Alibaba's Qwen team has described how it is building a personal agent, arguing that the next stage of AI assistants depends on three parts working together: the model, memory and an ecosystem of services. Jiang Guanjun, head of AI algorithms at Alibaba's Qwen business unit, set out the framework on October 22 at the 2026 China National Computer Congress (CNCC) in Chengdu, according to Leiphone, Sina Tech and InfoQ China.
Jiang split the development of AI applications into three stages: chat, agent and assistant. In the chat stage, AI answers questions. In the agent stage, it completes tasks it is given. In the assistant stage, which he said the industry is now moving into, AI combines professional knowledge with a user's personal context, plans and acts around the user's goals, and spots needs the user has not noticed. A real personal agent, he said, should create added value and offer proactive, personalized service.
He argued that, in theory, a personal agent could solve close to 100% of everyday problems in work, study and life. The bottleneck is matching what the system can do to the right path for each problem.
On the model side, Qwen says it focuses on stable task execution. The team built what it calls a user-needs map covering more than 30 major industries, broke it down into more than 8,000 atomic model capability requirements, and brought in industry experts to evaluate and tune the model against them.
On memory, Jiang said a personal agent has to understand a user over the long term without simply piling up chat history, which adds noise and inference cost. Qwen designs its memory around how strongly events relate to each other, storing and retrieving them in tiers. His example: an assistant that remembers an elderly user once mentioning their pension could give more fitting advice when the same family later asks about a child's job search.
On the ecosystem, Jiang said that as models and harness techniques improve, the ability to connect and coordinate outside services becomes decisive. Qwen is building a model-centered open service system that brings in professional knowledge, tools, industry skills and third-party agents, and links to e-commerce, local services, healthcare and education.
In his account, the three parts combine into proactive service: memory supplies personal background, the model uses expert knowledge to identify needs and plan, and the ecosystem carries out the work, such as tracking a patient's rehabilitation schedule or flagging new risks in a user's finances.
The talk is the most detailed public account yet of the technical thinking behind Qwen Go!, the personal agent Alibaba opened for sign-ups this month.
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