I have a to-do list. Somewhere. Finding it has been on my to-do list for quite some time now.

If our classrooms are still stopping at teaching bubble sort, I think that's a grave mistake. The classroom should go further: “Hey look, this is what an LLM is doing. Here is the code. What do you understand about it? What would you accept? What would you question?” What kind of data are we sorting? How large is it? Is it already nearly sorted? What does “improve” mean here? Now go ahead, use an LLM, and improve it. Then explain what you have changed, test whether it works, and justify why it is better for this situation. That, I think, is how it should go. Maybe.

A lot has changed in software engineering, and we are still trying to understand whether its older principles remain relevant. Coding has evolved significantly, but I think every major technological shift follows a similar pattern. We begin by exploring possibilities, often through brute force. As we understand the limitations, we start introducing principles, structures, and methods to optimise what we have built. Perhaps software engineering is going through a similar transition today.

As an education design lab, we keep discussing several things around teaching, learning, assessments, scaling quality learning, and all sorts of things. Sometimes we go back to the fundamental level of questioning: are we even needed in a classroom? What happens in a classroom? But at times we also have other discussions which are not at all related to education design, but are definitely a sign of how nerdy our brainstorming conversations get. Here is one example.

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.