Flipped Interaction: Make the LLM Interview You One Question at a Time Before It Acts
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In ordinary prompting, you ask and the model answers — which means you carry the burden of knowing everything the model needs and cramming it into one message. On a well-scoped question that's fine. On something open-ended like "plan me a trip" or "design a schema," it's a trap: you can't enumerate every detail up front, and every detail you forget, the model silently guesses . A fluent answer built on an unspoken wrong assumption is worse than no answer, because it looks right. Flipped…
1Key Takeaways
- In ordinary prompting, you ask and the model answers — which means you carry the burden of knowing everything the model needs and cramming it into one message.
- On a well-scoped question that's fine.
- On something open-ended like "plan me a trip" or "design a schema," it's a trap: you can't enumerate every detail up front, and every detail you forget, the model silently guesses .
- A fluent answer built on an unspoken wrong assumption is worse than no answer, because it looks right.
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3Why it matters
Prompt and agent patterns spread fast; staying current saves time and token cost. DEV — Prompt Engineering reports that in ordinary prompting, you ask and the model answers — which means you carry the burden of knowing everything the model needs and cramming it into one message.
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