Prompt Engineering Techniques — 20+ Methods

This is a curated collection of 20+ prompt engineering techniques, each with explanations, templates, and runnable Jupyter notebooks. Covers:

Foundational:

• Zero-Shot Prompting — No examples needed, just clear instructions
• Few-Shot Prompting — Provide examples for the model to follow
• Chain-of-Thought (CoT) — Step-by-step reasoning
• Role Prompting — Assign an expert persona

Intermediate:

• ReAct — Combine reasoning with tool use
• Self-Consistency — Multiple reasoning paths, majority vote
• Tree-of-Thought — Explore multiple solution branches
• Least-to-Most — Break complex problems into sub-problems

Advanced:

• Constitutional AI Prompting — Self-critique and revision
• Meta-Prompting — Prompts that generate prompts
• Automatic Prompt Engineering (APE) — Let the model optimize its own prompts
• Prompt Chaining — Sequential prompts where output feeds input
• Skeleton-of-Thought — Generate outline first, then fill in details

Each technique includes: concept explanation, when to use it, template, Python notebook, and real-world examples.