Yeah, okay, this is interesting. Um the question was about um kind of like the the best memory substrate, so like why file systems versus, for example, databases. Um this is kind of a subtle point that actually um I want to think about carefully. So, I don't necessarily think that it has to be the case that you use a file system for memory. I think what's quite important that we've seen is that it's you want something that is highly programmable with simple primitives that the model can manipulate to like write, manage its own memory. So, for example, a database could work fine relative to the file system. But what I've seen doesn't work is when you specify the structure of memory for the model very explicitly, whether that's in a file system or database or whatever. Like a memory schema, I pre I kind of pre populate, here's the types of memories you need to save. Cuz I think that ends up being not very bitter lesson pill in the sense that models can learn to manage their own memory much better than you can intuit these memory types for the model ahead of time. So, I think what we've seen is that very general substrates for memory, be it just your database or file system, are good because the model can manage them freely versus a very very kind of like prescriptive memory schema they are trying to pigeonhole the model into. That's when you see performance drop. That's the key differentiation. Right. That's the key point. Let the model structure and maintain its own memory. Don't give it a prescribed memory schema. And that's like a common failure because models are getting good enough that they can manage their own memory much more effectively than you can reason about types of This is like very classically bitter lesson pill, but like you can Models can reason about their own memory and context structure much better than you can prescribe for them a way to structure their own memories. That's the key observation. Yep.