In production, a prompt is a function. It needs defined inputs, expected outputs, and error handling. Enterprise prompt engineering is the discipline of treating prompts as first-class software artifacts.
1. Chain of Thought (CoT) and Reasoning
Force the model to think before it acts. By explicitly asking for a "reasoning" step, you drastically reduce hallucinations and improve logical consistency in complex tasks.
2. Few-Shot Examples
Don't just describe the output; show it. Providing 3-5 high-quality examples of input/output pairs is more effective than any length of instructions.
3. Output Schema (JSON)
Never accept raw text from a production agent. Use Function Calling or System Instructions to enforce a JSON schema that your backend can reliably parse.