---
title: "Using examples and output formats to control results"
description: "Why examples are so powerful Language models are exceptional pattern-followers. When you include examples in your prompt, a technique often called…"
url: https://optimizeall.com/learn/prompt-engineering-for-content-and-sales/examples-and-output-formats
updated: 2026-10-05
---

Prompt Engineering for Content & Sales · The anatomy of a great prompt · lesson 2 of 15 · 11 min

# Using examples and output formats to control results

## Why examples are so powerful

Language models are exceptional pattern-followers. When you include examples in your prompt, a technique often called **few-shot prompting**, you give the model a concrete pattern to match. It is the fastest way to transfer tone, structure and quality standards.

Compare these two instructions:

- "Write in a friendly, confident, slightly witty tone."
- "Here are two captions in our voice: [example 1] [example 2]. Write three more in the same voice."

The second almost always wins, because "friendly, confident, witty" means different things to different people, while the examples show exactly what you mean.

## How to use examples well

1. **Use your best real work.** Past posts that performed well, emails that got replies, scripts your audience loved.
2. **Show variety within the pattern.** Two or three examples that differ in topic but share voice teach the model what to keep constant.
3. **Label them clearly.** "Example 1 (Reel caption, product launch):" helps the model understand what each is.
4. **Say what to copy and what not to.** "Match the tone and structure, not the topic or specific phrases." Otherwise the model may reuse your exact lines.
5. **Use counter-examples sparingly.** "Here is a caption we dislike because it sounds salesy: [...]. Avoid this style." This can sharpen boundaries.

## Output formats that save editing time

Asking for a specific structure makes the output easier to review, compare and paste into other tools.

**Numbered options with rationale**
"Give 10 hooks as a numbered list. After each, add in brackets the psychological angle (curiosity, fear of missing out, social proof, contrarian)."

**Tables**
"Create a 2-week content calendar as a table with columns: Date, Platform, Format, Hook, Key message, CTA."

**Scripts with timing**
"Write a 40-second Reel script in three columns: Time, Visual, Voiceover. Keep the voiceover under 100 words."

**Structured for other tools**
"Return the result as CSV with headers: subject_line, preview_text, angle", for pasting into a spreadsheet or email platform.

**Fixed templates**
"Use exactly this structure: HOOK (1 line) / PROBLEM (2 lines) / SOLUTION (2 lines) / PROOF (1 line) / CTA (1 line)."

## Worked example: email subject lines

A UK online fashion boutique wants subject lines for a summer sale.

> Here are three past subject lines with high open rates for our audience (women 25–45, UK, value-conscious but style-led):
> 1. "The linen edit you asked for (finally)"
> 2. "Your Saturday outfit, sorted"
> 3. "We restocked the dress. Yes, that one."
> Match their voice: conversational, specific, a little knowing, no shouting. Avoid ALL CAPS, excessive emojis and the word "SALE" in the first three words.
> Task: write 12 subject lines for our summer sale (up to 40% off selected lines, ends Sunday).
> Format: table with columns Subject line, Preview text (under 90 characters), Angle.

The result is consistent, on-brand and easy to shortlist. The team then tests the top options with their email platform's A/B feature.

## Hands-on: build an example bank in 20 minutes

Examples are your strongest lever, so keep them organized. Create a document (or project file) called **Example bank** with labeled sections:

```text
EXAMPLE BANK - [Brand]
## Reel captions (top performers)
Example 1 (product launch, [date], [result e.g. 3x usual saves]): ...
Example 2 (behind the scenes): ...
## Email subject lines (highest open rates)
...
## Sales emails that got replies
...
## Counter-examples (don't sound like this)
...
```

Then reference it in prompts:

```text
Using the "Reel captions" examples in the attached Example bank, write 5 captions for [topic].
Match tone, sentence length and structure, not topics or phrases. Do not reuse any phrase of 4+ words from the examples.
Format: table - Caption | Angle | Why it fits the examples.
```

**Before:** "Write captions in a friendly, witty tone" returns the model's idea of "witty" (puns, exclamation marks).

**After:** captions with your real rhythm (short, dry, specific), because the model matched your top performers instead of an adjective.

## Structured outputs for your tools

When output goes into a spreadsheet, scheduler or CRM, ask for a machine-friendly format and test it once:

```text
Return only CSV with headers: date,platform,hook,caption,cta,hashtags. Quote any field containing commas.
```

If your assistant supports it, ask for a table you can export, or paste the CSV into a sheet and check that every column landed correctly before scaling up.

## Pitfalls

- **Copying examples too closely.** If outputs repeat your example phrases, add "Do not reuse phrases from the examples."
- **Examples that break your own rules.** If your example includes a claim you no longer make, the model will copy it.
- **Too many examples.** Beyond a handful, returns diminish and prompts get long. Choose your best.
- **Format without substance.** A beautiful table of weak ideas is still weak. Format supports thinking; it does not replace context.

## Mini-template

> Here are [2–3] examples of [content type] in our voice:
> [examples, labeled]
> Match their [tone/structure/length], but not their topics or exact phrases.
> Now write [number] [content type] about [topic] for [audience].
> Format: [list/table/script columns].

## Video lecture: Using examples and output formats to control results

Lecture coming soon · 11 chapters · about 8 minutes. Read the full transcript below.

1. Examples and output formats
2. Why examples win
3. The music analogy
4. Five rules for examples
5. Output formats
6. Example 1: the summer sale subject lines
7. Example 2: the skincare example bank
8. Watch me do it
9. Formats that feed your tools
10. Common mistakes
11. Recap and try this now

## Lecture transcript

### Examples and output formats

What does witty mean? To you, it might mean dry, understated and specific. To the AI, it might mean puns and three exclamation marks. That gap is why so many people describe their brand voice perfectly and still get output that sounds nothing like them. In this lecture you'll learn the fastest fix in all of prompt engineering: examples. And its partner: output formats, which make results easier to review and paste into your tools. You'll see a UK boutique's subject lines, an example bank for a skincare brand, and watch me turn adjectives into examples live.

### Why examples win

Why do examples work so well? Language models are exceptional pattern followers. When you include examples, a technique often called few shot prompting, you give the model a concrete pattern to match. Friendly, confident and slightly witty means different things to different people. But here are two captions in our voice, write three more, leaves very little room for misunderstanding. The model can see your sentence length, your punctuation habits, how you open, how you close, how much you joke. Here's the key idea. Adjectives describe a voice. Examples demonstrate it. And demonstration wins almost every time.

### The music analogy

Think of it like asking a band to play something in the style of your favorite artist. You could describe it: upbeat but a bit moody, with a strong chorus. Or you could just play them two tracks. Two tracks work better than one, because the band can hear what's consistent across both, the style, and what's specific to each, the song. That's why two or three varied examples beat a single example. And you'd add: same style, new song. Don't copy the melody. In prompts, that's: match the tone and structure, not the topic or specific phrases.

### Five rules for examples

Five rules for using examples well. One, use your best real work: posts that performed, emails that got replies. Two, show variety within the pattern: two or three examples on different topics with the same voice teach the model what to keep constant. Three, label them: example one, Reel caption, product launch. Four, say what to copy and what not to: match tone and structure, not topics or phrases, and don't reuse any phrase of four or more words. And five, use counter examples sparingly: here's a caption we dislike because it's too salesy. That sharpens the boundary without flooding the prompt with bad patterns.

### Output formats

Now formats. Asking for a specific structure makes output easier to review, compare and move into other tools. Numbered options with a rationale: ten hooks, each followed by the angle in brackets. Tables: a two week content calendar with columns for date, platform, format, hook, key message and call to action. Scripts with timing: time, visual, voiceover. CSV with headers for pasting into a spreadsheet or scheduler. Or a fixed template: hook, problem, solution, proof, call to action, one line each. One warning: a beautiful table of weak ideas is still weak. Format supports thinking. It doesn't replace context.

### Example 1: the summer sale subject lines

A simple example. A UK online fashion boutique wants subject lines for a summer sale. They paste three past subject lines with high open rates: the linen edit you asked for, finally. Your Saturday outfit, sorted. We restocked the dress, yes, that one. Then: match their voice, conversational, specific, a little knowing, no shouting. Avoid all caps, excessive emojis, and the word sale in the first three words. Write twelve subject lines for the summer sale, up to forty percent off selected lines, ending Sunday. Format: a table with subject line, preview text under ninety characters, and angle. The result is consistent, on brand and easy to shortlist, and the team tests the top options with their email platform's A B feature.

### Example 2: the skincare example bank

Now a business scenario, with illustrative details. A skincare brand in Dubai builds an example bank: top Reel captions, best subject lines, sales emails that got replies, and a short counter examples section. They store it in their brand project. A month later, outputs start including the phrase clinically proven to reduce wrinkles. Nobody asked for it. The culprit? An old caption in the example bank, written before legal withdrew that claim. The model was doing exactly what it was told: matching the examples. They remove the old caption, add a note to review the bank every quarter, and the claim disappears. Examples are powerful in both directions.

### Watch me do it

Let me show you the difference live. First, adjectives only: write five Instagram captions for a candle brand in a warm, witty, cozy tone. Here's the result: lots of puns about wick, and three exclamation marks. Now I attach the example bank and say: using the Reel captions section, write five captions for our new autumn candle. Match tone, sentence length and structure, not topics or phrases. Don't reuse any phrase of four or more words from the examples. Format: a table with caption, angle, and why it fits the examples. The captions are short, dry and specific, exactly like the brand's top performers. And I quickly scan for copied phrases. None. That's the power of show, don't tell.

### Formats that feed your tools

One more format tip for anyone who moves AI output into other tools. When content is headed for a spreadsheet, a scheduler or a CRM import, ask for a machine friendly format with named headers. Return only CSV with headers date, platform, hook, caption, call to action and hashtags, and quote any field that contains commas. Then test one small batch before you scale up. Paste it into a sheet and check every column landed where it should. Captions with commas are the classic problem, and one misaligned row can shift a whole content calendar. Once the format works, save that exact instruction in your prompt library, so it works the same way every time, for everyone on the team.

### Common mistakes

Common mistakes. Copying examples too closely. If outputs repeat your example phrases, add: don't reuse phrases from the examples. Examples that break your own rules, like an old claim or a missing disclosure. The model will copy the problem. Too many examples. Beyond a handful, returns diminish and prompts get long, so choose your best. And format without substance: a beautifully formatted table can hide weak thinking. Always ask whether the ideas in the table are actually good.

### Recap and try this now

Let's recap. Examples transfer voice better than adjectives, because models are pattern followers. Use your best real work, show variety, label your examples, say what to copy and what not to, and keep counter examples sparing. Ask for the output format you actually need, from tables to CSV. And keep your example bank clean, because the model will copy whatever's in it. Here's your try this now. Spend twenty minutes building an example bank from the template in the lesson text, with three to five top performers per content type. Store it in your project, and run your next content request against it.

## Key takeaways

- Few-shot prompting (giving examples) transfers tone and structure better than adjectives.
- Use your best real work, label examples, show variety, and say what to copy and what not to copy.
- Specify output formats (lists with rationale, tables, scripts with timing, CSV) to save editing time.
- Keep an example bank; remove examples that break current rules, or the model will copy the problem.

## Try it

Collect your three best-performing captions or emails, label them, and build a few-shot prompt that generates ten new options in the same voice.

- [Previous: The six-part prompt: role, context, task, constraints, examples, format](https://optimizeall.com/learn/prompt-engineering-for-content-and-sales/six-part-prompt-structure)
- [Next: Refine, don't restart: the feedback loop](https://optimizeall.com/learn/prompt-engineering-for-content-and-sales/refine-dont-restart)
- [All lessons of Prompt Engineering for Content & Sales](https://optimizeall.com/learn/prompt-engineering-for-content-and-sales)