Prompts

Understanding prompts and prompt engineering in PromptKit.

What is a Prompt?

A prompt is the text input sent to an LLM. It tells the model what to do and provides context for generating a response.

Basic Example

User: What's the capital of France?

LLM Response: The capital of France is Paris.

Structured Prompt

System: You are a helpful assistant. Be concise.

User: What's the capital of France?

LLM Response: Paris.

Prompt Components

Messages

Prompts consist of messages with different roles:

Example in PromptKit:

messages := []types.Message{
    {Role: "system", Content: "You are a helpful assistant"},
    {Role: "user", Content: "Hello"},
    {Role: "assistant", Content: "Hi! How can I help?"},
    {Role: "user", Content: "What's 2+2?"},
}

System Prompts

System prompts set the AI’s behavior:

Good system prompt:

You are a customer support agent for TechCorp.

Guidelines:
- Be professional and empathetic
- Keep responses under 100 words
- Reference documentation when possible
- Escalate complex issues to human agents

Available resources:
- Help docs: https://help.techcorp.com
- Status page: https://status.techcorp.com

Poor system prompt:

Be helpful.

Prompt Engineering Techniques

1. Clear Instructions

Bad:

Write something about dogs.

Good:

Write a 3-sentence summary about Golden Retrievers.
Include: origin, temperament, and typical uses.

2. Few-Shot Examples

Provide examples to guide the model:

Convert user questions to support ticket categories.

Examples:
Q: "I can't log in" → Category: Authentication
Q: "My credit card was declined" → Category: Billing
Q: "The app crashed" → Category: Technical

Q: "I forgot my password" → Category: ?

3. Chain-of-Thought

Ask the model to explain its reasoning:

Solve this math problem step-by-step:
If Alice has 3 apples and Bob gives her 5 more, how many does Alice have?

Let's solve this step by step:
1. Alice starts with: 3 apples
2. Bob gives her: 5 apples
3. Total: 3 + 5 = 8 apples

Answer: 8 apples

4. Role-Based

Assign a specific role:

You are an experienced software architect reviewing code.
Focus on:
- Design patterns
- Scalability
- Maintainability

Review this code:
[code here]

Prompts in PromptKit

Runtime

Runtime uses prompts with templates:

templates := template.NewRegistry()
templates.RegisterTemplate("support", &template.PromptTemplate{
    SystemPrompt: "You are a support agent. Be helpful.",
    Variables: map[string]string{
        "company": "TechCorp",
    },
})

pipe := pipeline.NewPipeline(
    middleware.TemplateMiddleware(templates, nil),
    middleware.ProviderMiddleware(provider, nil, nil, nil),
)

result, _ := pipe.Execute(ctx, "user", "Help me")

SDK

SDK simplifies prompt management:

conv := sdk.NewConversation(provider, &sdk.ConversationConfig{
    SystemPrompt: "You are a helpful assistant",
    Model:        "gpt-4o-mini",
})

response, _ := conv.Send(ctx, "Hello")

PackC

PackC packages prompts for distribution:

# support.prompt
system: |
  You are a  for .
  Be professional and concise.

user: |

Pack and use:

packc pack prompts/ -o support.pack
pack, _ := packc.LoadPack("support.pack")
template := pack.Templates["support"]

PromptArena

PromptArena tests prompts:

tests:
  - name: Support Query
    prompt: "How do I reset my password?"
    assertions:
      - type: contains
        value: "password reset"
      - type: max_length
        value: 200

Best Practices

Do’s

✅ Be specific - Clear instructions get better results
✅ Provide context - Give the model relevant information
✅ Use examples - Show what you want
✅ Set constraints - Specify format, length, tone
✅ Test variations - Try different phrasings
✅ Version prompts - Track changes over time

Don’ts

❌ Don’t be vague - “Be helpful” isn’t enough
❌ Don’t assume knowledge - Provide necessary context
❌ Don’t skip system prompts - They guide behavior
❌ Don’t ignore length - Longer ≠ better
❌ Don’t forget to test - Use PromptArena

Common Patterns

Task-Oriented

Task: Extract customer email from support ticket

Input: "Hi, my email is john@example.com and I need help"
Output: john@example.com

Input: "Please contact me at support@company.com"
Output:

Conversational

You are a friendly chatbot. Maintain context across messages.

Be:
- Conversational and warm
- Helpful and informative
- Concise (under 50 words per response)

Analytical

Analyze the following text and provide:
1. Main topic
2. Sentiment (positive/negative/neutral)
3. Key entities mentioned
4. Confidence score (0-1)

Text: [input]

Creative

Write a creative product description for:

Product: 
Features: 
Target audience: 

Style: Engaging and persuasive
Length: 50-100 words

Prompt Management

Development

Testing

Production

Troubleshooting

Problem: Inconsistent Responses

Solution: Add more specific instructions and examples

Problem: Wrong Format

Solution: Specify exact format in prompt

Before:

List the items.

After:

List the items in JSON format:
{"items": ["item1", "item2"]}

Problem: Ignoring Instructions

Solution: Emphasize important instructions

IMPORTANT: Always include sources.
NEVER make up information.

[rest of prompt]

Problem: Too Verbose

Solution: Set length constraints

Answer in exactly 2 sentences. Be concise.

Summary

Prompts are the foundation of LLM applications. Good prompts: