Why the AI answers the wrong thing
5 хв читанняUsually it isn't the model, it's the request. Here are five typical cases — the symptom makes it easy to spot yours and see what to fix.
The answer is generic and watery
- Symptom: paragraphs that would suit any business in any niche.
- Cause: no context. The model doesn't know your product, so it answers on average.
- Fix: add specifics — what you sell, to whom, what makes you different. The narrower the input, the sharper the output.
The answer is long but thin
- Symptom: three screens of text with two useful lines in them.
- Cause: no format and no length given. By default the model leans towards explaining and unpacking.
- Fix: “A list of five, each one sentence. No intro, no conclusion.”
The model answers a different question
- Symptom: you asked about one thing, the answer is about its neighbour.
- Cause: several tasks in one prompt, and the model picked the one you cared about least.
- Fix: one task, one request. The rest goes in the next message.
The answer looks right and isn't
- Symptom: numbers, links and quotes that don't exist.
- Cause: the model fills a gap with something plausible unless you stop it.
- Fix: explicitly allow it not to know — “if you don't have the data, say so, don't invent it”. And check anything that looks like a fact: dates, numbers, names.
It comes out different every time
- Symptom: the same prompt gives a good result, then a bad one.
- Cause: the prompt allows several readings, and the model picks a new one each time.
- Fix: put an example of the answer you want into the prompt. It's the strongest way to narrow the spread.