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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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Meher Mullapudi Associate Director| Ernst & Young Global Delivery Services Pune, Maharashtra, India
Crafting a prompt has significantly reduced the time to get relevant output making me extremely efficient.
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Therese NIYIBIZI Kigali, 01, Rwanda
refining the prompt helped getting better answers from AI
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Olivier Kurc Lausanne, VD, Switzerland
In my experience with GenAI, refining a prompt can completely transform the quality of the output. A vague or general prompt often leads to superficial or irrelevant results. However, by making the prompt more specific—adding context, defining the desired format, and even setting a tone—I’ve consistently received much more accurate, detailed, and useful responses. It’s like adjusting a lens to bring your target into sharp focus.
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Pankaj Kumar Mishra Program Manager| JPMorgan Chase Aubrey, TX, United States
I spend a lot time on prompting mainly the clarity , what I learn breaking prompt into smaller task and adding the flavor of persona, request, example ,output format and cross questioning with AI model (Chatgpt ,perplexity ,Gemini , Grok) provided a great output and then chaining on to of it became so useful. I'm solving a lot of complex documentations, project planning, Meeting notes refinement etc..
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Ashley Cotton Senior IT Project Manager/ Delivery Manager| Excelicon Brandywine, Md, United States
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).
Before I knew what prompt frameworks were called, I called it "priming". I would share pertinent details to ensure that I got a high-quality response. I already knew what I wanted to get out of the prompt at a foundational level, I wanted a higher level response (more refined, elevated) so it only makes sense to share those details with the AI so they can build on what I've already started. You want something quick, simple and general, just ask the question straight out. If you want something tailored to the nuance of a situation, you need to prime the AI with the appropriate details. And continue to respond and iterate with the AI to provide more nuanced details if the response you receive doesn't take into account certain particulars of the situation that would influence the response.
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Cláudio Manuel Gestor de Projectos| Banco BAI Luanda, Lua, Angola
Indeed. Refining helps a lot.
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Christian Aldana Santiago, Region Metropolitana, Chile
Refining a prompt allows us to be more concise and precise, aiming to break down tasks into more manageable parts with improved understanding and quality of results. By adding an iteration process, we achieve outstanding results.
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Farah Zafar Pakistan
Jul 12, 2024 4:04 PM
Replying to Olive BUME ADA NGOLE
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Using the formates correctly will provide a better prompt framework, refrinding with concised and specific with breaking down the structures into few prompts, also povides a great reaponse.
Iteratively and chaining provided a better prompt frame work
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Anonymous
Better the prompt, better is the output!
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