500 Production-Tested AI Prompts: How We Organized Them by Business Function

Over the past year, I've built and tested over 500 AI prompts for different business functions — sales, marketing, operations, customer support, HR, finance, and product development. Most prompt libraries dump 100 generic prompts and call it a day. I took a different approach: every prompt is tagged by function, tested against real business scenarios, and includes variable slots for industry customization. Here's the methodology and 10 production-tested prompts from different business functions. The Prompt Engineering Methodology Every prompt in our system follows a four-part structure: from dataclasses import dataclass , field from enum import Enum from typing import Optional class BusinessFunction ( str , Enum ): SALES = " sales " MARKETING = " marketing " OPERATIONS = " operations " SUPPORT = " customer_support " HR = " human_resources " FINANCE = " finance " PRODUCT = " product_development " LEGAL = " legal " class PromptComplexity ( str , Enum ): SIMPLE = " simple " # Single-turn,