Prompting is just asking well. It's also the single skill that separates people who get incredible results from AI from people who give up and say "it doesn't really work." Good news: it's learnable in an afternoon.
A prompt is the text you hand the model. That's it. But a model can't read your mind, it only has the words you gave it. So the whole game is putting enough of the right context into those words that the model can't help but give you what you wanted. Vague in, vague out. Specific in, sharp out.
Almost every strong prompt has four parts. Miss one and quality drops:
Same goal, wildly different results:
A system prompt is a prompt that runs before every conversation, setting the ground rules once so you don't repeat yourself. When you give an agent a lasting identity, name, voice, job, rules, that system prompt becomes its soul file. Same mechanism, bigger job.
Telling the model who to be genuinely changes the output. "You are a patient teacher explaining to a beginner" and "You are a blunt senior editor" will answer the same question in completely different voices. Pick the role that fits the job before you ask the question.
The fastest way to get the format you want is to demonstrate it. Paste one or two examples of good output and say "more like these." This is called few-shot prompting, and it beats paragraphs of description because the model learns the pattern directly instead of interpreting your instructions.
The pros don't write one perfect prompt, they steer. When an answer is close, tell the model exactly what to change: "shorter, drop the second point, more casual." You're not starting over, you're nudging. Two or three nudges gets you further than any single mega-prompt.