InfoQ Chinese recaps Alibaba Cloud's Yunqi conference forum on AI-native R&D organizations: over the past three months the company's CTO engineering line ran an AI Native exploration across a 6,000-plus-person R&D organization, using a "north star, blank space, sandbox" approach to select seven showcase teams that are in production, have observable business results and could be reused. Alibaba Cloud R&D vice president Tang Hong framed the agent computing paradigm as "model plus Harness plus Context," and argued that agents entering the production pipeline is the real dividing line, with AI Native passing through tool-native, workflow-native and organization-native stages. Reported results include one project cutting end-to-end processing from two hours to five minutes, another shortening release cycles from 40 days to 2 days, all alerts getting a first-pass agent analysis, STAROps accumulating more than 1,400 evaluation items, and an Agentic SOC team reducing average requirement cycles from 50.9 to 13.8 days; the authors state these figures do not represent overall performance and that reuse across teams still needs validation.