Insights
Writing on content operations for the AI era.
Each piece proves a problem is understood, then points to what to do about it.
The teardown: what AI really tells customers about a real product
A teardown takes one real product, asks the major AI engines the questions customers actually ask, and compares every answer to the approved source. The pattern is consistent: a mix of right, subtly outdated, and confidently wrong — all stated with equal fluency. It's the clearest way to see your exposure.
Read →Evidencing control over what AI says — for audits
To evidence control over AI answers about your products, keep a dated, traceable record: which claims were checked, against which approved source, what diverged, who signed it off, and when. Auditors and regulators want demonstrable process and evidence — not a promise of perfect accuracy.
Read →The rise of "the AI told me…" support tickets
Support teams are seeing a new ticket type: customers acting on wrong answers an AI gave about your product. The cause is usually upstream — unclear or stale source content — so the durable fix is to verify and correct what AI says at the source, not just to rebut tickets one by one.
Read →Making your documentation AI-ready: where to start
Start by making one current, authoritative source per topic that is structured answer-first and machine-readable, then add a loop that verifies what AI says against it. AI-ready docs aren't a rewrite — they're a content-operations function with sign-off and a traceable record.
Read →Why ChatGPT gets your product setup wrong
AI assistants get product setup wrong mainly because they blend multiple sources, favour older and more abundant content, and fill gaps with plausible guesses. The fix isn't a better prompt — it's making your authoritative source easy to find, current, and machine-readable.
Read →Are you liable for what AI tells customers about your product?
Short answer: in most cases the liability sits with you, not the AI vendor. If an AI assistant states a wrong spec, configuration or compliance claim about your product and a customer relies on it, the exposure tends to land on the brand whose product it is — not the model that said it.
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