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I think eventually you need some kind of system that ranks pieces of data based on how useful they are.

I.e. for the web we did that with link count etc.

We need some other mechanism for judging and ranking pieces of "memory" for "agents"

You can kludge it together by having the agent keep a log of what it does with any notes and lessons about friction / efficiency, and then on some interval review that + session history for items worth promoting into a topic-based memory, or for things that are needed constantly into the main AGENTS.md or a separate MEMORY.md that's loaded into every session. Reviewing the notes at the same time as session history helps provide enough context to make directionally correct decisions about what is worth keeping in context for future sessions.

Attention is all you need.

Seriously, isn’t this the core premise of RAG / modern embedding search systems?

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