Concept dictionary
Prompt Engineering
Prompt engineering is the deliberate design, testing, and revision of instructions and context used to guide an AI system toward a useful result.
- Review state
- Reviewed in POC
- Freshness
- Current
- Version
- 2
Also called
- Prompt Engineering
Remember it this wayDesign the request, test the result, and repair the conversation.
In plain language
People improve a request by clarifying the task, supplying relevant context, setting boundaries, showing examples, and checking the response. It is an iterative practice rather than a search for one magic phrase.
Why it matters
Clear inputs reduce avoidable ambiguity, but prompting cannot repair missing data, unsuitable models, broken workflows, or absent human review.
Example
A team tests several versions of a document-summary prompt, compares results against a checklist, and records which context and constraints improve reliability.
Common misconception
Prompt engineering is not a guarantee of correctness and is not the whole discipline of working effectively with AI.
Related terms
Sources
- Google Cloud, Introduction to Prompt Designvendor-primary guidance on designing, testing, and iterating instructions and context for generative models.
- NIST, Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST AI 600-1)risk-management context for prompts, prompt injection, testing, and human oversight.
Learn more
- Use the Learning Lab's conversation-engineering material with [[prompt|Prompt]] and [[human-review|Human Review]].