To use your example - more modularized technologies are more flexible and can be developed faster, but they no longer use resources efficiently. A modular CPU design makes design process easier, but a particular modular CPU will not outperform a hypothetical "mudball" CPU designed so that each transistor has close-to-optimal utilization (with "optimal" defined by requirements).
Or compare standard coding practices vs. the code demoscene people write for constrained machines, in which a single variable can have 20 meanings, each code line does 10 things in parallel, and sometimes compiled code is itself its own data source.
--
The way I see it, building abstractions on top of something is shifting around difficulty distributions in the space of things you could do with that thing.
But on bigger design spaces, when you let hundreds of thousands of people collaborate, create bigger markets faster, and grab more revenue - you enable a much more detailed exploration of the design space.
And often, you discover hidden gold. But also - if you've discovered you've made a terrible mistake in your abstractions - you can often fix that, maybe in the next generation.
And as for education, i don't think standardization always leads for performance loss. For example ,the area of reading has seen a lot of research, and one of the results is "direct instruction", one of the best methods to teach reading, and is a highly standardized method.
But maybe what's your saying is true for standardized tests in current implementation.