Prompt Engineering
technique technique
Designing effective prompts for LLMs
Supported languages
Prompt Engineering is the art and science of designing effective instructions for language models. It involves techniques for structuring, contextualizing, and formatting prompts to obtain optimal responses without modifying the underlying model.
Concepts
zero-shotfew-shotchain-of-thoughtsystem-promptsrole-playingoutput-formattingtemperature
Pros and Cons
Ventajas
- + No training or GPU resources required
- + Immediate and easily iterable results
- + Works with any LLM via API
- + Low implementation cost
- + Enables rapid experimentation
- + Transferable between different models
Desventajas
- - Limited by base model capabilities
- - Results can be inconsistent
- - Requires extensive experimentation
- - Consumes additional context tokens
- - Doesn't add new knowledge to the model
Casos de Uso
- Chatbot and assistant optimization
- Structured information extraction
- Controlled content generation
- Text classification and analysis
- Step-by-step reasoning