How is prompt engineering perform ? There is no single technique; each expert has their own practices and preferences. However, a good starting point is the recommendations that OpenAI itself offers us on this subject.
The basis of prompt engineering is trial and error
You have to put yourself in front of an AI and start asking it what you think you will ne in the future. Not exact questions, but types of questions for which you know the expect answer. Bas on these tests, you will discover that many times the AI does not return exactly what you want, or it returns it but not.
in the desir format, or in some cases
It returns it but you find several situations in which it gives the wrong answer, it hallucinates or its answer simply does not serve you as quality information. What do you do then? Instead of dialoguing with the AI, you make your question increasingly ios database more detail and more specific, giving it examples of the type of information you expect in response, or clarifying things that you do want it to do when preparing its response or paths that you do not want it to take.
In this way, we go straight out of the dialogue
Our prompts, the questions we ask the machine, are no longer simple short sentences, but a detail construction of what we are looking for. Once we have new infographic] boost your ecommerce sales that master prompt, we save it to reuse it on multiple occasions and ensure that the answers we get from the AI are much more qualifi when we use them.
As I said, OpenAI offers us a series of strategies
To carry out this prompt engineering process:
Write clear instructions: Speak to AI as if it were a particularly literal person, where everything must be detail without any ambiguity.
Provide reference texts: Examples help you model the tg data response and format; use them.