This is not just Anthropic. Almost all big AI companies, including OpenAI and Google, hide their model's actual reasoning. This is because revealing the raw reasoning exposes exactly how the AI processes information. These companies spend in huge amounts on R&D to develop a thinking process that is superior to their competition. Exposing those thinking mechanics to competitors would completely defeat the purpose of their spending. They simply won't do it. It's like you telling your exact location to someone who is trying to hunt you down.

Or like providing the world’s information in machine readable format that the AI companies can convert into model weights without getting permission or compensating the rights holders

More to the point - if they expose their model's "thinking" inference, competitors can train on that to replicate the results. If they postprocess that content, e.g. by summarizing it, it's no longer as useful to competitors.

> This is because revealing the raw reasoning exposes exactly how the AI processes information. These companies spend in huge amounts on R&D to develop a thinking process that is superior to their competition. Exposing those thinking mechanics to competitors would completely defeat the purpose of their spending. They simply won't do it. It's like you telling your exact location to someone who is trying to hunt you down.

I thought the reason was the "reasoning" didn't work very well with "aligned" model output, so they had to remove the alignment during reasoning and then hide it to avoid exposing "unaligned" model output.

The cynic in me is wondering whether it's more about how revealing how the sausage is made might bring bad publicity.

When you export your personal data Google hides all model responses leaving just user messages. So it's even worse

> Exposing those thinking mechanics to competitors would completely defeat the purpose of their spending.

I think one of the reasons could be to limit liability too.

What if reasoning helps in establishing provenance for questionable sources ?

What if reasoning and model's "thought" points to fundamental issues in how the model was trained to produce certain problematic responses ?

But that makes the product worse because for any complex problem the road to the solution is important to be reviewable.

Correct on all points. Nonetheless this leads to a less useful product. I

f we want more useful products, we need to come up with ways to disincentivize this behavior. Even if doing so poses an existential risk, we are better off if companies taking existential risks to please us is a necessary being a top player in this game.

There are actually fine tunes of qwen on opus “thinking” tokens that teach it to think like opus does.

https://huggingface.co/Jackrong/Qwen3.5-27B-Claude-4.6-Opus-...

Mistral displays some “thinking” text (in their basic online chat interface) in the thinking mode, do we know if those are the real tokens?

It’s quite interesting to read. I can’t imagine using a model like this without the ability to peek inside and see if it is getting stuck.

One thing I see noone asking, is this not a case of optimization? Hidden reasoning means they dont need to process the output of all that, it stays internal within the model. Less cost for them -> less cost for us (even if they benefit mroe), compared to streaming all of those reasoning tokens out?

> They simply won't do it.

They should be required to do it by force of law. Why is it that they can train on copyrighted works and then lock down the model? This contradiction is unbearable. Nobody cares how many trillions they spent training the model.

correct. this becomes difficult for us to understand what happens behind the scenes.

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