Director, Learning Design & Development| PMIAsheville, NC, United States
With Generative AI, iteratively refining and optimizing prompts can lead to better AI-generated results. This may involve adjusting the specificity or clarity of the prompt to increase relevance and accuracy of results.
What examples do you have of how improving a prompt drastically changed the output quality? What specific changes did you make that led to the improvement?
It is important to remember this: generative AI is just "predictive text with storoids". Obviously not only text will be the result. BUT the important thing is the answer will just to complete your question (prompt) with the things that have more probability to complete it. You can manage it using some of the parameters like temperature. So, it is very important when creating the prompt to put clear the role, the place where the role works/live/etc, the task the role has to accomplish and the format of the answer. This is an example of R-T-F. You have to eliminate as ambiguity as possible. If not, then hallucinations will happened.
Very well said, thanks for sharing! Saving Changes...
There are framewoks to create prompt. This is part of the Prompt Desing discipline. Those that gave me and the initiatives where I was included are:R-T-F (Role-Task-Format), T-A-G (Task, action, goal), B-A-B (Before, after, bridge), C-A-R-E (context, action, result, example), R-I-S-E (role, input, steps, expectations).
Thanks for sharing, i appreciate your knowledge and insight Saving Changes...
Kelly TerrellIBM - Learning and Knowledge Consulting Academy, Program Manager| IBMEvanston, Il, United States
Just yesterday I was working on analyzing data from one of my projects using AI. because I was not clear and detailed in what I wanted, I ultimately entered a flipped interaction where it was asking me what I wanted. After several attempts at refining the prompt, I was able to get usable data for my report as well as a template in xls, word and ppt. It was fantastic! Saving Changes...
CHRIS EKWEDAMProject Manager| Carmels Tekno LtdPort Harcourt, Rivers, Nigeria
The output leaves the arena of being generic to being specific and pointed. It becomes more concise and detailed in a specific area. Saving Changes...
CHRIS EKWEDAMProject Manager| Carmels Tekno LtdPort Harcourt, Rivers, Nigeria
Jun 22, 2024 7:08 PM
Replying to Winston C Ikekeonwu PMP
...
Thanks for sharing the prompt frameworks, Sergio. I'm always looking for ways to improve the quality of the input. Will look into them. Thanks again
Good response with growth mindset. Saving Changes...
Dale NolanSenior Services Consultant| GE HealthcareTrophy Club, Tx, United States
Refining a prompt drastically changed quality of output each time I've used AI because I've reviewed output and found missing info or more specific instruction was needed. Chaining prompts helps the AI build on the quality of the output by not being overwhelmed with too many instructions. Saving Changes...
In my experience with GenAI, refining a prompt has made a huge difference in the quality of responses I receive. When I started with vague prompts like “Explain Agile,” the answers were generic and lacked depth. But when I added context—like specifying the audience, intent, or role—the output changed completely. For example, asking “Act as a Delivery Head and explain Agile to a non-technical CFO using business impact metrics” gave me a clear, relevant, and business-focused explanation. That’s when I realized prompt refinement isn’t just useful—it’s the key to getting results that truly match what I’m looking for. Saving Changes...
Transitioning from the RTF to CREATE formula helped. Then, using Chain-of-Thought prompting pattern added needed details in the output to be more tailored and actionable. Saving Changes...
Christine LeeProject Management| EatonLOUISVILLE, CO, United States
It helped the AI learn what the user needs, and the user can understand the requirements. Saving Changes...
PMI Team Member
