A new paper proposes a modular architecture for deploying AI agents in resource-constrained embedded systems, addressing challenges posed by memory and energy limitations. This architecture separates on-device agents for low-latency tasks from cloud-augmented agents for higher-level reasoning, enhancing the feasibility of autonomous AI in pervasive computing environments.