How to write better AI Prompts? Examples and templates to start using it now

Summary

In this guide, you will learn:

• The quality of AI-generated content is directly dependent on the quality of the prompt given; specific, well-structured prompts yield far better results than vague ones.

• An effective prompt consists of four core elements: defining a Role (e.g., "act as a UX researcher"), stating a clear Task, providing all necessary Context, and specifying the desired output Format.

• To further enhance prompts, one should be specific, provide examples (few-shot prompting), ask the AI to think step-by-step for complex tasks, and be prepared to iterate and refine the initial prompt.

• Using visual context, such as mind maps or diagrams on a collaborative canvas like Miro, can serve as a powerful prompt by giving the AI a richer, more comprehensive understanding of the project.

You've probably noticed that everyone's using AI these days, but here's the thing: the quality of what you get out depends entirely on what you put in. A vague, poorly structured prompt gets you generic fluff that barely scratches the surface. A well-crafted prompt? That's your ticket to insights that actually move the needle on your projects.

If you've ever felt frustrated by AI responses that miss the mark or sound like they were written by a robot having a bad day, you're not alone. The difference between "meh" and "wow" often comes down to one skill: knowing how to write effective prompts.

In this guide, you'll learn a simple framework for crafting prompts that get results, plus see real examples you can adapt for your professional work. Let's turn that AI tool from a fancy search engine into your most reliable creative partner.

What is an AI Prompt? (And why getting it right matters)

Think of an AI prompt as your conversation starter with artificial intelligence. It's the instruction, question, or context you provide to get the AI to do something useful for you.

But here's where most people go wrong: they treat AI like Google. They throw in a few keywords and hope for the best. The reality? AI works more like working with a talented but literal-minded assistant. Give them clear direction and context, and they'll blow you away. Leave them guessing, and you'll get exactly that—guesswork.

This is where "garbage in, garbage out" becomes painfully real. Prompt engineering isn't just a buzzword—it's the difference between spending five minutes getting exactly what you need and burning through an hour of back-and-forth trying to course-correct a response that started on the wrong foot.

The anatomy of a perfect prompt: 4 key elements to include

Most people think writing good prompts is an art form that requires some mysterious talent. The truth? It follows a simple, repeatable framework that anyone can learn.

Every effective prompt has four core elements that work together like a well-oiled machine. Master these, and you'll consistently get better results from any AI tool.

Role: tell the AI who it should be

Start by giving the AI a specific persona or expertise to channel. Instead of talking to a generic AI, you're now talking to an expert who knows exactly what lens to use.

Example: "Act as an experienced UX researcher with 8 years in SaaS companies..."

This immediately sets the AI's knowledge base and perspective. You're not just getting generic advice—you're getting insights from someone who understands your specific challenges.

Task: Clearly state the specific action you want

Be crystal clear about what you want the AI to do. Vague tasks lead to vague results.

Instead of: "Help me with user feedback" Try: "Analyze the following user feedback and identify the top three pain points"

The more specific your task, the more focused and useful your results will be.

Context: Provide the necessary background information

Context is where most prompts fall flat. The AI doesn't know your industry, your users, your constraints, or your goals unless you tell it.

Example: "The feedback is from a mobile banking app targeting millennials who primarily use the app for budgeting and expense tracking. We're specifically looking at feedback from our recent checkout flow redesign."

This background information helps the AI understand not just what to do, but how to approach it in a way that's actually relevant to your situation.

Format: Specify the desired output structure

Don't leave the AI guessing about how you want your answer delivered. Be specific about format, length, and structure.

Example: "Present your findings as a bulleted list with specific user quotes as supporting evidence, and keep each point to 2-3 sentences."

When you specify format, you get results you can actually use without spending time reformatting or digging for the key insights.

Actionable Techniques for Crafting Effective AI Prompts

Now that you understand the basic framework, let's dive into some pro techniques that'll take your prompts from good to great.

Be specific and avoid ambiguity

Ambiguous language is the enemy of good AI output. The more specific you are, the more targeted your results will be.

Vague prompt: "Write a marketing email" Specific prompt: "Write a 150-word email to existing customers announcing our new project management feature, focusing on how it saves time and reduces missed deadlines"

See the difference? The specific version gives the AI clear boundaries and direction, while the vague version leaves everything up for interpretation.

Provide examples (few-shot prompting)

When you want a specific style or format, show the AI a few examples of what you're looking for. This technique, called few-shot prompting, is incredibly powerful for getting consistent output.

Example: "Write three social media captions for our new feature launch. Here are two examples of our brand voice: [Example 1] [Example 2]. Now create three more in this same style for the new feature."

This approach is particularly useful when you need to maintain brand voice or follow specific formatting requirements.

Encourage step-by-step thinking

For complex tasks, ask the AI to think through the problem step by step. This often leads to more thorough and accurate results.

Example: "Before providing your recommendation, walk me through your thinking process: 1) What are the key factors to consider? 2) How do these factors apply to our situation? 3) What's your recommended approach and why?"

This technique, known as chain-of-thought prompting, helps the AI (and you) follow the reasoning behind the final answer.

Iterate and refine

Your first prompt rarely produces perfect results, and that's completely normal. Think of prompting as a conversation where you refine and build on each response.

Start with your best attempt, see what you get, then follow up with refinements: "Can you make this more specific to B2B SaaS companies?" or "Focus more on the implementation challenges."

The best AI users treat prompting as an iterative process, not a one-shot deal.

AI Prompt examples for professional use cases

Let's put this framework into action with real examples you can adapt for your daily work. Each example breaks down the four key elements we covered.

Prompts for Marketing & Sales

Example 1: Writing personalized email subject lines

Role: "Act as a direct response copywriter with expertise in B2B SaaS email marketing..." Task: "...create 5 compelling subject lines for our feature announcement email..." Context: "...targeting product managers at mid-size companies who've been using our basic plan for 6+ months. The new feature is advanced analytics that helps them prove ROI to stakeholders..." Format: "...format as a numbered list with a brief explanation of the psychology behind each subject line."

Example 2: Generating social media content calendar

Role: "Act as a social media strategist specializing in B2B content..." Task: "...create a week's worth of LinkedIn post topics..." Context: "...for a project management tool targeting remote teams. Focus on productivity tips, team collaboration insights, and industry trends. Our audience consists of team leads and project managers dealing with hybrid work challenges..." Format: "...present as a table with columns for Day, Post Topic, Key Message, and Suggested Hashtags."

Prompts for Product & UX teams

Example 1: Creating user personas from research notes

Role: "Act as a UX researcher with expertise in persona development..." Task: "...synthesize the following interview notes into a detailed user persona..." Context: "...for a mobile expense tracking app. The interviews were conducted with 12 freelancers and small business owners who currently use spreadsheets or basic apps for expense management. Key themes include time constraints, tax preparation stress, and desire for automation..." Format: "...structure as a persona template including demographics, goals, frustrations, preferred tools, and a day-in-the-life scenario."

Example 2: Writing user stories for new features

Role: "Act as a senior product manager with experience in agile development..." Task: "...write comprehensive user stories for a team collaboration dashboard..." Context: "...the dashboard needs to show project progress, team workload, and upcoming deadlines for distributed teams working across different time zones. The primary users are team leads who manage 5-15 people..." Format: "...use standard user story format (As a... I want... So that...) with acceptance criteria for each story."

Prompts for brainstorming & ideation

Example 1: Generating ideas for team offsite

Role: "Act as an organizational development consultant specializing in team building..." Task: "...generate 8 creative workshop ideas for a 2-day product team offsite..." Context: "...the team of 12 people includes designers, developers, and product managers who've been working remotely for 18 months. Goals include improving cross-functional collaboration, aligning on quarterly priorities, and boosting team morale..." Format: "...list each workshop with title, duration, required materials, and expected outcome."

Example 2: Creating SWOT analysis

Role: "Act as a strategic business analyst..." Task: "...develop a comprehensive SWOT analysis..." Context: "...for a mid-stage SaaS startup in the project management space. We have 50,000 users, $2M ARR, 25 employees, and are competing against established players like Asana and Monday.com. Our key differentiator is AI-powered task prioritization..." Format: "...organize in a traditional SWOT matrix format with 4-6 specific points per quadrant and actionable insights for each."

Ready to supercharge your prompting game? Try these techniques with Miro AI and see the difference structured prompts can make.

Level up your prompts: Using Miro's AI-Powered visual canvas

Here's where things get really interesting: what if your prompt didn't have to be just text?

Most people think of prompts as typed instructions, but some of the most powerful prompting happens when you can show the AI a rich collection of ideas, diagrams, and context all in one place. That's where Miro's innovation workspace becomes your secret weapon for next-level AI collaboration.

Turn your visual work into powerful prompts

Instead of trying to describe your complex project in a few sentences, imagine being able to select a mind map full of brainstormed features, a user journey you've mapped out, or a collection of sticky notes from your last retrospective—and using all of that visual context as your prompt.

This is exactly what you can do with Miro AI. Select any combination of content on your board—whether it's sticky notes from a brainstorming session, diagrams showing user flows, or research insights you've organized—and use our "Create with AI" feature to summarize, expand, or transform that content.

Here's how it works in practice:

• Synthesize scattered research: Select all your user research sticky notes and ask Miro AI to identify the top themes and create actionable insights

• Transform brainstorms into plans: Turn a messy ideation session into a structured project roadmap with clear next steps

• Generate content from frameworks: Use your completed business model canvas or user journey map as context for creating detailed user stories or marketing copy.

Why visual prompts work better

When you're working on complex projects, context is everything. A traditional text prompt might capture the basics, but it can't show the relationships between ideas, the visual hierarchy of priorities, or the collaborative thinking process your team has already invested in.

Visual prompts give AI the full picture. Instead of starting from scratch every time, you're building on the collaborative work you've already done, making AI feel less like a separate tool and more like a natural extension of your team's thinking process.

Turn better prompts into better results

Writing effective AI prompts isn't rocket science, but it does require a systematic approach. Remember the four key elements: give the AI a specific role, clearly define the task, provide rich context, and specify the format you want.

The magic happens when you start treating AI as a collaborative partner rather than a fancy search engine. Use specific language, provide examples when you need consistency, encourage step-by-step thinking for complex problems, and always be ready to iterate and refine.

Most importantly, don't limit yourself to text-only prompts. The richest context often lives in the visual work you're already doing—the mind maps, diagrams, research syntheses, and collaborative boards that represent your team's collective thinking.

Ready to see how visual prompting can transform your next project? Try Miro AI and experience the difference a comprehensive, visual context can make in your AI collaboration. Your future self will thank you for taking the time to craft better prompts today.

Author: Miro Team Last update: August 29, 2025