I spent a week trying to make the brain layer do more. Every time I fixed one thing, the next wall was already there. The architecture was the problem.
Part 20 ended with nine concepts revived and a structural realization sitting underneath the wins. The vocabulary growth approach was running out of room before Origin's vocabulary had reached anywhere close to conversational. The architecture I was patching had become the thing that needed redesigning. I went back to the brain layer to see if it would scale up while I figured out what to do about the encoder.
The first thing I noticed was that training was painfully slow. A full brain layer retrain on the rebalanced corpus was projected at ninety hours. For a thirty-nine-thousand-pair dataset that should have taken minutes. Something was wrong with the math, and the way to find out was to profile it.
I built a profiler that broke the per-batch time down by sub-operation. Forward pass, backward pass, each of the routed circuits, the thalamus router, the two-stage reasoner. The result was unambiguous and embarrassing. The two-stage reasoner, which I'd spent significant time restoring from v1 as the "intellectual core" of compositional reasoning, was consuming 99.8% of training wall-clock. Every other operation in the brain layer combined consumed about four milliseconds. The two-stage reasoner ate two thousand seven hundred and six.
