The Art of Prompting: A Deep Dive Into 5 Remarkable ChatGPT “Frameworks”

Navigating the nuanced pathways of ChatGPT/LLMs for around a year, both as a prompt explorer and a developer crafting an alternative at EQS Group, has rendered a rich tapestry of insights into the art and knowledge of effective prompting. The interplay between machine and human communication is a delicate dance, one where strategic prompting can provide a spectrum of possibilities.

Mastering the art of prompting

In this article, I will share five personally tested prompt frameworks that have significantly enriched my interactions with ChatGPT. To illustrate each, I’ll harness the persona of a carpenter building a laptop stand.

1. Simplifying Complexity: The RTF Framework

Being the most widely-used framework due to its intuitive nature, RTF harnesses three pivotal points:

• Role
• Task
• Format

It functions as a universal tool for crafting prompts, simplifying them into a question, such as: “Act like a [role]. Can you [insert task] in [format] format?” Such a structure is not only easy to remember but also effortlessly applicable across varied scenarios, ensuring improved, tailored outputs.

Example:
“Act like a skilled carpenter. Can you guide me through building a laptop stand using wood in a step-by-step instruction format?”

Outcome:

Using RTF: Build Wooden Laptop Stand

2. Meticulous Outputs with RODES

The RODES framework shines, especially when examples similar to the anticipated output are at hand:

• Role
• Objective
• Details
• Examples
• Sense Check

Leveraging the RODES framework, the model is well-guided through the task with clear objectives, detailed information, real-life examples, and a final checkpoint to ensure the output aligns seamlessly with the expectations.

Example:
Taking on the Role of a master woodworker, help me to define a clear Objective in creating a functional laptop stand, offering all relevant Details and Specifics, perhaps providing Examples of similar designs, and conducting a Sense Check to ensure practicality and feasibility in a home woodworking setting.

Outcome:

Using RODES: Build Wooden Laptop Stand

3. Navigating Detailed Tasks: The RISEN Framework

RISEN lays down a structured path, especially when dealing with tasks that mandate a specific framework and discernible guidelines, such as writing tasks with constraints or crafting detailed plans:

• Role
• Instructions
• Steps
• End Goal
• Narrowing (Constraints)

By incorporating these elements, the model is offered a clear pathway to navigate through the task, aligning closely with predefined guidelines and achieving the desired end goal efficiently.

Example:
Assuming the Role of a seasoned DIY expert, with clear Instructions, guide me through the Steps to create a wooden laptop stand, ensuring we achieve the End Goal of a sturdy and aesthetically pleasing stand, while Narrowing our focus to using readily available tools and materials.

Outcome:

Using RISEN: Build Wooden Laptop Stand

4. Step-wise Clarity: The Chain of Thought Method

Achieving clarity and coherence in complex tasks like analytical endeavors, decision-making, and problem-solving becomes approachable with the Chain of Thought method. By merely appending, “Let’s think step-by-step” to your prompt, you invoke a sequentially reasoned output from the model, enabling it to demonstrate a visibly logical and structured thought process.

Example:
Could you assist me in developing a design for a wooden laptop stand? Let’s think step-by-step about the materials, dimensions, and assembly process.

Outcome:

Using Chain of Thoughts: Build Wooden Laptop Stand

5. Recursive Excellence: The Chain of Density Method

Navigating through tasks that necessitate a depth of recursion to produce progressively better outputs, the Chain of Density is a method to consider. Particularly potent for creating summaries, refining prompts, and generating valuable long-form content, this approach utilizes recursion to incrementally enhance and polish the outputs, optimizing them for usability and coherence.

Example:
Could you help me refine and elaborate on this initial idea: ‘Create a sturdy laptop stand using standard wood planks and screws’, progressively improving and detailing each subsequent version of the prompt to finally provide a comprehensive guide on building a laptop stand?

Outcome:

Using Chain of Density: Build Wooden Laptop Stand

Conclusion

Mastering ChatGPT or any other LLM involves not only understanding its capabilities but also effectively communicating tasks to it — and that’s where strategic prompting comes into play. The above frameworks have emerged as key allies in unlocking enhanced, targeted outputs from ChatGPT. Tailoring your prompts using these frameworks ensures that your interactions with ChatGPT are not only fruitful but also reliably consistent, optimizing your tasks and reducing the effort invested in refining outputs.

Exchange knowledge for the future

Your insights and experiences matter to us. Engage in the dialogue — share with us other frameworks or personal prompts that have proven effective in your ChatGPT explorations. Let’s continue to unravel the mysteries and capabilities of ChatGPT together, building a community where knowledge and experiences are shared openly and constructively.

Passionate about shaping the future of SaaS products? At EQS Group, we’re on the hunt for enthusiastic individuals ready to bring their talents to our dynamic team. Discover opportunities tailored for you: https://eqs-group.personio.de/recruiting/positions.