TRAINING AI

METHODOLOGY / READER EVIDENCE

A conclusion is only useful when you can see what supports it.

When an article could make you switch tools, change a workflow or grant more access to AI, the page should give you enough to inspect: source, scope, what cannot be concluded yet, and how fresh the information is.

See the reader standard ↓

WHAT READERS SHOULD SEE

Five things that matter when a conclusion affects a decision.

01 / SOURCEWhere the information came from and whether that source fits this claim type.
02 / SCOPEThe version, plan, workload or use case where the conclusion applies.
03 / LIMITWhat the current evidence does not establish, so you do not read past it.
04 / FRESHNESSWhen the information was checked and which facts need faster re-checks.
05 / CORRECTIONWhen facts change or we are wrong, the page should be corrected with an appropriate trail.

An official source can prove a feature exists. It does not prove the feature is “best.”

Rankings, productivity, security, reliability and ROI need different evidence — often direct tests, suitable data or independent corroboration. Training AI would rather say “not enough to conclude” than turn vendor documentation into a recommendation.