I think you’re overstating the impact of interpretability here. Your earlier point that latent reasoning models can’t be trained very well and that discretization may be load bearing rather than a readability tax in addition to significant inference infra hurdles (e.g. batching, speculative decoding) have limited any serious attempts and reduced the theoretical advantage over CoT at least in the near term.
> I think you’re overstating the impact of interpretability here
Outside of RLAIF, interpretability is the strongest way to do alignment right now. alignment is important because otherwise LLMs are incentivized to learn power seeking, dangerous behaviours [1]. a more downto earth example of alignment being important is that agents are incentivized to do tasks in the shortest way possible, and this way might not be what the user wants (I explain this further in another comment in this thread)
[1] https://www.forbes.com/sites/boazsobrado/2026/03/11/alibabas...