LLM Prompt Engineering: The Basics

Prompt engineering is the art and science of crafting effective inputs for large language models (LLMs). It’s become a crucial skill for anyone working with AI systems.

What is Prompt Engineering?

Prompt engineering involves designing inputs that guide LLMs to produce desired outputs. It’s about:

Clarity: Making your intent clear
Context: Providing relevant background
Structure: Organizing information logically
Constraints: Setting boundaries and expectations

Key Techniques

1. Be Specific and Clear

❌ Vague: “Write about AI”

✅ Specific: “Write a 500-word introduction to machine learning for beginners, focusing on supervised vs unsupervised learning”

2. Use Examples (Few-Shot Learning)

Classify the sentiment of these reviews:

Review: "This product is amazing!"
Sentiment: Positive

Review: "Terrible quality, wouldn't recommend"
Sentiment: Negative

Review: "It's okay, nothing special"
Sentiment: [YOUR CLASSIFICATION HERE]

3. Break Down Complex Tasks

Instead of asking for everything at once, break complex requests into steps:

First, analyze the problem
Then, propose solutions
Finally, evaluate each solution

4. Set the Context and Role

You are an expert data scientist with 10 years of experience.
A beginner asks you: "What's the difference between precision and recall?"
Explain it in simple terms with examples.

Common Pitfalls

Being too vague - LLMs need clear instructions
Overloading with information - Too much context can confuse
Not iterating - First attempts rarely work perfectly
Ignoring model limitations - Remember what the model can and can’t do

Best Practices

Start simple and add complexity gradually
Test variations of your prompts
Use delimiters to separate different parts
Ask for step-by-step reasoning when needed
Specify the output format you want

Advanced Techniques

Chain of Thought Prompting

Ask the model to think step-by-step:

Let's think through this step by step:
1. First, identify the key components
2. Then, analyze their relationships
3. Finally, draw conclusions

Constitutional AI

Include principles for the AI to follow:

Follow these principles:
- Be helpful and accurate
- Acknowledge uncertainty when unsure
- Provide balanced perspectives
- Cite sources when possible

Conclusion

Prompt engineering is both an art and a science. The key is to experiment, iterate, and learn from what works. As LLMs continue to evolve, so will the techniques for working with them effectively.

Remember: the best prompt is the one that consistently gets you the results you need.

Next up: We’ll explore advanced prompting techniques including role-playing, constraint specification, and multi-turn conversations.