Tag: prompt engineering tips

You type a question into ChatGPT. You wait. The response is… fine. It’s generic, a little surface-level, and frankly, something you could have found with a quick Google search. You sigh, close the tab, and think, “Is this really the technology that’s supposed to change everything?”

Sound familiar?

You’re not alone. Most people use powerful AI tools like ChatGPT or Gemini like a slightly smarter search engine. They ask isolated, vague questions in new chat windows, hoping for a miracle. The problem isn’t the AI; it’s the input. You’re asking it to fly a plane but only giving it the coordinates for a street address.

The future, however, will significantly favor those who have learned the art of prompt engineering. This isn’t a niche tech skill; it’s the new literacy. I see a world where doctors prompt AI to diagnose complex cases, engineers use it to solve intricate problems, and entrepreneurs leverage it to build business plans from the ground up.

The difference between those who get mediocre, generic responses and those who get breathtaking, expert-level results boils down to a simple, repeatable framework. This isn’t a hack; it’s how these large language models (LLMs) are designed to be used.

Let’s ditch the wishy-washy questions and learn how to command. Here is the six-part formula to 10x your productivity with AI.

The Foundation: Why Your Prompts Fail

At its core, an LLM is a prediction engine. It guesses the next most likely word in a sequence based on a colossal amount of data. When you ask a vague question like “Give me investing advice,” it has nothing to latch onto. It defaults to the most average, general response possible because it has no context about who you are, what you need, or why you’re asking.

Your goal is to narrow the infinite possibilities. You do this by providing constraints, background, and a clear direction. Think of it as replacing a spotlight with a laser beam.

The 6-Part Prompting Framework

To illustrate, we’ll build a single, powerful prompt throughout each step. Our goal: get expert financial advice tailored specifically to us.

1. The Command: Start with a Verb, Not a Question

The first word of your prompt sets the tone. Ditch “can you,” “will you,” or “give me.” Start with a strong, action-oriented command.

• Weak: “Can you give me some investing advice?”
• Strong: “Recommend a diversified investment strategy.”

This simple shift transforms your prompt from a casual request into a professional directive. The AI now knows an action is required.

Power Verbs to Use: Analyze, Create, Design, Develop, Recommend, Generate, Evaluate, Outline, Write.

2. The Context: The Secret Sauce of Great Prompts

If you take only one thing from this guide, let it be this: more context is always better. Context is the background information that allows the AI to move from generic to genius. Use the “Rule of Three”: Who, What, and When.

Let’s upgrade our command with context:

• Without Context: “Recommend a diversified investment strategy.”
• With Context: “Recommend a diversified investment strategy for a 32-year-old freelance graphic designer (who) with a moderate risk tolerance earning $85,000/year (what), saving for a house down payment within 5 years (when).”

Instantly, the AI has a persona, a financial reality, and a clear goal. The advice will be infinitely more tailored.

3. The Logic: Shape the Output’s Structure

You’ve told the AI what to do and why. Now, tell it how to do it. Define the reasoning structure you want to see. Do you want a list? A table? A step-by-step plan? Without this, you might get a long, rambling paragraph when you needed a concise bullet list.

Let’s add logic to our prompt:

• Addition: “…List the proposed asset categories, explain the percentage allocation for each, and briefly justify the rationale behind each choice.“

Now the AI knows exactly how to format its thinking. It will create an organized, logical, and instantly usable output.

4. The Roleplay: Assign an Expert Persona

This is where the magic happens. The way you prompt doesn’t just affect what the AI says; it affects who it becomes. You can channel decades of expert knowledge in a single sentence.

Assign a role to transform generic answers into expert-level insights.

• Addition: “You are a certified financial planner (CFP) with 15 years of experience specializing in helping freelancers and creatives achieve home ownership.“

Boom. The AI’s entire response will now be filtered through the lens of this expert persona. It will use appropriate terminology, consider specific challenges faced by freelancers (like variable income), and deliver advice with authority and depth.

5. The Formatting: Demand the Final Presentation

This is the polish on the logic. Specify the final format you need. This is crucial for workflow integration. Do you need to copy-paste this into a document? Share it in a Slack channel? Save it as a reference?

• Addition: “Format your final response as a clear, bolded heading for each section with bullet points below, suitable for saving in a note-taking app.“

You can ask for tables, Markdown code, JSON, or even a script outline. You are the director; tell your AI assistant how to dress the set.

6. The Secret Weapon: The Question Loop

This is the single biggest hack that separates pros from amateurs. After you’ve built your entire prompt, add this final command:

• The Power Move: “Before you provide your recommendation, ask me 10 questions that would help you tailor this strategy even further.“

Why is this so powerful? The AI will immediately identify the gaps in your initial context. It might ask:

• “What is your current debt-to-income ratio?”
• “Do you have an existing emergency fund?”
• “How much have you saved for the down payment already?”
• “Is your ‘moderate’ risk tolerance aligned with a 10% or 15% annual growth target?”

These are nuances you may not have considered. Answer these questions. Then, say, “Okay, based on my answers, ask me 5 more clarifying questions.” Keep this loop going until the AI starts repeating itself. The moment it has no new questions, it has all the information it needs to produce a result so personalized it will feel like you paid a four-figure consultant’s fee.

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Artificial Intelligence is transforming the way we work, create, and solve problems. But here’s the secret most people miss: the real power of AI doesn’t just come from the model itself—it comes from how you talk to it. In other words, better prompts create better results.

If you’ve ever felt like AI gave you generic, confusing, or completely wrong answers, the problem usually wasn’t the AI—it was the prompt. Crafting strong AI prompts is a skill, and once you learn it, you’ll unlock the ability to use AI like a pro.

In this guide, we’ll break down the best AI prompting techniques, including prompt chaining, meta-prompting, debugging prompts, and a simple five-box framework you can use for any task. By the end, you’ll know exactly how to write prompts that give you accurate, creative, and usable outputs every time.

Why AI Prompts Matter More Than You Think

When most people first use tools like ChatGPT or MidJourney, they type in a short, vague question like they’re searching Google. Then they’re disappointed when the answer is bland or misses the point.

That happens because AI isn’t a search engine—it’s a collaborator. The clearer you are with instructions, context, and format, the better the output. Think of prompting as a translation layer between your ideas and the AI’s language.

The difference between a bad and great prompt is like the difference between asking:

• “Write about marketing.”
  vs.
• “Act as a CMO. Write a 400-word LinkedIn post on how small businesses can use TikTok to reach Gen Z, using a professional yet approachable tone. Include 3 actionable tips and end with a call to action.”

See the difference? Same AI, completely different results.

Common Mistakes That Lead to Poor AI Results

Before we dive into frameworks and techniques, let’s cover the five biggest mistakes people make when writing AI prompts:

1. Being too vague – Short, unclear prompts produce generic answers.
2. Treating AI like Google – Asking for facts instead of directing it to create a specific output.
3. Polite fluff – “Please kindly write if you don’t mind…” wastes space. Be direct.
4. One-shot overload – Stuffing everything into a single long prompt without breaking it down.
5. Not iterating – Accepting the first draft instead of refining and guiding the AI.

The good news? All of these are easy to fix with the right approach.

The Five-Box Prompt Framework

One of the simplest ways to structure an effective prompt is the Five-Box Framework. It ensures you include all the necessary information without overloading the AI.

Here’s how it works:

1. Role – Who should the AI act as? (teacher, marketer, lawyer, travel guide, etc.)
2. Task – The action you want it to take. Use strong verbs (write, explain, summarize, analyze).
3. Context – Audience, background info, or data the AI needs to know.
4. Constraints – Rules for tone, word count, inclusions/exclusions.
5. Output Format – How the answer should look (bullet points, essay, table, JSON, etc.).

“Act as a professional recruiter. Write a 200-word LinkedIn job post for a remote software engineer. The tone should be friendly but professional. Include role responsibilities, required skills, and a closing call-to-action. Format it in bullet points.”

This structure reduces confusion and delivers high-quality results almost every time.

Powerful AI Prompting Techniques

Once you master the basics, you can take things to the next level with these advanced strategies:

1. Prompt Chaining

Instead of asking AI to do everything at once, break tasks into smaller steps. Each output becomes the input for the next step.

Example workflow for customer communication:

• Step 1: “List possible customer frustrations when a delivery is delayed.”
• Step 2: “Write professional responses addressing those frustrations.”
• Step 3: “Draft a customer email using the best response.”
• Step 4: “Write a script for a follow-up phone call.”

This step-by-step approach improves accuracy and creates polished final results.

2. Meta-Prompting

Sometimes you’re not sure how to ask the question. That’s where meta-prompting comes in. Instead of writing the final prompt right away, you ask the AI to help you design the best prompt.

Example:

• “Interview me to get the details you need to write a strong blog post outline.”
• “Suggest three different prompt styles to analyze this data.”

It’s like having the AI act as a prompt coach before it becomes the writer.

3. Debugging Prompts

Not happy with the first output? Don’t give up—debug your prompt.

Tips for debugging AI prompts:

• Clarify ambiguous words – Replace “it” or “they” with exact references.
• Add or tighten constraints – Specify tone, length, or style.
• Show an example – “Format it like this sample paragraph.”
• Use negative rules – “Avoid jargon and overly complex words.”
• Change the model – Some models are better at coding, others at writing.

Treat the first draft like a rough sketch, then refine.

Real-World Examples of Better AI Prompts

Let’s look at how these techniques apply in real scenarios:

• Email to a client:
  Bad prompt → “Write an email apologizing for a delay.”
  Better prompt → “Act as a project manager. Write a 150-word email to a corporate client explaining a 2-week delay due to supply chain issues. Include steps we’re taking to resolve the issue and end with a reassuring tone.”
• Image generation:
  Bad prompt → “Draw a dog.”
  Better prompt → “Create a realistic illustration of a golden retriever running on a beach at sunset. 16:9 ratio, photorealistic style, avoid cartoon features.”

Small tweaks, massive difference.

How to Build an AI Prompting Habit

Like any skill, writing better prompts takes practice. Here are a few ways to build the habit:

• Before typing, ask: What do I want? Who’s it for? What format?
• Always use the Five-Box Framework.
• Start with a draft prompt, then refine through iteration.
• Try prompt chaining for complex workflows.
• Use meta-prompting when you’re stuck.

With repetition, you’ll find yourself naturally writing sharper, more effective prompts.

Final Thoughts

AI isn’t replacing humans—it’s amplifying them. But the results depend on how well you can communicate your intent. Mastering the art of prompting is like learning a new language: the clearer and more structured you are, the better the AI can help you.

By using the Five-Box Framework, prompt chaining, meta-prompting, and debugging techniques, you’ll consistently get outputs that are not only accurate but also tailored to your goals.

So the next time you open ChatGPT, don’t just type a short question. Treat it like a partner. Guide it, refine it, and iterate with it. The difference in results will surprise you.

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