A Good Prompt is an Art: Learning to Write the Best Prompts for Neural Networks with Examples
Artificial intelligence (AI) is widely used today, from creative work and scientific research to analytics and business planning. Whether you use Chat to write text, Midjourney to generate an image, or a specialized neural network to process data, the quality of the result directly depends on your request. Artificial intelligence can help solve a variety of problems, but it requires extremely clear, consistent instructions.
To effectively and productively interact with any AI model, you need to master the art of prompting. Prompting is the skill of formulating highly precise and structured queries. The goal of this article is to provide step-by-step instructions on how to write a good prompt that guarantees the desired result. We will examine in detail all the key elements of a successful prompt and show examples of the best prompts for neural networks in various fields.
What makes a good prompt?
A good prompt isn’t just a set of keywords, but a comprehensive, multi-level instruction. The model must understand not only the task itself, but also its role, target audience, and desired format. If your request is too general or incomplete, the result will be unclear. This is what distinguishes a professional prompt from an amateur one.
For a prompt to work well, it must include key structural characteristics that guide the model along a clearly defined path. This ensures a usable result on the first try. Ignoring any of these elements significantly reduces the effectiveness of the work and increases the risk of receiving an irrelevant answer. A well-written prompt should be clear, complete, and consistent.
An effective prompt should consist of the following essential elements:
- Context: defining the role, topic, context of the work, and target audience. This is the foundation;
- Task: a specific, measurable action to be taken;
- Input: text, code, data, or other information the model should analyze or use as a basis;
- Response Format: the structure of the final result (list, table, text of a certain length, code in a specific language);
- Constraints: rules the model must not violate (style, tone, word limit, prohibition of certain words);
- Example: Providing a ready-made example for a complex or specific task helps the model better understand your intent.
Context
Context is a critical element of a prompt. It defines the framework within which the neural network will operate and establishes its level of expertise. You must communicate to the AI its role in the current task (e.g., marketer, scientist, writer), as well as the intended audience for the prepared response.
By establishing a role, you enhance the professionalism of the response. For example, asking the AI to act as an expert in quantum physics, you expect the language and terminology to be appropriate for this highly specialized field, and the model to use correct scientific terminology. A well-defined context transforms a general response into an expert opinion, and this is the key characteristic of a professional prompt.
It is also important to specify the intended audience for the prepared text or image. The audience (schoolchildren, executives, colleagues, the general public) influences the choice of language, the level of detail, and the complexity of concepts.
The best prompts for installing Context include:
- “You are a leading data analyst with 10 years of experience in fintech. Your answer is intended for executives without deep technical knowledge and should focus on key metrics and financial forecasting.”
- “You are an editor at an academic journal who reviews texts to ensure they meet academic standards. The target audience is undergraduate students who need to understand the basic principles of statistical analysis.”
Role: Art Director for a Mobile Game Advertising Campaign
- “You are a art director creating concept photos for an advertising campaign for a fantasy mobile game. The context is a medieval castle in the rain, in the style of a Renaissance painting.”
Effective Prompts: A Comprehensive Guide to Working with AI
1. Task
The task is the most crucial element, describing exactly what needs to be done. The more detailed the task, the more precise the result you’ll get. Avoid general phrases like “write about…” or “do something interesting.” This is a common mistake, forcing the model to make assumptions and choose from thousands of options.
Instead, use verbs that denote specific actions: conduct a comparative analysis, create a plan, write a summary, create an image in a specific style. This guides the model toward precise execution of the instructions. Breaking down a complex task into several simpler ones also helps achieve a higher-quality result.
Be sure to specify the key parameters of the task—its scope, number of steps, and the main points that should be included in the completed answer.
Examples of tasks for a good prompt:
- “Comparatively analyze two frameworks: React and Vue.js, based on three key characteristics (development speed, community size, and learning curve). Your answer should be at least 500 words long and include a market demand analysis. Focus on the benefits for startups.”
- “Create a startup presentation template, with each slide containing no more than three bullet points. The presentation should include a ‘Financial Model’ section with a three-year forecast. Use investor language and provide comments for each slide.”
- “Translate the following text into technical English, preserving all original source citations. Check the text for grammatical errors and improve the style, making it more formal and scientific.”
2. Answer Format
Defining the response format is critical to obtaining structured, ready-to-use data. If you require a list, table, code, or text for publication, be sure to specify this. This helps avoid clutter and simplifies processing.
A properly specified format ensures easy further work with the resulting output. You can choose between a bulleted list, a JSON object, an expanded essay, or ready-made code, but be sure to specify formatting rules: use of bold, Markdown headings, or specific syntax requirements.
Format options for a good prompt:
- “Provide your answer in bulleted format. End each bullet with a semicolon and end each bullet with a period. The list must contain at least five items.”
- “Organize the data in a table with columns labeled ‘Name’, ‘Pros’, and ‘Cons’. The ‘Pros’ column must contain at least three items. The table must be generated in Markdown format and be suitable for copying onto a website.”
- “Write a short, concise two-paragraph summary, avoiding quotations and introductory clichés. The text must be copy-pasteable and ready for use in a corporate report. Use only formal style.”
- “Create the code in Python 3.10. Use only standard libraries, add detailed comments to each function block, and perform error checking.”
For users who require advanced and high-load neural networks, chataibot.pro offers the ability to use various OpenAI models. A subscription provides unlimited access to premium bot variants, which is especially valuable when working with large and complex academic tasks that require generating long text or detailed presentations. This ensures stability, high query processing speed, and the ability to select the best response from multiple options.
3. Limitations and Style
Constraints set rules that the model must strictly adhere to when composing their response. These include word limits, style requirements (formal, humorous, neutral), or prohibitions on the use of certain words and phrases. This is one of the most important elements that helps customize the finished text or image to specific needs.