Prompting frameworks serve as the architectural backbone upon which AI models operate, determining the depth of understanding, coherence, and relevance of their responses. As the demand for more contextually appropriate, and coherent AI interactions rises, researchers have delved into the development of advanced prompting frameworks. Among these, three frameworks stand out: RISE, RISEN, and RODES.
Join us as we unravel the intricacies of RISE (Role, Input, Steps, Expectations), RISEN (Role, Input, Steps, Expectations, Narrowing), and RODES (Role, Objective, Details, Examples, Sense Check) and envision the transformative possibilities they hold for AI-driven applications across various domains.
RISE
The RISE prompting framework (Role, Input, Steps, Expectations) is a structured approach that enhances interactions with ChatGPT. Let’s break it down:
Role: Define the role you want ChatGPT to take. Is it an assistant, a creative writer, or an expert in a specific field?
Input: Provide clear instructions. Explain the task, context, and any constraints. Be specific about what you want the model to do.
Steps: Set the context by providing relevant background information. Specify any limitations or boundaries. Include examples or sample responses.
Expectations: These are the guidelines for ChatGPT. They help align its responses with your desired outcome.
RISE Prompt Examples
Role: Define the role or perspective for ChatGPT.
“Act as a Creative storyteller.”
“Act as a Knowledgeable tech expert.”
“Act as a Logical problem solver.”
Input: Provide clear instructions, context, and constraints.
“Write a short story about a mysterious antique shop.”
“Explain quantum computing to a beginner.”
“Solve the following riddle: ‘I speak without a mouth and hear without ears. I have no body, but I come alive with the wind.’”
Steps: Set the context, specify any limitations, and include examples.
Steps:
Context: Describe the quaint shop’s location, appearance, and the curious items within.
Constraints: Keep it under 300 words.
Example: “Once hidden on a cobblestone street, the shop beckoned with a faded sign.”
Steps:
Context: Introduce quantum bits (qubits) and their unique properties.
Constraints: Use simple language; avoid complex math.
Example: “Imagine a computer that can process multiple possibilities simultaneously.”
Steps:
Context: Analyze the riddle’s clues.
Constraints: Keep the answer concise.
Example: “The answer is an echo.”
Expectations: Guidelines for ChatGPT’s responses.
Engaging narrative with vivid descriptions.
Clear, beginner-friendly explanation.
Correct solution with minimal explanation.
By combining these elements, you create prompts that guide ChatGPT effectively, resulting in more relevant and useful answers.
RISEN
The RISE and the RISEN (Role, Input, Steps, Expectations, Narrowing) frameworks share similarities, but there is a key distinction:
RISE Framework:
Role: Define the specific role or perspective.
Instructions: Specify the main task.
Steps: Outline the necessary actions.
Expectations: Clearly state the desired outcome or end goal.
RISEN Framework (RISE + Narrowing):
Role: Same as in RISE.
Instructions: Same as in RISE.
Steps: Same as in RISE.
Expectations: Same as in RISE.
Narrowing: Set any constraints or limitations. For instance, you could specify a maximum word count or focus on high-impact technologies.
RISEN Example
Role: “Act as a Strategy Consultant.”
Instructions: Devise a digital transformation strategy for a traditional retail company.
Steps:
Evaluate current digital assets.
Identify key technology upgrades.
Propose an implementation roadmap.
Expectation: Create a phased digital transformation plan.
Narrowing: Max 1000 words, focus on high-impact technologies.
In summary, while both frameworks follow a similar structure, the RISEN framework includes an additional step for narrowing down the scope or imposing constraints on the task. This added layer of specificity helps tailor the approach to the given context or limitations.
RODES
The RODES framework (Role, Objective, Details, Examples, Sense Check) is also a structured approach for creating effective prompts when interacting with ChatGPT. Let’s break down each component:
Role: Assign a specific role or perspective to ChatGPT.
Objective: Clearly define the task or goal you want ChatGPT to accomplish.
Details: Provide any relevant context or additional information. Be specific about what you’re looking for. If there are constraints or limitations, mention them here.
Examples: Include examples or sample content related to the task. These can serve as guidelines for ChatGPT to generate relevant responses.
Sense Check: Before finalizing your prompt, review it to ensure it aligns with your intended outcome. Consider whether the instructions are clear, concise, and likely to yield valuable results.
RODES Prompt Examples
Role:
“You are a software developer working on an AI-powered task scheduler.”
“You are a mobile app consultant.”
“You are a writing coach.”
Objective:
“Create a weekly schedule for a list of tasks.”
“Provide guidance on building cross-platform apps.”
“Inspire a short story.”
Details:
“You have a list of tasks with varying priorities and deadlines.”
“Your client wants to develop an app for Android and iOS.”
“Your student wants to write a captivating story set in a haunted mansion.”
Examples:
The tasks include “Write a report” (high priority, due Friday), “Attend team meetings” (medium priority, recurring on Mondays), and “Review code” (low priority, flexible deadline).
Share best practices for building apps on each platform, Android, and iOS.
Describe the eerie atmosphere, introduce mysterious characters, and hint at a hidden secret within the mansion.
Sense Check:
Ensure the generated schedule balances priorities and allocates time effectively
Confirm that the advice covers all relevant platforms and addresses common challenges.
Ensure the prompt sparks creativity and sets the stage for an engaging narrative.
The RODES framework helps you craft prompts that lead to more accurate and context-aware responses from ChatGPT.
These frameworks hold immense promise for revolutionizing how we interact with AI systems, paving the way for more coherent, contextually aware, and human-like responses.
As we continue to witness rapid advancements in AI technology, the importance of effective prompting frameworks cannot be overstated. They serve as the cornerstone upon which the next generation of AI models will be built, enabling them to navigate complex linguistic structures, understand nuanced contexts, and generate responses that mirror human thought processes more closely than ever before.