Plausible language can hide missing evidence
A model predicts useful-looking text. It may complete a pattern with a detail that was not present in your material. The grammar and confident tone do not reveal whether the claim is supported.
Watch for ordinary forms of invention
Hallucinations are not limited to strange factual answers. They appear in routine drafts when the model smooths over missing context.
- A project update adds a reason for a delay that you never provided.
- A summary attributes a recommendation to the original author when it was only implied.
- A tool comparison states a price or feature from outdated model memory.
- A research answer supplies a publication, quotation, or link that does not exist.
Use source boundaries and claim checks
Tell the model to use only supplied material and mark gaps, but do not treat that instruction as a guarantee. Extract consequential claims, verify them at the primary source, and remove anything you cannot support.
Practise on real work
Find unsupported claims
Use a low-risk AI draft and keep the source material open beside it.
Prompt to adapt
Judgment checks
- Did you inspect the original source yourself?
- Are reasons and causal claims supported, not only names and numbers?
- Did you remove or label every unverified claim?
Keep these points
- Confidence and accuracy are separate.
- Ordinary drafts can contain invented context.
- Verify consequential claims outside the AI answer.
Optional paid help with Ikram Rana
Make uncertain answers easier to catch.
Bring a non-sensitive example of the answers you need. Discuss how source material, marked gaps, and a human review step could fit into the task.
Discuss your task with IkramScope and fees are agreed before work starts. The guides stay free.
Official sources and further reading
Product features and policies change. Check the linked source before relying on tool-specific details.