Prompt engineering is the practice of designing effective inputs to get desired outputs from AI language
models. It's both an art and a science of clear communication with AI systems.
Core Techniques
Zero-shot: Direct instruction without examples
Few-shot: Providing examples to guide the model
Chain-of-Thought: Asking the model to reason step-by-step
Role Prompting: Assigning a persona or expert role
Self-Consistency: Multiple reasoning paths for reliability
Tree of Thoughts: Exploring multiple solution branches
Best Practices
Be Specific: Clear, detailed instructions yield better results
Use Delimiters: Separate instructions from content (e.g., ###, """, ---)
Specify Format: Tell the model exactly what output format you want
Break Down Tasks: Complex tasks work better in steps
Iterate: Refine prompts based on outputs
Give Context: Background information improves accuracy