Field guide / 03 / AI
Prepare to be understood before trying to be recommended.
No business can guarantee inclusion in an AI answer. You can improve the clarity, consistency, evidence, and answer quality that retrieval and summarization systems have to work with.
Keep the claims honest
Separate what is known from what is hoped.
AI interfaces, indexes, prompts, sources, and retrieval behavior change. Treat visibility as an observable outcome, not a promise.
Clarity helps parsing
Direct answers, named entities, descriptive headings, and consistent facts make pages easier for people and software to interpret.
Evidence may improve reuse
Specific examples, citations, expertise, corroboration, and current information can make a source more useful for grounded answers.
Selection is not controlled
A system may use different indexes, sources, personalization, or generated knowledge. A citation today may not repeat tomorrow.
The answer-ready page
Write blocks that survive summarization.
Each important page should make sense without a sales call. A reader—or an answer system—should not need to assemble your core claim from six vague sections.
Lead with the direct answer
Answer the page’s primary question in one or two sentences. Name the business, service, audience, location, or condition needed to understand the claim.
Define ambiguous terms
Explain what your industry language means in this context. Avoid assuming that a reader—or a model—shares your internal vocabulary.
Attach evidence to claims
Place the example, source, credential, measurement, or caveat close to the statement it supports. Generic trust badges are not a substitute for context.
Answer the next questions
Cover fit, process, cost factors, timing, comparison points, risks, and alternatives. Use real customer questions rather than a keyword-generated FAQ dump.
Keep a test log
Record the exact prompt, tool, date, account state, sources shown, brand mention, answer summary, and repeat result. One screenshot is not a trend.
A sane testing loop
Observe without fooling yourself.
Use a small set of realistic customer questions and repeat them periodically. Avoid drawing conclusions from one prompt or one system.
Use the language customers bring to calls, consultations, reviews, and sales conversations.
Record tool, model or interface, date, prompt, location context, account state, and whether web retrieval appears active.
Note whether the answer is accurate, which sources appear, how the business is described, and what important context is missing.
Fix unclear facts and weak answer pages, then retest later. Do not treat short-term output movement as guaranteed causation.