What is LLM prompt engineering?
Prompt engineering is the practice of designing the text input to a language model so the model produces the desired output reliably. Clear instructions can improve results; longer prompts and additional processing can also affect cost and latency.
Common techniques
Useful techniques include clear roles, task boundaries, examples, output schemas and source references. Prompts should explain when to ask for clarification or hand a request to a person.
The grounding prompt
A support prompt can require answers based on supplied knowledge and a handoff when the answer is missing. Instructions help, but they do not guarantee factual accuracy. Retrieval quality, tool permissions and testing remain necessary.
When to fine-tune instead
Prompts hit a ceiling. For very specific output formats, very consistent tone, or task-specific reasoning patterns that need to fire reliably, fine-tuning becomes worth the operational cost. See LLM fine-tuning.
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