The important thing is not to stop questioning. Curiosity has its own reason for existing. One cannot help but be in awe when he contemplates the mysteries of eternity, of life, of the marvelous structure of reality. It is enough if one tries merely to comprehend a little of this mystery every day.
— Albert Einstein
Learning has been a discussion topic present in countless conversations throughout my life. At school, I wondered why learning seemed to come more naturally to some of my classmates. At university, I questioned whether the way I was being taught actually induced learning or if I was just ticking semesters off.
And now, in this strange, thrilling age of large language models, the landscape of learning has changed again. AI opens doors faster than we can name them. It can explain, summarize, generate, and even "reason". It can make you feel like you’re learning, even when you’re just scrolling through someone else’s understanding.
That’s the trap: the false sense of learning. When the answers come too easily, curiosity quietly atrophies.
The hard parts, the digging, the debugging, the small moments of friction where understanding actually forms, begin to fade.
I remember my father telling me to look things up in the encyclopedia myself, he said I’d remember them better if it cost me a bit of effort. Thank you, dad!
The best problems are still the ones that make you forget to eat lunch because your brain is fully alive, wrestling with the unknown.
That’s intrinsic motivation. It’s the hunger not for completion, but for comprehension.
AI
I believe in AI, I default to it.
But I believe even more in agency, the will to know why things work, not just that they do.
We stand at a strange frontier.
The model writes, builds, tests, and ships. It answers with perfect confidence, fluent and certain. But fluency isn’t understanding, and certainty isn’t truth.
You don’t need to know how SGD or Attention works to stay sharp. But you do need the will to question what the model gives you. To read between its confident lines. To pull at the seams of its reasoning until you see the pattern underneath. Agency is not about knowing every detail of how the system works, it is about refusing to take its word as final. It is about asking why this output? why this choice? what is missing?
It is about learning to use AI to amplify your thinking, not replace it.
The model accelerates you, but you decide the direction.
Trace the reasoning, refine the prompt, build intuition around what it tends to miss. Be passionate about understanding what it did, not just grateful that it did something. Master this new skill. Benefit from it.
That’s how you stay in control. That’s how you stay an engineer.
Yes, default to AI.
But let that be the start of inquiry, not the end of it.
Because in the age of infinite assistance, understanding is rebellion.
And the will to learn is what keeps us alive.