Experiences make us observe, comprehend, analyse, and eventually draw inferences. If we ask the most basic question of why we did anything on earth, when it all started, I don’t think it was for money. I don’t think it was for a good living. It might have been for survival. How did one feel hunger? How did we know we had to eat? What did we do? Did we crave a Michelin-star dish? When we had to commute, did we ask for a high-speed flight? I think all we did was take one step at a time. We experienced something, we tried something, we learnt from it, and then we tried again. Is this the crux of problem-solving?

Where is research heading? Does it still make sense that every research paper begins with the same ritual? Does every piece of research need to be packaged into the same formal sections? Does every discovery really begin with an introduction and end with a conclusion? Programming began as a way of thinking. Over time, we created paradigms, conventions, design patterns, frameworks, and best practices so that more people could write software. In doing so, programming became easier to learn, but somewhere along the way we also forgot that programming is fundamentally about solving problems, not following patterns.

Consider an example of a teacher walking down a row of desks, searching for the highest test score in the class. The teacher picks up the first student's paper. Since it’s the only one the teacher has seen, it represents the highest score so far. As the teacher moves to the second desk, a comparison is made between the new score and the one in memory. If it's higher, the teacher updates the memory; if not, the teacher retains the old score. After comparing the scores of fifty students, the value that the teacher is holding on to is always the maximum score encountered up to that exact moment. In computer science and algorithm design, we call this reliable anchor an “invariant”.

Abstractions, help us focus on what we want to achieve instead of worrying about every tiny detail underneath. Now what does this mean? Think about the case of ordering food, then (not very long ago) and now. Ordering food earlier involved many small steps, delays, and uncertainties. The same task today can be completed with just a few taps on a screen. Let us observe both situations closely and understand what has changed, something that most of us already know but never analysed with the devil details.

Are we forgetting how to be curious? I mean, if there isn’t a puzzle anymore, there should not be any curiosity anymore as well. Not knowing answers was not considered as a defect in the human system. It was a hook that made thinking possible. Dewey’s greatest concern, in his book ‘How we Think’ wasn't the acquisition of facts; rather, it was about the cultivation of habits of thinking. He believed education was the process of training the mind to sit with uncertainty and to test claims against evidence. I will ask again, are we forgetting how to stay curious?

Did we abandon calculators because they reduced mental arithmetic? No. We learned when to use them and when to think without them. Did we stop writing things down because it reduced memory effort? No. We learned what to remember and what to record. Did we stop using spell check because it corrected our mistakes? No. We learned to write better while still paying attention to language. Did we stop using autopilot because it reduced manual control? No. We learned when to trust automation and when to take control. It feels like we have a pattern and also we don’t.

Take a sentence and convert its words into numbers so the computer can process them, then organize them so it understands the order. Next, look at the sentence as a whole to capture the overall meaning, while also letting each word relate to others to identify what matters most. At the same time, process the sentence in multiple ways to refine the understanding without losing context. Then begin forming the response one word at a time, without looking ahead, while continuously checking back with the original sentence to stay aligned. At last, choose the most likely next word at each step to build a clear and meaningful answer.

AI gives us “wow” content in seconds, and we often mistake it for meaning and clarity. We open a tool, ask a question, and within seconds information comes back that does feel magical. This magic appears to have solved our problem. The solution reads well (we might not read it completely). It sounds right (we might not have the knowledge to evaluate). It feels like intelligence (until we try to use it). But what exactly is that “wow”? That wow is only a first impression and like most first impressions, it is also incomplete.

I am talking about the time when purchases happened face-to-face. Oh wait, they still do happen. A product hunt today has become easy. Purchases can now happen online. Reviews, recommendations, and price comparisons have always been there. AI today is helping to take the next leap. That already gives us enough information to decide what has stayed and what has changed. Did the markets disappear? No. The way we make decisions has changed. As we can see, markets have stayed, products have stayed, and human needs have stayed. The speed, scale and the way we access the information has changed and that leading to how we take the decisions.

We all live with two dimensions of meaning in how we understand things. One meaning is given by the world in the form of standard definitions, while the other is internalized through our thoughts and lived experiences. The ability to recognize both and reflect on how we interpret them, when to use what, may be is what we call consciousness. Let’s take a pause here.