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I definitely buy this argument within industries, but not across the whole economy. Mathematically, you can have a kinda smooth distribution even if the underlying components are very jagged (cf Central Limit Theorem). Mechanically, this is because you should expect the tipping point of different jobs and industries to be at different points in the capabilities growth curve, so even if (eg) customer support agents go from losing 10% of jobs to losing 99% of jobs over night, you still shouldn't expect the 10%-99% job loss transition to be at approximately the same time as other jobs.
There are a few ways this assumption breaks. The most obvious break is automated AI R&D/RSI. It's easy to see how a smooth growth in AI capabilities there can potentially translate into a sharp increase in the pace of AI capabilities overall, which leads to ripple effects across the economy.
If I squint, I can also maybe buy a story here with superhuman non-AI R&D, where smooth increases in R&D ability of AIs nonetheless translates to non-smooth increases in scientific advancements and thus total factor productivity across the whole economy.
But I don't think there are many things quite like that.
This is an experiment in short-form content on LW2.0. I'll be using the comment section of this post as a repository of short, sometimes-half-baked posts that either:
I ask people not to create top-level comments here, but feel free to reply to comments like you would a FB post.