Comparing Different Prompt Templates and Frameworks for AI Assistants

As a prompt engineer, having a diverse toolkit of templated frameworks is invaluable for tailoring prompts efficiently. Certain templates tend to work better for specific use cases and AI models. In this post, I’ll provide an overview comparing the most popular prompt templates and when to apply each.

With the right framing, prompts become more coherent, effective, and aligned to your goals. Let’s explore some prompt architecture options to inform your prompt design choices.

Why Templated Prompt Frameworks Help

First, why use prompt templates at all? Some key benefits:

• Provides an optimal starting structure to build upon
• Encapsulates proven prompt engineering best practices
• Accelerates prompt drafting with fill-in-the-blank components
• Guides prompt shaping for specialized applications or AI models
• Makes iteratively testing variations easier by adjusting template modules
• Helps avoid common prompt anti-patterns

Of course creativity and customization beyond any template is still essential. But templates provide scaffolding to enhance prompts.

Types of Prompt Templates

Here are some of the most common prompt template structures:

A/B/C Prompts

Contains:

A – Instructions and context B – Examples C – Completion command

Ex:

A: You are an AI assistant created by Anthropic to be helpful, harmless, and honest. I would like you to act as a tutor explaining quantum computing concepts. B: For example, you could explain qubits as the basic units of quantum information in simple terms that a high school student could understand. C: Please explain the key principles of quantum computing in a simple tutorial format.

Situation, Behavior, Intent Prompts

Contains:

Situation – Background context Behavior – Desired AI action Intent – Goal and motivation

Ex:

Situation: I am preparing remarks as a keynote speaker at a technology conference next week. Behavior: Please write a draft 2 minute opening statement. Intent: It should introduce me and get the audience excited about developments in AI.

Goal-Oriented Prompts

Contains:

Goal – Specific objective Plan – Strategic guidance to achieve goal Call to Action – What AI should do

Ex:

Goal: I want to learn more about advances in renewable energy. Plan: Please summarize recent innovations in solar panel efficiency in the last 5 years based on reputable reports.

Call to Action: Provide a 1-2 paragraph overview of the new solar innovations I should know about.

Choosing the Right Template for the Job

Certain templates work better for some applications:

• A/B/C for question-answering and explanation
• Situation/Behavior/Intent for task completion
• Goal-Oriented for research and recommendations
• Mix and match modules as needed
  
  

Consider the use case when selecting templates.

Template Examples for Specific AI Models

Some templates also align better to different AI architectures:

Claude (Anthropic)

• Activate helpfulness and truth in prefix
• Use A/B/C structure focused on concise Q&A
  
  

CoPilot (GitHub)

• Frame requests conversationally as collaborator
• Build on shared context with goal-based prompts
  
  

GPT-3 (OpenAI)

• Provide rich examples to steer its broad knowledge
• Goal/Plan/Action structure guides large-scale reasoning
  
  

Developing Your Own Prompt Templates

You can also develop custom templates optimized for your common use cases and AI assistant. Analyze the prompts that reliably work well for you and extract a reusable framework.

Over time, you will assemble your own library of time-saving templates tailored to your needs.

Template Consistency vs. Variety

Use templates consistently where they excel, but also mix it up. Too much repetitiveness can bore certain AI systems. Cycle through your template collection for diversity.

And always customize by fleshing out details – never just plug and play. Templates are starting points, not total solutions.

Treat Prompts as Living Structures

No single template will be a silver bullet. Prompts must evolve as capabilities improve. Continually test new frameworks and hybrid templates.

View prompt templates as helpful kickstarters that still require creative, iterative enhancement based on performance.

The goal is prompts that feel hand-crafted for each use case while benefiting from templated best practices. Master prompt architects artfully blend structure with customization.

I hope this overview provides a helpful starting point for assessing and applying prompt templates. As always, please reach out if you need any personalized consulting on finding the right prompt frameworks. Keep innovating!