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In your experience with GenAI, how has refining a prompt drastically changed the output quality?

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Sarah Philbrick
PMI Team Member
Director, Learning Design & Development| PMI Asheville, 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?
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Anonymous
I was not familiar with the techniques described and am excited to include them and breakdown complex scenarios to gain better results and continue to educate the AI!
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Efrain Aylas Project Manager| INGETEC C&E Magdalena Del Mar, Lima, Peru
In my experience using GenAI, refining prompts has made a remarkable difference in output quality—especially in technical fields like electrical engineering
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Maria Salami Project Manager Ontario, Canada

Refining a prompt has had a significant impact on the quality of AI outputs in my experience. One clear example was when I used GenAI to draft a stakeholder communication plan. My initial prompt was too general (“Create a stakeholder communication plan for a renewable energy project”), and the result was vague, missing context, and not tailored to my audience.



After refining the prompt to include specifics—such as stakeholder roles, communication frequency, tone, and key concerns—the quality of the output improved dramatically. The AI was able to deliver a structured plan with relevant messaging strategies for each stakeholder group, aligned with the project's communication goals.



This experience reinforced that prompt engineering is not just a technical skill—it’s a strategic one. The more context, constraints, and intent I provide, the more actionable and aligned the AI output becomes. It's a bit like managing a team: clear expectations lead to better results.
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Mokhtar Abdelaal Badawy Management| National Contractin Co. Ltd. Cairo - Abdeen -Roshdy St., C, Egypt
I usually distribute my requirements in items
one by one I requested
finally I found all the results are Balanced, satisfactory, consistent, and logical.
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Courtney Svoboda Green Bay, WI, United States
Adding the persona of who you are writing to or from has drastically improved my AI prompting results.
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Natasha Falke Project and Process Manager| Animal Legal Defense Fund Boston, MA, United States
Being specific is key! I use AI often for generally smaller tasks and as long as you remain specific and detailed, as well as using punctuation properly so AI depicts separate prompts, it works really well. Having an iterative conversation with AI (may seem strange to be "talking to a computer") is very helpful as well to refine the ask. Recently, I worked on a rebranding of a website and the prompts I used were very detailed and the first output was nearly there. With some back and forth, I was able to achieve what I was hoping to get from the system. I made some of my own personal touches to the product, but it was helpful to use especially having been stuck in a creative loop. AI helped me see other paths to what I wanted to achieve.
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Colin Carroll Aldie, VA, USA
I found that refining prompts, specifically the character or role has led me to much better and more in line with what I am looking for results. Adding more personality traits such and history, further refines the results to pinpoint accuracy. Example "I am a program manager at a top 10 tech company that has been in this position for over 15 years and is confident in their work however wants to bring some issues to upper managements attention"
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Anonymous
Refining GenAI prompts improves output quality. It is an iterative process.
A well-crafted prompt will lead to outputs that better align with your expectations, while a vague prompt may result in generic or irrelevant results.
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Mark Gadson Abingdon, MD, United States
Refining prompts will ensure favorable outcomes. As adjustments are made Gen AI learns over time. This can help with future use cases.
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Gaurav Saxena Associate Director| Cognizant Technology Solutions Pune, Maharashtra, India
Have started using AI in my day-to-day management tasks recently and based on little experience I'd say that the divide and conquer strategy is as applicable to machines as to humans. Ultimately Machines are being trained to simulate human intelligence - the way human brain works. Just like a human brain is likely to get confused and respond with incomplete answers or miss answering some of the questions if it's bombarded with a lot of information and asked to process it, I think Machines are also likely to react similarly - although scale may be different and they may be able to respond and process more information compared to human brain but ultimately desired output won't be there.
Bottomline - Divide and conquer while using AI too. Refine your prompts, Ask the machine to complete one task at a time, chain the tasks (or prompts), use RTF and CREATE and you will see that the output you receive from your AI tool is more in line with your expectations.
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