Prompt Engineering

Prompt engineering is the systematic design and evaluation of instructions, context and output requirements for a language model.

The objective is not supposedly perfect wording, but a reproducible task definition whose results can be tested against defined criteria.

Elements of a good prompt

A prompt may define the task, relevant context, domain criteria, boundaries and required output format. Examples can demonstrate patterns that are difficult to describe precisely.

Few-shot prompting provides the model with several input-output examples. Whether this improves results should be tested with representative cases.

Why this goes beyond simple wording

In production systems, prompts, model versions and test cases should be versioned together. Representative examples and measurable criteria make changes comparable.

Where the limits are

Prompt engineering does not reliably add missing factual knowledge. This may require RAG, tools or other data access; fine-tuning primarily addresses model behaviour.

If results remain unstable despite clear instructions, review the model, data access, task decomposition and control mechanisms.