🌟 What Is Prompt Engineering?
Learn to talk to Artificial Intelligence like a pro – and get way better results.
Prompt engineering is the art of asking questions in a way that makes AI more useful. You’re not programming – you’re communicating. Clear, creative prompts = better answers. It’s about shaping your requests so that you guide the AI toward giving you output that’s accurate, useful, and styled how you need it. Think of it as crafting the perfect instruction to a very capable, very literal assistant.
Let’s explore the most effective AI prompt engineering techniques.
🎯 The 3 Levels of Prompting
- Start with direct, easy-to-understand language. Make sure your requests aren’t ambiguous. Think about what you actually want: do you want a list, an explanation, a summary, a script? Ask for that specifically. Also, framing your request with a role helps the AI respond in a more focused way. “You are a science teacher. Explain how photosynthesis works to a 10-year-old using emojis.”
- Style, Tone & Format. Once you understand how to be specific, try playing with style and structure. Want it to sound funny? Formal? Like a news article? Say that. Also, think about output format — do you want it in bullet points, as a poem, or in a dialogue? “Act like a startup founder pitching to investors. Explain my app idea: a social network for introverts that encourages offline meetups.”
- Multi-Step and Creative Flows. At this level, you can start combining prompts into workflows. Ask the AI to break things down, reason step-by-step, or even evaluate and improve its own answers. This level is great for writing, coding, planning, or ideating across multiple stages. “Generate 5 names for a meditation app. Then rank them by uniqueness and write a tagline for the best one.”
⚠️ Common Mistakes
- Too vague: “Tell me about marketing” → What type? For whom? In what format?
- Overloaded prompts: Avoid asking for too many things at once. Break it up.
- Forgetting to iterate: If the answer is not perfect, ask for tweaks. Don’t restart from scratch!
- Missing context: The model doesn’t know your goals unless you tell it.
📚 Prompting Glossary
- Zero-shot: Asking a question without giving examples.
- Few-shot: Giving a few examples in your prompt to set the format or tone.
- Chain-of-thought: Asking the model to explain its reasoning step-by-step.
- Temperature: A setting that controls how creative or random the responses are (lower = more focused, higher = more varied).
🧐 AI Prompt Examples
- “You are an expert in [topic]. Explain [concept] in a beginner-friendly way using bullet points.”
- “Act like a news reporter. Write a short article about [event], keeping a neutral tone.”
- “List 5 tools for [task], and present them in a table with: Name, Cost, Pros, Cons.”
- “You are a UX designer. Critique the following website homepage for clarity and user flow: [paste link or description].”
🎯 AI Prompt Engineering Techniques
- Write Clear Instructions. The more specific you are, the better the result. Avoid vague instructions like “Tell me about technology.” Instead, guide the AI by being precise: “Summarize the advantages of using blockchain technology in supply chain management in under 100 words.”
- Provide Reference Text. When asking for an opinion or analysis, giving a source improves relevance and reduces hallucinations (retrieval-augmented generation, RAG). “Based on the article below, summarize the key trends in renewable energy: [paste article text]”
- Split Complex Tasks into Simpler Subtasks. Break big tasks into smaller, focused steps. For example, instead of “Write a marketing plan,” try: “List 3 potential target audiences for our new product.”, “For each audience, describe a marketing channel that would reach them effectively.”, “Now create a 3-paragraph plan using that information.”
- Give the Model Time to Think. Use step-by-step prompting for better reasoning and accuracy. Try phrases like: “Let’s solve this step by step: What are the key causes of inflation, and how do they interact?”
- Use External Tools. Some tasks are enhanced by pairing an AI with other tools. For instance, use real-time data, code, or charts for a complete solution. “Using the latest data from the UN, summarize the top 5 refugee host countries in a markdown table.”
- Test Changes Systematically. Prompt engineering is iterative. Change one variable at a time – wording, formatting, or constraints – then test and compare outputs to find the most effective version. “Draft a 1-paragraph product description in 3 different tones: playful, formal, and persuasive.”
- Prompt: “Tell me about Rome”. Response: General history and tourism info.
- Prompt: “Write a travel blog post from a first-time visitor’s perspective about eating pasta in Rome.”. Response: Vivid, story-like, specific writing.
📏 The R.I.C.E. Formula
- Role: Who should the AI pretend to be?
- Intent: What’s the goal of this prompt?
- Constraints: Word count, tone, format?
- Examples: Give a few samples if needed.
🔧 Debugging a Bad Prompt
- Was the instruction clear and complete?
- Did you specify a format or style?
- Did you ask too much at once?
- Try breaking the prompt into smaller steps.
💬 Chaining Your Prompts
AI remembers previous context during your session, so you can build more complex responses in steps. Try:
- “Great – expand idea #2 into a short paragraph.”
- “Now rewrite it with more humor.”
- “Add a quote from a fictional character.”
🤷 Forget Everything You Just Read
Or not. It’s actually very useful info! However, crazy as it sounds, why not get the AI to generate the prompt for you? Here’s an example that does exactly that (replace anything in curly braces with your requirement)…
You are a prompt engineer assistant. Generate an AI prompt that will help a language model achieve the following user goal:
“{goal}“
The tone should be {tone}, intended for a(n) {audience} audience. The prompt should be {length} in length and provide {detail} detail. Format the response as {a single sentence} prompt ready to be used in an AI model.
🚀 Final Advice
Think of AI like you would a brilliant intern. It has endless potential, but you need to give it clear instructions, context, and room to iterate. Don’t treat your first result as final. Ask it to improve, clarify, rephrase, or try again. Prompting is a skill – and with a little practice, you’ll be guiding the AI like a pro.
📋Prompt Engineering Technique Summary
| Technique | What It Means | When to Use It | Example Prompt |
|---|---|---|---|
| Clear Instruction | Be specific about format, tone, and goal | Anytime you want precise, relevant output | “Summarize blockchain in 100 words for a teen audience.” |
| Role Assignment | Tell the AI to act as someone with a specific role | To get tone or expertise that matches your goal | “You are a nutritionist. Explain the keto diet.” |
| Style & Format Control | Define the tone or structure of the response | When you need it funny, formal, bullet-pointed, etc. | “List pros and cons of remote work as a table.” |
| Step-by-Step Prompting | Ask for logical reasoning steps | For planning, logic, math, or troubleshooting | “Let’s solve this step by step: What causes inflation?” |
| Few-Shot Prompting | Give examples to set tone or format | When structure or tone needs to match specific examples | “Translate these sentences casually…” |
| Chain-of-Thought | Encourage the model to explain its reasoning | For depth, accuracy, and learning use cases | “Explain your thinking before choosing the answer.” |
| Provide Reference Text | Include relevant content to guide the response | To reduce hallucinations or ground outputs | “Based on the article below, summarize key energy trends.” |
| Break Down Tasks | Split broad tasks into smaller steps | When a prompt feels vague or overloaded | “First list audiences, then write a pitch for each.” |
| Iterate and Refine | Tweak and rephrase to improve results | When initial outputs are close but not perfect | “Now rewrite it in a more playful tone.” |
| Use External Tools | Augment with real data, code, or APIs | When AI needs support from dynamic content | “Using latest UN data, list refugee host countries.” |
Learn more about Prompting Strategies
Here’s an article from OpenAI all about the subject:
- https://platform.openai.com/docs/guides/prompt-engineering/six-strategies-for-getting-better-results
Lastly, can an AI recognise its own work?
I asked ChatGPT about the authorship of this article. With the prompt:
“Can you read this article and analyze the language, tone etc.? Can you determine whether the author was a human or an AI? Can you explain your reasoning? Does the language style change implying more than one author? https://www.flatcoder.co.uk/mastering-prompt-engineering/”
The reply from ChatGPT concluded:
The article “Mastering Prompt Engineering” is well-crafted, informative, and accessible. Its consistent tone, personalized examples, and practical advice suggest it was authored by a human with experience in AI and prompt engineering. There are no indicators of multiple authors or AI-generated sections.
Which, for the record, is completely wrong. Quite a large percentage of this article was written by ChatGPT. Ergo, what’s wrong with the prompt above?
Happy prompting…