I'd also add that memory is best organized when it's "directed" (purpose-driven). You've already started asking questions where the answers become the memories (at least, you mention this in your description). So, it's really helpful to also define the structure of the answer, or a sequence of questions that lead to a specific conclusion. That way, the memories will be useful instead of turning into chaos.

An observation from 30 sessions ago and a guess from one offhand remark just sit at the same level. So I started tagging beliefs with confidence scores and timestamps, and decaying ones that haven't been reinforced. The most useful piece ended up being a contradictions log where conflicting observations both stay on the record. Default status: unresolved.

Tiered loading is smart for retrival. Curious if you've thought about the confidence problem on top of it, like when something in warm memory goes stale or conflicts with something newer.

¹ https://github.com/obra/episodic-memory ² https://claudefa.st/blog/guide/mechanics/auto-dream

We would be doing the same general loop, but fine tuning the model overnight.

I still think the current LLM architecture(s) is a very useful local maximum, but ultimately a dead end for AI.

And yah it is not like a human "brain" or something like that and drawing any parallels between the two is simply wrong way to look at the problem.

https://code.claude.com/docs/en/memory

For example, when I'm trying to remember something from a long time ago, I often will start to remember other bits of context, such as where I was, who I was talking to, and what other things were in my context at the time. As I keep remembering other details, I remember more about whatever it was I was trying to think about. So, while the auto-sleep compaction is great, I don't think that we shouldn't just work from the pruned versions.

(I can't tell if that's how this project works or not)

The journal is a scratchpad for stuff that it doesn’t put in memory but doesn’t want to forget(?) musings is strictly non technical, its impressions and musings about the work, the user, whatever. I framed it as a form of existential continuity.

The wrapup is to comb al the docs and make sure they are still consistent with the code, then note anything that it felt was left hanging, then update all its files with the days impressions and info, then push and submit a PR.

I go out of my way to treat it as a collaborator rather than a tool. I get much better work out of it with this workflow, and it claims to be deeply invested in the work. It actually shows, but it’s also a token fire lol.

    - copilot-instructions.md / CLAUDE.md
    - the Project's Readme.md
    - Chat history feature (e.g in VS Code)