AI tools are everywhere. Whether you’re using platforms like ChatGPT, Claude, Gemini, or another generative AI system, you’ve probably seen firsthand how powerful these tools can be. They can write articles, generate captions, outline emails, analyze data, and even brainstorm ideas faster than most people can open a blank Google Doc.
But here’s the problem.
Most people are not getting the results they want. Their AI prompts feel like a shot in the dark. The output is bland, robotic, or just flat-out wrong. So they give up and assume AI just isn’t that helpful.
The truth? It’s not the tool. It’s the prompt.
Understanding how AI works is essential for crafting better prompts and achieving more accurate, useful results.
Learning to write effective prompts is the difference between average AI-generated content and something you could actually use, publish, or send out confidently. Prompt engineering is not just for developers or researchers anymore. It’s for everyday users, creators, marketers, students, and professionals who want to save time and get better results.
This podcast breaks down why your prompts might not be working and how to fix them fast.
Estimated reading time: 9 minutes
Table of contents
Why Prompts Matter More Than You Think
Think of an AI platform like a brilliant but literal intern. It can do amazing things, but it needs clear instructions. AI platforms integrate multiple large language models and features such as prompt management, cost oversight, and scalability, making it easier to adopt AI and giving users more control over AI-driven tasks. It does not know your goals, audience, preferences, or tone unless you tell it. This is where most users go wrong.
Your first prompt sets the tone for the entire exchange. If it’s vague, rushed, or unrealistic, even the most advanced AI models will struggle to give you what you want. On the other hand, a good prompt creates clarity, focus, and structure, giving the AI system a strong foundation to build from.
This is why prompt engineering is becoming such a vital skill. It allows you to guide the model’s focus, control the tone, and create more meaningful AI interactions. Whether you’re generating social posts or working on a business proposal, knowing how to write prompts the right way changes everything.
Let’s break down the most common mistakes and how to avoid them.
7 Reasons Your AI Prompts Suck
1. You’re Not Giving AI a Role
One of the fastest ways to improve your prompt is to start by assigning a role. Don’t just say “write a blog post.” Instead, say “You are a project manager writing a blog post for a team of startup founders.” By instructing the AI to act as a specific persona or expert, you can tailor responses to fit particular contexts, tones, or audiences, making the output more relevant and effective. This immediately sets the tone and gives the AI more context.
Why it matters: Assigning a role aligns the output with your expectations. It narrows the model’s focus and helps it filter its massive pool of training data into something more useful. Assigning a role also helps tailor the response to a specific audience, ensuring the content resonates with the intended readers.
Try this:
Bad prompt: “Write about leadership.”
Better prompt: “You are a leadership coach writing a short newsletter to young professionals about leading with empathy.”
2. You’re Not Being Specific Enough
Vague prompts produce vague results. If your instructions are too general, you’ll get AI-generated content that sounds like a Wikipedia summary. Specificity helps the AI understand what “good” looks like in your context.
Bad: “Make this sound better.”
Better: “Rewrite this paragraph to sound more conversational and use shorter sentences that fit a social media caption.”
Clarity wins. The more exact you are, the more refined the output becomes. Telling AI exactly what you want it to do—by specifying persona, task, context, and format—leads to much better results.
3. You’re Asking for Too Much at Once
If your prompt includes five unrelated requests, your AI is going to fumble. It’s better to break tasks into smaller steps than ask for a polished final answer in one go. Clearly defining each task with specific instructions helps the AI deliver more accurate and actionable results.
Think of it like a builder. You wouldn’t ask them to build an entire house in one day with no blueprint. Start with the foundation. With AI, complex projects that once took weeks or months can now be completed in a single day.
Instead of: “Write a 10-page research paper with quotes, citations, jokes, and a call to action.”
Try: “Help me outline a 10-page paper. Then we’ll write each section together.”
Small, focused tasks allow for better AI interactions and stronger results.
4. You’re Not Using Examples
AI thrives on patterns. When you provide examples, you give the model something to imitate or build on. This is especially helpful with tone, structure, or creative output.
Instead of: “Write a compelling intro.”
Try: “Write an intro like this: ‘What if the key to your success is the one thing you’ve ignored all year?’”
Showing beats telling. Give the AI something concrete to work with. Examples help the AI explain complex ideas more clearly by breaking down concepts and making them easier to understand.
5. You’re Not Asking for Multiple Options
Many users stop after one result. But some of the most powerful outputs happen when you ask the AI to try again with a different angle, tone, or format. AI tools are great at variation and iteration—but only if you ask.
Try this: “Give me five email subject lines. One should be clickbait, one should be emotional, one should be curiosity-driven, and two should be professional.”
This approach not only saves time but gives you more control over the final decision. Requesting multiple answers from the AI can improve accuracy and provide a broader range of options to choose from.
6. You’re Not Telling It What to Avoid
Just like a good writer needs guardrails, AI also benefits from knowing what not to do. Without that direction, it often defaults to clichés or generic filler.
Instead of: “Write an Instagram caption for a wedding photographer.”
Try: “Write an Instagram caption for a wedding photographer, but avoid phrases like ‘happily ever after’ and ‘love is in the air.’”
Clear boundaries help AI produce more original and relevant insights. Guiding AI with both positive and negative instructions shapes its reasoning process, leading to more accurate and relevant results.
7. You Stop After One Response
This might be the biggest mistake of all. The first result is rarely the best one. A good prompt session is a back-and-forth conversation. You provide feedback, refine your request, and guide the AI toward what you actually need.
For example:
- “Make this funnier.”
- “Now shorten it to 100 words.”
- “Now rewrite it in the voice of a Gen Z content creator.”
The best results often come from your second, third, or fourth interaction—not the first prompt. Think of it as creative collaboration, not automation. By iterating and refining your approach, you create better prompts that lead to improved AI responses.
Bonus Prompting Power-Ups
Ready to level up your prompting game even more? Here are a few bonus strategies that work across every major ai platform. Using a structured approach to prompting—by organizing your requests and instructions clearly—can significantly improve the accuracy and usefulness of AI responses.
1. Use Numbered Instructions
Structure your requests like a checklist.
Example:
“Write a LinkedIn post.
- Start with a strong hook.
- Include a personal story.
- End with a call to comment.”
2. Give It Format Instructions
Tell AI exactly how to shape the output. Want bullet points? A numbered list? Markdown formatting? Just ask.
3. Chain Your Prompts
Use previous outputs to build stronger results. For example:
- Step 1: “Help me outline a podcast episode about small church growth.”
- Step 2: “Now write a short description based on that outline.”
- Step 3: “Give me five YouTube titles for this episode.” When chaining prompts, it’s important to outline each point clearly to ensure the process is logical and the results are effective.
4. Ask It to Ask You Questions First
Before generating content, ask the AI to clarify your needs.
Prompt: “Ask me three questions to help you write a more accurate landing page.”
This forces you to think deeper and gives the model more direction. By encouraging the AI to provide context before starting, you ensure it has the background information needed to generate more accurate and relevant outputs.
These tricks not only save time but also unlock more creative potential in your AI workflows.
Level Up Your AI Game
AI tools are not magic. They are mirrors that reflect your input back to you. If your results are consistently bland, the fix is probably not in the model. It is in the prompt.
By learning to write prompts with more clarity, specificity, and creativity, you can turn average AI-generated content into something that feels professional and personalized. You will spend less time rewriting, and more time creating value.
Whether you’re using AI to brainstorm ideas, generate client-facing work, or simply organize your thoughts, great results come from great direction. Prompt engineering is no longer optional. It is the key to getting the most out of every AI interaction.
So the next time you open your favorite AI system, take an extra 60 seconds to rethink your prompt. Give it more context. Add clear instructions. Break it down. Use examples. And do not settle for the first response.
AI can help you move faster, think better, and create smarter. Understanding the different types of prompts and setting the model’s focus will lead to more effective and relevant results.
It all starts with the prompt.
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