Most people say AI is overhyped.
They're wrong. They just have a prompts problem.
You know what you want — but you can't put it into words the AI actually understands. So you type something short. ChatGPT gives back something generic. You tweak it three times. Still not right. Eventually you just do the task yourself and think "AI is useless."
That's not an AI problem. That's a prompts problem. And the fix isn't complicated — you don't need a prompt engineering course. There's a simpler system.
Why Most People Get Poor AI Results
Tools like ChatGPT AI and AI Claude are built on LLMs — Large Language Models — developed by companies like OpenAI and Anthropic. These models are trained to respond to natural language inputs. Plain human language, not code, not commands — just words.
But when your natural language inputs are vague, the LLM has nothing solid to work with. It guesses. And guesses are always generic.
A ChatGPT prompt that actually works gives the LLM four things. Most people give it one. That's why results feel off.
| 🎯 Element | ❓ Question to Answer |
|---|---|
| What | What do you want? |
| Who | Who is it for? |
| Format | What format / length? |
| Context | What's the background? |
Cover all four and your AI output improves immediately. The problem is most people don't know how to fill all four before they start typing. That's what this method solves.
What Is Prompt Engineering — And Why You Don't Need to Learn It
Prompt engineering is the practice of writing clear, structured natural language inputs to get the best possible output from a large language model. It's a real skill. OpenAI and Anthropic both publish guides on it. There are full prompt engineering courses on every learning platform.
But here's the honest truth — you don't need any of that for regular work.
Learning AI prompt engineering properly takes time. For someone who just wants better results from AI ChatGPT or AI Claude today, a prompt engineering course is overkill.
What you need is a system that handles the hard thinking for you. And the funny thing? The LLM itself can build that system. That's the whole trick.
The 2-Tool Method — Use AI to Write Your Prompt
Simple idea — use AI to write your prompt before you use AI for the actual task.
Two tools. ChatGPT AI first, then AI Claude.
✏️ Step 1 — Figure Out What You Actually Want
Before opening any tool, write your task in plain language. Not "I want a blog post" — more like "1000-word blog post for people new to AI, friendly tone, one practical tip."
No tools yet. Just getting clear on what you're asking for.
✏️ Step 2 — Write Down the Key Points
Two minutes. Bullet points.
- Audience — who is this for?
- Length — how long?
- Format — bullet points, paragraphs, table?
- Tone — professional, casual, friendly?
- Things to include — must-haves
- Things to skip — what to avoid
🟢 Step 3 — Ask ChatGPT AI to Build the Prompt
Open ChatGPT AI (by OpenAI) and say:
"I need to [your task]. Here are my notes: [key points]. Write me a detailed prompt I can use with an AI tool."
ChatGPT AI turns a messy pile of ideas into something complete. Covers angles you missed. Builds structure you didn't think of.
After this step — a real, complete ChatGPT prompt.
🟣 Step 4 — Use Claude as Your Prompt Polisher
Copy what ChatGPT AI gave you. Open AI Claude (by Anthropic) and say:
"Here's a prompt I'm going to use. Make it clearer and more precise. Remove anything vague."
Claude doesn't just reorganize — it tightens. Language gets sharper. Vague parts get replaced with specific instructions. The LLM now has zero room to misinterpret.
✅ Step 5 — Run It
That's it. First-try output that actually matches what you wanted.
Why This 2-Tool Approach Works
ChatGPT AI and AI Claude are both powerful LLMs — but they think differently. Use their strengths together.
| ChatGPT AI (OpenAI) | AI Claude (Anthropic) | |
|---|---|---|
| Strength | Brainstorms wide | Thinks precisely |
| Good at | Covering every angle | Removing vagueness |
| Result | Nothing is missing | Nothing is fuzzy |
| Best for | Structure | Refinement |
- Use ChatGPT AI alone → complete but slightly vague
- Use AI Claude alone → sharp but sometimes missing something
- Use both in order → nothing missing, nothing vague ✅
Real Proof — Live Example Walkthrough
I used this method to build a complete landing page for an offline tuition company.
What I Asked ChatGPT AI (Step 3)
Write a prompt to create a simple landing page for a company that provides offline tuition classes. Build using HTML, CSS, and JavaScript. Design should be clean, modern, responsive. Include hero banner, about section, courses, benefits, testimonials, contact form, and a strong call-to-action.
ChatGPT gave me a solid prompt — but read the output carefully:
"Design the page with a clean educational theme, **modern typography, **appealing colors, **soft shadows, and easy navigation."
Words like "appealing colors" and "modern typography" are still vague. An LLM filling in those gaps will just guess. This is exactly where AI Claude comes in.
The Before & After — Side by Side
❌ ChatGPT AI output (vague):
"Design the page with a clean educational theme, modern typography, appealing colors, soft shadows, and easy navigation."
✅ Claude output (precise):
"Use a professional color palette built around **deep blue, white, and soft accent colors like green, gold, and violet. Choose distinctive and elegant typography — **avoid generic system fonts* — and pair a stylish display font with a refined body font imported from Google Fonts. Use rounded cards, soft box shadows, smooth transitions, and subtle background patterns to create a premium and polished visual identity."*
Every vague word got replaced with a specific, actionable instruction. The LLM now has zero gaps to fill with generic guesses.
The Final Output
✅ First try. Three files — index.html, style.css, script.js — exactly as specified. Zero revisions.
| 📦 Section | What Got Built |
|---|---|
| Hero Section | Dark navy theme, bold headline, Enroll Now + Book Free Demo CTAs, SVG illustration, stats badge |
| About Section | Company intro, three teaching pillars, years of experience badge |
| Courses Grid | 6 course cards — Maths, Science, English, Computer Basics, Competitive Prep, Social Studies |
| Contact Form | Two-column layout, real-time JS validation, success popup on submission |
| Testimonials | Auto-sliding carousel, star ratings, prev/next controls and dot indicators |
| Fully Responsive | Mobile-first design, hamburger menu, scroll-triggered animations, back-to-top button |
Comparison: All Prompting Methods
| Method | Time | Output Quality | Skill Needed |
|---|---|---|---|
| Random / vague prompts | 1 min | ❌ Low | None |
| Copying prompts from Reddit/Twitter | 5 min | ⚠️ Hit or miss | None |
| Taking a prompt engineering course | Weeks | ✅ Very High | High |
| Learning full AI prompt engineering | Months | ✅ Very High | Very High |
| ⭐ This 2-tool method (ChatGPT + Claude) | 10–15 min | ✅ High | None |
Tips to Get Even Better Results
🎯 Get specific in Step 1 — the clearer you are before touching any tool, the better everything else goes. Vague task in = vague prompt out.
👥 Always mention who the output is for — audience is the most powerful context you can give a large language model.
📐 Name the format explicitly — bullet points, paragraphs, table? Tell the AI. Don't leave it to guess.
🔍 If the result still feels off — ask Claude: "What's missing or vague in this prompt?" It'll tell you exactly what to fix.
💾 Save your good prompts — Notion, Notes, Google Doc. Build a personal library. You will use them again.
Try It on Your Next Task
Most people read something like this, think it's useful, and do nothing. Next time you open any AI tool — run this method.
| Step | Action |
|---|---|
| 1️⃣ | Write your task in plain language |
| 2️⃣ | List key points (audience, tone, format) |
| 3️⃣ | Build the prompt in ChatGPT AI |
| 4️⃣ | Polish it in AI Claude |
| 5️⃣ | Run it |
No prompt engineering course. No special skills. Just a smarter system.
💡 If this helped — share it with someone who keeps saying AI never gives them what they want.
About the Author
Dhaval Prajapati — AI Web Developer & MCA Graduate
I build AI-powered web experiences and write about practical AI workflows for developers.
🌐 Portfolio: dhaval-prajapati.onrender.com
📝 Blog: dhaval-prajapati.onrender.com/blog.html
💼 LinkedIn: linkedin.com/in/dhaval-prajapati-900b8818b
🐙 GitHub: github.com/dhavalMCA
Originally published on my portfolio blog → dhaval-prajapati.onrender.com/blog-single.html?id=b1
