Prompt engineering is what most teams reach for first when an AI output is wrong: rewrite the prompt. Done well it is concrete — clear role, explicit task, an example of good output, a list of things to avoid. Done poorly it becomes wishful thinking phrased as instructions.
For agencies, prompt engineering is the cheapest lever in the toolbox. A well-written prompt template can take a generic brainstorm tool and turn it into "our agency brief writer" without any code changes. Templates also make AI workflows auditable — you can read the prompt and know what the model was asked.
It is also the most overrated lever. Past a certain point, you cannot prompt your way past missing context. If the model does not have the brand guidelines, the campaign goals, or last week results, no amount of clever wording will rescue the output. At that point you have a context-engineering problem, not a prompt one.