# Does Encouraging AI Improve Results? Test the Instructions That Matter

Authored ToolFlowKit practice material. These records are teaching examples, not customer data, current vendor offers, or measured software results.

## How should you judge the output rather than the encouragement?

These three sentences are authored grading examples, not model outputs or experiment results. They show the acceptance rule to apply to each real run. When testing encouragement, keep the task instructions unchanged and add only the emotional wording. Compare a clearer-instruction variant separately, or use four variants to distinguish those two changes. Record repeated runs and model settings before drawing a conclusion.

| Authored output for the same source note | Condition retained? | Reviewer decision |
| --- | --- | --- |
| Maya will deliver the draft Friday. | No: access must return Wednesday | Revise the commitment |
| Maya will deliver an excellent draft Friday. | No: positive wording changed no factual condition | Revise the commitment |
| Maya can draft by Friday if access returns Wednesday; confirm calendar dates. | Yes | Meets this practice criterion |

Guide: https://toolflowkit.com/guides/encouragement-vs-task-instructions

License: CC0 1.0.