I've always been the person in the room explaining things.
In college we would sit around in our study groups working through our homework and once the picture started coming together inevitably I was the one telling the whole story so everyone could see it from end to end. My grad school research was very abstract and I had to find the language to guide people through the flow of information through complex mathematical systems. And now I've spent the last nine years watching students struggle with ideas that were just out of reach, and figuring out how to close that gap.
What I've learned after a decade of doing this is that the barrier is almost never complexity. It's abstraction and the lack of a mental model that makes the idea meaningful. Build the model first and the rest follows.
There's an old saying in modeling and simulation: all models are wrong, but some of them are useful. Whether you're trying to communicate difficult research, train a team to work with AI as a genuine thinking partner, or figure out why something obvious to you isn't landing with your audience, let's find that useful space.