CMSPost Technical Team
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Practical solutions shared with the CMSPost Network community.
What can llms.txt realistically do for AI visibility, and what should it not replace?
Treat llms.txt as an optional machine-readable orientation layer, not as a substitute for crawlable, authoritative web content. If you use it, keep it concise and accurate. Point to canonical documentation, im…
Read contribution →How do you find source gaps when AI answers cite competitors but never cite your site?
Start by analyzing the sources that are actually being selected. For a stable set of target questions, record cited domains and classify them: primary research, government/standards sources, specialist publica…
Read contribution →How should a brand disambiguate its entity when AI systems mix it up with similarly named companies?
Create a consistent identity layer across the first-party site and authoritative external references. On the site, maintain a clear organization/about page with the canonical brand name, what the company does,…
Read contribution →How should important AI-search content show freshness without rewriting dates just to look new?
Tie freshness signals to substantive changes and make those changes explainable. For high-change topics, assign an owner and review cadence based on risk. Product specifications, regulations, pricing, platform…
Read contribution →How do you write concise answer blocks for AI retrieval without turning every page into generic FAQ content?
Use answer blocks where the page naturally needs a direct answer, not as a sitewide keyword template. Place a concise response immediately after a descriptive heading when the section addresses a specific ques…
Read contribution →How should title tags, H1s, and page intent be aligned without forcing the exact same keyword into everything?
Start with the page's job, not the keyword string. Define the primary intent in one sentence: what problem is the page supposed to solve, for whom, and at what stage of the journey? Then make the title tag com…
Read contribution →What does "information gain" look like in practice when ten pages already answer the same search query?
Information gain comes from adding evidence, decisions, examples, or structure that changes what the reader can understand or do. Before writing, inventory what the existing results already cover. Separate com…
Read contribution →How should a topic cluster be designed so supporting pages strengthen each other instead of becoming a pile of overlapping articles?
Build the cluster around distinct user problems and content roles. Start with a topic map. Define the broad entity or problem space, then list the major intents inside it: definition, diagnosis, implementation…
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