Good post.

You seem to excessively focus on recursive self-improvement to the exclusion of other hard takeoff scenarios, however. As Eliezer noted,

RSI is the biggest, most interesting, hardest-to-analyze, sharpest break-with-the-past contributing to the notion of a "hard takeoff" aka "AI go FOOM", but it's nowhere near being the only such factor. The advent of human intelligence was a discontinuity with the past even without RSI...

That post mentions several other hard takeoff scenarios, e.g.:

• Even if an AI's self-improvement efforts quickly hit a wall, a small number of crucial optimizations, or the capture of a particular important resource, will provide it a massive intelligence advantage over humans. (Has evolutionary precedent in that the genetic differences between humans and chimps are relatively small. )
• Parallel hardware overhang: if there's much more hardware available than it takes to run an AI, an AI could expand itself and thus become more intelligent by simply "growing a bigger brain", or create an entire society of co-operating AIs.
• Serial hardware overhang: an AI running on processors with more serial speed than neurons could be able to e.g. process longer chains of inference instead of relying on cache lookups.

(Also a couple more, but I found those a little vague and couldn't come up with a good way to summarize them in a few of sentences.)