We're a tiny team that so far only got the confirmation that it works. The focus right now is to make the first batch of customers happy, and continue to spend effort on the metaplanner.

Btw, I advise you to take a look at the metaplanner's code. It's the definition of the planning task for the planner. So that the planner can learn to solve the planner's (it's own) task. It is leveraging the HyperC core that sits in a separate repository in the same github org.

I heard the approach was circulating in the AI planning academic circles but no one had put it together as many academically-uninteresting details needed to be cared for first. That's exactly what we did.