Jagarin: A Three-Layer Architecture for Hibernating Personal Duty Agents on Mobile
Jagarin addresses the critical problem of enabling personal AI agents to operate effectively on mobile devices for users who need assistance with time-sensitive obligations, without compromising battery life or privacy.
This paper introduces Jagarin, a three-layer architecture designed to enable personal AI agents on mobile devices to manage time-sensitive obligations without continuous background execution. It achieves this by using a heuristic engine (DAWN) to compute urgency scores and wake agents, an email proxy (ARIA) to route commercial inbox messages, and a protocol (ACE) for direct machine-readable communication from institutions to agents.
Personal AI agents face a fundamental deployment paradox on mobile: persistent background execution drains battery and violates platform sandboxing policies, yet purely reactive agents miss time-sensitive obligations until the user remembers to ask. We present Jagarin, a three-layer architecture that resolves this paradox through structured hibernation and demand-driven wake. The first layer, DAWN (Duty-Aware Wake Network), is an on-device heuristic engine that computes a composite urgency score from four signals: duty-typed optimal action windows, user behavioral engagement prediction, opportunity cost of inaction, and cross-duty batch resonance. It uses adaptive per-user thresholds to decide when a sleeping agent should nudge or escalate. The second layer, ARIA (Agent Relay Identity Architecture), is a commercial email identity proxy that routes the full commercial inbox -- obligations, promotional offers, loyalty rewards, and platform updates -- to appropriate DAWN handlers by message category, eliminating cold-start and removing manual data entry. The third layer, ACE (Agent-Centric Exchange), is a protocol framework for direct machine-readable communication from institutions to personal agents, replacing human-targeted email as the canonical channel. Together, these three layers form a complete stack from institutional signal to on-device action, without persistent cloud state, continuous background execution, or privacy compromise. A working Flutter prototype is demonstrated on Android, combining all three layers with an ephemeral cloud agent invoked only on user-initiated escalation.