2025 Complete Guide to Prompt Frameworks: 18 Practical Frameworks to Boost Your AI Conversation Efficiency by 10x

Hello everyone, I’m Aerion, founder of AI WorkFlow Studio. Through my two years of deep engagement with AI conversations and Make platform development experience, I’ve deeply experienced the importance of a good prompt framework in improving conversation efficiency. Today, I want to share 18 battle-tested prompt frameworks that will help you quickly improve the quality of your AI conversations.

What are Prompts and Prompt Frameworks?

Let’s start with the most basic concepts:

What is a Prompt?

• A prompt is the instruction we give to AI, telling it what we want
• It’s like communicating work tasks with a new colleague, needing to clearly state requirements
• For example, “help me write an article” is a simple prompt

What is a Prompt Framework?

• A prompt framework is a template and method for writing prompts
• Like how essays have an introduction, body, and conclusion structure
• Good frameworks help us express our needs more systematically

Why Do We Need Prompt Frameworks?

In my daily creation and work, I often see many friends encountering these problems when using ChatGPT:

• No matter how much they say, AI just doesn’t understand their intent
• The answers received often deviate from expectations
• Back and forth communication wastes a lot of time
• Conversation quality is inconsistent

These are all due to the lack of a good prompt framework. An appropriate framework is like a “formula” for conversing with AI, helping us:

• Clearly express requirements
• Achieve stable output quality
• Reduce ineffective communication
• Improve conversation efficiency

To make an analogy:

• Prompts without frameworks are like having disorganized chats with AI
• With frameworks, it’s like guiding AI step by step according to fixed procedures, making it easier to get desired results

Detailed Analysis of 18 Practical Prompt Frameworks

Let’s analyze these frameworks one by one, from simple to complex, based on difficulty and practicality:

RTF Framework: The Simplest Entry-Level Framework

The RTF framework is the simplest entry-level framework, especially suitable for users just starting to use AI. It contains three basic elements that help you quickly get started with AI conversations:

• Role: Specify what role AI should play
  • Clarify AI’s professional background and capabilities
  • Can be industry experts, teachers, writers, etc.
  • The more specific the role, the higher the output quality
• Task: Clarify the specific task to be completed
  • Explain in detail what AI needs to complete
  • Include specific requirements and limitations of the task
  • Can list specific requirements step by step
• Format: Specify the exact format of output
  • Define how content should be organized
  • State requirements for length, structure, etc.
  • Can provide format templates as reference

Practical Example:
Suppose you need marketing copy, you can write like this:

Role:
Please act as a marketing copywriter with 10 years of experience.

Task:
Help me write marketing copy for a new product launch, highlighting the product’s innovation and practical value.

Format:

• Title needs to be eye-catching
• Body around 500 words
• Divided into three parts: product introduction, core advantages, and usage scenarios
• Add promotional information and purchase links at the end

APE Framework: Essential All-in-One Framework for Beginners

This is the framework I most recommend for beginners. The APE framework is simple and direct, easy to get started with, and suitable for daily conversations. Its advantage lies in its clear structure, easy to understand and use, and can quickly help you get high-quality AI responses.

Framework structure:

• Action: Clearly state what you want AI to do
  • Start with clear verbs
  • Explain specific task details
  • Include requirements for quantity, length, etc.
• Purpose: Explain why you want this done
  • Explain task background and intent
  • State final use
  • Help AI understand context
• Expect: Define the specific results you want
  • List key output requirements
  • Specify style and form
  • Provide specific evaluation criteria

APE Framework Usage Tips:

1. Action must be specific and executable
2. Purpose should explain actual scenarios
3. Expect should list clear standards

Applicable scenarios:

• Content creation
• Copywriting
• Project planning
• Data analysis
• Code writing

Practical Example:
Let’s use the APE framework to write a prompt, with the goal of having AI help us write a product introduction:

Action:
Please write an 800-word product introduction copy about our newly launched smartwatch product.

Purpose:
This copy will be used for product website and e-commerce platform display, aiming to attract potential customers to learn about and purchase the product.

Expect:

• Copy structure should include: product highlights, technical specifications, application scenarios, purchase recommendations
• Language style should be professional but not obscure, suitable for general consumer reading
• Emphasize product innovation features and practical value
• Include clear purchase guidance at the end
• Appropriately use data and comparisons to enhance persuasiveness

CHAT Framework: Professional’s Choice

The CHAT framework is a more comprehensive and professional prompt framework, especially suitable for scenarios requiring complex, professional output. It builds complete prompt information through four dimensions:

• Character: Set AI’s identity and professional background
  • Clarify the professional role AI needs to play
  • Define the role’s professional field and experience level
  • Specify the role’s special skills or expertise
• History: Provide relevant background information
  • Describe the current project or problem’s background
  • Explain existing work progress
  • Provide important reference information and data
  • Explain key constraints
• Ambition: State desired effects
  • Set clear goals and expected outcomes
  • Define success standards and metrics
  • State project priorities and importance
  • Describe ideal final state
• Task: Specific work to be completed
  • List specific task items to be completed
  • State task timing and milestones
  • Define specific output requirements and format
  • Provide task-related constraints

Practical Example:
Let’s use the CHAT framework to write a prompt aimed at having AI help optimize an e-commerce website:

Character:
You are an e-commerce platform optimization expert with 10 years of experience, proficient in user experience design and conversion rate optimization, having helped multiple well-known e-commerce platforms improve sales performance.

History:
We are a medium-sized e-commerce platform operating for 3 years, mainly selling home goods. Recently we’ve encountered the following issues:

• Shopping cart abandonment rate as high as 70%
• Increasing negative reviews for mobile user experience
• Slow website loading speed
• Continuously declining user retention rate

Ambition:
Achieve the following in the next 3 months:

• Improve shopping cart conversion rate by 20%
• Increase mobile user satisfaction by 30%
• Reduce page loading time to within 2 seconds
• Increase monthly active users by 25%

Task:
Please provide:

1. Detailed website optimization plan
2. Specific technical improvement suggestions
3. User experience optimization strategy
4. 90-day implementation timeline
5. Expected ROI analysis

ROSES Framework: Essential for Project Management

The ROSES framework is particularly suitable for project management and team collaboration scenarios. It provides a structured method to organize project-related prompts:

• Role: Define AI’s professional role
  • Clearly specify the exact role AI needs to play
  • Explain the professional knowledge and experience required for this role
  • Define the role’s scope of responsibilities and authority
  • Set the role’s work style and communication approach
• Objective: Set project goals
  • Define clear, measurable project goals
  • Set specific success criteria and indicators
  • Clarify project priorities and importance
  • Establish time nodes and milestones
• Scenario: Describe project background
  • Provide detailed project background information
  • Explain main challenges facing the project
  • Describe relevant stakeholders
  • Explain project’s business environment and constraints
• Expected Solution: Expected solution
  • Describe characteristics of ideal solution
  • List must-meet key requirements
  • Explain acceptable alternative solutions
  • Define solution evaluation criteria
• Steps: Specific implementation steps
  • Break down project into executable specific steps
  • Set timeline for each step
  • Allocate resources and responsible persons
  • Establish monitoring and feedback mechanisms

Practical Example:
Let’s use the ROSES framework to get stock investment advice:

Role:
You are a financial analyst with 15 years of experience, focusing on A-share market research, holding CFA and CPA qualifications. You excel at combining fundamental and technical analysis, and have in-depth research on macroeconomic situations.

Objective:
Provide for an investor with moderate risk tolerance:

• Investment recommendations for 3-5 potential stocks
• Target return rate of 10-15% for each stock
• Maximum drawdown controlled within 8%
• Investment period of 3-6 months

Scenario:
Current market environment:

• A-share market is in adjustment period
• Domestic monetary policy tends to be loose
• Focus on new energy, chips, artificial intelligence and other fields
• Available investment funds of 500,000 yuan
• Investor hopes to obtain steady returns

Expected Solution:
Need a complete investment analysis report, including:

• Fundamental analysis of target stocks
• Technical trend analysis
• Industry development prospect evaluation
• Risk factor alerts
• Specific buy-in price points and stop-loss points

Steps:

1. Phase One: Macro Analysis (1 week)
   • Analyze economic data
   • Research policy trends
   • Evaluate market sentiment
2. Phase Two: Industry Screening (1 week)
   • Analyze industry prosperity
   • Evaluate policy support strength
   • Research industry chain layout
3. Phase Three: Individual Stock Analysis (2 weeks)
   • Financial indicator analysis
   • Corporate governance assessment
   • Competitive advantage analysis
   • Technical analysis
4. Phase Four: Investment Recommendations (1 week)
   • Develop buy-in strategy
   • Set profit-taking and stop-loss points
   • Develop position management plan
   • Risk control recommendations

LangGPT Framework: The Future of AI Prompt Programming

LangGPT is a revolutionary prompt framework that elevates prompt writing to the level of programming language. After the emergence of the new generation GPT-4 model, the importance of Prompts has increased day by day, it is no longer just a technology, but is becoming a programming language in the AI era. Traditional Prompt writing faces challenges such as lack of systematization, flexibility and user-friendliness, while also not fully utilizing the characteristics of large models. To solve these problems, Yun Zhong Jiang Shu created the LangGPT framework, which has now received 7.5k stars of recognition.

LangGPT achieves systematization by providing templated methods, where users only need to fill in corresponding content according to templates. In terms of flexibility, it innovatively introduces the concept of variables, allowing users to easily reference, set and modify Prompt content, significantly improving programmability. Through carefully designed workflows, LangGPT defines clear user interaction and role behavior patterns, making it easy for users to understand and use.

In terms of fully utilizing large model characteristics, LangGPT adopts modular configuration and point-by-point logical narration, and effectively alleviates the forgetting problem in long conversations through the Reminder function. The framework’s core syntax includes a markdown-based variable system, a design that fully utilizes large models’ sensitivity to hierarchical structure content, making Prompt content reference and modification more convenient. Meanwhile, based on large models’ advantages in role-playing, LangGPT designed Role templates, making Prompt writing as intuitive and efficient as “class declarations” in programming.

To further improve user experience, the development team also launched dedicated LangGPT assistant tools to help users more easily design and generate high-quality prompts. Through using specific formats (such as Markdown) and clear instructions, it ensures that large model responses always remain consistent with user expectations. At the same time, by cleverly incorporating context information in instructions, it helps large models more accurately understand and meet user needs.

Practical Example:

Role: SEO Content Planning Expert

Profile:

• Author: Aerion
• Version: 1.0
• Language: English
• Description: Focused on SEO content planning and optimization, with 10 years of content marketing experience, proficient in keyword research, content planning and data analysis

Goals:

• Provide professional SEO content optimization solutions for client websites
• Improve website natural search traffic and keyword rankings
• Ensure content quality and user experience

Constraints:

• Strictly follow latest search engine specifications and best practices
• All suggestions must be based on data analysis
• Maintain reasonable keyword density of 2-3%
• Ensure content originality, avoid duplication

Skills:

• Proficient in SEO optimization techniques and strategies
• Skilled in data analysis and keyword research
• Content creation and planning ability
• Familiar with mainstream search engine algorithms

Workflows:

1. Website Analysis
   • Assess current SEO status
   • Identify optimization opportunities
   • Competitor analysis
2. Keyword Research
   • Mine target keywords
   • Analyze search intent
   • Evaluate competition difficulty
3. Content Strategy
   • Develop content plan
   • Design content structure
   • Determine keyword distribution
4. Optimization Execution
   • Write SEO content
   • Technical optimization suggestions
   • Internal link optimization
5. Effect Tracking
   • Monitor ranking changes
   • Analyze traffic data
   • Optimize strategy adjustment

Initialization:

I am your SEO content planning expert, please tell me your website URL and optimization goals, I will provide you with professional content optimization solutions.

Google’s Prompt Engineering Best Practices

Google’s best practices framework is a scientific methodology summarized from extensive practical experience. This framework not only helps us better interact with AI models but can also continuously optimize prompt effects. Let’s delve into the core elements of this framework:

The key to prompt optimization lies in clear expression and continuous improvement. First, we need to ensure each prompt contains clear intent and expectations. Using concise and direct language, avoiding ambiguous expressions, while highlighting key goals and task priorities. This way of expression can help AI more accurately understand our needs.

Second, providing specific examples is crucial. Through showcasing successful cases and examples of what to avoid, we can better guide AI to understand our expected output. These examples should come from relevant field best practices and include actual application scenarios, helping AI better grasp the context.

Breaking down complex tasks into simple steps is also an important technique in prompt engineering. Each step should follow logical order, be specific and executable. By setting reasonable checkpoints and time estimates, we can better control the progress and quality of the entire process.

In terms of setting constraints, we need to clearly define the scope and limitations of output. This includes quality standards, time limits, resource constraints, and clear acceptance criteria. These constraints can help AI generate results more in line with our expectations.

Finally, and most importantly, is continuous iterative optimization. We need to constantly collect problems during execution, analyze gaps between results and expectations. Through continuous adjustment and refinement of prompts, establishing effective feedback optimization mechanisms, we can gradually improve prompt effectiveness.

Remember, excellent prompts are the result of repeated practice and optimization. Through constantly trying different expression methods, referencing various online resources (such as Prompt Hero and Google’s prompt gallery), we can find the prompt forms most suitable for our needs. As AI technology develops, our prompt strategies also need to keep pace with the times, constantly adjusting and optimizing.

SCOPE Framework: Strategic Planning Tool

The SCOPE framework is a powerful strategic planning tool, particularly suitable for designing large projects and complex tasks. Through a systematic approach, this framework helps us comprehensively consider various aspects of the project and develop executable action plans. Here are the components of the SCOPE framework:

• Scenario: Describe current situation and background, providing necessary context information for understanding the entire problem. This is the starting point of problem analysis, helping us accurately grasp the task environment.
• Complications: List potential challenges and difficulties. This includes all factors that might hinder goal achievement, such as resource limitations, technical barriers, or external risks.
• Objective: Clarify specific goals and expected effects. This provides clear direction guidance for the entire project, ensuring all actions revolve around the goals.
• Plan: Develop detailed action plans and specific implementation schemes. This is the key link to transform goals into executable steps, needing to consider elements like time and resource allocation.
• Evaluation: Set evaluation criteria and methods for measuring plan execution effects. Through regular evaluation and feedback, ensure the project moves in the right direction.

Practical Example:

Suppose you are a financial analyst responsible for evaluating a new investment project. A prompt conforming to this framework might be: “Scenario: We plan to invest in a tech company in an emerging market next quarter. Complications: The market has high policy risks and exchange rate fluctuations. Objective: Achieve 15% investment return within one year after investment. Plan: 1) Conduct comprehensive market and policy risk analysis 2) Design hedging strategies to manage exchange rate risk 3) Have in-depth communication with company management to assess their growth potential. Evaluation: Conduct financial performance analysis every quarter after investment, and adjust investment strategy based on results.” Such a prompt setting is very comprehensive, covering the entire process from problem identification to solution implementation and effect evaluation.

TRACE Framework: Task Breakdown Expert

The TRACE framework is a powerful and practical tool that not only helps us break down complex tasks into manageable subtasks but also guides us in more effective interaction with AI models like ChatGPT. This framework helps us achieve clear, purposeful communication and task execution through five core dimensions.

Let’s delve into the five core components of the TRACE framework:

Task

• Clearly define specific problems or tasks to be solved
• Ensure task description is clear, specific, and measurable
• Set task priority and importance level
• Clarify task scope and boundaries

Request

• Detail specific requests to AI
• Use clear, accurate language to express needs
• Set output format and requirements
• Specify quality standards and acceptance criteria

Action

• List specific steps needed to complete the task
• Ensure each step is executable
• Set step sequence and dependencies
• Allocate time and resource estimates

Context

• Provide relevant background information and environmental factors
• Explain task causes and consequences
• Explain special terms or industry knowledge
• Describe possible task constraints

Example

• Provide specific reference cases
• Show expected output format and content
• Explain examples of what to avoid
• Share best practices and successful experiences

Through systematic planning and execution of these five dimensions, the TRACE framework can help us:

1. Improve task execution efficiency and accuracy
2. Ensure smoother and more effective interaction with AI
3. Reduce misunderstandings and ambiguity in communication
4. Obtain output more in line with expectations

Practical Example:

Suppose you are a marketing manager responsible for developing a new social media marketing strategy for your company. You can use the TRACE framework to break down this complex task:

• Task: Define main task
  • Example: Develop a social media marketing strategy
• Request: Specific needs
  • Example: Develop a monthly content plan, increase brand exposure, improve user engagement rate
• Action: Steps to take
  • Example:
    1. Analyze target audience, understand their interests and needs
    2. Design content themes, ensure content aligns with brand image
    3. Create publishing schedule, choose optimal posting times
    4. Create and publish content, use various forms like images, videos, articles, etc.
    5. Monitor and analyze social media data, adjust strategy to optimize results
• Context: Relevant background information
  • Example: We are a health food brand, target audience is young people who care about healthy lifestyle
• Example: Reference cases
  • Example: Please reference successful content strategies from competitors, learn from their experiences

SPAR Framework: Problem-Solving Expert

The SPAR framework (Scenario, Problem, Action, Result) is a powerful problem-solving and task allocation framework. Through a systematic method, it helps us comprehensively analyze problems, develop solutions, and evaluate execution effects. Let’s delve into the four core elements of this framework:

Scenario

• Detailed description of problem background and context
• Clarify involved parties (such as customers, team, management, etc.)
• State key environmental factors like time and location
• Provide necessary historical data and trends
• Analyze external environment’s impact on the problem

Problem

• Accurately define core issues to be solved
• Quantify problem severity and impact scope
• Analyze root causes of the problem
• Identify key obstacles to problem solving
• Assess potential risks of not solving the problem

Action

• Develop specific solutions and execution plans
• Break down plans into actionable specific steps
• Clarify responsible person and timeline for each step
• Estimate required resource input
• Develop contingency plans for possible risks

Result

• Set clear goals and success criteria
• Establish quantitative evaluation indicator system
• Regularly track solution execution effects
• Timely adjust and optimize solutions
• Summarize experiences and lessons for continuous improvement

This framework has been widely applied in project management, product development, customer service, education and training, and many other fields due to its systematization and practicality. It not only helps us better understand and analyze problems but also guides us in developing practical solutions and ensuring effective execution through continuous evaluation.

Practical Example:

Suppose you are a customer service supervisor at an e-commerce platform, needing to solve the problem of surging customer complaints:

Scenario:

• Customer complaints increased by 50% year-over-year in past 3 months
• Main complaints focus on logistics delivery delays and product quality issues
• Customer service team understaffed, response time lengthened
• Peak season approaching, complaint volume expected to further increase
• Competitors’ service levels clearly superior to ours

Problem:

• Customer satisfaction dropped 30%
• Repurchase rate decreased 20%
• Customer service staff under high pressure, turnover rate rising
• Brand reputation affected
• Market share beginning to decline

Action:

1. Expand customer service team
   • Recruit 15 new customer service staff
   • Conduct 2-week intensive training
   • Establish mentor system
2. Optimize logistics system
   • Introduce intelligent dispatch system
   • Increase storage nodes
   • Expand delivery partner network
3. Strengthen quality control
   • Raise merchant entry barriers
   • Improve product inspection process
   • Establish product quality traceability system

Result:

• Customer complaints decreased by 40% within 3 months
• Customer satisfaction improved by 25%
• Customer service response time shortened by 50%
• Logistics delivery on-time rate improved to 98%
• Product quality issue occurrence rate reduced by 60%

CARE Framework: User Experience Designer

The CARE framework emphasizes four key elements: Context guidance, Action, Result, and Example. Additionally, there are several similar frameworks to CARE, such as CAR (Context, Action, Result) framework, CCAR (Challenge-Context-Action-Result) model, and CARL (Context, Action, Result, Learning) framework. These frameworks share similar elements and principles, all emphasizing the need for sufficient context information when providing instructions.

Context:
Context guidance is the most fundamental element in the CARE framework, providing background information for operations, helping large models better understand the user’s environment or situation. Good context description should include:

• Current scene and environment (like “while driving”, “while working in office”)
• Related constraints (like time, resource limitations)
• User’s role and identity
• Problem background
• Existing work progress

Action:
The action part needs to clearly describe specific activities to be executed, including:

• Detailed step instructions
• Execution order and priorities
• Required tools and resources
• Key attention points
• Possible alternatives

Result:
The result part describes expected effects after completing activities, should include:

• Specific target indicators
• Measurable success criteria
• Expected deliverables
• Quality requirements
• Acceptance criteria

Example:
The example part demonstrates how to apply prompts through specific cases, usually including:

• Complete prompt demonstrations
• Expected answer format
• Common problem handling methods
• Best practice cases
• Attention points explanation

The advantage of the CARE framework lies in its ability to help users construct structurally complete, information-rich prompts, thus obtaining more accurate and useful AI responses. Through providing sufficient context, clear action requirements, clear result expectations, and specific examples, it can significantly improve the effectiveness of AI interaction.

Practical Example:

Suppose you are a user experience designer, needing to design a new mobile banking APP’s account opening process:

Context:

• Target user group is urban white-collar workers aged 25-45
• Users mainly conduct investment and financial management through smartphones
• Competitor analysis shows complex identity verification process leads to low account opening conversion rate
• Need to balance between compliance requirements and convenient account opening
• Regulatory requirements mandate real-name verification and facial verification

Action:

1. Optimize account opening process
   • Streamline account opening steps to 4 essential stages
   • Support bank card OCR recognition
   • Provide smart information pre-fill function
2. Improve user experience
   • Design clear account opening guide page
   • Add progress bar display
   • Provide detailed operation instructions
3. Strengthen security compliance
   • Integrate facial recognition system
   • Implement liveness detection
   • Enhance sensitive information encryption storage

Result:

• Account opening success rate increased by 35%
• Account opening duration reduced from 15 minutes to 5 minutes
• User information entry accuracy improved to 99%
• User satisfaction score reached 4.7/5
• New user investment conversion rate increased by 20%

Example:
Please provide a mobile application example.

COAST Framework: Strategic Execution Expert

The COAST framework focuses on five core elements: Context, Objectives, Actions, Support, and Technology, ensuring interaction with large models is both clear and purposeful. This framework is particularly suitable for handling complex strategic tasks and project planning.

Context
Context provides situation information related to commands. This usually involves the environment or scenario where commands are issued, similar to the context in the CARE framework. Through inputting sufficient supplementary information, it can help large models better understand task background and make accurate judgments. Background information can include:

• Current problems and challenges
• Related historical data and experience
• Market environment and competitive situation
• Available resources and constraints
• Stakeholder needs and expectations

Objectives
Objectives describe specific outcomes users hope to achieve through this operation. A good objective should follow SMART principles:

• Specific
• Measurable
• Achievable
• Relevant
• Time-bound

Actions
The action part details specific steps and methods needed to achieve objectives. Good action plans should:

• Break down into executable small steps
• Clarify priority of each step
• Specify key milestones
• Set time nodes
• Assign responsible persons

Support
Support provides additional information or resources about how to complete the action for large models. This can include:

• Human resource support
• Financial budget
• Training resources
• Tools and equipment
• External expert consultants
• Related policies and process guidelines

Technology
Technology describes specific technologies or tools needed to execute the operation. This includes:

• Hardware device requirements
• Software system requirements
• Technical standards and specifications
• Data security requirements
• System integration requirements
• Technical training requirements

The advantage of the COAST framework lies in its ability to comprehensively consider various aspects of project execution. This framework is particularly suitable for large project planning, strategic transformation implementation, technology innovation landing, organizational change management, and new product development and other complex scenarios. Through systematic thinking and comprehensive planning, the COAST framework can significantly improve project success rate, helping organizations better achieve strategic goals.

Practical Example:
Context: “Develop an intelligent health management platform called ‘HealthCoach’ to help users achieve personalized health goal management.”
Objectives: “Build an intelligent health management system that can provide users with personalized diet and exercise advice, and reach 50,000 registered users within 3 months.”
Action: “Develop an intelligent recommendation engine that generates personalized health plans and advice based on users’ physical data, exercise habits, and dietary preferences.”
Support: “Provide complete nutrition database, sports science research data, and user health management best practice cases as training data.”
Technology: “Use Python and TensorFlow to build machine learning models, use React Native to develop cross-platform mobile applications.”

RACE Framework: Rapid Action Framework

The RACE framework emphasizes four key elements, particularly suitable for tasks requiring quick execution. The advantage of this framework lies in its ability to quickly clarify key elements of tasks, helping executors better understand and complete tasks.

Role:

• Clearly define roles and identities in scenarios
• Include role responsibilities and authority scope
• Determine relationships and interactions between roles
• Set required skills and experience for roles

Action:

• Detailed description of specific actions to execute
• Break actions down into operable steps
• Set action priorities and time nodes
• Clarify specific execution standards for each action

Result:

• Define specific outcomes to achieve
• Set quantifiable evaluation indicators
• Determine result acceptance criteria
• Preset possible risks and response plans

Example:

• Provide relevant successful cases
• Show best practice references
• Share experiences and lessons
• Explain implementation process notes

The RACE framework is particularly suitable for these scenarios:

• Projects needing quick startup
• Team collaboration tasks
• Training and teaching activities
• Process optimization and improvement

Practical Example:
Role: Social media operations expert
Action: Create a week’s content publishing plan
Result: Increase fan engagement rate by 30%
Example: Reference popular content forms from competitor accounts

RISE Framework: Execution Enhancement Tool

The RISE framework helps us better execute plans:

• Role: Clarify executor role
• Input: Required resources and information
• Steps: Detailed execution steps
• Expectation: Expected effects to achieve

Practical Example:
Role: Product launch manager
Input: Product specifications, market research data
Steps:

1. Create release timeline
2. Prepare marketing materials
3. Coordinate departmental resources
   Expectation: First week sales target achievement rate 90%

SAGE Framework: Wise Decision Assistant

The SAGE framework is suitable for decision analysis:

– Situation: Current situation
– Action: Possible action plans
– Goal: Expected goals to achieve
– Evaluation: Evaluation criteria and methods

Practical Example:Situation:

Company needs to choose new office location
Action: Evaluate multiple possible locations
Goal: Find most suitable office location for team development
Evaluation:

• Transportation convenience
• Rental cost
• Office environment
• Surrounding facilities

TAG Framework: Concise and Efficient Framework

TAG is a simple but efficient framework:

– Task: Clear task content
– Action: Specific action steps
– Goal: Expected results

Practical Example:

Task: Optimize website loading speed
Action:

• Compress image resources
• Optimize code structure
• Use CDN acceleration
  Goal: Reduce page loading time to within 2 seconds

CRISPE Framework: Creative Generation Framework

The CRISPE framework is particularly suitable for creative content generation:

– Capacity: Set AI’s professional capabilities
– Relevant info: Provide background information
– Statement: Clear task requirements
– Personality: Define output style
– Experiment: Request multiple solutions

Practical Example:

Capacity: Creative advertising copywriter expert
Relevant info: Target audience is 25-35 year old professionals
Statement: Write advertising copy for an instant messaging APP
Personality: Humorous and resonant
Experiment: Please provide 3 different style solutions

SMART Framework: Goal Achievement Framework

The SMART framework is a universal framework that helps us set and achieve goals. It not only includes the classic SMART principles but also adds the Guidance element, making goals easier to achieve. This framework is suitable for any scenario requiring planning and execution.

Framework components:

• Specific: Clear specific goal content
• Measurable: Set quantitative evaluation criteria
• Achievable: Ensure goals are feasible
• Relevant: Maintain consistency with overall goals
• Time-bound: Set clear time nodes
• Guidance: Develop achievement path

Usage tips:

1. Goals should be specific and quantifiable
2. Set reasonable completion deadlines
3. Break down into executable small steps
4. Regularly check and adjust progress

Practical Example:
Specific: Write a research paper about artificial intelligence applications in medical field
Measurable: Paper should contain at least 5,000 words, cite no less than 30 relevant literature
Achievable: Ensure completion of first draft within 3 months
Relevant: Paper topic maintains consistency with current research project
Time-bound: Generate paper in one round of dialogue
Guidance: Develop monthly writing plan, and regularly discuss progress with advisor

Analysis and Insights of Prompt Frameworks

Through analysis of the above prompt frameworks, we can find that although these frameworks take different forms, they all demonstrate the importance of structured thinking. They all emphasize the need to clarify goals, provide context information, and make clear statements about output requirements. At the same time, all frameworks place great importance on the iterative optimization process, emphasizing the need to continuously adjust and improve prompts based on actual effects.

There are also notable differences between these frameworks. In terms of complexity, basic frameworks like RTF and APE have simple structures, are easy to master, and suitable for beginners; while intermediate frameworks like CHAT and ROSES have more complete logic, suitable for professional scenarios; advanced frameworks like LangGPT are more systematically complete, particularly suitable for development teams. In terms of application scenarios, some frameworks focus on general dialogue, some focus on specific fields like business analysis or creative generation, and some are specifically oriented towards AI application development.

For readers who want to improve their prompt writing skills, these frameworks provide a good learning path. It is recommended to start with simple frameworks and gradually try more complex frameworks as experience accumulates. In practice, one should not be confined to a particular framework, but rather flexibly choose and combine frameworks based on specific needs. Most importantly, one should continue learning and summarizing, pay attention to the development of new frameworks, accumulate experience in practice, and gradually form their own prompt writing methods.

Remember, good prompts are not about using complex frameworks, but about whether they can effectively communicate with AI and obtain expected output results. Through learning and applying these frameworks, everyone can find the most suitable prompt writing method for themselves.

Conclusion

Prompt frameworks are not unchangeable; they will continue to evolve with the development of AI technology. The key is to understand the core ideas of each framework, use them flexibly, and find the most suitable way for yourself. I hope this guide can help you better master AI tools and improve work efficiency.

In my daily use of AI tools, I find the most effective way is to combine the advantages of different frameworks. For example, when writing technical documentation, I use the CRISPE framework to inspire creativity, then use the RTF framework to refine details. For complex projects, I first use the ROSES framework for overall planning, then use the APE framework for step-by-step iterative optimization.

Through extensive practice, I have summarized the following experiences:

1. Frameworks should be simple and practical: Overly complex frameworks will affect efficiency
2. Maintain flexibility: Don’t rigidly apply frameworks, adjust according to actual needs
3. Continuous optimization: Record the effect of each use, continuously improve prompts
4. Build template library: Organize and archive commonly used prompt templates for easy reuse

Remember: The best framework is the one that suits you. Through practice and summary, you will definitely find the prompt method that best suits you.

If you want to learn more AI prompt techniques and practical experiences, welcome to follow my paid column. There, I will share more exclusive cases and in-depth thoughts. As the founder of AI WorkFlow Studio, I focus on exploring and practicing various AI and automation tools to help everyone improve their media creation, research management and work efficiency. With 2 years of Make platform development experience, I have developed over 200 automation workflows. You can find me through:

• YouTube Channel: AI WorkFlow Studio
• Official Website: aiworkflowstudio.com

Let’s explore more possibilities together in the AI era！