Agreed, regarding the computational simplicity of CoT LLMs, and that this solution certainly has much more flexibility. But is there a reason to believe that this architecture (and training method) is as applicable to the development of generally-capable models as it is to the solution of individual puzzles?

Don't get me wrong, this is a cool development, and I would love to see how this architecture behaves on a constraint-based problem that's not easily tractable via traditional algorithm.