The encoder-gradient path through the decoder was transposing the decoder
before the matmul, producing `[batch, d_model] × [d_sae, d_model]` — a
shape mismatch for every batch > 1. The decoder is stored as
`[d_model, d_sae]`, so `recon_grad @ decoder` is already the right shape
(and matches the comment at the call site, which reads
"recon_grad @ decoder @ d_relu").
All 9 existing `sae::tests` still pass. Omni-Cortex's `LatentDictionary`
now trains correctly on batches larger than 1.
Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>
