Like me, you’ve probably been dazzled by the strides recently made in the sector of Generative AI. It appears like we live in a science-fiction reality, where machines understand us.

At the center of this revolution, OpenAI’s GPT-4 has emerged as a marvel within the realm of language models. As someone who had the privilege of fooling around with it, I can testify to its astonishing capabilities.

In this text I would like to share a method that intrigued me quite rather a lot. In literature it’s referenced because the Flipped Interaction Pattern, and I discovered it to be a really powerful framework to assist in problem solving tasks. The distinct aspect of this prompt engineering method lies in its “reversed” (i.e. flipped) approach: as a substitute of directly asking for answers or solutions from the AI, it primarily focuses making the AI deliver the best questions that might effectively drive us towards our desired solution.

In this text, I’ll walk you thru how it really works, why it’s useful, and supply real-life examples of its effectiveness. By the tip of it, I hope you’ll be equipped with a useful technique – one which may be applied to an unlimited array of problems, possibly with results which will surprise you.

In today’s world, the depth of our knowledge can often be in comparison with a pool — long and narrow. We dive deep into some specialties, becoming experts in some specific domains. This hyper-specialization allows us to excel in our respective fields, but at the identical time, it might leave us feeling lost after we encounter problems outside our areas of experience. As a software engineer, I could also be well-versed in algorithms, data structures, and coding, but put a spade in my hand and ask me to tend a garden, and I’ll transform any green right into a wasteland.

That is where the Dunning-Kruger effect may come into play. As per this psychological hypothesis, there’s a cognitive bias where individuals with low ability at a task…