Writing
How to measure what AI assistants say about a company without fooling yourself. Arithmetic where the arithmetic matters, and the sample size on every number.
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What the Air Canada chatbot ruling means for what AI says about your company
What the chatbot told a customer, what the tribunal ordered, and what the ruling means for answers from your own bot and from assistants you do not run.
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How to check what ChatGPT, Gemini and Perplexity say about your company
A seven-step method for checking what ChatGPT, Gemini and Perplexity tell buyers about your company, from a dated list of facts to a claim-by-claim comparison you can repeat.
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Why AI answers about your company go stale
Why assistants keep repeating facts that used to be true, how training memory and live retrieval each produce stale answers, and why the fix starts with a dated list of your own facts.
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When AI says something false about a business: what the cases show so far
A plain summary of the public cases on false AI statements, from a company answering for its own chatbot to the suits over Google AI Overviews, and what they mean for a business now.
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How many prompts before an AI visibility number means anything?
The arithmetic behind AI visibility percentages: what interval a given sample size actually earns you, and how many runs it takes to detect a change rather than noise.
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How to fix a wrong AI answer about your company
How to find every wrong claim an assistant makes about your company, trace it to the page it came from, correct that page, and confirm the answer actually changed.
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AI visibility and answer accuracy are different things
Visibility tools score a mention; accuracy tools score a claim. A single worked example separates the two categories and shows which problem each one leaves unsolved.
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