Prompting
Prompt engineering
Designing prompts and context so an AI model produces more useful, reliable outputs.
Example
A support team tests different instructions to make ticket summaries consistent and useful.
Why it matters
It reduces avoidable misunderstandings between what someone needs and what an AI delivers.
You'll hear it
“That extra instruction made the summaries much easier to use.”
Can you control it?
Yes
Yes. You can often use or adjust prompt engineering directly when the product supports it. The available options and their effect still depend on the tool.
Common questions
- Does it require programming?
- No. Many improvements come from clearer instructions and examples, although automated testing may use code.
- Can a prompt that works today stop working well later?
- Yes. Changes to the service or the task can affect how the same wording behaves.
- Can careful prompting fix every weakness?
- No. Missing knowledge, limited abilities and poor source material may require a different approach.