What is a prompt and how to formulate requests effectively
A prompt is the instruction you give to a generative AI. Its quality determines the quality of the response. Effective principles are documented and stable: provide context, specify the expected format, give examples, iterate. This is a skill you can learn in a few hours.
A prompt is the instruction you give to a generative AI. Its quality directly conditions the quality of the response. Contrary to common belief, using AI well requires no technical skill: it requires clarity. Effective principles are stable and documented: provide context, specify the expected result, give examples, proceed iteratively. It is a skill acquired in a few hours of practice.
The four levers of a good prompt
Context. The AI only knows what you tell it. Specify who you are, who the output is for, and what the purpose is. A complaint letter request benefits from specifying the recipient, the reason, and the desired tone.
Precision of the request. Say what you want and in what form: length, format, language level, structure. A vague instruction produces a vague response.
Examples. Showing an example of what you expect powerfully steers the response. It is often more effective than long explanations.
Iteration. The first response is a starting point. React, correct, refine. Say what is wrong rather than starting over.
A reflex that changes everything
Ask the AI what it is missing to answer well. A simple formula like "before answering, tell me what information would be useful" often transforms the quality of the result, because it forces the need to be made explicit.
What a good prompt does not do
It does not make the response true. A perfect prompt on a topic where AI hallucinates will produce a well-formed hallucination. Prompt quality improves relevance and form, not truthfulness, which remains to be verified.
Frequently Asked Questions
Do I need magic formulas?
No. Clarity is better than ready-made formulas. Simply and precisely say what you want.
Should I be polite?
It does not change the model's performance, but there is no harm in it. What matters is precision.
Can I say too much?
An excess of unnecessary details can muddy the request. Aim for precision, not length.
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