prompt-engineering-patterns

Master advanced prompt engineering to enhance LLM performance, reliability, and control in production.

• Master advanced prompt engineering techniques
• Optimize LLM outputs and performance
• Design reliable, controllable production prompts
• Build reusable, structured prompt templates

• Few-shot learning with semantic similarity and dynamic example selection
• Chain-of-thought reasoning with step-by-step and self-consistency
• Iterative refinement and A/B testing for performance
• Variable interpolation and conditional prompt sections
• System prompt design with role, constraints, and safety
• Error recovery with fallbacks and confidence checks
• Token efficiency and latency reduction strategies

1. 1.Define a structured prompt template with system, instruction, and output format
2. 2.Select relevant examples using semantic similarity or diversity sampling
3. 3.Integrate retrieved context or knowledge base content into the prompt
4. 4.Add verification and self-consistency steps for output validation
5. 5.Test and iterate on diverse inputs to refine performance
6. 6.Monitor metrics and version control prompt changes