the gap between human intent and machine execution.