Prompt Engineering for Production Applications

Beyond Prompt Hacking

Prompt engineering in production requires systematic approaches, not clever tricks found on Twitter.

The Prompt Development Lifecycle

1. Define Success Criteria

Before writing prompts, define what good looks like:

interface EvaluationCriteria {
accuracy: number;      // % correct responses
relevance: number;     // % on-topic responses
safety: number;        // % responses passing safety checks
latency: number;       // p95 response time
}
const requirements: EvaluationCriteria = {
accuracy: 0.95,
relevance: 0.98,
safety: 1.0,
latency: 2000
};

2. Build an Evaluation Dataset

Collect representative examples:

interface TestCase {
input: string;
expectedOutput: string;
category: string;
difficulty: "easy" | "medium" | "hard";
}
const testCases: TestCase[] = [
{
input: "What is the return policy?",
expectedOutput: "contains:30 days,full refund",
category: "policy",
difficulty: "easy"
},
// ... hundreds more
];

3. Iterate Systematically

Track prompt versions:

Prompt Patterns

Few-Shot with Diverse Examples

You are a customer support assistant.
Example 1 - Product Question:
Customer: "Does this come in blue?"
Response: "Yes! This item is available in blue, red, and black."
Example 2 - Shipping Question:
Customer: "When will my order arrive?"
Response: "Standard shipping takes 5-7 business days..."
Example 3 - Complaint:
Customer: "This product broke after one week!"
Response: "I apologize for the inconvenience..."
Now respond to:
Customer: "{user_input}"

Structured Output

Respond in the following JSON format:
{
"intent": "question|complaint|feedback|other",
"sentiment": "positive|neutral|negative",
"response": "your response here",
"escalate": true|false
}

Testing in Production

A/B Test Prompts

async function getResponse(input: string) {
const variant = getUserVariant();
const prompt = variant === "A" ? promptV1 : promptV2;
const response = await llm.complete(prompt + input);
trackMetric("llm_response", {
variant,
latency: response.latency,
tokenCount: response.tokens
});
return response;
}

Conclusion

Treat prompts as code: version them, test them, and deploy them systematically. The era of copy-pasting prompts from blog posts is over.