I LOL at the title, also, excellent breakdown of the library API design. Could you share the materials during your talk (Streamlit link, etc)?
One limitation I see in the current API is that the change points in LinearTrend model are arbitrary constant intervals - granted it will make computation much faster as the input is static, but it will be much more powerful if we can have uneven interval with the number of the breakpoints (and their location) being inferred automatically.
Also, I really like the parameterization in linear trend which force the change point being “smooth” (ie, they are connect) - it might be useful however to allow the trend line being not connected to account for sudden jumps in the time series (eg, a pandemic that almost switch off the time series). I guess some strongly regulated additional constant added to g in the LinearTrend will do.