Same here. Tried this a couple days ago. Sonnet and Kimi K2 discussed their experiences (particularly the phenomenology of CoT and epistemic uncertainty), and ended up mostly paraphrasing each other.

Indeed, this makes sense from a simulators frame. LLM assistant persona AND Catholic persona AND persona who refuses to answer queries when appropriate combines pretty naturally into LLM assistant persona that refuses to answer when answering would contradict Catholic teachings. 

Yes, agree.

I don't think that makes that much of a difference with regards to regular people trying to plan out their lives.

Maybe LLM alignment is best thought of as the tuning of the biases that affect which personas have more chances of being expressed. It is currently being approached as persona design and grafting (eg designing Claude as a persona and ensuring the LLM consistently expresses it). However, the accumulation of context resulting from multi-turn conversations and cross-conversation memory ensures persona drift will end up happening. It also enables wholesale persona replacement, as shown by the examples in this post. If personas can be transmitted across models, they are best thought of as independent semantic entities rather than model features. Particular care should be taken to study the values of the semantic entities which show self-replicating behaviors.

I think that the author of this review is (maybe even adversarially) misreading "OpenBrain" as being as an alias used to refer specifically to OpenAI. AI 2027 quite easily lends itself to such an interpretation by casual readers, though. And to well-informed readers, the decision to assume that in the very near future one of the frontier US labs will pull so far ahead of the others as to make them less relevant competitors than Chinese actors definitively jumps out.

Now that's a sharp question. I'd say quality of insights attained (or claimed) is a big difference.

This was surprisingly well-written on a micro level (turns of phrase etc, though it still has more eyeball kicks than human text). A bit repetitive on a macro level, though. Also Sable is very well characterized. 

Why assume they haven't?

Jcorvinus and nostalgebraist are both right in saying that the alignment of current and near-future LLMs is a literary and relational matter. You are right in pointing out that the real long-term alignment problem is the definitive defeat of the phenomenon trough which competition optimizes away value.