The Art of Show vs Tell: Crafting Effective Prompts for Generative AI

Generative AI systems like ChatGPT have taken the world by storm. Their ability to generate human-like text on demand has captured people's imagination. However, behind the magic is the art and science of "prompt engineering" - composing effective prompts to get the desired output from these large language models. In this post, we'll explore the timeless writing principle of "show vs tell" and how it can help create better prompts.

The key to unlocking the potential of ChatGPT and similar AI systems lies in how you frame the initial prompt. A well-crafted prompt acts like a mapping function, guiding the model to generate relevant, high-quality responses. On the other hand, a poorly framed prompt can lead to rambling, inconsistent or even nonsensical AI-written text.

As AI researcher Anthropic puts it: "The prompt is like the genie's lamp - rub it right and magical things come out. Rub it wrong and the genie might misinterpret your wish."

With the prompt being so crucial, techniques like show vs tell prompting can help provide the genie with useful guardrails.

What is an AI prompt? An AI prompt is essentially the initial input or question that you provide to an AI model like ChatGPT. It sets the stage for the conversation, providing the AI with the context it needs to generate a relevant response.

Mastering the ChatGPT basic prompt structure is a crucial step in effectively using the system. This involves understanding how to frame your prompts in a way that guides the AI towards generating the desired output. It's about learning the language that the AI understands and responds to best.

"Show, don't tell" is a longstanding principle in writing and storytelling. The basic idea is that showing events and details through vivid description is often more engaging than simply stating facts. For example:

Tell: Jane was very sad. 

Show: Jane sat alone in the dark bedroom, tears rolling down her cheeks as she clutched a photo of her late husband.

The "show" version helps readers visualize the scene and connect emotionally with the character. 

This technique can be adapted when creating prompts for ChatGPT and other generative AI systems.

Applying show vs tell to AI prompts gives us two stylistic options:

Show-me prompts demonstrate the desired output by providing examples.

Tell-me prompts give instructions by explaining specifications directly. 

Let's see how this works in practice.

Say we want ChatGPT to generate a poem in the style of Robert Frost. A show-me prompt might look like:

Here are two example poems in the style of Robert Frost:

The woods are lovely, dark and deep,
But I have promises to keep,
And miles to go before I sleep.

The river glides so sweet and slow,
As into town the people go
To markets filled with fruits and flowers
For summer's finest hours.

Now, please write an original poem in the style and tone of Robert Frost.

This demonstrates the lyrical, naturalistic style we're looking for. The AI can then pattern match and emulate that style in its output poem.

A tell-me prompt achieves the same goal by directly explaining what we want:

Please write an original poem in the style of poet Robert Frost. The poem should have:

- Rhyming lines with a simple ABA or ABCB rhyme scheme

- Vivid natural imagery like forests, rivers, trees, mountains, etc.

- Thoughtful reflections on nature, the passing of time, changing seasons, life's journeys, etc.

- Clear, conversational language using words of 1-2 syllables

- An introspective tone and melancholic mood

The tell-me prompt communicates the key specifications without providing any examples.

So which approach is better for prompting generative AI? Let's weigh the tradeoffs.

Show-me and tell-me prompts each have advantages and disadvantages:

Show-Me Pros:

- Provides tangible examples for the AI to analyze
- Reduces chances of misinterpretation  
- Often faster/easier than elaborating specifications

Show-Me Cons:

- Hard to find suitable examples for some tasks
- May bias AI towards imitating the exact examples
- Requires multiple examples to avoid overfitting 

Tell-Me Pros:

- Precisely communicates desired qualities  
- Avoids imitation risks of examples
- Can work with no examples (zero-shot)

Tell-Me Cons:

- Hard to articulate nuanced qualities  
- More time-consuming to write detailed specs 
- Higher risk of misinterpretation by AI

There are also some key considerations:

- Nature of the task/question being posed
- Personal preferences in learning styles  
- Time available for composing prompts

In practice, combining both approaches often works best - show some examples, tell some specs. The art is finding the right mix.

Based on the tradeoffs, here are some principles to guide show-me and tell-me prompting:

When showing examples:

- Use 2-4 samples to avoid overfitting on one
- Keep samples concise and tailored to the task
- Use examples representative of desired qualities 

When telling specifications:

- Focus on 3-5 key attributes to convey
- Be precise yet avoid overly rigid constraints
- Use natural language rather than bullet points 

When combining show and tell:

- Order matters: Tell then show or show then tell
- Blend and interleave don't work as well  
- Leverage strengths of each: Show nuance, tell structure

For any prompt:

- Frame the actual task clearly at the end
- Keep prompt focused, simple, free of humor/fluff
- Revise prompts based on AI output quality

These principles help craft prompts that provide the AI with just enough guidance - like giving helpful writing advice to a student.

Just as writing has subjective nuances, so does the art of prompting AI systems. Experience and experimentation over time can help develop "prompt intuition".

Some additional tips:

- Vary prompt structure - don't always follow one template
- Try unusual blends of show-tell techniques 
- Analyze AI outputs to diagnose prompt issues
- Treat prompt crafting like a creative writing exercise

Prompt engineering guides the AI, but doesn't overly constrain it. Well-designed prompts strike a balance, providing a spark without smothering the AI's creativity.

Your ultimate ChatGPT cheat sheet from beginner to pro would include tips on crafting effective prompts, understanding the model's limitations, and how to iterate on your prompts to improve the AI's responses. This cheat sheet would be a valuable resource for anyone looking to harness the power of ChatGPT, whether they're just starting out or are already experienced users.

The ultimate prompt engineering secret lies in understanding the nuances of the AI model and how it interprets different prompts. It's about finding the right balance between being too vague and too specific, and knowing how to guide the AI without over-constraining it. This secret is what separates the average users from the pros, and it's what allows you to truly unlock the potential of ChatGPT. 

As generative AI grows more powerful, prompt engineering will only become more crucial in steering these models safely and effectively.  

Future research may reveal additional prompting techniques beyond show-tell. But for now, these principles provide a solid starting point for extracting the best output from ChatGPT and similar systems.

The core ideas of show vs tell prompt design - demonstrating through examples and specifying attributes - will continue empowering both human and AI creators.

So next time you use an AI assistant, think about how show-me or tell-me prompting can help it generate higher quality responses. With practice, you'll gain intuition for which approach works best in different situations.

The future of AI is bright, as long as we light its path with thoughtful, well-designed prompts.