Introduction
Prompting is quickly becoming one of the most valuable skills in the age of AI. Whether you’re using ChatGPT, Claude, Gemini, or any other LLM, how you ask determines what you get. Yet, most users fall into the same traps that lead to vague, unhelpful, or even wrong answers.
At Groath.ai, we work with AI every day to build smarter workflows, marketing agents, and creative tools — and we’ve noticed the same five mistakes come up again and again. Let’s go through them, with clear examples and quick fixes.
1. Being Too Vague
❌ Mistake: Asking things like “Write a blog post about productivity.”
✅ Fix: Add context, audience, tone, and goal. For example:
“Write a 500-word blog post about productivity for startup founders who struggle with focus. Keep it motivational but practical, and end with a call to action.”
Why it matters:
AI tools can’t read your mind. The more context you give, the closer the result will be to what you actually need.
2. Asking for Output Instead of Thinking
❌ Mistake: Jumping straight to the end result — e.g., “Write me an SEO plan.”
✅ Fix: Ask the model to think or plan first:
“List the steps you’d take to create an SEO plan for a B2B SaaS startup, then write the plan.”
Why it matters:
By asking for reasoning before writing, you get higher-quality, structured outputs — and avoid shallow or repetitive results.
3. Ignoring Iteration
❌ Mistake: Treating prompting as a one-shot task.
✅ Fix: Use conversation loops. For example:
“That’s a good start. Now make it more concise and add examples.”
Why it matters:
Prompting is a dialogue. Each round refines the output — like working with a designer or editor, not a search engine.
4. Not Defining the Role or Perspective
❌ Mistake: Saying “Explain SEO” with no context.
✅ Fix: Give the AI a role:
“You are an SEO expert explaining SEO basics to a beginner marketing intern. Use simple analogies.”
Why it matters:
LLMs can adapt their style and expertise — but only if you tell them who they’re supposed to be.
5. Forgetting Format and Constraints
❌ Mistake: Asking for content with no structure — e.g., “Summarize this article.”
✅ Fix: Add format and constraints:
“Summarize this article into 3 bullet points and one key takeaway, under 100 words.”
Why it matters:
Clarity in structure leads to clarity in results. Constraints make the model prioritize quality over length.
Quick Reference Table
Mistake | Example of a Bad Prompt | Example of a Good Prompt | Why It Matters |
|---|---|---|---|
Too Vague | "Write about marketing" | "Write a 400-word blog post about B2B marketing trends in 2025 for LinkedIn" | Context defines relevance |
No Reasoning | "Write an SEO plan" | "First outline the steps, then write the SEO plan" | Encourages structured thinking |
One-Shot | "Generate product names" | "Generate 10, then refine based on my feedback" | Iteration improves creativity |
No Role | "Explain blockchain" | "Explain blockchain as if to a 10-year-old" | Tone and complexity adjust accordingly |
No Constraints | "Summarize this" | "Summarize in 3 bullet points under 60 words" | Forces concise, focused output |
Pro Tip: Layer Your Prompts
Instead of writing one giant prompt, stack them logically. Start with research (e.g., “List 5 key angles for this topic”), then draft (“Now write the intro for the best angle”), then refine (“Make it sound more confident and modern”). This layered prompting mirrors real human workflows.
FAQ
Do I need to write long prompts for better results?
Not necessarily — you need clear prompts. Long doesn’t mean better; clarity and structure do.
Should I use fancy prompt frameworks (like RICCE or CO-STAR)?
They can help, but even simple structure (context → task → tone → format → constraints) works just as well.
How do I know if my prompt is good?
If you can read it and instantly understand what you’d expect as output — it’s good. If not, the AI won’t either.
What’s the fastest way to get better at prompting?
Practice with feedback loops. Ask the model, “How could I improve this prompt?” — and you’ll learn fast.
Can prompting replace real expertise?
No — prompting amplifies your expertise. The better you understand your field, the better your prompts (and results) will be.
Conclusion
Prompting is not just about talking to AI — it’s about communicating ideas clearly. Like any skill, it improves with feedback, reflection, and creativity. Start small, iterate often, and remember: AI is only as good as your next question.
👉 Want to level up your prompting and automation skills?
At Groath.ai, we help teams turn prompting into performance — building AI agents, tools, and workflows that actually work.