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A practical way to prepare for AI-assisted discovery without unsupported adoption forecasts or guaranteed outcomes.
Improve local business information across maps, websites, directories, and AI-assisted discovery without unsupported timing promises.
Six dated AI search statistics records with direct sources, plus a practical verification method for checking definitions, scope, dates, and limitations.
Structure content so people can find, verify, and reuse answers without unsupported citation-rate promises.
Define and measure AI mentions, citations, accuracy, referrals, and outcomes without unsupported market statistics.
A practical playbook for accurate public information, direct evidence, and repeatable citation observations without guarantees.
A transparent guide to SkillAEO's experimental agent.json format, its fields, limits, and safe deployment.
A practical guide to the llms.txt community proposal, including a conservative example, deployment checks, and clear limits.
A 20-point review for content, technical access, structured data, evidence, and repeatable AI visibility observations.