"coding" is the skill that realizes other skills: it's a delivery medium.

The skill to learn is to be able to see and address the problems that will need solving in the medium term.

Even before AI, software changes a lot (desktop, enterprise, consumer web, IoT, devices, robotics...). So for the "seeing" part, it's like planning to cross the continent not knowing what transport or maps will be available: you can mainly guess they'll come out of the terrain and available materials and expertise.

For the "address" part, it's helpful to have seen similar problems, but probably more helpful to have seen a variety of problems and developed some high-level approaches, typically in academic study. Depending on your domain, that might involve math, or engineering, or biology, or.... All coding is encoding, which is fitting some domain to data structures and algorithms.

For the "delivery" part, it's especially important that your code restrict itself to what's needed by the actual end use. That might not be cool or interesting, and it often requires getting more direct appreciation of the end-use than the often-weak problem statement. It's a trap to just enjoy the beauty of it.

Someone like Noam Shazeer demonstrates the value of good coding: lots of people in his environment had lots of good ideas, but he made it happen (and it looks like he enjoyed it).