If you've been using artificial intelligence for a while, you've probably already noticed something curious: The same tool can produce brilliant results or completely useless answers.. The difference? It's not in the AI. It's in how you talk to it.
This is where the prompt engineering, a skill that is becoming essential for those who want to truly benefit from artificial intelligence.
Let's look at it calmly and without unnecessary technicalities.
What is prompot engineering?
He prompt engineering It is, basically, the art of formulating clear, precise, and well-structured instructions for an AI.
A prompt engineer does not "program" AI, but rather:
- He knows what to order
- He knows how to order it
- He knows how to adjust the question until the desired result is obtained
It's like learning to give good directions. If you explain what you need clearly, the AI responds better. If you're vague or ambiguous… just improvise.
And in science, we already know that improvising is usually not a good idea.
Why does prompt engineering improve AI outcomes?
Because AI has no context of its own. It doesn't know if you're a researcher, a student, a science communicator, or just curious... unless you tell it.
A good prompt:
- Reduce generic responses
- Improves accuracy
- Save time
- Avoid misunderstandings
In other words: The quality of the output depends directly on the quality of the input. Exactly the same as with the experimental data.
Therefore, learning prompt engineering is not about "tricks", but about effective communication with intelligent systems.
Basic principles of prompt engineering
There's no need to memorize magic formulas. With these principles, you've already done most of the work:
Clarity above all
Avoid ambiguous phrases such as "tell me about..." or "give me information about...".
The more specific you are, the better.
Sufficient context
Why do you need the answer? In what area? At what technical level?
A couple of sentences of context can completely change the outcome.
One task at a time
Asking for too many things in a single prompt often leads to confusing responses.
It's best to break it down into steps.
Iteration
The first prompt doesn't have to be perfect. Adjust, correct, fine-tune.
The AI improves when you improve the question.
Key skills of a prompt engineer
- Critical thinking: knowing how to evaluate whether an answer is valid or not
- Ability to synthesize: ask for just what is necessary, no more and no less
- Clear communication: express objectives directly
- Curiosity: test, adjust, experiment
- Scientific criterionDo not accept results without review.
A good prompt engineer doesn't delegate thinking to AI. They use it as a tool, not a substitute.
Learning to ask questions can also be practiced
Just as no one learns to design experiments overnight, Formulating good prompts requires practice and method..
There are resources that delve deeper into this skill and teach how to structure questions, avoid common mistakes, and adapt language to the objective. Learning to master the the art of asking It makes a huge difference between using AI superficially and truly integrating it into your work.
Biotechnologist and biostatistician specializing in data analysis and artificial intelligence applied to research. Founder of Maxymia, combines science and technology to develop solutions and training in automation for the scientific field.
