Study first
Review the ideas behind the questions
These notes prepare you to judge AI-search content proposals without chasing myths, artificial page splits, or automation shortcuts that weaken reader value.
Keep the audience test first
Google's guidance for generative AI features still points back to useful, reliable, people-first content.
- Unique point of view, first-hand experience, and non-commodity content are stronger long-term bets than recycled summaries.
- Creating pages for every possible query variation primarily to influence AI or ranking systems can create scaled-content risk.
- There is no ideal page length or special writing style required only for generative AI search.
Do not replace foundations with myths
AI search features still depend on Google's core Search systems and publicly accessible, crawlable content.
- SEO basics remain relevant because generative AI features are rooted in Google's core ranking and quality systems.
- Google Search ignores LLMS.txt files, so they should not be treated as a visibility lever for Google results.
- Structured data can help with rich result eligibility, but there is no special schema markup required for generative AI search.
Review automation like any other source of risk
Generative AI can support research and structure, but teams still own the accuracy, quality, relevance, and context of the final page.
- AI-generated drafts should be checked for accuracy, relevance, originality, and usefulness before publication.
- Automation used mainly to produce many low-value pages for rankings can violate spam policies.
- If automation materially shaped a page, give readers context when that context would reasonably matter.