Overall, this textbook takes cognitive autonomy as its axis and covers the key content of AI — basic concepts, core principles, typical applications, cross-domain integration, and values and governance — while scientifically designing goals for different stages from primary school through lifelong learning, showing a very clear systematic character. Although I am very interested in AI, on the whole I am still learning, so I can only offer some modest thoughts on three points for the experts to consider: first, whether the account of the scientific system of AI in Chapter 5 should more sharply distinguish two main threads — "how the machine operates" and "training human cognition"; second, the ethics part comes rather late in the book and focuses on risk prevention, which can lead learners to take AI ethics lightly, so I suggest moving the AI ethics content to a different place in the book, running key AI-ethics ideas through the whole book as its underlying logic, and adding hands-on practice in effectively rejecting AI suggestions; third, although the appendices are detailed, most grassroots teachers may lack the ability to make full use of them, so could a package of thought experiments be developed alongside to support implementation? In addition, adding common-knowledge modules on AI computing power, energy consumption, and the like would help students build a richer cognitive framework.