- Clear understanding of LLM behavior: setting expectations via style, context, and persona.
- Few-shot prompting: including example inputs and outputs to guide the model.
- Chain-of-thought reasoning: prompting the model to think step-by-step before giving an answer.
- Pattern-based prompting: applying structured templates repeatedly for consistency.
- Iterative refinement: testing, adjusting phrasing, and evaluating outcomes to optimize performance.