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?
When using Gen AI we should refine a prompt as it significantly improves output quality by making it more specific, contextual, and goal-oriented. I have observed that clearer, detailed prompts lead to more accurate and actionable responses, while vague prompts often yield generic or irrelevant outputs. Iteratively adjusting the prompt -- by adding context, specifying the desired format, or providing examples , consistently enhances the output's relevance and precision, ultimately saving time and improving project outcomes Saving Changes...
Anonymous
RTF and CREATE frames are intuitive and easy-to-use models to prompt more effecttively and achieve coicise, pertaning and focused responses Saving Changes...
Refining a prompt can dramatically change the quality of AI-generated output. A vague or generic prompt often leads to incomplete or irrelevant responses, while a well-structured, specific prompt delivers more accurate and actionable insights.
For example, asking “Generate ten project management questions” may result in broad, unfocused questions. However, refining it to “Generate ten PMP-style multiple-choice questions with answer choices and explanations” ensures the AI understands the format, level of detail, and expected structure.
Key improvements include
1. Adding context (e.g., PMP certification focus)
2. Specifying format (multiple-choice with answers)
3. Clarifying expectations (explanations for each answer)
By iterating and refining, you guide the AI to produce results that better align with your needs. The key is to be clear, precise, and iterative—treating AI interactions like a structured conversation rather than a one-time query.
Michael FarinProject Control Manager/ Claims Analyst| Hawk InternationalMalolos, Bulacan, Philippines
In my experience, refining a prompt has significantly improved output quality. Clearer prompts help generate more tailored insights. Small adjustments in wording, context, tone, or specificity can drastically change the depth and relevance of the response. Saving Changes...
Refining prompts is crucial for achieving high-quality outputs from Gen AI. It involves a continuous process of adjusting, experimenting, and fine-tuning the prompts to guide the AI toward producing the most valuable and relevant results
The main factor to consider while refining is use of prompt Formula like RTF , CREATE. inputting required data and previous related documents if the privacy policy permits, Saving Changes...
Ciprian DavidDirector IT Project Management| Cocomore AGLinden, Hesse, Germany
this is basically the bread and butter of my interactions with the LLM Saving Changes...
Harold HobgoodTest (Program) Manager| DCS CorpDayton, OH, United States
It is important to know and ask what you want. It is possible as a Project Manager you may not be the subject matter expert and the request may start out generic as an RTF, and slowly evolve to CREATE after a couple prompts. It may take patience and practice, but well worth the effort to develop the framework required to get the solution or product you need. Saving Changes...
Aaron IngramBusiness Applications Manager| Real Capital SolutionsGolden, United States
We extract rent tables from CRE Leases, and we've found that you can both make a prompt too specific, and too simple to get the answer you want, there is a fair amount of trial and error, along with best practices for creating context, analysis, and output directions. Saving Changes...
Yau Chang SiewHead of Digital Business and Services | AgrobankKuala Lumpur, Malaysia
Jun 21, 2024 7:28 AM
Replying to Sergio Luis Conte
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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).
It really helps to have structures in prompt engineering. More importantly, structures help me organize my thinking and output. Saving Changes...
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