Qwen-Planner-Agent explores using AI systems as active participants in building next-generation AI, via a closed-loop ‘AI-for-AI’ framework applied to mobile planning agents — a domain where complex long-horizon tasks and costly real-device interaction make development hard to scale. The framework links data production, model training, and deployment through a shared action-feedback-verification contract, including a human-gated agentic data flywheel in which specialized agents construct tasks and collect interaction data to continuously improve the planner agent.
