Glossary
Prompt Engineering
Prompt engineering is the practice of writing instructions and context for a language model so it produces reliable, useful output: specifying the task, the format, the constraints and what to do when unsure.
Glossary
Prompt engineering is the practice of writing instructions and context for a language model so it produces reliable, useful output: specifying the task, the format, the constraints and what to do when unsure.
The gains come from stating the task precisely, giving relevant context, showing an example of the expected output, and defining what the model should do when it lacks information, not from a magic phrase.

Prompts get versioned, tested against a set of known inputs, and changed deliberately, because a small edit can alter behaviour across every case the system handles.
A prompt cannot supply information the model does not have; that requires retrieval. It cannot make output deterministic. And it cannot make a model reliable on a task it is fundamentally unsuited to, which is a design problem, not a wording problem.
Only when the cause is ambiguity in the instruction. If the model lacks the information, the fix is retrieval; if the task is unsuited to the model, the fix is a different design.
Yes, in any production system. A prompt determines behaviour across every request, so it should be versioned, tested against known inputs and changed as deliberately as code.
Prompt engineering is the practice of writing instructions and context for a language model so it produces reliable, useful output: specifying the task, the format, the constraints and what to do when unsure.