AI tools like ChatGPT, Gemini or Claude are powerful.
But if your prompt is vague, the output will also be vague.

This guide explains what a prompt is, how to design a good one, and 3 simple rules you can use every day to get better results from any AI model.

1. Core Concepts: Prompt, Prompt Engineering, Input Data

What is a prompt?

A prompt is the instruction you give to an AI system.
It tells the model:

• what you want,
• how you want it,
• and sometimes who it should act as.

You can think of a prompt as the recipe.
If the recipe is clear, the “dish” (the AI output) is usually much better.

What is prompt engineering?

Prompt engineering is the process of designing prompts so that AI can understand them and produce the result you want.

It includes:

• choosing the right words,
• adding enough context,
• giving clear constraints (length, tone, format),
• and asking AI to explain its reasoning when needed.

What is input data?

Input data is any information you give to the AI so it can work:

1. text,
2. images,
3. code,
4. numbers in a table,
5. or even a mix of all of them.

The classic rule still applies: “garbage in, garbage out.”
Good input → better output.

2. Seven Common Types of AI Input

When you talk to a modern GenAI model, you can use many kinds of input.
Here are 7 common types:

1. Text
   • The most common input.
   • Example: “Summarise this article in 5 bullet points.”
2. Image
   • You upload an image and ask the AI to describe, analyse or transform it.
   • Example: “Describe this chart and give the main insight.”
3. Code
   • You paste code and ask AI to debug, clean or complete it.
   • Example: “Find the bug in this Python function and fix it.”
4. Data
   • You provide tables, CSV files or spreadsheets.
   • Example: “Analyse this sales data and list 3 key trends.”
5. Multimodal
   • You combine text, images and data in one prompt.
   • Example: “Using this chart and these notes, write a short report.”
6. Context
   • You explain the background, limits or scenario.
   • Example: “You are helping a small e-commerce shop with limited budget.”
7. Role
   • You tell AI which role to play.
   • Example: “Act as a senior marketing manager with 10 years of experience.”

3. A Simple 3-Step Prompt Design Process

You don’t need to be a researcher to design good prompts.
You only need a 3-step process:

Step 1 – Prepare: Think Before You Type

Before you write the prompt, check 4 things:

1. Goal – What result are you looking for?
   • Example: “I want 3 ad ideas for our new product launch.”
2. Audience – Who will read or use the result?
   • Yourself, your manager, your client, your team, etc.
   • This changes tone, depth and format.
3. Information – What data do you already have?
   • Numbers, docs, old reports, brief from client, etc.
   • The more useful context you add, the better.
4. Scope – What should AI do, and what is still human work?
   • Example: AI drafts the outline; you edit and finalise.

Step 2 – Create: 6 Core Components of a Good Prompt

A strong prompt is clear, specific and structured.
Most good prompts use these 6 components:

1. Task (what to do)
   • The main action.
   • Example: “Write”, “Summarise”, “Analyse”, “Compare”, “Rewrite”.
2. Context (background)
   • Short description of the situation or project.
   • Example: “We are a small B2B SaaS company selling to HR managers.”
3. Role
   • Ask the AI to act as a certain expert.
   • Example: “Act as a content strategist for LinkedIn.”
4. Requirements
   • Specific details or criteria.
   • Example: “Use simple language, max 120 words, and add a clear CTA.”
5. Constraints
   • Limits for length, format, tone, tools, etc.
   • Example: “Answer in a table with 3 columns: Idea, Target Audience, Key Message.”
6. Reasoning
   • Ask AI to show its thinking.
   • Example: “Explain your reasoning in 3 bullet points.”

Examples by complexity

Basic prompt (Task + Context)

“Summarise the latest 2024 marketing trends for consumer brands in 5 bullet points.”

Focused prompt (Task + Context + Role + Requirements)

“You are a senior digital marketer. Summarise the key 2024 social media and content marketing trends for consumer brands.
Highlight strategies that can increase engagement by at least 20%. Limit to 7 bullet points.”

Complex prompt (all 6 components)

“Act as a marketing analyst.

1. Read the latest 2024 marketing trend reports.
2. Write a 500-word report on the most important trends in social media marketing for consumer brands.
3. Explain why these trends work, using data or recent examples when possible.
4. Use a professional but clear tone.
5. Finish with 3 practical actions a small brand can take next month.”

Tip: Use bullet points inside the prompt (like above). It’s easier for both you and the AI to follow.

Step 3 – Refine: Improve the Output

Good prompts usually need 1–3 follow-up messages.

1. Let AI refine itself

Use follow-up prompts to adjust:

• Accuracy
  • “Check this answer against more recent data.”
  • “Add sources for the statistics you used.”
• Tone
  • “Rewrite in a more friendly and informal tone.”
  • “Make it sound like a LinkedIn post, not an academic article.”
• Scope
  • “Shorten this to 150 words.”
  • “Expand section 2 with one more example.”

2. Let humans refine the final result

You (the human) still need to:

• verify facts,
• remove bias or sensitive statements,
• adapt to your brand voice,
• and make the final decisions.

AI is a smart assistant, not your boss.

4. Three Practical Rules for Better Prompts

Rule 1 – The “Rule of Three”

Ask AI for three options or three angles:

• “Give me 3 headline options.”
• “Suggest 3 ways to improve this email.”

Why it works:

• You get variety without feeling overwhelmed.
• It forces the model to be more specific.

Rule 2 – The Funnel Rule

Start wide, then narrow down.

1. Ask a broad question: “What are the main challenges for small e-commerce brands in 2025?”
2. Pick the parts you care about, then go deeper: “Focus on challenge number 2. Suggest 5 content ideas to solve it.”
3. Keep drilling down until you have something you can execute.

This “funnel” approach helps you discover ideas you didn’t even know to ask about at the beginning.

Rule 3 – Break Big Tasks into Small Steps

Instead of one giant prompt like:

“Create a full marketing strategy for my brand.”

Break it into smaller tasks:

1. “Define my target audience based on this product description.”
2. “List 5 priority channels for this audience.”
3. “Suggest 3 content ideas for each channel.”
4. “Turn these ideas into a 4-week content calendar.”

This gives you:

• more control,
• better quality for each step,
• and easier editing.

5. AI is an Assistant, Not a Replacement

AI can:

• save you time,
• reduce repetitive work,
• and give you new ideas when you feel stuck.

But AI cannot:

• understand your company culture as deeply as you do,
• take full responsibility for your decisions,
• or replace human judgment, empathy and ethics.

So keep this mindset:

You are the manager. AI is your assistant.
You decide the goal. AI helps you get there faster.

6. Quick FAQ About Prompts (Good for SEO)

What is a prompt in AI?

A prompt is the instruction or question you give to an AI model so it knows what to do.

Why is prompt engineering important?

Because good prompts produce clearer, more useful answers. Bad prompts waste time and can lead to wrong or unclear results.

How can I write better prompts?

Use the 3-step process: Prepare → Create → Refine, include the 6 components (Task, Context, Role, Requirements, Constraints, Reasoning), and apply the Rule of Three, Funnel Rule and Break Big Tasks.

1. Why Your Team Needs an AI Mindset

According to 2024 data, more than 77% of companies are already using or exploring AI.
This means AI skills can no longer stay only with one person.
To grow together, your team needs a shared mindset, shared tools, and shared habits.

2. Two Key Approaches to Developing AI Skills in a Team

2.1. Sharing Knowledge and Teaching Automation Thinking

Automation only works when everyone is part of the process.

• If only one person uses AI but others stay manual, the team slows down.
• Share courses, resources, or simple AI tips.
• Learning AI together gives everyone support, motivation, and better ideas.

2.2. Staying Consistent in AI Usage

Consistency is the secret to long-term improvement.

• Bring AI and automation into weekly meetings.
• Accept slower progress at the beginning. It pays off later.
• One example: the speaker spent one hour per day for one month so employees could explore AI tools.

3. Start Small: Try AI on Simple, Low-Risk Tasks

Small experiments help the team build confidence.

Examples:

• Automating email replies using tools like ChatGPT
• Improving meetings with auto-scheduling, agendas, and meeting notes

Simple tasks create early wins—and early wins create momentum.

4. Four Practical Steps to Improve Team Workflow with AI

Step 1: Identify Your Workflow

Choose a clear goal. Analyze your current process.
Pick the workflow that will bring the highest impact if improved.

Step 2: Use AI Where It Works Best

AI performs well in tasks that are:

• repetitive
• error-prone
• time-sensitive

Map out which tasks AI should handle—and which tasks require human judgment.

Step 3: Run a Test

Plan a small pilot project.
Include training time.
Track progress, identify problems, and adjust.

Step 4: Review and Scale

Look at the results.
Share what worked best.
Decide whether to expand the AI solution to more teams or tasks.

5. Final Advice

There is no universal formula.
AI changes quickly, and your team must continue learning, adapting, and improving.

Your value grows when your entire team grows with you.
Work together, try new tools, learn from mistakes, and improve step by step.