Prompt Engineering
Designing instructions, examples and constraints so a model reliably produces the desired output.
In plain language
Prompt engineering is not magic words; it is clearly specifying goals, context, output format and boundaries. Common techniques include role setting, few-shot examples, step-by-step reasoning, structured output and self-checks. Complex tasks also need tools, retrieval and evaluation.
Example
Change write some copy into three Xiaohongshu headlines under 20 characters for junior operators, in an honest tone.
Recommended tools
Related terms
Chain of Thought
Prompting a model to write intermediate reasoning steps before concluding.
Large Language Model
A model trained on massive text to understand and generate natural language.
Temperature
A parameter controlling output randomness; higher values produce more diverse results.
Agentic Workflow
Breaking a task into steps planned by AI, executed by tools and reviewed by humans.