Growth
You’ve probably heard someone say that time management is the key. schedules, blocks, wake up earlier, compress the day. people will say this is how you build a productive life, a good life, a life where you end the day feeling satisfied. I don’t use that term, and I have never mentioned it in the most recent years. and that’s because I think it’s the wrong game entirely.
It is not time management. it is energy management. and the moment you understand that distinction, of finally knowing that how it felt, the contrast between your sharpest days and your worst, everything I need to hear was this term, and then everything reorganized.
If the first thing to accept is that you’re not managing time, you’re managing energy , the second thing is asking where the energy is actually going. because it doesn’t just disappear. it goes somewhere else. and most of the time it’s going to things you’d never guess were costing you anything.
I don’t like productivity tips. they just give you the schedule. and that’s truly like naming the car should cruise in this highway, without understanding the mechanics of how and why.
Humans are full of love. full of empathy at their core. they were born to love, not to hate. the state of hate costs a man more than loving ever could, loving prospers, hate drains. you can feel this in the texture of any given day. the meaning you pull from it, the power you feel inside it, it traces back almost always to the love you’re carrying. for a mother, a father, a brother, a sister, a lover. a man is full of those emotions.
My friend Yahia once asked me how I coordinate between everything on my plate. not how I manage the volume, he understood that part. what he wanted to know was how I handle the context switch. one hour I’m deep in SQL queries and database design. the next I’m reading a machine learning paper. how does that work, he asked. how does the mind move between places that different without losing something.
When I was a kid, I wanted to learn almost everything. theology, physics, chemistry, computer science, artificial intelligence, biology, not as curiosity for curiosity’s sake, but as a genuine orientation. I was drawn toward knowledge as a category, not toward any subject inside it. I wanted to understand how things worked, and I wanted to understand how they related to each other.
The problem was the people around me. not their fault, but they were the evidence I kept looking at. no one I could see excelled at all of it. not even close. the picture the world was showing me was that you pick a lane, you go deep, and that depth is where the results live. every system I was in, school, university, the way people talked about careers, rewarded the vertical. the specialist. the one who knows one thing completely. and I was not that. I was the one who kept moving horizontally, touching everything, carrying a general picture without owning any particular depth yet.
Almost everyone can build a machine learning model now. you can prompt your way into a working pipeline in a matter of five minutes. building a model is not the problem, optimizing it is, understanding how and what it is doing are two completely different things, and that gap becomes very visible the moment you step into a competition.
I spent time participating in competitions on Kaggle and Zindi , joining teams, reading solutions, watching people work. and the pattern I kept seeing was the same: build a baseline, iterate, submit, repeat, and that’s fine, that’s how it works, but without ever asking why the iteration was moving in a particular direction. not having a compass. is what mostly happen. the leaderboard becomes the only signal, and you start optimizing for a number without understanding what the number means. that’s not learning. that’s just another form of guessing.