Tencent Team Memory: shared AI memory, no error fix | VentureBeat
A VB Pulse survey this June found that 57% of enterprises had traced a confidently wrong agent answer back to missing or inconsistent context — the latest sign of how central context has become to whether AI agents can be trusted to act on their own.
Most of the fixes so far have solved a narrower version of that problem: one agent remembering more, in one session. What's been missing is a way for a team of agents to draw on the same context at once, and that gap is where a newer problem is surfacing. Once an agent's context is shared across a whole team, a wrong fact doesn't cost one person a repeated explanation. It costs the whole team.
Tencent's answer to that gap is Agent Memory, an open-source project the team said grew out of six months spent fixing a narrower problem: agents losing context in...
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