@9hills: After trying many Agent Memory implementations, I found only two that are somewhat useful: 1. Hermes-style strictly length-limited entry-level memory and session recall, used to address personal assistant memory needs. But this has nothing to do with coding. 2. Skills precipitated from trajectories and skill evolution...
Summary
The author shares insights after trying various Agent Memory implementations, concluding that only strictly length-limited entry-level memory (like Hermes) and skill evolution based on trajectory precipitation are somewhat useful, while other graph-based or card-based methods are ineffective.
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Cached at: 05/26/26, 05:01 AM
I’ve tried many Agent Memory implementations, and only two I think are somewhat useful:
- Hermes, which uses strictly limited-length entry-level memory and session recall to handle the memory needs of a personal assistant. But this has nothing to do with coding.
- Those that precipitate skills and skill evolution based on trajectory, but I haven’t found a suitable library yet.
Other graph-based or card-based ones—after all that effort creating a bunch, they’re completely useless. https://t.co/GceMr7BMrg
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