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China's first national framework for emotionally interactive AI took effect today, July 15, 2026, triggering the simultaneous shutdown of personalized AI companion features on ByteDance's Doubao and Alibaba's Qwen — two of the country's most widely used AI applications, as South China Morning Post first reported. The event is more than a compliance deadline: it reveals that no platform anywhere in the world has yet built AI companion architecture that can pass a regulator's addiction-safety test, because the features that make a companion feel personal are the same ones that make it impossible to regulate.

AI agents can independently complete full-link business workflows and deliver clear business outcomes, making pure outcome-based pricing theoretically feasible. However, due to practical hurdles in implementation such as outcome definition, external interfering factors and customized negotiation, vendors generally compromise by adopting hybrid pricing models including premium seat pricing, subscriptions combined with usage fees or outcome revenue sharing. Pure outcome-only billing is only applicable to a small number of mature customized cooperation projects.

After the commercialization of the model, profits shift upward to the implementation layer

AI-native teams secure high valuations with extremely small headcounts, and open-source frameworks paired with community skill libraries form their moat.

Gemini 3.5 Pro was targeted for general availability (GA) on July 17 but has not been officially announced yet. Reports state Google scrapped the nearly finished model and rebuilt it from scratch to address gaps in mathematical reasoning, SVG scene generation and image quality. Meanwhile, news emerged that four senior Google researchers have moved to Anthropic. Gemini 3.5 Flash has launched, while the Pro variant remains limited to enterprise preview access.

💬 This delivers a more pronounced competitive and talent-related signal than the July 13 update that it was "still in preview": the delay stems not from fine-tuning but a full rebuild, coupled with an outflow of core talent to Anthropic. This offers direct implications for gauging the pace of progress among the second tier of cutting-edge model developers and Anthropic’s ability to attract top industry talent.