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Glossary Term
AI & LLM

Prompt Engineering

The practice of crafting effective prompts to guide AI models toward desired outputs, a key skill for working with LLMs.

Related Service: Custom Solutions

Prompt engineering: getting reliable outputs from AI

Prompt engineering is the practice of structuring instructions so an AI model produces consistent, usable outputs. The goal isn’t “clever prompts” - it’s repeatable behaviour: correct format, correct constraints, and correct tone.

High-signal prompt pattern

  • Role: who the model is acting as (editor, analyst, developer).
  • Task: what to produce, in what format.
  • Constraints: what not to do (no invented numbers, cite sources, avoid legal advice).
  • Inputs: provide context, examples, and edge cases.

Best practice

  • Use examples of good outputs to anchor style and structure.
  • Ask for “unknowns” explicitly (what needs clarification) to reduce hallucinations.
  • Prefer retrieval (real docs) over asking the model to “remember”.

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