Prompt engineering is the process of designing, refining, and optimizing instructions (prompts) to guide AI models especially large language models (LLMs)—to generate accurate, relevant, and safe outputs. In 2025, with AI powering everything from business operations to creative projects, prompt engineering is a must-have skill.
Give the AI clear instructions, but no examples. The model relies on its general knowledge.
For simple or common tasks.
Summarizing an email:
Summarize this email in one sentence.Language translation:
Translate the following to French: "Where is the nearest train station?"Show the AI a few examples first, then give it a new task to follow the pattern.
For tasks with specific formats or styles.
Classifying reviews:
Review: "Loved the movie!" – Positive
Review: "Too slow." – Negative
Review: "It was okay." – Neutral
Review: "The plot was exciting." –Generating email replies:
Email: "Can you send the report by Friday?"
Reply: "Yes, I will send it by Friday."
Email: "Are you available for a call tomorrow?"
Reply: "Yes, I am available for a call tomorrow."
Email: "Can you review my presentation?"
Reply:Ask the AI to show its reasoning step by step for better accuracy in complex tasks.
For logic, math, or troubleshooting tasks.
Math problem:
If you have 3 apples and buy 2 more,
how many apples do you have?
Explain step by step.Decision making:
Should I bring an umbrella today?
Let's think step by step:
1. Check the weather.
2. See if rain is likely.
3. Decide if I need an umbrella.Give the AI a specific direction or focus, so its answer stays on track.
For summaries, reviews, or tasks where you want the AI to stay focused on a theme.
Summary with focus:
Summarize this article in two sentences,
focusing on environmental impact.Product description:
Describe this smartwatch,
highlighting its health and fitness features.Ask the AI to solve a problem by writing and running code.
For tasks involving numbers, data, or logic.
Math calculation:
Write a Python function to calculate
the area of a circle with radius 7.Data analysis:
Given this list of sales numbers,
write Python code to find the average
monthly sales: [1200, 1500, 1700, 1600].The AI reasons, takes action (like searching), and then answers, combining thinking and doing.
For real-time info, research, or when the AI needs to “act” before answering.
Weather check:
Question: What’s the weather in Mumbai right now and should I wear a jacket?
Thought: I need to check the current weather.
Action: Search[Current weather in Mumbai]
Observation: It is 22°C and raining.
Answer: Yes, you should wear a jacket.Restaurant search:
Question: Find a good Italian restaurant near me.
Thought: I need to look up Italian restaurants nearby.
Action: Search[Italian restaurants near user location]
Observation: "Pasta Palace" is rated 4.5 stars and is 2 km away.
Answer: Try "Pasta Palace" – it's highly rated and close by.Tell the AI to act as a specific expert or character.
For tailored advice, customer support, or creative writing.
Travel advice:
You are a travel expert.
Suggest a 3-day itinerary for Rome.Nutrition advice:
You are a nutritionist.
Give me a healthy meal plan for a vegetarian athlete.Ask the AI the same question multiple times, then pick the answer that comes up most often for reliability.
For important or factual tasks where accuracy is critical.
Simple math:
What is 25% of 200?
Show your calculation.
(Run several times)Fact-checking:
Who is the current president of France?
(Run several times)Keep improving your prompt based on the AI’s responses until you get what you want.
For any task—always review and tweak your prompts.
Article summary:
First try:
Summarize this article.
Improved:
Summarize this article in 3 bullet points, focusing on the main arguments.Email drafting:
First try:
Write an email to my boss about my sick leave.
Improved:
Write a polite and concise email to my boss explaining that I am unwell and will be taking sick leave for two days.Tells the AI exactly how to organize its output.
Reduces the chance of hallucination or missing information.
Structured outputs (like XML or JSON) can be directly fed into databases, dashboards, or other applications.
XML Example:
Extract the following details from the text and format as XML:
<person>
<name></name>
<age></age>
<occupation></occupation>
</person>
Text: "Sarah Lee, a 29-year-old architect, lives in Toronto."JSON Example:
Summarize the article and return the result as JSON:
{
"main_points": [],
"recommendations": []
}
Article: [Paste article here]Markdown Table Example:
List three pros and three cons of remote work in a markdown table.Prompt engineering is the bridge between human intent and AI capability. Mastering it in 2025 means being clear, creative, and structured using the right techniques, adding context, and always thinking about ethics and security. As AI continues to evolve, so will the art of prompt engineering. Stay curious, keep experimenting, and you’ll unlock the full potential of AI for work, creativity, and beyond!
