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AFAIK no provider guarantees compatibility of reasoning traces, even in the same model generation, and we've in practice seen most of the big LLM APIs throw errors indicating incompatibility (at least transiently) when switching models. The only stable solution right now is to just throw away reasoning traces whenever a model is switched.
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Fair (I haven't been using the encrypted-reasoning systems, though this is common in open ones - I'm kinda surprised it's an option in encrypted ones too), though what they're doing here is cross-user replays in addition to cross-model.
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There seems to be an obvious choice to make here, should you give the users to decrypt and use the COT that they did not generate themselves?

This is only required if you want users to be able to share things with everyone and you are going for the simplest implementation.

If not you could try to keep a record of keys associated with a user, then when a new request comes in look through to see if the user has a valid key to decrypt the COT.

For explicit shares, just add the key used in that one conversation to the users valid keys. For global shares use the global keys. But that's adding more complexity to the system.

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It’s about being able to change models mid-task. For example, I want to be able to plan using Fable but implement the plan using Sonnet, and that won’t work if this is implemented.
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Or even my fable credits run out mid task and need to switch back to opus >.<
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Actually, that brings up a good reason they can't fix it. Fable falls back to Opus when the topic is too "unsafe". That behavior requires traces than can move between models!
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Prior to LLMs I never considered that I might have to make a resource-usage decision between hiring Star Trek's Data vs. his stupider brother B4...

https://memory-alpha.fandom.com/wiki/B-4

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Star Trek is a post-scarcity society, those problems don't exist there unless you're in the middle of a crisis and on emergency power.

LLMs briefly seemed like this too, after subscriptions made the SOTA models too cheap to meter, but before they walked back on that and introduced quotas...

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For plan it's relatively easy, just make the plan the artifact. The point is to ingest knowledge with one model and use it in another, and that is not necessarily easily expressible in natural language.
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I really don't understand why server-side storage of the trace isn't a viable approach here, with only a unique key flowing to the client and back. Does it have something to do with how backend load-balancing works?
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Makes no difference. There is a policy as to whether to allow use of a reasoning trace in a given context. Whether that trace originates from authenticated ciphertext or a backend database is basically irrelevant.
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Good point, thanks.
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Yes, this storage would be growing exponentially making the disk space and latency problems harder (add the disaster recovery/backups). I think the choice of using client side is not too bad if you ensure that its secured properly. Also the company can excuse itself from the liability of storing sensitive data on its servers, thats a big deal in itself to be compliant for enterprise audits

1. The down side is that it cannot be used across the clients even for the same user

2. Using the same encryption key was a bad choice here, a per user key would have solved this issue for sure.

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Having thought about this a little more, it's clear that server-side storage is not compatible with Zero Data Retention (ZDR). However, in non-ZDR settings, it seems likely that the providers are capturing all that data anyway?

> a per user key would have solved this issue for sure

It would have helped with PII leakage, but not with plain-text trace extraction attacks, right?

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Per user encryption key ties it with the user session (assuming you do authentication properly), no one else can access it. User being able to see the information is not really an attack vector in this case.

The compliance rules at times are outdated and people skirt around them by following the worded rule instead of the intent.

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That’s incompatible with zero data retention and so you’ll lose a lot of enterprise customers.
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100% guaranteed that this research just forced this to happen now.

Sucks.

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It’s already patched according to the authors. Details were not specified.
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or add some metadata and don't allow downgrading.
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