Neural network for creating prompts

A prompt is your primary tool for communicating with artificial intelligence. Essentially, it’s an instruction or request you give to the neural network to obtain the desired result. Whether it’s text, an image, or a video, the quality of the response directly depends on how well your prompt is crafted.

You can draw an analogy with ordering from a chef. If you say, “I want something delicious,” the result will be random. But if you provide a clear description of the dish, including ingredients and preparation method, you’ll be treated to a culinary masterpiece. It’s the same with neural networks: the more detailed your request, the more accurate and useful the result will be.

The main components of the prompt:

1. Object: Who or what is the main character (e.g., “cat,” “programmer,” “mountain landscape”).
2. Action: What is happening (“sitting at a laptop,” “rising over a lake”).
3. Context and Setting: Where and when the action takes place (“in a cozy coffee shop,” “early morning,” “in a futuristic city”).
4. Details and Style: Color, lighting, mood, artistic style (“cinematic lighting,” “impressionist,” “bright colors”).
5. Technical Parameters: Format, aspect ratio, quality (often specified in a separate neural network interface).

Types and examples of prompts

They can be classified by the type of content you want to produce. The approach to creating them will vary depending on the end goal. Understanding these differences is key to working effectively with AI.

Let’s look at the main categories:

1. Text. Used to generate articles, scripts, poems, letters, advertising texts, and even programming code.
   A simple example: “Write a short story about a robot.”

   Complex example: “Write a professional blog article on the topic ‘The Benefits of Remote Work.’ The target audience is middle management. Use a formal, business-like style, present three arguments with research data, and include subheadings. Length: 3,000 characters.”

2. For image generation. These are the most popular and detail-intensive queries. They are used to create realistic photos, game art, book illustrations, and avatars.
   Example for realistic style: “Photo of a bearded man, 40 years old, wearing a red flannel shirt, sitting by a fire in a pine forest at night, starry sky, smoke, atmospheric lighting from the fire, high detail, photography, 8K.”

   An example for the cartoon style: “A kind, plump cat in a chef’s costume prepares pizza in the kitchen of an Italian restaurant, Disney cartoon style, bright colors, dynamic pose, cute expression.”

3. Prompts for other tasks. AI can help create music, videos, 3D models, and even be used for data analysis or coding. The principle is the same everywhere: a clearly defined task.

Rules for composing prompts

Creating an effective prompt is a skill that can and should be developed. By following a few simple rules, you’ll significantly improve the quality of interaction with the neural network.

The key is to be specific. Instead of “draw a house,” write “draw a two-story modern house with panoramic windows and a swimming pool, a glass and concrete façade, a sunny day, and a lawn with green grass.” Detail is the foundation of a good result.

Use references and keywords. If you’re looking for a specific style, specify it: “Van Gogh-style,” “cinematic still from a Nolan film,” “pixel art.” Many neural networks understand specialized terms like “highly detailed,” “atmospheric,” and “portrait photography.”

Structure your request. It’s best to break a long prompt into paragraphs or points. This helps the neural network better analyze each component of your request. Don’t be afraid to experiment and refine your request in the dialogue.

The main steps to creating a strong prompt:

1. Define the main goal. What exactly do you want to achieve?
2. Gather the basic details: object, action, location.
3. Add clarifying elements: style, lighting, colors, mood.
4. Enter technical parameters, if possible.
5. Test the prompt, evaluate the result, and iterate, refining the request.

Where and how to use prompts

The applications of well-written prompts are virtually limitless. They have become an indispensable tool in the digital world for professionals and amateurs alike.

In business and marketing, they are used to generate ideas for advertising campaigns, write social media posts, and create presentation prototypes and design layouts. Creating unique visual content for a website or blog now takes minutes, not days.

For creative people, prompts have opened up new horizons. Artists find inspiration by generating concept art. Writers overcome creative block by getting AI to develop their stories. Bloggers create unique avatars and illustrations for their channels.

If you don’t want to create queries from scratch, you can copy and adapt other people’s working prompts. Many communities and services share successful examples. There are also specialized generators and neural networks for prompt creation, which help formulate ideas into structured queries. Some of these tools are free, allowing you to experiment freely.

Our service offers an advanced prompt generator that will simplify your work with neural networks. You don’t need to rack your brain over wording—our tool will help you create the perfect prompt for any content creation: from realistic photos to commercial text materials for your presentation. We’ll help you achieve exactly the result you expect.

Errors and their solutions

Beginners often make common mistakes that lead to disappointing results. Understanding these mistakes will save you time and frustration.

The most common problem is being too brief. The search query “cat” will return a random image. The solution is to add details: “a fluffy ginger cat playing with a ball of yarn, a cozy home interior, soft light from a window.” Remember, a neural network doesn’t read your mind; it reads your query.

Conflicting instructions are another pitfall. For example, “a realistic cartoon character…” Neural networks have a hard time combining incompatible things. The solution is to choose one stylistic direction and stick to it. When in doubt, make several queries with different styles.

Many people expect a perfect result on the first try. But working with AI is an iterative process. The first answer is a draft. Don’t be afraid to clarify: “make the sky darker,” “add more greenery to the foreground,” “rewrite this paragraph shorter.” Use the copy your previous prompt function and refine it.

Avoid ambiguities. The word “key” can mean a wrench, a door key, or a musical clef. Clarify the context. And most importantly, practice. The more you work with neural networks, the better you understand their logic and the better your queries will become.