AMA proposes adaptive memory through multi-agent collaboration — hierarchical granularity, adaptive query routing, consistency verification and targeted refresh for long-running agents
The AMA framework treats agent memory as a coordination problem rather than a storage problem: hierarchical granularity, adaptive query routing, consistency verification and targeted memory refresh, handled by multiple agents working together over long-horizon interaction.
The framing is the contribution. Most agent-memory work treats recall as retrieval — embed everything, search it later. AMA treats it as maintenance: what should be kept at what granularity, which query should be routed where, and how do you detect that stored memory has gone stale or inconsistent. Those are operational questions, and they are the ones that actually break long-running deployments.
Consistency verification is the part with the most immediate practical weight. An agent operating over weeks accumulates memory that contradicts itself, and no amount of retrieval quality fixes a corpus that disagrees with itself. Making verification a first-class component rather than an afterthought is the right shape for the problem.
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