Yeah the rate at which I'm learning is insane! I think the key is picking a project with practical goals that you can track towards, ideally backed with concrete evidence (like data) and measuring progress by how close you are getting to those goals via working code.

As such, I'm learning through motivated, self-directed, focused exploration, using the AI to answer questions, run experiments, explain findings, investigate surprises, and explore new directions to research, all grounded in concrete data related to those goals.

The data and our results on it are what keep us honest. The data is also what helps understanding nuances and building intuition because the AI can explain outcomes in the context of samples data points that you can reason about independently.

The difference between YOLO vibe-coding and engineering is understanding. I think this is the future of learning and skill-building.