Is there a useful algorithm with a decreasing asymptotic time? Algorithmic complexity is usually increasing and almost always strictly increasing based on input size. This is logical since algorithms take time to execute steps, and for almost all problems, the larger the input the more steps are needed to handle that input.

I want to know if there is an algorithm that does not increase with input size but rather decreases.

You could make an algorithm with decreasing asymptotic time by for example, making it loop -n + 10000 times, where n is the size of an array of integers.

This however doesn't do anything other than cycling, it shows that you could make such an algorithm, if the algorithm doesn't do anything useful. Is there an algorithm that decreases asymptotically as the size of the input increases, that solves an actual problem (theoretical or other)?

EDIT:

Some people seem to be getting confused by the question so i want to clarify.

Is there a non-trivial algorithm that executes less steps as the size of the input increases?
No. If the running time is approaching zero as the input size grows, then the algorithm can’t even perform a single step.

If you mean that the running time approaches some positive constant, then this is just $O(1)$, because $\Omega(1)$ is a lower bound for any algorithm.