Prompt Engineering

What Is Prompt Engineering?

Prompt engineering is the difference between an AI demo and a production system. A well-engineered prompt can improve LLM accuracy from 60% to 95% without changing the model or fine-tuning.

Key techniques include: system prompts (setting behavior), few-shot examples (showing the model what you want), chain-of-thought (forcing step-by-step reasoning), output formatting (JSON, structured data), and guardrails (preventing hallucinations and off-topic responses).

For enterprise applications, prompt engineering also involves: version control for prompts, A/B testing prompt variants, monitoring output quality, and building fallback chains when primary prompts fail.