The meta approach to getting exactly what you want from AI
I stared at the ChatGPT interface, trying to figure out how to word my prompt. Again. We’ve all been there – knowing exactly what we want but struggling to get AI to understand and deliver. Then it hit me: Why am I trying to become a prompt engineer when I have a prompt engineering expert right in front of me?
That’s when I discovered what I call the “meta-prompting” approach – using AI to write better prompts for AI. It sounds simple, almost obvious in hindsight, but this technique has transformed how I interact with AI tools. More importantly, it’s given me consistently better results while saving hours of trial and error.
The best part? You don’t need any special knowledge or skills. You just need to know how to ask the right questions. Let me show you how to turn ChatGPT into your personal prompt engineering teacher.
The prompt engineering paradox
Here’s an ironic truth about AI: To get the best results, you need great prompts. But to write great prompts, you need expertise in prompt engineering. It’s a catch-22 that leaves many of us stuck in a cycle of trial and error.
Think about it – when you’re starting with a new AI tool, you’re essentially trying to become fluent in a new language while using that very language to learn it. It’s like trying to learn French by only speaking French. Possible? Yes. Efficient? Not really.
This is where the meta approach comes in. Instead of trying to master prompt engineering yourself, you leverage the AI’s built-in knowledge of how it works. Modern AI models like ChatGPT and Claude have been trained on vast amounts of data about prompt engineering and how to write effective prompts.
By asking AI to help write prompts, you’re tapping into this deep well of knowledge. It’s like having a native French speaker teach you French, instead of trying to figure it out on your own.
The process is surprisingly simple:
- Define exactly what output you want
- Ask AI to create a prompt that will generate that output
- Iterate and improve based on results
Let’s dive into how each step works.
Step 1: Define your perfect output
When I first started using AI, I made the classic mistake of being vague about what I wanted. But here’s what changed everything for me: Instead of starting with the prompt, start by writing down exactly what you want the AI to give you.
Think about format, style, tone, length, and structure. The more specific you are about your desired output, the better your results will be.
For example, instead of thinking “I want blog post ideas”, define it like this:
- Format: A list of 5 blog post ideas
- Topic area: Content marketing for SaaS companies
- Style: Each idea should have a compelling headline and 2-3 sentence description
- Special requirements: Include target keyword suggestions for each post
This detailed definition becomes the foundation for asking AI to write your prompt. It’s like giving detailed specifications to an architect before they design your house.
Here’s a simple template I use to define my desired output:
- What’s the end goal? (Generate ideas, write content, analyze data, etc.)
- What exact format should the output take?
- What style or tone requirements matter?
- What constraints or special requirements apply?
- What should the AI absolutely avoid?
With this clear picture in mind, you’re ready to ask AI to craft the perfect prompt.
Step 2: Ask AI to create the prompt
Now comes the meta part. Go to ChatGPT or Claude and say something like: “Can you write me a prompt that will generate [your defined output]?” Be sure to include all the specifications you defined in step 1.
Here’s how this looks in practice:
“Can you write me a prompt that will generate 5 blog post ideas for a SaaS content marketing blog? I want each idea to have a compelling headline and 2-3 sentence description, plus target keyword suggestions. The topics should focus on customer acquisition and retention.”
The AI might respond with a prompt like:
“Generate 5 blog post ideas for SaaS content marketing, focusing on customer acquisition and retention. For each idea, provide:
- An attention-grabbing headline
- A 2-3 sentence description explaining the main value points and takeaways
- 2-3 relevant target keywords for SEO Each post idea should be actionable and backed by specific examples or data points. Ensure topics address common pain points in the SaaS customer journey.”
This gives you a solid base prompt. But we can make it even better through iteration.
Step 3: Iterate and improve
The first prompt you get might be good, but it can always be better. Here’s where you can really leverage the AI’s knowledge:
“That’s helpful, but can you make the prompt more specific about generating unique angles? I want to avoid common topics that everyone writes about.”
The AI might then enhance the prompt with additional parameters:
“Generate 5 unique blog post ideas for SaaS content marketing that challenge conventional wisdom or explore underserved topics in customer acquisition and retention. For each idea:
- Write a headline that promises a specific, unconventional insight
- Provide a 2-3 sentence description highlighting the unique angle and key takeaways
- Suggest 2-3 long-tail keywords with lower competition but high intent Focus on emerging trends, counterintuitive strategies, or overlooked aspects of the customer journey. Each post should offer a fresh perspective backed by specific examples or data points.”
Advanced techniques
Once you’ve mastered the basic meta-prompting approach, you can take it further by creating reusable prompt templates and systems.
Ask AI to create template frameworks like this:
“Can you create a flexible prompt template I can use for any blog post topic that will consistently generate well-structured, engaging content?”
The AI might provide a template like:
“Write a comprehensive blog post about [TOPIC] that focuses on [SPECIFIC ANGLE]. Include:
- An engaging introduction that highlights [PAIN POINT/CHALLENGE]
- [NUMBER] key sections covering [ASPECT 1], [ASPECT 2], and [ASPECT 3]
- Actionable examples and case studies demonstrating each point
- Data points and expert insights to support main arguments
- A clear conclusion with next steps for implementation Tone should be [TONE] and length approximately [LENGTH] words.”
You can also use AI to create specialized prompts for different purposes:
- Research prompts that gather and synthesize information
- Editing prompts that improve existing content
- Brainstorming prompts that generate novel ideas
- Analysis prompts that provide strategic insights
The key is to save your best AI-generated prompts and templates for reuse. Create a personal library of proven prompts that consistently deliver results.
Final thoughts
By letting AI write your prompts, you bypass the steep learning curve of prompt engineering while getting expert-level results. The meta approach works because you’re focusing on what you know best – defining what you want – while letting AI handle the technical aspects of how to ask for it.
Start small with a single task you want to improve. Define your ideal output, ask AI to write the prompt, and refine it through iteration. Soon you’ll have a collection of powerful, personalized prompts that consistently deliver exactly what you need.
The best prompt engineer is the one sitting right in front of you, ready to help.