To ease that fear even a little, and to understand AI better by actually using it myself, I started an AI Study group. It began fairly casually with MBA classmates, and while it launched with real ambition last year, it didn’t run as well as I’d hoped.
We met for an hour on weekend mornings each week over Zoom, and for the most part I was the one doing the explaining. But turnout kept dropping, and above all, it lacked the feeling of moving forward together.
After mulling it over during the winter, I changed the format and restarted it in February. It turned out to be far more satisfying than I expected.
Personally, the biggest payoff was that studying in order to teach made me learn even more myself. Not long ago, over a meal with a senior colleague from my previous company, I heard the line, “the fastest way to learn something is to teach it to someone else” — and I felt that firsthand.
The second change was cutting the frequency to once a month and switching to in-person sessions. It raised the sense of presence and engagement, and let us exchange feedback much more nimbly.
These two changes gave a clear sense of impact. The people who joined told me they were getting something out of it too, which gave me a real sense of reward.
It wasn’t anything grand. We demoed better ways to use Gems along with a few practical examples, and I wrapped up by sharing my personal experience across several foundation models — why I currently rely mainly on Google Gemini, and the strengths and weaknesses of each model.
There’s real fun in learning and real reward in sharing, but a vague sense of fear still lingers.
Even so, I think that if I keep using AI directly for even 30 minutes a day, experience the new updates as they come, and get a clear grip on my own way of using it and its limits, that vagueness will gradually fade.
This isn’t very organized, but I wanted to jot down today’s experience, feelings, and thoughts briefly before they faded.
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