Andrew Ng Style AI Course Notes Generator

topic: "Prompt Engineering for Large Language Models", language: "Spanish"

# Ingeniería de Prompts para Modelos de Lenguaje Grande *Prompt Engineering for Large Language Models* ## 1. Conceptos Clave / Key Concepts **Prompt Engineering** is the discipline of designing inputs that effectively communicate with AI systems to achieve desired outcomes. Think of it as learning the "language" that helps AI understand exactly what you want. **Core Principles:** - **Specificity (Especificidad)**: Precise instructions yield better results - **Context Setting (Establecimiento de Contexto)**: Providing relevant background information - **Output Formatting (Formato de Salida)**: Defining how you want responses structured ## 2. Practical Implementation **Step-by-Step Framework:** 1. **Role Assignment**: "You are a [specific expert role]..." 2. **Task Definition**: Clear description of what needs to be accomplished 3. **Constraints**: Boundaries and limitations 4. **Output Format**: Specific structure requirements 5. **Examples**: Few-shot learning demonstrations ## 3. Case Study: Customer Service Automation **Challenge**: A tech company needed to automate 80% of customer inquiries while maintaining quality. **Solution**: Implemented structured prompts with role-playing, sentiment analysis, and escalation protocols. **Results**: 85% automation rate, 40% faster response times, 15% improvement in customer satisfaction scores. 💡 **Pro Tip**: Always test prompts with edge cases before production deployment.