What are prompts and why are they important for using AI?

In just a few years, talking about artificial intelligence has become as common as talking about smartphone or social network. And along with AI, a word that until recently was almost unknown has entered our vocabulary: prompt. Today, it’s not enough to know it exists; we need to understand its meaning, how it works, and above all, the opportunities it offers to people, professionals, and businesses.

Generative AI—popularized by systems like ChatGPT, Gemini, Claude, or Meta’s open models—depends entirely on the quality of the instructions it receives. This is where the prompt comes in: a tool that’s simple in appearance, but crucial in substance. Its importance has grown so much that today there are marketplaces dedicated to selling optimized prompts and a full-fledged profession, prompt engineer, increasingly sought after in sectors ranging from marketing to the tech industry. Before understanding why, we need to start with the basics.

Translation and Meaning of Prompt

The word prompt comes from English and literally means push, urge, stimulus. In traditional contexts, it indicates a call to action or a signal that elicits an immediate response: in theater, it is a line suggested at the right time; in computers, it is the line where the user enters a command; in communication, it is the stimulus that triggers a reaction. This conceptual root has persisted even in the era of artificial intelligence.

When talking about generative AI, prompt takes on an even more precise meaning: it is the instruction we give to a model to obtain a useful, coherent, and readable response.

In Italian, we could translate it as instruction or description, but no translation fully captures its dynamic nature. The prompt is not just a written text: it can be a photo, audio, video, or a mix of formats. It’s an input that guides the model’s behavior and directs it toward a result. Thinking of a prompt as a simple sentence underestimates its significance. In the context of AI, it’s a true interface between human thought and the model’s computational capacity. Through a prompt, we decide what AI should generate, how it should do it, and with what degree of precision. For this reason, in recent years there has been increasing discussion of prompt design and prompt engineering, disciplines that study how to construct optimal stimuli so that AI produces exactly what it needs.

Today, the prompt is considered the new "language for communicating with machines." Just like a language, it has rules, nuances, and semantic implications. Context also influences its effectiveness: a generic prompt generates generic responses, a precise prompt generates quality results. Truly understanding what this term means means understanding the way AI "thinks" and responds.

What are prompts? The Practical Explanation

To understand what a prompt is in practice, just look at how generative artificial intelligence works. This technology can produce output of any kind: text, images, audio, video, and even structured data. To do so, it needs input, which is the information we provide to start the generation process.

The prompt is precisely this: the description we enter into the system to activate its creative and computational capabilities. If we type "yellow car with a cat on it" into an image generator like OpenAI’s DALL E, we’re giving the model enough instructions to create a coherent scene. The model analyzes the prompt, interprets it based on its training, and produces an image that matches what we requested. The clearer the prompt, the more accurate the output will be.

It’s important to remember that a prompt defines not only the desired content, but also the tone, style, form, and even contextual conditions. With a single input, we can ask a model to analyze data, summarize complex texts, recreate a photographic style, generate an illustration inspired by a specific artist, or write content consistent with a specific audience. The prompt is therefore a set of instructions that not only concerns "what" the AI should generate, but also "how" and "for what purpose." In this sense, it has become a powerful tool for creative and operational control: it allows you to obtain personalized results aligned with your goals without the need for advanced technical skills or programming knowledge.

Prompt: why it’s important for artificial intelligence

Knowing a prompt and knowing how it works is essential for a very simple reason: AI is poised to revolutionize work, education, creative production, and the way we solve everyday problems. According to analyses published in 2024 by McKinsey, the quality of prompts can increase AI efficiency by up to 60% in complex tasks. A well-constructed prompt allows for accurate output, while a confusing prompt leads to inconsistent or unusable results.

Furthermore, the ability to formulate effective prompts is an important driver of innovation. In recent years, a veritable prompt market has developed, populated by platforms like PromptBase, for example, where it is possible to buy and sell prompts optimized for different models. These marketplaces are used by professionals, companies, and creators who want immediate results without having to learn advanced prompting techniques. The economic value of the sector has grown rapidly: in 2025, prompt marketplaces exceeded $100 million in global transactions.

Alongside this phenomenon, a crucial role has emerged: the prompt engineer. This profession is now a well-established reality. The prompt engineer’s job is to provide artificial intelligence with increasingly precise descriptions, improving the quality of responses and ensuring consistent output. The narrative that AI will "steal jobs" is giving way to a more mature vision: AI is changing existing professions and creating new ones. The prompt engineer is one of these: a role that doesn’t replace, but rather enhances, human creativity and efficiency.

Some prompt examples to understand

A thorough understanding of how prompts work also means looking at concrete examples. The effectiveness of a prompt depends on the clarity of the instruction, the context, and the precision with which we describe what we want to achieve. When we ask a model to create a text, a prompt that’s too general leads to a vague response; conversely, a detailed prompt allows the system to produce content that meets our expectations.

A bad prompt for generating text might be: "Write an article about technology." This is such a broad request that it results in generic, superficial, and unhelpful text. A correct prompt, on the other hand, might be: "Write a 400-word article explaining how artificial intelligence is changing the job market in 2025, with references to official sources and a popular style." Here, the system has detailed instructions on length, topic, tone, and content.

For images, the principle is the same. A bad prompt for a visual generator might be: "Draw a dog." The result will be random: a generic breed, a generic style, with no control over lighting, environment, or pose. A correct prompt would instead be: "Watercolor-style illustration of a Labrador sitting in a flowery meadow at sunset, with muted colors and soft light." In this case, the model has enough information to produce an output consistent with the user’s intent.

These examples demonstrate that a prompt isn’t just a simple command, but a narrative guide that helps AI build understandable content. An effective prompt defines the objective, context, and qualitative criteria. This is what allows impressive technology to be transformed into a truly useful and controllable tool.

Prompt engineering and prompt engineer: what is it?

We’ve already mentioned it, but it’s better to go even deeper. prompt engineering is the discipline that studies how to create structured, effective, and optimized prompts to guide AI models to produce the best possible results. It’s a young science, but it’s now central to the development of AI applications.

Its goal is to understand how models interpret human language and how we can leverage this expertise to obtain precise answers. A prompt engineer is a professional who masters this skill: they "train" the model through clear, contextualized instructions.

A prompt engineer must be knowledgeable about the field of generative AI and the specific domain in which they operate. If they need to train a model to provide output related to Ferrari, for example, they must have in-depth knowledge of the automotive industry and the Maranello-based company’s models. A prompt engineer is not just a technician: they bridge creative, linguistic, and vertical skills.

The role is increasingly in demand by companies that develop proprietary models, such as OpenAI, but also by companies that integrate generative AI into internal processes. Those who master this discipline can work as consultants or create prompts to sell independently on specialized marketplaces. Prompt engineering represents one of the new professions born from the evolution of artificial intelligence, a perfect example of how technology, in some cases, doesn’t eliminate jobs, but transforms them, generating new opportunities and skills.

Original article published on Money.it Italy. Original title: Cosa sono i prompt e perché sono importanti per usare l’AI