Let AI Be your Prompt Engineer using a Simple Trick

In today's world, many of us frequently interact with AI models like GPT, spending significant time prompting, reading responses, and refining our queries. Through this process, we gain valuable experience and start to understand how "our" AI works, learning the best ways to phrase our requests to achieve desired outcomes.

The Challenge of Perfect Prompting

However, sometimes the AI gets stuck and doesn't quite understand what we're aiming for. Frankly, there are even times when we ourselves don't fully grasp what we want until we see the AI's output. In such situations, prompt engineering can become a truly challenging endeavor.

How can we create an effective prompt if we don't yet know all the specific details, or even more, if we're unsure what information to emphasize for a particular AI model?

For example, Gemini can be incredibly verbose, so if you don't explicitly state otherwise in your prompt, you might end up using a lot of unnecessary "tokens" Each AI model has its own strengths and weaknesses, and understanding these nuances is key.

Introducing Incremental Prompt Engineering

One remarkably simple solution to this problem is incremental prompt engineering.

With this technique, you don't need to provide the perfect prompt right from the start. Instead, you begin with something simple, then refine it iteratively until you achieve the ideal result. This perfected outcome then becomes the foundation for your ultimate, perfect prompt.

In this blog post, I'll demonstrate how you can not only refine your prompts to get great results immediately but also reuse the insights gained from these previous interactions to produce perfect results right from the get-go in the future.

The Core Idea

The concept is quite straightforward:

• Start with a simple prompt.
• Inspect the AI's output and refine your request.
• Once you have the perfect result, ask the AI itself to generate the optimal prompt for you.

And here’s how I do it: