Better prompts usually come from clarity, not complexity.
A strong prompt usually does one thing well.
Good:
Weaker:
If you want several different outcomes, split them into separate prompts.
If the results feel vague, add more direction:
Example:
Rewrite the text to sound warm and professional. Keep it under 120 words. Keep the main point. Do not add extra explanation.
That gives the AI a much better target.
Many prompts work with one clear instruction.
Examples help when you need:
In TypeBoost, those examples usually live in the extra user and assistant messages inside the prompt.
Use them when they help. Do not feel forced to add them to every prompt.
The fastest way to improve a prompt is to test it on real work.
When a result is close but not right, edit the prompt and try again.
Small changes are usually enough:
Learn is for cases where the AI result is close, but you still need to improve it.
Edit the result inside TypeBoost first.
After you change the output, Learn can save:
TypeBoost stores that as a user and assistant example pair inside the prompt.
That gives the prompt a better example to follow on similar inputs later.
What Learn means:
What Learn does not mean:
So use Learn after you improve a result and want the prompt to learn from that correction.
If a prompt works well in daily use, it is a good prompt.
Do not optimize for theory. Optimize for whether it makes your work faster and more consistent.
Next: Review and apply results