Write Better Prompts

Better prompts usually come from clarity, not complexity.

Start with One Clear Job

A strong prompt usually does one thing well.

Good:

• Rewrite this to sound more professional.
• Turn this into three action items.
• Translate this into plain German.

Weaker:

• Rewrite this, shorten it, make it funny, add strategy advice, and turn it into a sales pitch.

If you want several different outcomes, split them into separate prompts.

Tell TypeBoost What Good Looks Like

If the results feel vague, add more direction:

• the tone you want
• the length you want
• the structure you want
• what to avoid

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.

Use Examples Only When You Need Them

Many prompts work with one clear instruction.

Examples help when you need:

• a very specific tone
• a specific format
• more consistency across repeated runs

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.

Improve a Prompt Through Real Use

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:

• make the tone clearer
• limit the length
• say “return only the final text”
• add one useful example

Use Learn the Right Way

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:

• the original input
• your improved output

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:

• it saves a corrected example for that prompt
• it works like a few-shot example

What Learn does not mean:

• model training
• changes to the AI model itself

So use Learn after you improve a result and want the prompt to learn from that correction.

Keep Prompt Writing Practical

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