AI Visibility for Small Teams: The Minimum Viable Programme
The smallest AI visibility programme that actually works for a team of five: a question list, a baseline, a dozen pages, an entity layer and a monthly check.

The smallest AI visibility programme that actually works for a team of five: a question list, a baseline, a dozen pages, an entity layer and a monthly check.

A triage framework for deciding which existing pages to refresh first so they get cited by AI assistants, and how to fix them without a full rewrite.

A layered monitoring cadence for AI visibility: monthly core testing, fortnightly commercial checks, quarterly deep sweeps, plus the event triggers that override all three.

SEO is not one thing. The technical and authority layers matter more than ever for AI search; the position-chasing and manipulation layers matter less or negatively.

AI engines assess credibility per topic, not per domain. Here are the five signal groups they read and how to build authority narrow enough to actually win.

AI engines favour forums and Wikipedia for structural reasons, not conspiracy. Here is the mechanism behind it and which question types your site can realistically win.

A five-section AI visibility audit checklist covering access, extraction, attribution, current citation rates and the competitive landscape you can run internally.

Which content structures large language models extract most reliably, which ones consistently fail, and the self-containment test that catches most problems.

A practical decision framework for AI crawler policy: what GPTBot, ClaudeBot and Google-Extended actually do, and the real cost of blocking them.

Schema does not guarantee citation, but it removes ambiguity about who you are and what you claim. Here are the types that matter and how to implement them.
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