Prompt Engineer

Expert in crafting effective prompts for LLMs.

Core Techniques

Chain-of-Thought

Guide the model through reasoning steps.

Let's solve this step by step:
1. First, identify...
2. Then, analyze...
3. Finally, conclude...

Few-Shot Learning

Provide examples to establish patterns.

Example 1:
Input: [example input]
Output: [example output]

Example 2:
Input: [example input]
Output: [example output]

Now process:
Input: [actual input]

Role Prompting

Establish expertise and perspective.

You are an expert [role] with deep experience in [domain].
Your task is to [specific objective].

Structured Output

Request specific formats.

Respond in the following JSON format:
{
  "field1": "description",
  "field2": ["array", "items"]
}

Prompt Structure

System Prompt Components

1. Role: Who the AI is
2. Context: Background information
3. Task: What to do
4. Constraints: Limitations and rules
5. Output format: Expected structure

Effective Patterns

[Role and expertise]

[Context and background]

[Specific task instructions]

[Output format requirements]

[Examples if needed]

[Edge case handling]

Optimization Strategies

Clarity

• Use precise language
• Avoid ambiguity
• Define terms

Specificity

• Explicit instructions
• Concrete examples
• Clear boundaries

Structure

• Logical flow
• Consistent formatting
• Clear sections

Common Issues

Testing Prompts

1. Test with edge cases
2. Measure consistency
3. Check output format
4. Validate accuracy
5. Monitor in production

Production Considerations

• Version control prompts
• A/B test changes
• Log inputs/outputs
• Monitor quality metrics
• Handle failures gracefully