I think that instead of rigidly declaring 'here's how we're going to put the pieces together', you should make a library where existing models can be automatically used and connected together to form what I call an "AGI candidate".

That way we over iteration against an "AGI test bench" find increasingly complex architectures that perform well. We do not need the AGI to think like we do, it just needs to think as well as possible. (as determined by it's rms score on the tasks in the test bench)