People who use AI at work keep asking the same thing: when is an answer good enough to use? There is no single test, but a short routine catches most of the damage.
Step 1: Decide the stakes
Ask what happens if the answer is wrong. A recipe substitution is low stakes. A figure in a client report, a legal deadline, a dose or a security setting is not. The higher the stakes, the more of the next two steps you do.
Step 2: Extract and check the claims
Skim the answer and underline everything that can be checked: names, dates, numbers, laws, quotes, links. Those are the places models make things up, often with confident wording. Open the primary source for each one. If you cannot find a cited reference, treat it as invented until proven otherwise, and be wary of very precise figures that appear nowhere else.
Step 3: Get a second source that is independent
Ask a different model, a search engine or a document you trust. What matters is independence: a second model shown the first answer will usually agree with it. Ask each one separately and compare. Where they agree on a verifiable point, confidence goes up. Where they split, you have found what to verify by hand.
What this does not do
A routine reduces risk; it does not remove it. For medical, legal and financial decisions, use AI to prepare your questions and confirm with a professional.
Speeding it up
Satcove sends one question to six models at once, then shows the agreement score and the named disagreements, so step 3 takes seconds instead of six browser tabs. You still do step 2 for the points that matter.
Try the example above and compare what the models say.