What this case covers
After exchanging with multiple AI experts in Guangzhou and Shenzhen, the author sorted out landing cases of Agent automation in cross-border, e-commerce, quantitative, content production and other businesses, and proposed a four-stage framework from "letting AI do" to "letting AI manage" and AI Native judgment criteria.
Questions it answers
- What are the four stages of using AI?
- Why does local efficiency improvement make things more tiring the more you use it?
- What are the judgment criteria for AI Native?
- What are humans responsible for in the Agent era?
- How can content engineering achieve scaled output?
Our observations
- Cramming AI into old processes can only bring limited efficiency improvement; only by reconstructing processes can an automated closed loop be achieved.
- The deeper one's business understanding and the higher one's aesthetic, the greater the role their Agent can play.
- Search traffic has more moat attributes than recommendation traffic, and a content matrix requires long-term accumulation.
From the author
What we really need to do is let AI manage—replace our own work, so that we do not have to work, so that we feel happy. We should get used to going from being a producer to an idle consumer.