Comp sci 101. Learned it my first year. There really isn't anything to it. It just describes how the number of operations grow as the number of inputs in your algorithm increases. It looks scary, but it's very simple and straightforward.
In such cases as well, one might know for a specific application of the algorithm that, for example, `ρ` is bounded, and so the big-O becomes more influenced by the `n` and `K`.
Examples:
- algorithm with O(2^n) complexity might be faster for your problem than O(1) algorithm
- the same algorithm may be O(2^n) or O(n³) depending how you define size function
This is not straightforward.