The rate of model improvement has slowed, and may not recover. It's unclear if Mythos2 or 3 or whatever they're calling their next model will be an improvement

The rate of model improvement has slowed, and may not recover. It's unclear if Mythos2 or 3 or whatever they're calling their next model will be an improvement for most common enterprise use cases. LLMs can't solve basic things (writing non-slop documents, understanding context without massive handholding) and for coding other models are quickly becoming 'good enough' without the same cost and nannying. That's why Anthropic is 'stealing' workflows. But it turns out it's much harder to push adoption when your users don't really want to use your product. Code was a unique use case where the code luddites were loud but a minority - most people don't want to update 300 cases of variables across their code base for a name change. Most don't want to write unit tests. There are a few use cases where that will happen (law is next, maybe quant finance) - but otherwise most companies are throwing money into a pit and getting 0 return. It's a very interesting race and state of affairs, but Kimi K3 and likely the next DeepSeek models will put the high price token affair to rest. Unless of course, mythos / next model really does solve some universally applicable problem that people want it it to do.