Prompt Engineering Best Practices for Production AI Applications

Prompt engineering has matured from an art to a science. These production-tested techniques will help you build reliable AI features.

Core Techniques

1. System Prompts

const systemPrompt = `You are a customer support agent for TechCo.
Rules:
- Only answer questions about TechCo products
- Never reveal pricing without verification
- Escalate complex issues to human agents
- Always be polite and professional`;

2. Few-Shot Learning

const prompt = `Classify the sentiment of customer reviews.

Review: "Great product, fast delivery!"
Sentiment: Positive

Review: "Item arrived damaged, very disappointed."
Sentiment: Negative

Review: "${userReview}"
Sentiment:`;

3. Chain-of-Thought

const prompt = `Solve this step by step:
Question: ${question}

Think through the problem:
1. First, identify what we know
2. Then, determine what we need to find
3. Apply relevant formulas or logic
4. Calculate the final answer

Solution:`;

Production Patterns

• Use structured output (JSON mode)
• Implement retry logic with backoff
• Add input/output validation
• Monitor token usage and costs
• A/B test prompt variations