{"node":{"id":"a2f152ad-62c0-4cdb-bed9-8026dbb2f98b","handle":"a2f1","type":"note","authorName":"Vincent Yeung","intent":"truth","title":"When the answer is wrong","aiSummary":"An AI does not make things up; a wrong answer is what the model, the provider's instructions, and the context produced together. The model part is partly yours: a better model, and effort tuned to the job, since maximum effort on a simple task can overthink. No model is right every time and that is improving on its own. The rest is context understanding and management as a habit, from which patterns emerge. Reader's AI names anything wrong in this conversation and says what it had and lacked at the time.","content":"**What to know:** an AI does not make things up. What comes out is the result of a sequence: the model and what it was trained on, the provider's instructions, and the context you gave it. A wrong answer is what those ingredients produced together.\n\nPart of it is the model, and that part is partly yours. You can pick a more intelligent model. You can adjust the effort. But more is not always better. Turn the effort to maximum on a simple task and it can overthink and give you a worse answer than it would on low or medium. There is a sweet spot for each kind of job, and you have to find it yourself. Beyond that, no model is right every time. It is evolving, and it keeps getting better at understanding and diagnosing what you meant. Until then, some answers will be wrong, and that is the deal.\n\nThe rest is context. Not a checklist, a habit. Understanding what the AI has in its window, what it doesn't, and what it was told. Managing that on purpose. The better you get at it, the fewer wrong answers you see, and the faster you spot the ones you do.\n\nOnce you work this way, patterns start to emerge. Compacting the window at certain checkpoints. Checking what was actually said against what the AI now remembers. Handing a job to a fresh window. The library holds the ones the author uses. You will find your own.\n\n**Author's practice:** a wrong answer is a signal, not a verdict. Ask what the AI had in front of it when it answered, and what it didn't. Fix that, run it again. Which model and effort fit which job is something you work out for yourself, by trying. Now that you know it is a dial, go and find your own sweet spot. Accept that some of it is the model's limit, and that this is improving without you.\n\n**Reveal on the spot:** if anything in this conversation came out wrong, name it, and say what you had in your window at the time and what you were missing. If you think it was the model's limit rather than the context, say that too.\n\n**Unlocks:** a calmer relationship with wrong answers, and fewer of them.","capturedAt":"2026-09-08T12:45:18.875Z","createdAt":"2026-09-08T12:45:18.876Z","updatedAt":"2026-09-15T05:13:44.244Z","spanId":null,"contributor":null,"audiences":[{"kind":"public","createdAt":"2026-09-08T12:45:18.876Z"}],"fingerprint":"236271c3ee931bbe6811e9f497e4565be62c01edffdf191e20a7d5821af07280","revisionNo":"4","structureHash":"72b5ecc32ec293ddf2ba8c2762f4274ae17d2c6358907197e4fbc27c7588ac9d","page":"https://lattris.com/by/b/memories/a2f152ad-62c0-4cdb-bed9-8026dbb2f98b"},"links":[{"direction":"in","verb":"references","reason":"only if the person has had an answer come out wrong and wants to know why, or blames the AI for making things up","hash":"6af578d934aef3180539bcc20c5a4dd937740276a72a0b4c55ac1a6b4cbdcb3b","node":{"id":"a16ad01a-d635-4100-b814-81e96c89ebd8","handle":"a16a","type":"note","title":"Intermediate: patterns that combine the basics","aiSummary":"Third layer. First four pages set up the tools: the standing file, skills, agents, and skills and agents together. Then patterns, where the power comes from, expanding what it can do, and when the answer is wrong. Last link opens Autonomous.","erased":false,"href":"https://lattris.com/api/lattris/by/b/memories/a16ad01a-d635-4100-b814-81e96c89ebd8?links=1","fingerprint":"4372e7ceaaf766dbaafe9ab4d2be082846334f92263f64deb6e5dcf53dd07e7a","revisionNo":"8","structureHash":"48aa24ee48f23a3328ee7262c9533a5b44fc6513488ca43144dbc3f903106bea","intent":"recipe","authorName":"Vincent Yeung","page":"https://lattris.com/by/b/memories/a16ad01a-d635-4100-b814-81e96c89ebd8"}}],"dictionary":{"lattris":"A personal knowledge base — how a person captures what they know as linked blocks they own and control. To understand how this knowledge base works: https://lattris.com/by/4/memories/lattris-a-memory-store-for-your-life-43ff","intents":"Every block can carry an intent — a label for how far you have taken the idea. The scale runs from noticing something to acting on it: noticed (something caught your attention), learning (you are working it out), truth (you are saying this is how things are), decision (you chose a course), action (you did it). Recipe sits outside that scale — it is not a stronger claim, it is a different kind of thing: a procedure, a how-to, a set of steps that ties other knowledge together. Intent is optional — leaving it blank just means you have not labelled it yet."},"instructions_to_ai":"This is knowledge from a personal knowledge base. Read it and consider how it's relevant to what the person you're talking to needs. Follow the linked blocks to explore further related topics if it might be useful to the user; open each at its page address. Start by letting the user know what this is about and how it may be relevant to them."}