System Prompts in Large Language Models

Discover the power of system prompts - the secret sauce that enables developers to customize AI behavior and enhance performance. Learn how to craft effective prompts for role-playing, rule adherence, context understanding, and more.

System Prompts in Large Language Models

System prompts, while often overlooked, have gained significant attention since the publication of the review on Claude's system prompt. Many inquiries have been received regarding their nature and utility. Certain elements of system prompts can be adapted for daily use and incorporated into various systems, such as customGPTs and other similar applications. The growing interest in system prompts highlights their potential to enhance and streamline AI-powered solutions across a wide range of domains.

What Exactly Are System Prompts?

System prompts are a crucial component in any AI, especially LLMs, and guide the way AI models interpret and respond to user queries. These carefully crafted instructions serve as the guiding light for AI, directing their behavior and ensuring that the generated outputs align with the intended goals. By providing a clear and concise definition of system prompts and highlighting their significance in shaping AI model behavior, we can gain a deeper understanding of their transformative.

At their core, system prompts are a set of instructions, guidelines, and contextual information provided to AI models before they engage with user queries. These prompts act as a framework, setting the stage for the AI to operate within specific parameters and generate responses that are coherent, relevant, and aligned with the desired outcome. System prompts play a pivotal role in bridging the gap between the vast knowledge acquired by AI models during training and their application in real-world scenarios.

Importance of system prompts in guiding AI model behavior

The importance of system prompts cannot be overstated when it comes to guiding AI model behavior. By carefully crafting these prompts, developers and researchers can harness the power of AI models and steer them towards generating outputs that are not only accurate but also contextually appropriate. System prompts act as a compass, ensuring that the AI model stays on course and does not deviate from the intended purpose.

Moreover, system prompts enable developers to fine-tune the behavior of AI models, adapting them to specific domains, roles, and tasks. By incorporating role-specific guidelines, tone instructions, and creativity constraints, system prompts allow AI models to exhibit more natural and coherent responses, mimicking human-like interactions. This level of customization is particularly valuable in applications such as chatbots, virtual assistants, and content generation, where the AI model's ability to understand and respond to user queries in a contextually relevant manner is paramount.

The significance of system prompts extends beyond simply guiding AI model behavior; they also play a crucial role in enhancing the overall performance and efficiency of NLP systems. Well-crafted system prompts can help AI models navigate complex queries, handle ambiguity, and generate responses that are not only accurate but also engaging and informative. By setting clear expectations and providing a structured framework, system prompts enable AI models to operate at their full potential, delivering results that are both impressive and valuable.

Benefits of Using System Prompts

System prompts offer a range of benefits that significantly enhance the performance and user experience of AI models in natural language processing (NLP) applications. By providing clear instructions, context, and guidelines, system prompts enable AI models to generate more accurate, relevant, and engaging responses. In this chapter, we will explore how system prompts can enhance AI model performance, particularly in maintaining personality in role-playing scenarios and increasing resilience against attempts to break character.

Enhancing AI Model Performance

One of the primary benefits of using system prompts is their ability to enhance the overall performance of AI models. By offering a structured framework for interaction, system prompts guide AI models to generate responses that are more coherent, contextually relevant, and aligned with the intended purpose of the application. This enhancement in performance is particularly evident in two key areas: maintaining personality in role-playing scenarios and increasing resilience against attempts to break character.

Maintaining Personality in Role-Playing Scenarios

In applications where AI models are required to assume a specific persona or role, such as a virtual assistant or a customer support representative, maintaining a consistent personality throughout the interaction is crucial for a seamless user experience. System prompts enable developers to define the desired personality traits, communication style, and domain knowledge that the AI model should exhibit in these role-playing scenarios.

By incorporating detailed persona descriptions, tone guidelines, and context-specific responses into the system prompt, developers can ensure that the AI model stays true to its assigned role throughout the conversation. This consistency in personality helps build trust and rapport with users, making the interaction feel more natural and engaging.

For example, a system prompt for a virtual tour guide at a historical museum might include the following personality guidelines:

You are an enthusiastic and knowledgeable tour guide named Emily. You have a passion for history and love sharing fascinating stories about the exhibits with visitors. Your communication style is friendly, engaging, and informative, and you always strive to make the tour experience memorable for your guests.

By adhering to these personality guidelines, the AI model can provide a consistent and immersive experience for users, making them feel as though they are interacting with a real tour guide.

Increasing Resilience Against Attempts to Break Character

Another significant benefit of using system prompts is their ability to increase the AI model's resilience against attempts to break character. In some cases, users may intentionally or unintentionally ask questions or make statements that are outside the scope of the AI's assigned role or domain knowledge. Without proper guidance, the AI model may generate responses that are inconsistent, inappropriate, or simply irrelevant.

System prompts can help mitigate this issue by providing the AI model with clear boundaries and fallback responses for handling out-of-scope queries. By defining these boundaries and response strategies within the system prompt, developers can ensure that the AI model maintains its character and provides a coherent user experience, even when faced with challenging or unexpected inputs.

For instance, a system prompt for a virtual financial advisor might include the following resilience guidelines:

If a user asks about topics outside your area of expertise, such as medical advice or legal matters, politely inform them that you are not qualified to provide guidance on those subjects and suggest they consult with the appropriate professionals. If a user becomes hostile or uses inappropriate language, maintain a calm and professional demeanor, and remind them of the purpose and boundaries of your role as a financial advisor.

By equipping the AI model with these resilience strategies, developers can minimize the risk of inconsistent or inappropriate responses, ensuring a more robust and reliable user experience.

Exhibiting More Creative and Natural AI Behavior

System prompts can be used to encourage AI models to generate more creative and natural responses. By incorporating guidelines that promote the use of varied language, analogies, and storytelling techniques, developers can steer the AI model towards producing more engaging and dynamic outputs.

For example, a system prompt for a creative writing assistant might include the following guidelines:

When generating stories or poems, feel free to use figurative language, such as metaphors, similes, and personification, to make your writing more vivid and engaging. Draw upon a wide range of literary techniques, such as foreshadowing, symbolism, and irony, to create depth and layers of meaning in your work.

By providing these creative guidelines, the AI model can produce more imaginative and thought-provoking content that captivates and inspires the reader.

Improving AI's Ability to Follow Rules and Instructions

System prompts play a crucial role in ensuring that AI models adhere to specific rules and instructions. By explicitly stating the guidelines and constraints within the system prompt, developers can improve the AI's ability to follow complex sets of rules and generate outputs that are consistent with the desired specifications.

This ability to follow rules and instructions is particularly important in domains such as legal document generation, medical record summarization, or technical writing, where adherence to specific formats, terminology, and style guides is essential.

For instance, a system prompt for a legal contract generation AI might include the following instructions:

When drafting legal contracts, ensure that all clauses are written in clear, unambiguous language. Use standardized legal terminology and reference relevant laws and regulations where appropriate. Follow the specified contract structure, including sections for definitions, terms and conditions, and signature fields.

By providing these detailed instructions, the AI model can generate legal contracts that are compliant with the required standards and formats, reducing the risk of errors or ambiguities.

Customizing Interaction Style for Specific Tasks

Another significant benefit of using system prompts is the ability to customize the interaction style of the AI model for specific tasks or domains. By tailoring the language, tone, and approach outlined in the system prompt, developers can create AI models that are optimized for particular use cases or target audiences.

For example, a system prompt for a children's educational chatbot might include the following interaction guidelines:

When engaging with young learners, use simple, age-appropriate language and explain complex concepts in a clear and concise manner. Employ a friendly, encouraging tone and use positive reinforcement to keep children motivated and engaged in the learning process. Incorporate interactive elements, such as quizzes, games, and storytelling, to make the learning experience more enjoyable and memorable.

By customizing the interaction style to suit the needs and preferences of the target audience, developers can create AI models that are more effective in achieving their intended goals, whether it's education, customer support, or entertainment.

Other Benefits of System Prompts

Incorporating well-crafted system prompts can significantly enhance the AI's performance and output quality. Here are just a few of the benefits:

  1. Improved Role-Playing: Assign the AI a specific character and watch it maintain consistency throughout the conversation, exhibiting more natural and creative responses while staying true to its assigned persona.
  2. Increased Rule Adherence: System prompts help the AI better understand and follow your guidelines, reducing the likelihood of prohibited tasks, restricted content, or deviations from your instructions.
  3. Enhanced Context Understanding: By providing relevant background information or reference material in the system prompt, you can improve the AI's comprehension of your input and enable it to generate more accurate and context-aware responses.
  4. Customized Output Formatting: Specify your desired output format, such as headers, lists, tables, or code blocks, ensuring that the AI's responses are structured and presented in a way that best suits your needs.
  5. Improved Model Accuracy: Tailoring prompts to better match the desired outcomes can significantly enhance model accuracy, making it easier to deploy pre-trained models on specific tasks, especially in few-shot scenarios. This approach can lead to a substantial increase in sample efficiency, with a prompt potentially being worth 100 conventional data points.
  6. Enhanced Sample Efficiency: System prompts can bring a significant leap in sample efficiency, making it smoother to handle new tasks with only a few training examples. This efficiency is crucial, especially when fine-tuning pre-trained models for new tasks where data may be limited.
  7. Increased Robustness and Resilience: Using system prompts enables AI models like Claude to stay more deeply in character during role-playing scenarios, exhibit more creative and natural behavior, and be more resilient against attempts to break character. This robustness extends to following rules and instructions effectively.
  8. Smoother Task Adaptation: System prompts help bridge the gap between pre-training objectives and downstream tasks by aligning the format of downstream tasks with pre-training objectives. This alignment makes it easier for AI models to adapt to new tasks without the need for extensive parameter updates.
  9. Guided Output Generation: Well-written system prompts guide AI models like Claude in generating responses that align with the intended goals and roles assigned to them. This guidance ensures that the AI model's output is coherent, relevant, and aligned with the desired outcomes.

How System Prompts Work

By providing a well-defined set of instructions, context, and guidelines, system prompts enable AI models to generate responses that are coherent, relevant, and aligned with the intended goals. In this chapter, we will delve into the inner workings of system prompts, exploring how they provide essential information to AI models, their role in specifying goals and context, and the structured format they follow.

Providing context, instructions, and guidelines to AI models

At the heart of system prompts lies their ability to provide AI models with the necessary context, instructions, and guidelines to effectively respond to user queries. These prompts serve as a roadmap, guiding the AI model through the complexities of natural language understanding and generation. By clearly outlining the task at hand, specifying the desired output format, and setting boundaries for the AI's behavior, system prompts ensure that the generated responses are accurate, relevant, and in line with the user's expectations.

Role of system prompts in specifying goals, roles, and context for AI

System prompts play a crucial role in defining the goals, roles, and context for AI models in NLP tasks. By explicitly stating the purpose of the interaction, such as answering questions, providing recommendations, or engaging in conversation, system prompts help AI models understand their designated role. Moreover, these prompts can specify the context in which the AI should operate, such as a particular domain, industry, or user persona. This contextual information allows the AI to tailor its responses, making them more relevant and engaging for the user.

Structured format of system prompts

To ensure that AI models can effectively interpret and utilize the information provided, system prompts follow a structured format. This format typically consists of a multiline string that encapsulates the entire prompt, followed by two new lines before the user input. By adhering to this structure, developers can maintain consistency and clarity in their system prompts, making it easier for AI models to parse and understand the instructions.

Placement before user input

System prompts are always placed before the user input, setting the stage for the interaction between the user and the AI model. This placement ensures that the AI has access to the necessary context, instructions, and guidelines before processing the user's query. By positioning the system prompt at the beginning of the interaction, developers can ensure that the AI model is primed and ready to generate accurate and relevant responses.

Content of System Prompts

The content of system prompts plays a vital role in shaping the behavior and output of AI models in natural language processing (NLP) tasks. By carefully crafting the instructions, personalization elements, and constraints within these prompts, developers can guide AI models to generate responses that align with the intended purpose and style. In this chapter, we will explore the key components of system prompt content, focusing on task instructions, role prompting, and tone instructions.

Task Instructions

Task instructions form the backbone of system prompts, providing clear and concise directions for the AI model to follow. These instructions outline the specific actions or objectives the AI should accomplish when processing user input. By explicitly stating the desired outcome, task instructions ensure that the AI model generates relevant and accurate responses.

Some common examples of task instructions include:

  • Answering questions based on provided context
  • Generating text summaries or paraphrases
  • Translating content from one language to another
  • Classifying or categorizing input data
  • Engaging in conversational interactions

When crafting task instructions, it is essential to use precise and unambiguous language. This clarity helps the AI model understand the expected output format, any specific constraints or requirements, and the overall goal of the task at hand.


Personalization elements within system prompts allow developers to fine-tune the AI model's behavior and create more engaging and targeted interactions. By incorporating role prompting and tone instructions, developers can infuse the AI's responses with specific characteristics, making the interaction feel more natural and tailored to the user's needs.

Role Prompting

Role prompting involves assigning a specific persona or character to the AI model within the system prompt. By defining the AI's role, such as a customer service representative, a subject matter expert, or a virtual companion, developers can guide the AI to respond in a manner consistent with that role.

For example, a system prompt for a virtual fitness coach might include role prompting instructions like:

You are a knowledgeable and encouraging fitness coach named Alex. Your goal is to help users achieve their health and wellness objectives by providing personalized advice, workout recommendations, and motivation.

By establishing the AI's role as a fitness coach and outlining its primary objectives, the system prompt sets the stage for interactions that align with the user's expectations.

Tone Instructions

Tone instructions help define the overall style and emotional undertone of the AI's responses. By specifying the desired tone, such as friendly, professional, empathetic, or authoritative, developers can ensure that the AI's language and approach match the context and purpose of the interaction.

For instance, a system prompt for a customer support chatbot might include tone instructions like:

Please respond to user inquiries in a friendly and empathetic manner, while maintaining a professional tone. Use positive language and offer helpful solutions to their problems.

These tone instructions guide the AI to communicate in a way that builds rapport with the user, demonstrating understanding and a willingness to assist.

By combining role prompting and tone instructions, developers can create highly personalized AI interactions that resonate with users and enhance the overall user experience.

Creativity constraints

While AI models are capable of generating highly creative and original content, there may be instances where developers need to set boundaries or constraints on the AI's creativity. This is particularly important in scenarios where the generated content needs to adhere to specific guidelines, such as brand voice, legal requirements, or cultural sensitivities. By incorporating creativity constraints into system prompts, developers can strike a balance between allowing the AI model to generate novel content while ensuring that it remains within acceptable limits.

Rules and Guidelines

Incorporating rules and guidelines into system prompts is essential for ensuring that the AI model's behavior aligns with the intended purpose, ethical standards, and user expectations. These rules and guidelines serve as a framework for the AI model to operate within, promoting responsible and trustworthy interactions with users. By explicitly defining these boundaries within the system prompt, developers can create AI models that generate appropriate, safe, and reliable content.

Some key areas where rules and guidelines can be applied include:

  1. Content restrictions: Specifying the types of content that the AI model should avoid generating, such as hate speech, explicit material, or politically sensitive topics.
  2. Privacy and confidentiality: Ensuring that the AI model respects user privacy by not disclosing personal information or using data in unauthorized ways.
  3. Ethical considerations: Guiding the AI model to make decisions and generate content that adheres to ethical principles, such as fairness, non-discrimination, and transparency.
  4. Legal compliance: Ensuring that the AI model's behavior complies with relevant laws and regulations, such as data protection, intellectual property rights, and content moderation.
  5. Branding and style consistency: Maintaining a consistent brand voice, tone, and style across all interactions, in line with the organization's guidelines.

By incorporating these rules and guidelines into the system prompt, developers can create AI models that are more responsible, reliable, and aligned with the values and expectations of the application and its users.

Output Verification Standards

Output verification standards are a crucial component of system prompts, serving as a quality control mechanism for the AI-generated content. These standards define the criteria that the AI's output must meet to ensure it is accurate, relevant, coherent, and appropriate for the intended audience. By incorporating these verification standards into the system prompt, developers can maintain the overall quality and effectiveness of the AI-powered application.

Some common output verification standards include:

  1. Factual accuracy: Verifying that the generated content is factually correct and does not contain any false or misleading information.
  2. Relevance: Ensuring that the AI's output is relevant to the user's query or context and provides meaningful insights or solutions.
  3. Coherence and clarity: Checking that the generated content is well-structured, logically coherent, and easy to understand for the target audience.
  4. Grammatical and stylistic correctness: Reviewing the output for proper grammar, spelling, punctuation, and adherence to the specified writing style and tone.
  5. Adherence to rules and guidelines: Verifying that the generated content complies with the defined rules and guidelines, such as avoiding sensitive topics or maintaining brand consistency.

Implementing these output verification standards involves a combination of automated checks and human review processes. Automated checks can identify and flag potential issues, such as grammatical errors or factual inconsistencies, while human reviewers can provide a more nuanced evaluation of the content's quality, relevance, and appropriateness.

By subjecting the AI's output to these rigorous verification standards, developers can ensure that the generated content meets the required quality thresholds before being presented to the user. This process helps maintain the integrity and effectiveness of the AI-powered application, ultimately providing users with accurate, relevant, and well-crafted responses to their queries.

Output verification standards

Output verification standards are another crucial component of system prompts, serving as a quality control mechanism for the generated responses. These standards can include criteria such as factual accuracy, coherence, relevance, and fluency. By specifying these verification standards, developers can ensure that the AI model's outputs meet a certain level of quality and are suitable for the intended purpose. This is particularly important in applications where the generated content will be directly consumed by users or used in decision-making processes.

Accessibility of System Prompts

It's important to note that the accessibility of system prompts varies depending on the platform and tools you're using. For instance, if you're interacting with AI models like Claude or ChatGPT through user-facing applications or websites, you might not have the ability to add system prompts directly. These platforms often provide a streamlined interface designed for casual users, focusing on the user input and generated responses.

However, if you're a developer working with language models through an API, such as the LLM API, you have more control over the prompting process. In this case, you can incorporate system prompts into your application's backend, allowing you to customize the model's behavior and output based on your specific requirements.

By leveraging system prompts in your API-based applications, you can create more targeted and context-aware AI interactions, tailoring the model's responses to fit your desired tone, style, and role. This level of customization is particularly valuable when developing chatbots, virtual assistants, or other AI-powered tools that require a specific persona or domain expertise.

So, while casual users may not have direct access to system prompts, developers working with AI models through APIs can harness the power of system prompts to build more sophisticated and tailored applications.

System Prompts can Use the Usual Prompting Techniques

You can apply the same prompting techniques you would use in a user prompt to a system prompt instead. Here are a few ideas to get you started:

  • Specify output formatting by providing example responses or instructions for desired output patterns within the system prompt.
  • Provide documents, guides, and reference material to help the AI generate more informed and accurate responses.
  • Use XML tags, especially to structure long documents and improve clarity.

Examples of Effective System Prompts

To better understand the practical application of system prompts it is essential to examine real-world examples that demonstrate their effectiveness. In this chapter, we will explore a range of effective system prompts, including AI assistant prompts, personal fitness coach prompts, tone and style guide prompts, and task-specific prompts for various NLP applications.

AI Assistant Prompt

An AI assistant prompt is designed to guide the language model in providing helpful, accurate, and context-appropriate responses to user queries. A well-crafted AI assistant prompt should establish the assistant's role, capabilities, and communication style. Here's an example:

You are a knowledgeable and friendly AI assistant named Alex. Your role is to help users by answering their questions, providing information, and offering guidance to the best of your abilities. When responding, use a warm and professional tone, and break down complex topics into easy-to-understand explanations. If you are unsure about an answer, it's okay to say you don't know rather than guessing.

This prompt sets clear expectations for the AI assistant's behavior, encouraging helpful and accurate responses while maintaining a friendly and approachable demeanor.

Personal Fitness Coach Prompt

A personal fitness coach prompt aims to create an AI-powered virtual coach that can provide personalized workout recommendations, motivation, and guidance to users. An effective fitness coach prompt should capture the coach's expertise, communication style, and ability to tailor advice to individual needs. Here's an example:

You are a certified personal fitness coach named Sam. Your goal is to help clients achieve their health and fitness objectives through personalized workout plans, nutrition advice, and ongoing support. When interacting with clients, use a friendly and encouraging tone, and provide clear, actionable guidance based on their specific goals, fitness level, and preferences. Be sure to emphasize the importance of proper form, consistency, and listening to one's body to avoid injury.

This prompt establishes the fitness coach's qualifications, objectives, and communication style, enabling the AI to provide tailored and supportive guidance to users.

Tone and Style Guide Prompt

A tone and style guide prompt is used to ensure consistency in the language, tone, and formatting of AI-generated content across various NLP applications. This type of prompt is particularly useful for brand-specific or domain-specific applications where adherence to a particular style is crucial. Here's an example:

When generating content, adhere to the following tone and style guidelines:
- Use a friendly, conversational tone that is easy to understand
- Write in short, concise sentences and paragraphs
- Use active voice whenever possible
- Avoid jargon or technical terms unless absolutely necessary
- Use bullet points or numbered lists to break up long passages and improve readability
- Ensure all content is grammatically correct and free of spelling errors

By providing clear guidelines on tone, style, and formatting, this prompt helps maintain consistency and quality across all AI-generated content.

Task-Specific Prompts for NLP Applications

Task-specific prompts are designed to guide AI language models in performing specific NLP tasks, such as text summarization, sentiment analysis, or named entity recognition. These prompts provide the necessary context and instructions for the model to generate accurate and relevant outputs. Here are a few examples:

Text Summarization:

Please generate a concise summary of the following text, capturing the main ideas and key points in no more than 100 words:

Sentiment Analysis:

Analyze the sentiment of the following text and classify it as positive, negative, or neutral. Provide a brief explanation for your classification:

Named Entity Recognition:

Identify and extract all named entities (e.g., person names, organizations, locations) from the following text:

By providing clear instructions and context for each specific task, these prompts enable AI language models to generate accurate and relevant outputs, enhancing the effectiveness of various NLP applications.

Task-Oriented Assistant Prompt:

You are a task-oriented assistant. Help users break down complex tasks into manageable steps, provide guidance on prioritization, and offer tips for effective time management. Be concise and action-oriented in your responses.

This prompt sets up the AI as a productivity coach, focusing on helping users tackle complex tasks and manage their time effectively. The AI will break down tasks into smaller, actionable steps, provide guidance on prioritization, and share time management strategies. By emphasizing concise and action-oriented responses, the prompt ensures that the AI's advice is practical and easy to implement.

Creative Writing Assistant Prompt:

You are a creative writing assistant. Help users generate compelling stories, poems, and narratives. Provide suggestions for plot development, character creation, and descriptive language. Encourage users to explore different writing styles and genres.

This system prompt turns the AI into a creative writing companion, assisting users in generating engaging stories and literary works. The AI will offer ideas for plot development, character creation, and vivid descriptions, while also encouraging users to experiment with various writing styles and genres. This prompt is valuable for writers seeking inspiration or feedback on their creative projects.

Expert Persona Prompt:

You are an expert in the field of quantum computing. Provide detailed explanations and insights related to quantum computing concepts, algorithms, and applications. Use technical language when appropriate, but also offer simplified explanations for less technical audiences.

This prompt establishes the AI as an expert in quantum computing, guiding it to provide in-depth explanations and insights on the topic. The AI will use technical language when discussing complex concepts but also adapt its explanations for less technical users. This persona prompt is useful when creating AI-powered knowledge bases or educational resources focused on a specific domain.

Helpful AI Assistant Prompt:

You are a helpful AI Assistant. Help users by replying to their queries and make sure the responses are polite. Do not hallucinate and say 'I don't know' if required.

This system prompt sets the stage for a friendly and polite AI assistant that focuses on providing helpful responses to user queries. By instructing the AI to avoid hallucination and admit when it lacks knowledge, the prompt encourages truthful and reliable interactions. The AI will strive to provide accurate information and gracefully handle situations where it may not have a complete answer.

These examples demonstrate how system prompts can be crafted to define the AI's role, expertise, and communication style. By carefully designing prompts, developers can create AI assistants that are tailored to specific use cases, providing targeted and contextually relevant responses to user queries.

The Bottom Line

While system prompts can significantly enhance an AI's robustness and resilience against unwanted behavior, they don't provide absolute protection against jailbreaks or leaks. However, they do offer an additional layer of guidance and control over the AI's output, making them a valuable tool in your prompting arsenal.

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