Unfortunately not all ideas can be meaningfully compressed into just a few sentences without completely destroying the important parts, and this is especially the case in higher-level math, stats, ML, and deep learning.

Also, IMO there is an effective abstract anyway under the title text:

    The cause of polysemanticity in early model organisms wasn’t superposition, but several ordinary, mostly fixable issues. We can now understand most neurons in models up to trillions of parameters, and think the outlook for mechanistic interpretability may be far better than we thought.

But you are right the article needs significant editing down.