I think it cuts both ways - for example I've definitely had the experience where when typing into ChatGPT I know ahead of time that whatever "memory" they're storing and injecting is likely going to degrade my answer, so I hop over to incognito mode. I've also had the experience where I've had a loosely related follow-up question to something and I didn't want to dig through my chat history to find the exact convo, so it's nice to know that ChatGPT will probably pull the relevant details into context.

I think similar concepts apply to coding - in some cases, you have all the context you need up front (good coding practices help with this), but in many cases, there's a lot of "tribal knowledge" scattered across various repos that a human vet working in the org would certainly know, but an agent wouldn't (of course, there's somewhat of a circular argument here that if the agent eventually learned this tribal knowledge, it could just write it down into a CLAUDE.md file ;)). I think there's also a clear separation between procedural knowledge and learned preferences, the former is probably better represented as skills committed to a repo, vs I view the latter more as a "system prompt learning" problem.