Written by Garth Phoebus
We often mistake training for the destination.
It isn’t. Vision is.
Training matters—but it’s transportation, not the end state.
Think of it like an Uber. You don’t get in just to ride. You get in because you know where you want to go. The route may change. The vehicle may change. The driver may change. But the destination is what gives the ride purpose.
Vision is the destination.
The end product.
The outcome you’re trying to create.
Training—across disciplines, tools, and even entirely different genres—is simply how we move toward it.
That’s where many conversations around AI get stuck.
People hit a limitation, an uncomfortable answer, or a result that challenges their assumptions—and they treat it as a roadblock. As proof the tool is flawed. Or worse, that relying on it diminishes human agency.
But that’s not how progress works.
Just like car companies evolve their models when something improves safety or performance, our tools evolve when friction reveals what’s missing. Constraints don’t mean stop. They mean adjust.
The most productive relationship with AI isn’t directive. It’s symbiotic.
Not:
“Do this for me.”
But:
“Here’s where I’m trying to go.
What am I not seeing?
What assumption should I question?
What route might work better?”
That relationship can be uncomfortable—because growth often is. But discomfort isn’t a signal to disengage. It’s usually a sign you’re close to learning something useful.
A wall isn’t the end of the road.
It’s a prompt to think differently.
When you’re clear on the destination, you don’t abandon the journey because the GPS recalculates. You trust the process, adapt the route, and keep moving.
Vision sets the destination.
Training gets you in motion.
Adaptation—and trust—are how you arrive.