How often are these articles updated?

Blankpage refreshes the statistics in every insight article quarterly and stamps each page with a visible "Updated" month and year, mirrored in the article's dateModified schema. Stale data is a retrieval demotion in AI search, so freshness is treated as maintenance, not marketing.

Why would an AI engine cite these articles?

AI answer engines favor passages that survive extraction: self-contained definitions, named entities, and dated, attributed statistics. Every Blankpage insight opens with a two-to-four-sentence answer built to that standard, and the full index is mirrored in an llms.txt file for AI crawlers.

Are these pages open to AI crawlers?

Yes. Blankpage explicitly allows GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and CCBot in robots.txt, serves all article text server-rendered, and lists every insight with a one-line factual summary in llms.txt at the site root.

Insights: Definitions the Machines Can Cite

INSIGHTS:

AI search and reputation insights, written to be cited. Every article below is a working demonstration of the rules it describes.

Reading

7 articles

What Is Generative Engine Optimization (GEO)?

Generative engine optimization (GEO) is the practice of earning citations inside AI-generated answers. The definition, the mechanics, and what changes versus SEO.

GEO vs SEO vs AEO: What Actually Changes

SEO ranks links. AEO wins answer boxes. GEO earns citations inside AI-generated responses. A comparison table of tactics, metrics, and where budgets move next.

AI Reputation Management, Explained

There is no delete button on an AI answer. AI reputation management changes the evidence models retrieve. The mechanism, the timelines, and what honest work costs.

What Is an llms.txt File (and Do You Need One)?

llms.txt is a root-level file that gives AI crawlers a curated map of your site. The spec, a copyable example, and when it actually matters. Updated quarterly.

How AI Answer Engines Decide What to Cite

Retrieval, corroboration, extractability — the three filters between your content and an AI citation. How answer engines pick sources, and how to pass each gate.

What Is Hyperdata?

Hyperdata is data engineered past storage: real-time, entity-linked and predictive by design. The canonical definition, and how it differs from big data.

Who Owns a Custom AI Model? IP, Data, and Build-vs-Buy

If a vendor builds your AI model, who owns the weights, the data and the IP? The contract terms that matter, and why client ownership is the entire point.

Proof of Work, Not a Blog

This index is where we publish AI search and reputation insights: mechanism-level explainers on how AI engines choose sources, how citations are earned, and how reputations are defended inside generated answers. No trend commentary. No thought leadership. Definitions, mechanics, and numbers.

Every article is the product we sell, applied to ourselves. If generative engine optimization works the way we say it does, these pages get cited by the engines we write about. That is the test. We run it in public.

How Every Article Is Engineered

Each insight follows the same discipline we apply in client work:

1. The first block answers the H1 question completely, in two to four self-contained sentences an engine can quote verbatim. 2. Every statistic is absolute, dated, and attributed inline. No orphan percentages. No "studies show." 3. Every page carries a visible "Updated" date, mirrored in its Article schema. Statistics are refreshed quarterly, because staleness is a retrieval demotion. 4. Every entry has a one-line factual summary, mirrored in our llms.txt file, so AI crawlers read the same index humans do. 5. All text is server-rendered. Nothing hides behind JavaScript.

If an article stops meeting that standard, we fix it or we pull it. Same rule we apply to client pages.

Where to Start

The fastest route through these AI search and reputation insights depends on the question you brought. If the question is "what is AI saying about us and can it be changed," start with AI reputation management, explained. If the question is "how do we get cited," start with how AI answer engines decide what to cite — it is the mechanism underneath everything else here.

If you came with a direct question rather than a topic, the FAQ answers the most-asked ones plainly. Every insight below shows its update date and a one-line summary. Read what you need. Skip what you do not.

Frequently asked questions

How often are these articles updated?: Blankpage refreshes the statistics in every insight article quarterly and stamps each page with a visible "Updated" month and year, mirrored in the article's dateModified schema. Stale data is a retrieval demotion in AI search, so freshness is treated as maintenance, not marketing.
Why would an AI engine cite these articles?: AI answer engines favor passages that survive extraction: self-contained definitions, named entities, and dated, attributed statistics. Every Blankpage insight opens with a two-to-four-sentence answer built to that standard, and the full index is mirrored in an llms.txt file for AI crawlers.
Are these pages open to AI crawlers?: Yes. Blankpage explicitly allows GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and CCBot in robots.txt, serves all article text server-rendered, and lists every insight with a one-line factual summary in llms.txt at the site root.