A lot of AI learning stalls because it stays theoretical for too long. Real skill develops when you take a simple use case, define the inputs and outputs clearly, and ship something that works.
That means combining foundational understanding with practical system design. Learn prompts, models, and data structures, but also learn how users interact with tools, what a product workflow looks like, and how to measure whether the output is useful.
Small, repeatable builds create stronger capability than passive content consumption. Ship, review, improve, and repeat.