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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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Tubagus Helmy Bin Abdullah Wangsa Maju, 14, Malaysia

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luis cantu Clearfield, Ut, United States
For me, prompt refinement has dramatically improved the outputs by aligning better with the expected requirements. I noticed early on that generating good prompts aligned with developing a solid scope statement. I started to explain what I wanted, and what I didn't want. I provided opportunities for clarifying questions, rather than just executing. Additionally, I saw a reel that suggested that Gen AI is simply an actor. Therefore, it was important to tell it the role to play - with specificity.
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Calvin Dsylva Consultant| Accenture Mumbai, MH, India

Precision in input, processes an exact output
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Pradeep Shukla Continuous Improvement & RPA Lead| Bunge India Mohali, PB, India

Refining a prompt can dramatically improve GenAI output by making it clear, specific, and structured.

h3Example:/h3
  1. Weak prompt:
  2. “How to improve productivity?”
  3. → Generic, vague ideas
  4. Refined prompt:
  5. “List 5 data-driven ways to improve factory productivity with metrics and implementation steps.”
  6. → Practical, structured, actionable output
h3Key impact:/h3
  1. More relevant (fits your role/context)
  2. More accurate (less guesswork)
  3. More useful (ready to apply)

✅ Bottom line: Better prompts = better results.
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Tariq Hussain Deputy Director| Government of Balochistan Quetta, Pakistan
Jun 21, 2024 10:50 AM
Replying to Kiron Bondale
...
Sarah -

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

You should ask LLM to answer the question too.
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Anonymous

specifity and clarity brings better results.
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Rakesh Prasad San Diego, CA, United States

Refining the prompt has consistently yielded more accurate responses in less time.
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James Robert Resendiz PM Consultant| IBM Santa Clarita, CA, United States
I found big gains in the accuracy and alignment of my expected outcomes. As well as raising my own experience and abilities build better prompts.
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MOHAMMAD R. BOZORGI Project Manager

Hi

As my experiance, Providing precise constraints, explicit goals, or reference examples (few-shot prompting) stops the AI from guessing. It anchors the model's pattern prediction, which drastically reduces hallucinations and gives you deployable results on the first or second try.

Regards
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Gaurav Pande India

Refining the prompts have definitely yielded much better outputs / resonses.
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