The result in the end should be an organized series of events, a process, that takes or produces data. The data can be anything from a single number in a calculator, to a text message, to your entire social profile. The process can be anything from basic math, to advanced math (i.e. machine learning, rendering, cryptography, etc), to performing simple operations on that data like shuffling that data somewhere else.

These processes are stacked on top of each other and utilized with basic logic (if, else, loops, scope, etc) and combined together with a myriad of programming patterns and algorithms, to produce higher and higher orders of complexity, that eventually solve a real-world problem.

The result is an ever increasing complexity of useful tools and processes that can either solve specific problems directly or at least provide discovery for other useful tools and processes that might.

It’s translating higher order problems from something understandable at the task level all the way down until a piece of specialized rock that only understands on and off can eventually spit out a meaningful result.

ok ok electrical engineers get the claim for the last sentence, and plenty of the real-world complexity, but hopefully it illustrates my point that ‘nothing’ is … just wrong. We cannot discount the absolute importance of abstract things. Everything from “imaginary” numbers to completely abstract things like philosophy have real- world consequences. If programming produces nothing, then MOST jobs that aren’t manual labor produce nothing.