🎯 Stop Settling for Mediocre AI Outputs: The Few-Shot Prompting Advantage

AI models are pattern-matching algorithms, not mind readers.

When most people get disappointing results from AI, they're using it fundamentally wrong. They're entering vague requests, getting mediocre outputs, and then blaming the technology.

The problem isn't the AI. It's the approach to prompting.

The Three Approaches to AI Prompting

Let me break down your options, and explain why two of them are setting yourself up for disappointment. I’ll even use a popular use case that I swore I’d never demonstrate - create me a social media post… 🤦‍♂️

Zero-Shot: Amateur Hour

You: "Write a social media post about our new beauty product launch."

AI: produces generic content that could be for any brand.

Zero-shot prompting is fundamentally limited and bland, often resulting in textbook "AI speak" saying things like: "we're beyond excited".

You give the AI zero examples and expect it to read minds. This approach rarely delivers optimal results and it shows in the output.

One-Shot: The Bare Minimum

You: "Write a social media post about our new beauty product launch. Here's an example of a post that performed well: [1 example]"

AI: produces something better, but still missing your brand's unique voice

One-shot prompting is akin to riding a bicycle in a Formula 1 Grand Prix. Better than walking, but you're still severely underequipped.

It does, however, start to talk the talk - if only I knew what all of these things were I could do the same.

Few-Shot: The Gold Standard

You: "Write a social media post about our new beauty product launch. Here are five examples of posts that generated over 500 engagements and aligned perfectly with our brand voice. Two are static posts and three are UGC which seems to work well for our demographic: [5 examples]"

AI: produces content that captures your brand's unique voice and style:

ChatGPT is enthused about the context provided and you can see it starts to delve more into the strategy of the task.

We managed to trigger ChatGPT's feedback mechanism - a win for us! (This feature appears randomly, but you're more likely to see it when you're active on the platform. The OpenAI team typically targets specific interactions they want feedback on, which shows they're interested in gathering deeper insights on your usage patterns.)

The output captured the tone, hallmarks, and warmth of the brand - it even used the brand’s hashtags. A proper, usable post that is almost finished (game-changing is a little cliche but we’ll give it a pass for now).

How and Why?

1. Pattern recognition built-in. With one example, the AI can't distinguish between your brand voice and general social media conventions. With multiple examples, it recognizes your unique patterns.

2. Your unique styles are captured. Multiple examples reveal your tone, your messaging priorities, your specific engagement techniques—not just generic best practices.

3. Edge cases are covered. Different examples showcase different types of announcements, campaigns, or audience segments and how to address them - enhance this by varying your inputs.

4. Results improve exponentially, not linearly. Going from zero to one example helps a little. Going from one to three examples helps a LOT.

AI isn't magic—it's a pattern-matching machine that needs clear patterns to follow. You either dictate these patterns or you rely on the patterns created by guys like me - developers (and you really don’t want developers dictating the tone of your beauty brand…)

If you’re looking to dive deeper, the Prompt Engineering Guide has got you covered. We’ve also covered other prompting techniques in a previous post.

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From around the AI traps

🎨 Canva releases Visual Suite 2.0

Canva's Visual Suite 2.0 blends productivity and creativity. Key additions include Canva Sheets (AI-powered spreadsheets), Canva Code (create interactive elements from text prompts), enhanced AI tools, and a new integrated Photo Editor, all designed for seamless cross-format creation.

📊 Stanford releases the AI Index Report 2025

Stanford just published their big AI Index report for 2025. It gives you a great overview of everything happening in AI – from tech advances and investment trends to education and new laws. They even boiled it down to 10 key charts.

🚀 OpenAI launches GPT-4.1, o3, o4-mini & more specialized models

OpenAI dropped several models. The GPT-4.1 series (including 4.1-mini & 4.1-nano) brings existing ChatGPT 4.0 improvements (better instruction following, coding) to the API, featuring a massive 1 million token context window.

Sheesh, we’ve got a lot to get through in the coming weeks!

Have a cracking weekend and I’ll see you next Thursday,

Adam