How to write an AI prompt

Knowing how to write an AI prompt helps artificial intelligence (AI) tools better understand what you’re asking for. A good prompt gives the tool you’re using the structure, context, and direction it needs, whether you’re generating blog content, summarizing an article, or solving a complex problem.

Clear AI prompts start with a defined goal, include relevant context, and specify the type of output you expect. Small changes, like adjusting the prompt tone and formatting or breaking tasks into steps, dramatically improve the quality of your results. With the right approach, it is easy to write prompts that are custom-made for the task.

If you’re new to AI prompting, we’ll explain how prompts actually work, with real examples, templates, and practical use cases.

1. Define your goal

Every effective AI prompt starts with a clear goal. Before you ask anything, decide what you want the AI to do – whether it’s generating or rewriting text, brainstorming ideas, explaining a concept, or even creating a website.

Defining your goal reduces vague or off-topic outputs. AI models perform best when they understand the task upfront. Think of it as giving instructions to a human assistant: the more focused your request, the better the result.

Here’s a simple example:

❌ Vague prompt:
“Help me with my website.”

✅ Clear prompt with a goal:
“Suggest 5 homepage headline ideas for a personal portfolio website focused on web development.”

The second prompt gives the AI a specific task – idea generation – and ties it to a purpose and context. It’s an example of how great prompts save time by telling the AI precisely what needs to get done.

As you progress, you’ll find that combining this goal-first mindset with other prompt engineering practices, like refining structure or chaining tasks, leads to more accurate outputs (in our example, a portfolio website instead of just a general site) and saves time in the long run.

2. Add the right context

A prompt becomes far more effective when it includes background and framing. Adding context helps the AI understand your intent, your audience, and the role that audience should play in its response. Without it, even a clear goal can lead to overly generic or misaligned results.

One of the easiest ways to provide context is to use role prompts. For example, asking the AI to “act as a marketing expert” immediately changes how it responds. Another helpful trick is to mention your target audience, such as “for small business owners,” “for students,” or “for job seekers.” These small additions help the model adjust its tone, vocabulary, and level of detail.

Let’s look at a quick before-and-after example:

❌ Without context:
“Give me tips for writing emails.”

✅ With context:
“Act as a sales copywriting expert. Give me 5 tips for writing persuasive emails that convert cold leads into paying customers.”

The second version frames the request with both a role and a specific audience. It results in more targeted and useful output – a core principle behind writing effective prompts that align with real-world goals.

As you practice, remember: the more relevant context you provide, the less guesswork the AI has to do, and the better your results will be.

3. Be specific and direct

Vague prompts lead to vague answers. One of the most common reasons people get unhelpful or generic results from AI tools is that their prompts aren’t specific enough. If the AI doesn’t know exactly what you’re asking for, it’ll fill in the blanks, and not always in the way you want.

Be detailed about what you need, how many items or steps you want, and in what format. This clarity helps the AI focus, especially when paired with context and a clear goal.

Here’s a before-and-after to show the difference:

❌ Vague prompt:
“Write social media content.”

✅ Specific and direct prompt:
“Write 3 short Instagram captions for a bakery promoting weekend brunch specials. Use a cheerful tone and include food-related emojis.”

The second prompt gives the AI direction on format (3 captions), platform (Instagram), tone (cheerful), and even stylistic elements (emojis).

Improve your prompts by thinking about narrowing the scope and pointing the AI toward a clear outcome, just like you would when briefing a human teammate.

4. Define your desired output

A good AI prompt doesn’t just ask for content – it explains what the final result should look like. The more guidance you give about the format, tone, or structure, the more usable the output will be on the first try.

You can tell the AI to respond in bullet points, complete paragraphs, a numbered list, a table, or even in a specific style. Specifying the tone (friendly, formal, persuasive) and length (three lines, under 100 words) also helps the model tailor its response.

Here’s a strong example:

✅ Prompt:
“List 5 one-sentence blog title ideas for an article about SEO trends in 2025. Keep the tone informative but catchy.”

This prompt works because it sets a clear format (list of 5), defines the scope (SEO trends in 2025), limits the length (one sentence), and requests a tone (informative but catchy). That’s everything the model needs to stay on target.

Start your prompts by clearly stating what you want. This saves you time on editing and gives you more effective prompts from the get-go.

5. Break down complex requests

If your task has multiple parts, don’t ask the AI to do everything at once – break it into steps. When prompts are too broad or overloaded, the output can become messy, inconsistent, or miss key details. It’s much easier to guide the AI by handling one task at a time.

This approach is known as prompt chaining, where you divide a larger goal into smaller, manageable requests. Each step builds on the last, making it easier to stay focused and improve quality as you go.

Here’s a quick example of how to chain prompts:

Step 1:
“Create a blog post outline titled ‘How to Start a Freelance Business’ for beginners.”

Step 2:
“Using the outline you just gave me, write the introduction in a motivational tone. Keep it under 100 words.”

Step 3:
“Now write the first section: Choosing your freelance niche. Make it easy to follow and include 3 examples.”

Instead of writing an entire blog post in one shot, you’re guiding the AI through each part, which leads to better structure, improved flow, and fewer edits.

If you’re aiming to improve prompts for more complex outputs like reports, landing pages, or scripts, breaking them down is one of the most reliable ways to get stronger results.

6. Test, review, and tweak

Even the best AI prompts don’t always deliver perfect results on the first try, and that’s completely normal. Prompting is an iterative process. The key is knowing how to adjust and refine your inputs based on what the AI gives back.

If something feels off, send a follow-up prompt. Most AI tools respond well to quick revisions like:

• “Make it more concise.”
• “Rewrite this for a younger audience.”
• “Add an example to support your point.”
• “Turn this into a table comparing pros and cons.”

These small adjustments are often faster than rewriting the prompt entirely. You can also rephrase your original prompt if you notice patterns in the output that feel too generic or repetitive.

Think of it like editing a rough draft – each tweak helps shape the result. And over time, you’ll build your own instinct for what makes a great prompt and how to spot what’s missing.

By reviewing and improving your prompts regularly, you’ll get more relevant, reliable outputs and spend less time fixing avoidable mistakes.

What are some advanced tips for writing good AI prompts?

Once you’ve mastered the basics of AI prompting, you can start using more advanced techniques to fine-tune your results. These strategies come from the field of prompt engineering and are especially helpful when you want consistent, repeatable output for complex tasks.

The most effective methods include:

• Giving the AI a specific persona or role, like “Act as a UX designer.”
• Providing few-shot examples to guide the tone, format, or structure you expect.
• Using prompt chaining to build long-form content or solve layered problems.
• Setting clear constraints, like word count, reading level, or perspective.

You can find many more tips like these in our guide on advanced prompt engineering best practices. Combining multiple prompt engineering and fine-tuning techniques works better than relying on one. For example, pairing a role prompt with a defined format and follow-up questions gives the AI structure while still allowing flexibility.

These techniques take practice but can drastically improve the way you use AI for writing, coding, planning, and more.

How to become a prompt engineer?

Becoming a prompt engineer requires a strong understanding of the way AI models work and how to communicate with them effectively. You need a mix of creativity, logic, and language skills to design prompts that generate consistent, high-quality results.

To get started, focus on mastering the basics: writing clear instructions, testing different formats, and refining prompts based on feedback. Over time, you’ll learn how to identify patterns in AI behavior, reduce errors, and improve outputs through structure and iteration.

While you don’t need to know how to code, understanding the AI model’s capabilities and limitations will help you prompt better. Roles in this field often overlap with product development, data analysis, and user experience, making prompt engineering a valuable skill in a variety of industries.

Do AI tools require different types of prompts?

Yes, AI tools respond better to different types of prompts based on their purpose and design. Writing an effective prompt for a chatbot isn’t the same as crafting one for an image generator or a long-form summarizer. Each model has its own strengths, output format, and quirks.

Here’s how to adapt your prompts depending on the tool:

ChatGPT (OpenAI)

ChatGPT works best with detailed instructions, especially when you include a clear desired role, tone, and format. You can guide this model by setting constraints like word count or style.

Example prompt:
“Act as a career coach. Write a 100-word LinkedIn summary for a recent marketing graduate applying to tech companies. Use a confident and professional tone.”

If you want more control, you can also create a custom GPT with pre-set instructions for your use case.

Midjourney and DALL·E (image generation)

Visual models like Midjourney and DALL·E (integrated within ChatGPT) rely on descriptive prompts that paint a clear picture. The more details you give on the subject, environment, lighting, color, and style, the more accurate the image.

Example prompt:
“Close-up portrait of a robot with reflective metal textures in neon lighting, cyberpunk style, dark background, sharp focus.”

These tools don’t need complete sentences – just rich, layered descriptions.

Claude and Gemini

Tools like Claude and Gemini are designed for deeper reasoning, longer context, and structured tasks. They’re ideal for summarizing articles, comparing ideas, or generating multi-step outputs.

Example prompt:
“Summarize the key takeaways from this 2,000-word article about remote team management. Include a one-sentence summary for each major section.”

For best results, provide longer input context and tell the model exactly how to structure the output (list, paragraph, or bullet format).

Hostinger Horizons

Hostinger Horizons works differently from text-based or image-generating AI tools. Instead of generating a paragraph or a photo, it builds a whole website or web app based on your input.

To get the most helpful output, focus on what your website is for, who it’s meant to serve, and what pages or features it should include. A clear, beginner-friendly prompt might look like this:

Example prompt:
“Build a simple website for a yoga teacher. It should include a homepage, class schedule, prices, and a contact page. Use a calm and professional tone.”

Hostinger Horizons is designed for people with no coding experience, so you don’t need to include any technical details. Instead, treat your prompt like a to-do list for your idea and keep things short, clear, and goal-oriented.

See our collection of AI prompt examples for Hostinger Horizons to see what types of input work best with this tool.

Generate exceptional AI prompts

Learning how to write an AI prompt isn’t just about saving time – it’s about getting better results with less effort. Clear, structured prompts lead to more accurate answers, faster workflows, and less back-and-forth when refining your output. Whether you’re creating content, solving technical problems, or automating tasks, the right prompt gives you more control over what the AI produces.

As you continue improving your prompting skills, you’ll eventually want to go beyond one-off inputs and start customizing how models behave. That’s where techniques like tailoring your prompts, also known as prompt tuning, come in. With these advanced methods, you can fine-tune AI responses to specific instructions, so your results stay consistent and reliable. 

The better your prompts, the more powerful your AI tools become. And with practice, writing exceptional prompts becomes second nature, opening the door to faster work, better ideas, and smarter problem-solving.

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