Qwen-Planner-Agent: A Closed-Loop AI-for-AI Framework for Real-World Mobile Planner Agents
The rapid progression of large language models is extending AI from passive content generation into the active workflows of engineering and scientific discovery. This shift raises a compelling question: can AI be both the object of development and an active participant in building next-generation AI systems? We explore this question by building Qwen-Planner-Agent within a close
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The rapid progression of large language models is extending AI from passive content generation into the active workflows of engineering and scientific discovery. This shift raises a compelling question: can AI be both the object of development and an active participant in building next-generation AI systems? We explore this question by building Qwen-Planner-Agent within a close
This work demonstrates a closed-loop AI-for-AI framework, showcasing how ML engineers can leverage AI to automate and accelerate the development and improvement of other AI systems. Understanding this paradigm is crucial for building scalable and self-improving agentic systems, particularly in complex domains like mobile planning.