Quick definition
Prompt engineering is crafting prompts to improve output quality.
- Category: Prompting
- Focus: control and response quality
- Used in: Standardizing responses with templates and clear instructions.
What it means
It involves structuring instructions, examples, and constraints. In prompting workflows, prompt engineering often shapes control and response quality.
How it works
Prompting structures the instructions, context, and examples the model sees. Small changes in wording and format can shift output quality.
Why it matters
Prompting controls behavior, format, and response quality.
Common use cases
- Standardizing responses with templates and clear instructions.
- Improving quality with few-shot examples.
- Constraining format for JSON, tables, or checklists.
Example
Provide format, tone, and length constraints.
Pitfalls and tips
Overly long prompts dilute key instructions and waste tokens. Keep prompts concise and explicit.
In BoltAI
In BoltAI, you will see this in prompts, system instructions, and templates.
