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This is not a good metric IMHO. I would expect new projects to have bigger changes initially as they try to find a suitable architecture. That is not slop. This is no different than rewriting a project 2-3 times pre-AI to find out what sticks and how to organise it better.

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I have yet to see the churn ever go down. I'm not saying it won't but what I see is that current frontier LLMs are still bad at identifying functional abstractions or patterns that can actually scale.

I have not seen an LLM rewrite 2-3 times and then settle on what sticks, it just rewrites constantly and usually while leaving residue of previous attempts behind.

Which in some projects is still fine. Like I said, they are generally producing working code, but I haven't seen proof yet that it can actually scale and evolve well over time.

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