After the AI summary covers most commercial queries, should the content selection change the approach?
After AI abstracts cover most commercial queries, the selection of topics should change: from 'create a page for keywords' to 'write an answer that can stand alone for a question'. Public tracking shows that the coverage of AI Overview increased from 45.75% in September 2025 to 88% in August 2026, nearly doubling in a year. The structure of the display positions has changed, and if the content production method does not keep up, it will lose exposure qualifications.
What has the expansion of coverage changed?
The expansion of coverage means that the abstract occupies more space on the first screen of search results, leaving less room for traditional ten blue links. It has three direct impacts on the content side.
First, the marginal benefits of the title-based keyword page are decreasing. The keyword solution is to deal with the situation that 'this word appears on the page', and the abstract extraction is concerned with whether 'this paragraph is answering the question'. Second, the unit cited has changed from the page to the paragraph. It is difficult to extract usable sentences from a page with high quality but mixed paragraphs. Third, the selection should be more in line with the real question.
The difference between question-based selection and keyword-based selection.
The starting point of keyword-based选题 is a list of keywords, the output logic is 'This word must have a page.' The starting point of question-based选题 is a list of questions, the output logic is 'This question must have an answer that can be taken away.' There are three differences in the writing style.
Title: Write in the way users would ask, not a combination of words. First paragraph: Conclude directly in the first one hundred and twenty words, do not pad. Section title: Each subtitle is a sub-problem, the content of the section is self-contained, the reader can get complete information by reading this section only, and the program can also extract this section without missing the context. At the end, put a few common questions to cover the variant question methods that really appear in the search.
Judging criteria are very simple: take a section out and show it to someone who hasn't read the full text, can they get the answer. If they can, this section is qualified; if not, it's not finished yet.
Which capabilities within the site can reduce the cost of execution?
After the topic shift, the production pressure is still there, and cost reduction can be achieved at the production end. The AI writing capability was integrated into the site early on and has been continuously provided since 2023, suitable for expanding the issue list into a draft in bulk. When creating articles, it can also automatically generate tags, illustrations, and title keywords (TDK), and the description field is particularly important - it is often used directly as an answer reference and is worth checking each article instead of allowing it to be generated arbitrarily. On the site side, llms.txt is also automatically generated to make it easier for large language models to understand and index the site content, reducing the cost of reading.
It is necessary to clarify boundaries: these capabilities solve the problem of writing quickly, but not of writing correctly.选题, conclusion, and data sources are still responsible by humans, and the machine draft goes through content safety and human review before entering the publishing process.
Common questions
Question: With the coverage increasing so much, do we need to redo all the keyword pages?Answer: It is not necessary to be arbitrary. Prioritize the redoing of pages with search volume and commercial intent, transforming them into Q&A structures; maintain the status quo of long-tail low-traffic pages, and deal with them when resources are sufficient.
Question: Will there be a conflict between the self-inclusion of paragraphs and the integrity of the article?Answer: The conflict is not as big as imagined. Integrity is maintained by the order of the sections and the transitional sentences, and self-containment is achieved by each section providing all premises and conclusions, both of which act on different levels, and can be satisfied at the same time.
Question: Can the descriptions generated by AI be used directly?Answer: They can be used as drafts, but each item should be checked before publication: the description should be able to be cited independently of the text, and should not conflict with the conclusions of the text. The generated content sometimes exaggerates or lags, and going live directly can lead to incorrect answers.