Glossary
Prompt Engineering
The skill of crafting effective instructions to get high-quality outputs from AI tools.
Definition
Prompt engineering is the practice of designing, refining, and optimizing the text instructions (prompts) given to AI language models to produce the best possible outputs. It involves techniques such as role-setting, chain-of-thought reasoning, few-shot examples, and output constraints to guide AI behavior.
Why It Matters
The same AI tool can produce vastly different outputs depending on how you phrase your prompt. A skilled prompt engineer can consistently extract high-quality, specific, and accurate responses from AI, while an unskilled user receives generic, error-prone outputs.
Examples
Few-shot promptingProviding 2–3 examples of the desired output format before asking the AI to produce more
Chain-of-thought'Think step by step: first outline the structure, then write each section'
Constraint setting'Do not include any statistics. Write at a 7th-grade reading level. Use only bullet points.'
Common Mistakes
Treating prompts as one-and-done — the best outputs come from iterative refinement.
Not specifying negative constraints.
Assuming more words in a prompt always produces better results.
Not saving effective prompts — build a prompt library of what works.