The “prompt engineering” craze is overhyped. Seminars, gurus, and courses all promise that if you just ask AI the perfect question, you will get the perfect answer.
Here is the problem. Prompt engineering trains you to ask, not to learn.
I call this the J.A.R.V.I.S. Complex. Like Iron Man’s assistant, you ask and instantly get an answer. It feels powerful, but it makes you passive.
In my research on AI-Augmented Exploratory Learning (AAEL), I have found that the real value comes when we stop chasing perfect prompts and start using AI as a partner in learning.
Here is the shift:
Explain the problem to me. Make sure I understand it clearly.
Show me how to solve it. Walk me through the steps or methods.
Check my work. Here is my attempt. Give me feedback.
Take real estate as an example. Let’s say you want to forecast how many homes will sell in a specific zip code.
A prompt engineer would ask, “Build me a model to forecast sales in 85254,” and copy-paste the result.
With AAEL, you would instead ask: “Explain how sales forecasting works in real estate,” then “Show me how to build a model using my zip code data,” and finally, “Here is my attempt at the model. Can you critique it?”
The second approach not only gives you a forecast, it teaches you how to build, refine, and use the model again in the future.
That is how AI becomes a coach, not just a shortcut. And that is how you build skills that last beyond a single answer.
So before you spend money on the next “prompt engineering” seminar, ask yourself: do you want better questions, or do you want to actually learn?
Robert Foreman
Doctoral Student in Educational Technology | Data Analytics Consultant
| Real Estate Broker & Loan Officer
📧 forem1r@cmich.edu
🌐 NhanceData.com
📞 480-415-0783