Build a verification loop
Add a repeatable quality check to the AI work you do regularly.
Before you start
Practice locally with fictional details. This lesson does not require a paid AI tool.
Define success, test the result, and revise before you reuse a workflow.
Define the finish line first
For a weekly research summary, success might mean three relevant findings, a source for each factual claim, clear uncertainty, and no private information. Write those checks before asking for a draft.
Create a small test set
Keep a few representative inputs: a normal example, one with missing facts, and one with conflicting information. Use these to check whether a revised prompt improves the workflow across different situations.
Verify outside the answer
Open the cited sources and check that they support the claims. Recalculate important numbers independently. Asking the same AI if it is correct may help identify issues, but it is not independent evidence. A citation can also be wrong or nonexistent.
Keep a version you can explain
Record the prompt version, tool used, test inputs, and the changes that improved the result. Keep a human review step for consequential decisions. Automate only the parts you can measure and check.
What is the strongest check for a factual claim in an AI-written summary?
Sources and review
These examples are fictional and written for new2.ai. The references support the methods taught; they do not endorse this course.
Reference material may be in English.