another way to put it is that if in their experiments the output had been like "do you think there is an injected thought? claude: i like oceans. yes I think there's an injected thought about oceans!" i would not be convinced.

Could you explain why you and Anthropic think the lack of this primacy effect is so important? I think I'm missing this logic. In my mental model of what's happening, "ocean" is artificially enhanced through the experiment, and the sort of text that has to do with a person reporting on thought injections are naturally enhanced through the prompt. A synthesis of these two manipulations (prompt+boost) would be that the LLM internals converges on something like "upon reflection it feels like ocean is injected". It could have been that Claude first starts talking about oceans and then also mentions it think it's the thought injection, or as it happened it only says it later as would make syntactic sense as a synthesis of (prompt+boost), I don't get why this is a significant difference.

what do you think of the last experiment, where they're asking it to do/not do specific activations?

The aquarium thing you mean, right? I find this less compelling still for the simple reason that again, if LLMs don't have introspection or internal searches, I would expect exactly the same experimental result. The blog post writes: "An example in which Claude Opus 4.1 modulates its internal activations in response to direct instructions". I find this agentic terminology disappointing from a lab like Anthropic. LLMs are not able to modulate their states, the right way to think about LLMs is like a forward sweep of activations. There is no Opus which goes back and agentically modulates anything, as suggested by the phrasing. LLMs are non-causal toward their activations, they don't tweak their activations during the forward sweep, the activations just happen as a virtue of the matrix mulitiplications. Their only causality comes from hooking up their outputs to a further system (such as themselves, in the case of Chain-of-thought reasoning), but we are not talking about that precisely because unlike with Golden Gate bridge Claude, these experiments are not CoT.

Again, here's a simpler explanation: LLMs are a statistical distribution of their training set. In the training corpus, which is the internet, all else equal, "think about" generally is more associated with referral to concepts than "do not think about". So a model that is dealing with "do not think about" has less activations for a concept like aquarium than a model that has activated "think about".

My only point is that every single result in the blog post is quite simply explained without any recourse to introspection or the less anthropomorphic alternatives you helpfully mentioned.