I Tried TencentDB Agent Memory — Here's What the Token Reduction Looks Like

The context window problem in long-running agents is familiar: by turn 20, you are paying for tool logs the agent does not need anymore. Truncation loses detail. Summarization compresses but also forgets.

Tencent Cloud open-sourced TencentDB Agent Memory (MIT license, May 2026), and it takes a different approach: offload the verbose stuff to local files, keep a Mermaid task graph in context, let the agent drill back in when it needs specifics.

The Architecture

Four memory layers, each traceable back to raw data:

L0 Conversation : raw dialogue + tool logs

L1 Atom : structured facts extracted every N conversations

L2 Scenario : aggregated solution patterns

L3 Persona : user behavior profiles built over time

The short-term trick: verbose tool output gets offloaded to refs/*.md files. In context, only a lightweight Mermaid graph remains.…