you just make Alzheimer a feature lol , but seriously this is very interesting

I am sorry but the whole "biological memory" thing seems like marketing fluff on basic cache mechanisms.

You said it cuts token usage by 84% but isn't that typical for any typical chunked RAG system?

And why did you specifically chose to test against the LoMoCo dataset when there's a lot of issues with it and it being very easy to cheat?

I haven’t had much like with memory implementations. I tried a few.

What I do now is preserve all my claude code conversations and set the context from there.

This allows me to curate memory and it’s been the best way so far.

on the other "biological memory" post in so many weeks, I pointed out that the decay rate shouldn't be based on a real clock but a lifetime of it's use within the coding session. Elsewise your memory fades even when there's no process change (eg, coder goes on vacation). I'm not going to check whether thats true here, but it seems like a naive first assumption thats failed conceptualization.

The other comment is that spatial memory is probably a better trigger for memory, so if you're not tracking where the coding session starts, the folders it's visits, etc, then you're not really providing a good associative footpath for the assistant to retrieve whats important for any given project.

I know everybody seems to want the agent to remember every conversation they've ever had with it, but I just don't see the value in that. In fact, it seems to hurt productivity to have the agent second guessing me based on something I said yesterday. Every time I've used any memory system, the agent gets distracted from the current tasks based on previous conversations and branches of development...often comingling unrelated projects (I work on code for work, open source projects, a bunch of unrelated side projects, etc.) and trying to satisfy requirements that don't make sense.

I've stopped trying to achieve general "memory". I just ask the agent to thoroughly, but concisely, document each project. If it writes developer documentation and a development plan/roadmap, as though a person was going to have to get up to speed and start working on the project, it provides all the information the agent needs tomorrow or next week to pick up where we left off.

The agent is not my friend. I don't need it to remember my birthday or the nasty thing I said about React last week. I need it to document what anyone, agent or human, would need to know to get productive in a particular repo, with no previous knowledge of the project.

Good, concise, developer and user documentation and a plan with checklists solves every problem people seem to think "memory" will solve: It tells the agent what tech stack to use (we hashed it out in planning), it tells it what commands it needs to run and test the app, it covers the static analysis tools in use (which formalizes code style, etc. in a way a vague comment I made a month ago cannot), and it is cheap. Markdown files are the native tongue of agents. No MCP, no skills, no API needed. Just read the file. It works for any agent, any model, and any human just getting started with the project.

Basically, I think memory makes agents dumber and less useful. I want it to focus on the task at hand.

It strikes me as funny how we want to get super AI inteligence but keep trying to anthropomorphizing all AI aspects to make it more "human". IMHO, if we keep doing it we will create Human AI with all errors and deficiencies humans have.