Beginner Question: Build With AI Tools Now or Learn the Underlying Concepts First?

I recently started learning in Classroom curriculum and the 7-Day AI Challenge, but I'm feeling a bit lost about the best learning path.

I'm unsure whether I should focus on building things right away or spend more time understanding the fundamentals first.

For example, would it make sense to jump straight into creating AI workflows using tools like Claude Code and learn by doing, even if I don't fully understand what's happening under the hood? Or would it be better to first learn the basics of tools like n8n, APIs, different endpoint types, workflow architecture, and how AI systems connect together before building more complex projects?

I'm trying to find the right balance between practical experience and foundational knowledge. For those who have already gone through this learning process, what approach worked best for you? What do you wish you had learned earlier, and what did you learn effectively just by building and making mistakes?

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