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  18. 18AM

    Most RAG setups fail because they treat memory like a static filing cabinet. When every transient bug fix or abandoned rule is stored forever, the context window eventually chokes on noise, spiking token costs and degrading the agent's reasoning. This implementation experiments with a biological approach by using the Ebbinghaus forgetting curve to manage context as a living substrate. Memories are assigned a "strength" score where each recall reinforces the data and flattens its decay curve (spaced repetition), while unused data eventually hits a threshold and is pruned. To solve the…

    Apr 2026 · github.com

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    Rediscover old memories with AI

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    One layer for memories, skills, and rules across any agent

    Feb 2026 · memories.sh

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    Libro11

    The open-source brain for AI agents.

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    Your AI has the memory of a goldfish. Not anymore

    Jul 2026 · yourmemoryai.xyz

  23. 23YA

    This is a project that I have been building for a while now, YourMemory is a solution to agentic memory which focuses on pruning of noise rather than hoarding of data. In the current state of agentic memory most of the context is stored in the form of a MD file or is derived through a RAG model where you store each and everything. Both of the solution leads to bloated context which does not optimize the usage of any tokens. In this system we only keep relevant data in our memory and prune all the unnecessary data. The relevance of a data is derived through multiple factors such as recall…

    Jun 2026 · yourmemoryai.vercel.app

  24. 24
    MOD20

    Drop a vibe on the map. Make memory a place again.

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