AI is not just one story

When I learn something new, the last step is to put it into practice. Only then do my understanding of concepts, their relationships, and the steps of a process actually change. That is when learning becomes real.

The community I am in makes that hard to forget. People study, practice, and use what they learn. If I dismiss a lesson, I soon see classmates pull ahead. It has happened often enough that I feel both regret and a desire to catch up. In this environment, reminders to keep learning arrive every day. As AI develops, I need to work harder to stay involved.

For the past three weeks, our community has focused on applying AI. I have gone almost all in. I ask advanced tools about things I do not understand, use them in serious investment research, and work with them on career decisions. That raises a difficult question: where should I draw the boundary around AI’s use? Asking an AI for an answer is easy; knowing how to ask, and what to do with the answer, is harder.

After listening to my teacher’s latest talk and trying out the ideas today, I began to find my own answer. AI has helped with repetitive tasks, but it has also widened what I can search and notice. I encountered concepts and categories I would not have thought to look for. With a better framework for thinking, I feel more able to direct the interaction myself. That has given me confidence.

Looking back, finding opportunities in the AI era is still closely tied to how well I think.