The proper level of complexity

Looking at the human cell and then organs and then people and then communities does it really surprise you when I say the the path to the proper level of complexity is through the multiverse of compute and the implementation is that of the Uber language?

In order to evolve you must free your mind.  See the prototype in its pure form as code is thought and thought is code.   In effect "be the ball" - Ty Webb 1980.

If that is still too abstract, think of the gears in a watch.  The watch is more than the single gear.  The watch is the set of gears.  When designing a watch, would it be proper to aim at a single gear solution thereby limiting designs to an improper level of complexity?

There is only so much you can learn from the single gear.

Systems built on systems; we have not yet built our watch.  First, we must understand how gears turn in aggregate. At that point, we can make any type of watch we want.

It can scarcely be denied that the supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience.  often quoted as ‘Everything should be made as simple as possible, but not simpler’ ‘ Einstein - On the Method of Theoretical Physics’, lecture delivered at Oxford, 10 June 1933

So in designing "simple" systems the goal is not simplicity for its own sake. If you look at the quote you see the key is finding the "irreducible elements"  -- this is what gives you the building blocks for your architecture.

This has been the attempt of the Uber Language of compute.  To define the irreducible parts and make them as simple to implement as possible.  The aggregation of these ideas is then at the proper level of complexity. 

Another resource to draw upon in this area is Elon Musk.  He applies "first principles" thinking to guide him to the irreducible elements thereby creating an actual formula for the process:

STEP 1: Identify and define your current assumptions.
STEP 2: Breakdown the problem into its fundamental principles. ...
STEP 3: Create new solutions from scratch.