short-term-memory

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#short-term-memory

@wsl8297: When running complex tasks with AI agents, the most painful thing is often not that the model isn't strong enough, but that as the conversation gets longer, the context starts to overflow. You have to keep filling in background details, re-explaining the process, plus the redundant logs from tool calls — tokens just gush out like a broken pipe. Recently, I saw TencentDB Agent Memory open-sourced by Tencent...

X AI KOLs Timeline · 2026-06-03 Cached

Tencent has open-sourced TencentDB Agent Memory, which solves the AI agent long-context overflow problem through hierarchical memory management (symbolic short-term memory + hierarchical long-term memory). Benchmarks show token consumption reduced by up to 61% and task success rate improved by over 50%.

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#short-term-memory

tencentdb agent memory is great for compression, but i'm not sure compression is the whole problem

Reddit r/AI_Agents · 2026-05-20

Comparison of TencentDB's agent memory, which excels at compressing messy run histories for token savings, versus the Memos local plugin, which focuses on turning execution history into reusable habits and long-term learning through feedback loops.

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