A beginner’s guide to different prompt engineering techniques

In the world of Artificial Intelligence (AI) and Natural Language Processing (NLP), Prompts serve as catalysts that start meaningful interactions between humans and machines. These short, instructive sentences or phrases are intended to guide AI models in generating responses that are contextually relevant, accurate and insightful. Whether you're asking a virtual assistant to set a reminder or querying a complex AI model for data analysis, it all starts with a well-crafted prompt.

Why effective prompt writing matters

The importance of effective prompt writing cannot be overstated. A poorly designed prompt can lead to ambiguous or irrelevant responses, thereby diminishing the user experience and the utility of the AI model. On the other hand, a well-structured prompt can unlock the full potential of an AI system, enabling it to deliver precise and valuable outputs. This is especially crucial in professional settings where the stakes are high; for example healthcare diagnostics, financial forecasting or legal document analysis. In such scenarios, the quality of the prompt directly impacts the quality of the decision-making process.

Navigating the landscape of prompt frameworks

Given the pivotal role that prompts play, it's essential to approach prompt writing in a structured manner. This is where prompt frameworks come into play. These frameworks offer a systematic way to construct prompts, ensuring that they are clear, focused and effective in eliciting the desired response from AI models.

In this article, we will explore various frameworks designed to optimise prompt writing. We'll delve into established frameworks such as the RTF (Request, Task, Format) and introduce newer additions to the toolkit, such as the Chain of Thought, RISEN, RHODES and Chain of Destiny frameworks. Each of these frameworks has its unique strengths, applications and best practices, which we will discuss in detail.

The need for a structured approach

In the world of AI and NLP, where models are becoming increasingly sophisticated, the need for a structured approach to prompt writing is crucial. A structured prompt not only ensures that the AI model understands the user's request but also significantly enhances the quality of the output. Frameworks provide a systematic way to formulate prompts, incorporating various elements such as context, specificity and clarity, which are essential for generating meaningful responses.

Challenges of unstructured prompts

Conversely, unstructured prompts often lead to a host of challenges that can undermine the effectiveness of an AI model. Here are some of the key issues:

Ambiguity: Unstructured prompts can be vague, leading to ambiguous responses from the AI model. For example, asking a financial AI model, "Tell me about stocks," could yield a wide range of answers, from stock definitions to current market trends. The lack of specificity makes it difficult for the model to provide a focused and useful answer.

Inconsistency: Without a structured framework, prompts can vary greatly in their construction and intent, leading to inconsistent results. This inconsistency can be particularly problematic in professional settings where uniformity and reliability are crucial.

Inefficiency: Unstructured prompts often require multiple iterations to get the desired output, wasting both time and computational resources. This inefficiency becomes increasingly problematic as AI models grow more complex and resource-intensive.

Ethical and compliance risks: In sectors such as healthcare and finance, where compliance with regulations is mandatory, unstructured prompts can lead to outputs that are not only incorrect but also legally risky. A structured approach ensures that all necessary guidelines and parameters are considered when formulating a prompt.

The value proposition of prompt frameworks

Prompt frameworks offer a solution to these challenges by providing a structured methodology for crafting effective prompts. They act as a blueprint, guiding the user in asking the right questions in the right way. By adhering to a framework, users can ensure that their prompts are clear, focused and aligned with their Objectives, thereby maximising the utility and efficiency of AI models.

In the following sections, we will explore various prompt frameworks, examining their unique features and applications. Whether you are a novice looking to understand the basics or a seasoned professional aiming to refine your skills, these frameworks offer invaluable insights into the art and science of prompt writing.

1. The RTF Framework

What is the RTF Framework?

The RTF Framework stands for Request, Task and Format. It is a structured approach to prompt writing that aims to streamline the interaction between the user and the AI model. By breaking down the prompt into three distinct components, the RTF Framework ensures that the AI model receives a well-defined, actionable request that is easy to understand and execute.

Components of the RTF Framework

Request: The Request component is the initial part of the prompt where the user specifies what they want the AI model to do. This is usually a direct question or command aimed at eliciting a specific type of response. The Request sets the stage for the interaction, providing the AI model with the context it needs to generate a meaningful output.

Task: The Task component elaborates on the Request, providing additional details or specifications. This could include parameters, conditions or any other information that helps the AI model understand the scope and requirements of the task at hand.

Format: The Format component is optional and is used to specify the desired format of the AI model's response. This could be a particular data structure, a specific layout or even a preferred language style. The Format component helps tailor the output to meet specific needs or preferences, making the interaction more user-friendly and effective.

Where is the RTF Framework most effectively used?

The RTF Framework is particularly useful in scenarios where a complex or multi-step interaction is required. It is ideal for professional settings, such as customer service, healthcare and data analysis, where clarity and precision are paramount. The framework is also beneficial in educational contexts, helping students interact more effectively with educational AI tools.

Real-world examples of using the RTF Framework

Example 1: Customer Service

• Request: "Tell me about your refund policy."
• Task: "Specifically, I want to know the conditions under which I can return an electronic item."
• Format: "Please provide the information in bullet points."

Example 2: Healthcare

• Request: "List the symptoms of Type 2 diabetes."
• Task: "Include both common and rare symptoms."
• Format: "Organise the symptoms in order of severity."

Example 3: Data Analysis

• Request: "Generate a sales report for the last quarter."
• Task: "Include revenue, expenses and net profit, broken down by department."
• Format: "Present the data in a bar chart."

By employing the RTF Framework, users can craft prompts that are not only clear and actionable but also tailored to their specific needs and contexts. This structured approach significantly enhances the quality of the interaction, making it a valuable tool for anyone looking to leverage the power of AI and NLP effectively.

2. The Chain of Thought Framework

What is the Chain of Thought Framework?

The Chain of Thought Framework is a specialised prompt engineering technique designed to enhance the reasoning capabilities of language models such as GPT-4. By instructing the AI to approach a problem "step-by-step," this framework guides the model through a logical sequence of thoughts, making it particularly effective for complex analytical tasks and problem-solving.

Key components and flow

The primary component of this framework is the phrase "Let's think through it step-by-step," which is added at the end of your prompt. This phrase serves as a directive for the AI model to break down the problem into smaller, more manageable parts and think through each one logically.

The flow is straightforward:

Problem Statement: Clearly define the problem or question you're trying to solve.

Step-by-Step Directive: Add the phrase "Let's think through it step-by-step" to guide the AI in its reasoning process.

Where is it most effectively used?

The Chain of Thought Framework excels in scenarios that require detailed analysis or problem-solving. Whether you're wanting to dissect a complex issue or find a solution to a challenging problem, this framework helps by encouraging the AI to think logically and sequentially.

Real-world examples and template

Prompt Template: "[insert your prompt instructions]. Let's think through it step-by-step."

Example: Analysing Market Trends

Prompt: "What factors are contributing to the declining market share of our product? Let's think through it step-by-step."

In this example, the AI would systematically evaluate various factors such as competition, consumer behaviour and marketing strategies, providing a comprehensive analysis that could lead to actionable insights.

The Chain of Thought Framework simplifies the process of tackling complex issues by encouraging a step-by-step analytical approach, making it a valuable tool for anyone who wants to harness the problem-solving capabilities of AI.

3. The RISEN Framework

What is the RISEN Framework?

The RISEN Framework is a prompt engineering technique designed to break down complex or constrained tasks into actionable components. The acronym RISEN stands for Role, Instructions, Steps, End goal and Narrowing (constraints) and it provides a structured approach to guide AI in executing tasks with multiple layers, such as blog posts, research projects or business plans.

Key components and flow

The RISEN Framework consists of the following key components:

Role (R): Define the role you want the AI to take. This sets the tone and expertise level for the output.

Instructions (I): Clearly state the main task you want the AI to complete.

Steps (S): Provide a numbered list of steps for the AI to follow in completing the task.

End Goal (E): Specify the goal of the output, what you aim to achieve with it.

Narrowing (N): List any constraints that the AI should consider, such as word count limits or specific focus areas.

The flow is sequential, starting with defining the role and ending with setting constraints, to ensure that the AI understands the task in its entirety and can execute it effectively.

Where is it most effectively used?

The RISEN Framework is particularly useful for tasks that require a multilayered approach, such as creating content, planning projects or developing business strategies. It is effective in situations where you need the AI to consider multiple variables and constraints while still focusing on a specific end goal.

Real-world examples and template

Prompt Template:

Role: [insert the role you want AI to take.]

Main Task: [Insert the task you want AI to complete.]

Steps to complete task: [Insert numbered list of steps to follow.]

Goal: [Insert goal of the output]

Constraints: [Enter constraints].

Example: Planning a Marketing Campaign for a New Product

Prompt:

Role: "You are a seasoned marketing strategist with a decade of experience in launching successful products".

Main Task: "Develop a comprehensive marketing plan for the launch of our new eco-friendly water bottle".

"Steps to complete the task:"

"1. Begin by outlining the target audience and market research findings".

"2. Discuss the marketing channels to be used and why they are effective for this product".

"3. Provide a timeline for the campaign, including key milestones and deadlines".

"4. End with a budget allocation and expected ROI for each marketing channel".

Goal: "The goal is to create a well-rounded marketing plan that maximises reach and ROI, while aligning with our brand values".

Constraints: "Maximum of 1000 words. Use layman's terms. Include both online and off-line strategies. Make it actionable".

By using this RISEN Framework prompt, you can expect to receive a comprehensive marketing plan that starts with identifying the target audience, moves through channel selection and timeline planning and ends with budget and ROI considerations. All of this will be done within the constraints of a 1000-word limit, easy-to-understand language and a mix of online and off-line strategies.

This example demonstrates how the RISEN Framework can be applied to complex tasks that require a structured approach for effective execution. It ensures that all critical aspects of the task are covered, making it a valuable tool for project planning and strategy development.

4. The RHODES Framework

Definition and key components

The RHODES Framework is a structured approach to prompt writing that is particularly useful when you have good examples of your desired output. The acronym stands for Role, Objective, Details, Examples and Sense Check. (Note the extra H in the acronym). Each component serves a specific purpose:

R (Role): Specifies the role you want the AI to take on. This sets the tone and expertise level for the output.

O (Objective): Clearly states what you want the AI to accomplish.

D (Details): Provides any context or constraints that the AI needs to consider for generating a good output.

E (Examples): Offers examples that the AI can use as a model for its answer. These examples serve as a guide for the style, tone or structure.

S (Sense Check): Asks the AI to confirm its understanding of the objective and guidelines.

Effective use cases

The RHODES Framework is most effective when you have a clear idea of what you want but need the output to adhere to specific styles or examples. It is excellent for creative tasks, marketing copy or any situation where the style and tone are as important as the content itself.

Real-world examples

Here's how to use the RHODES Framework in a real-world scenario:

Example: Creating a LinkedIn Headline for a Digital Marketing Expert

Prompt:

Role: "You are an experienced copywriter specialising in LinkedIn profiles".

Objective: "Craft a LinkedIn headline that will attract recruiters in the digital marketing field".

Details:

• "The headline should be no longer than 120 characters".
• "Use language that highlights expertise and experience".
• "Avoid using buzzwords or clichés".

Examples: "Here are some examples to model your answer after (note: these are not on my desired topic but they illustrate the kind of impactful language and structure that I want)":

1. "Transforming businesses through data-driven strategies. ROI is my middle name."

2. "Empowering teams to reach their full potential. Leadership through innovation."

3. "Cutting through the noise to deliver measurable PR results. Your story, well told."

Sense Check: "Do you understand the objective and the specific guidelines for this task?"

By employing the RHODES Framework in this manner, you can expect a LinkedIn headline that not only stands out but also closely aligns with the style and tone set by the examples. This makes the RHODES Framework an excellent choice for tasks that require a blend of accuracy and creativity.

5. The Chain of Destiny Framework

Definition and key components

The Chain of Destiny Framework is an iterative approach designed to refine and improve content through multiple cycles of feedback and revision. It is particularly useful for tasks such as summarising articles, enhancing long-form content and even refining your prompts for better AI output.

The framework consists of the following key components:

Instructions: Define the content you want to improve.

Recursion: A set of steps that are repeated multiple times to refine the output.

Benchmark: Additional information to guide what constitutes a good output.

Additional Guidelines: Specific rules or constraints to follow during the process.

Where it's most effective

The Chain of Destiny Framework is most effective when you have a piece of content that requires multiple iterations for improvement. It's excellent for refining marketing materials, academic papers or any content that can benefit from a recursive, iterative process.

Real-world example

Instructions: "Here is a draft of my LinkedIn summary: 'Experienced in marketing with a focus on digital strategies. Looking for new opportunities.'

"You will generate increasingly improved versions of this LinkedIn summary".

Recursion: "Repeat the following 2 steps 5 times".

"Step 1. Identify 1-3 points from the initial output that are missing or could be improved".

"Step 2. Write a new, improved output of identical length which includes the missing or improved points".

Benchmark: "Here is more information on what makes a good LinkedIn summary":

• "Be Clear: The summary should succinctly describe your experience and goals".
• "Be Specific: Include specific skills or achievements to stand out".
• "Call to Action: Encourage the reader to connect or reach out to you".

Additional Guidelines: "Keep the summary under 300 characters. Use professional language. Avoid buzzwords".

By following this framework, you can expect a LinkedIn summary that not only stands out but also closely aligns with professional standards. This makes the Chain of Destiny Framework an invaluable asset for tasks that require a blend of accuracy and creativity.

Comparative analysis of different prompt frameworks

We have learned that Prompt frameworks are essential tools for generating precise and effective outputs from AI and Natural Language Processing systems. Each framework has its unique features, making it more or less suitable for certain types of tasks. Let's compare our five frameworks (RTF, Chain of Thought, RISEN, RHODES, and Chain of Destiny), in terms of ease of use, effectiveness, and application areas.

Ease of use

RTF: This framework is straightforward and easy to use, requiring only three main components: Role, Task, and Format. It's ideal for beginners or those who need quick, structured prompts.

Chain of Thought: Also easy to use, simply requiring the addition of the phrase "Let's think through it step-by-step" to your prompt. It's accessible for users at all levels.

RISEN: Requires more planning as it involves multiple steps and constraints, making it moderately easy to use. It may take some practice to master but is still accessible to most users.

RHODES: Similar to RISEN in complexity but includes examples, adding a layer of intricacy. It's moderately challenging to use effectively but can be powerful when mastered.

Chain of Destiny: This is the most complex of the five frameworks, requiring multiple iterations and a clear understanding of the desired outcome. It's best suited for advanced users or those dealing with complex, multi-faceted tasks.

Effectiveness

RTF: Highly effective for generating specific outputs but may lack depth for more complex tasks. It's particularly useful for straightforward queries and simple content generation.

Chain of Thought: Exceptional for problem-solving and analytical tasks. It's highly effective when you need the AI to break down complex problems into manageable steps.

RISEN: Highly effective for complex tasks that require a structured approach. It excels in situations where multiple factors need to be considered within specific constraints.

RHODES: Effective when you have good examples to guide the output. It's particularly powerful for tasks where style and tone are as important as content.

Chain of Destiny: Extremely effective for refining and improving content through iterations. It's the most potent tool for tasks that require multiple revisions and fine-tuning.

Application areas

RTF: Best for quick queries, data extraction and simple content generation. Ideal for customer service interactions, basic research tasks, and straightforward content creation.

Chain of Thought: Ideal for problem-solving, decision-making, and analytical tasks. Well-suited for strategic planning, troubleshooting and complex analysis in fields such as business, science and engineering.

RISEN: Suited for research projects, blog posts and other complex tasks requiring a structured approach. Excellent for content creation, project planning, and strategy development across various industries.

RHODES: Useful when you have examples to guide the output, such as copywriting or content creation. Particularly effective for marketing materials, creative writing and any task where maintaining a specific style or tone is crucial.

Chain of Destiny: Perfect for iterative content refinement, such as academic papers, marketing materials or any content that benefits from multiple revisions. Ideal for tasks that require high precision and continuous improvement, such as technical documentation or high-stakes business proposals.

Conclusion

While each framework has its strengths and limitations, the key is to choose the one that aligns best with your specific needs and level of expertise:

For quick and specific outputs, RTF is a great choice.

If you're tackling complex problems that require logical breakdown, Chain of Thought is probably most suitable.

For multi-layered tasks with specific constraints, RISEN offers the most comprehensive approach.

When you have good examples and need to match a particular style, RHODES is excellent.

For tasks requiring iterative refinement and the highest level of precision, Chain of Destiny is the ultimate choice.

Understanding the strengths and weaknesses of each framework can help you make an informed decision for your specific use-case. As you gain experience with these frameworks, you may find yourself mixing and matching elements to create hybrid approaches that best suit your unique requirements.

Remember, the effectiveness of any framework ultimately depends on how well it's applied and how closely it aligns with the task at hand. Experimentation and practice are key to mastering these prompt engineering techniques and leveraging them to their full potential.