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?
GenAI is like talking to whom has opinion to everything, so you'll never be without an answer, even neither all answers are useful so it's necessary to give direction, exemples and refined questions to achive your goals.
Refinement on prompt is mandatory as is reviewing all outputs to not be fooled or have generical responses. The best way to refine is giving to AI its persona, background, example and asks to not hallucinate by inventing, giving answers based on reliable and searchble sources.
GenAI is like talking to whom has opinion to everything, so you'll never be without an answer, even neither all answers are useful so it's necessary to give direction, exemples and refined questions to achive your goals.
Refinement on prompt is mandatory as is reviewing all outputs to not be fooled or have generical responses. The best way to refine is giving to AI its persona, background, example and asks to not hallucinate by inventing, giving answers based on reliable and searchble sources.
This morning, one of my LinkedIn contacts complained that GenAI tools don't seem to have the ability to craft decent quality PMP practice exam questions. He had used the public version of ChatGPT. I decided to check the same with PMI Infinity and got better results - seven out of ten questions were acceptable.
My first prompt was "Generate ten different questions about project management which would be similar in style and level of difficulty to what is asked on the PMP exam"
It only gave me the questions but neglected to provide any answers. Realizing that this was likely it interpreting what I had asked for "as is", I then added: "Generate ten different questions about project management which would be similar in style and level of difficulty to what is asked on the PMP exam".
With that it was able to provided more useful output.
Kiron
With Generative AI, the biggest jumps in quality for me came from making prompts more concrete and constrained. I stopped asking things like “Why isn’t my function working?” and instead included the exact code, the full error message, what I expected to happen, and what was actually happening. This single change turned vague, generic replies into precise explanations that pointed directly at the bug. I also changed “Refactor this code” into prompts that listed my goals (for example: reduce duplication, keep behavior identical, and briefly explain the changes), which consistently produced cleaner, more usable outputs.
Refining a prompt can dramatically improve AI output by transforming it from generic, surface-level content into targeted, context-aware, and decision-ready insight. Adding specific details—such as constraints, audience, timelines, and desired format—helps narrow the problem space and produces more relevant, prioritized results. Including instructions to surface assumptions, risks, or counterarguments further elevates the quality by encouraging deeper analysis. In essence, clearer and more structured prompts turn AI from a basic content generator into a more strategic thinking partner. Saving Changes...
LaWanda YoungProject Management| USAFSt. Clair Shores, MI, United States
Refining a prompt can drastically shift AI output from basic to granular, detailed and targeted. Saving Changes...
It honestly has made a world of difference. I have seen it go from awkwardly crafted responses to smooth and clear responses that hit the nail on the head for the tasks that I need it to complete. Saving Changes...
Refining a prompt drastically changed the output in my experience with GenAI by providing more aligned feedback with my intended prompt. Vague prompts provided vague data, refined prompts provided refined data. Saving Changes...
I think it is important to give the context and also to refine, asking for a different output in case that the first one is not completely suitable to our purpose or to the outcome that we were looking for. I think that consistency and preseverance in looking for the result, is crucial as well.
I agree with this statement. Also, in reviewing the answer of the AI, it is often obvious what additional context might have been lacking. This gives an opportunity to refine the prompt further. Saving Changes...
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