The answer is well-written but factually wrong — how do I fix the prompt?

You mostly cannot fix this by rewording the prompt, because it is not a wording problem. See why AI hallucinates, linked below, for what is actually happening and what does help, such as asking the model to cite sources it can check or using a research mode that looks things up.

Should I keep correcting in the same conversation or start a new one?

Either can work, but a long chain of small corrections risks leaving contradictory instructions behind. If a conversation has had several corrections already, a fresh, complete prompt is often more reliable than one more patch.

How many times should I try before giving up on a prompt approach?

There is no fixed number — but if two or three specific, diagnosed fixes have not helped, the issue may not be the prompt at all. See choosing a model for your task, linked below, for whether the task might need a different kind of model instead.

What to do when the first AI answer is not right

All prompt guides · Last reviewed: 2026-09-09

Diagnose what went wrong before rewriting the whole prompt

A disappointing answer usually falls into one of a few categories: it missed context you had but did not state, it ignored a constraint, it used the wrong format, or it is confidently wrong about a fact. Naming which one happened points to a specific fix — a missing constraint calls for adding the constraint explicitly, not rewriting the whole prompt from scratch or repeating it more forcefully.

Add the specific thing that was missing, not more instructions in general

Once you know what was missing, add exactly that: the constraint, the example, the piece of context, or the format description that would have made the ask clear. See how to write a clear, specific prompt, linked below, for the fundamentals this step usually draws on — most iteration is applying the same handful of things the first prompt skipped.

Know when to start a fresh prompt instead of patching

A long back-and-forth of small corrections can leave a conversation carrying contradictory instructions the model is now trying to reconcile — at that point, a fresh, complete prompt that states everything you have learned you need is often faster and more reliable than one more patch. This is also worth remembering when the answer is confidently wrong about a fact rather than just off-format: patching the wording will not fix that, since it is not a wording problem — see why AI hallucinates, linked below, for what is actually happening in that case.

Questions people ask

The answer is well-written but factually wrong — how do I fix the prompt?: You mostly cannot fix this by rewording the prompt, because it is not a wording problem. See why AI hallucinates, linked below, for what is actually happening and what does help, such as asking the model to cite sources it can check or using a research mode that looks things up.
Should I keep correcting in the same conversation or start a new one?: Either can work, but a long chain of small corrections risks leaving contradictory instructions behind. If a conversation has had several corrections already, a fresh, complete prompt is often more reliable than one more patch.
How many times should I try before giving up on a prompt approach?: There is no fixed number — but if two or three specific, diagnosed fixes have not helped, the issue may not be the prompt at all. See choosing a model for your task, linked below, for whether the task might need a different kind of model instead.

Practice on a real conversation

Every conversation in ClawAI keeps its history, so you can iterate on a prompt across several turns and see exactly what changed between one answer and the next.

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