Stop giving AI instructions.

Start giving it examples.

Most people write long, detailed prompts.

Then wonder why the output sounds generic.

Here's the secret the top 1% use:

It's called few-shot prompting.

Instead of telling AI what to do...

You show it what good looks like.

The spectrum:

↳ Zero-shot: Instructions only. No examples.

↳ One-shot: One example to guide format.

↳ Few-shot: Multiple examples. Best results.

More examples = better context = faster understanding.

Why does this work?

Humans are pattern recognition machines.

AI learns the same way.

When you show it 2-3 examples of exactly what you want...

It stops guessing. It starts matching.

The benefits:

☑︎ Reduces hallucinations and errors

☑︎ Aligns output to your expectations

☑︎ Improves quality significantly

When to use few-shot:

↳ Complex or nuanced tasks

↳ Specific formatting needed

↳ Niche domains or specialised language

↳ When precision is critical

How to craft good examples:

1) Make them diverse - cover different aspects

2) Keep them representative - match real-world data

3) Ensure quality - error-free and well-structured

4) Add context - explain why each example is good

Think of it like teaching someone a recipe.

Reading ingredients (zero-shot) is hard.

Seeing photos of the final dish (few-shot) makes it click.

Stop writing longer prompts.

Start showing better examples.

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