I've also concluded that it's essential: Programming is the solution for the broadest space of problems in computing.
If you can narrow the problem space to some finite number of goals and workflows, you have a viable application. Application environments with sufficiently many workflows always reincorporate programming as a way to let the user build their own solution - and most things are implicitly programmable, whether through a defined API or through tricky reverse-engineered methods.
What I think muddies the picture is the line between "design" workflows and "engineering" workflows - in the first, you're piecing together the existing technology in a different way, while in the second, you are transferring math and science knowledge into original technology. As individuals we experience personal bias as to which side of programming is more "necessary," which is reflected in the resulting choices of tooling, code style, and preferred problem domains.
Sometimes you want design-heavy programming - e.g., you add some business logic and a UI on top of a database. Other times you want to add engineering to an existing design - you're writing hardware drivers using a common protocol, a data formatting plugin for an application, etc.
Library code acts as a way to expose units of engineering, while a framework defines a broad, but still configurable design space. Sometimes you have overlapping design spaces - you can have client code that works with a GUI framework, but also talks to an internal model and remote data sources.
One of the things that is exciting about programming's evolution is how much it is based on an ecosystem of technologies. Outside of some embedded fields, the era where you are given a hardware manual and are told to come up with your own development environment is over. Successful technologies tend to act parasitically on prior ones. This leads to a lot of compromises, but the general direction remains toward "better fit."