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?
Sometimes the refining has little effect, in example get the output in the desired format. But many types helps to get much more accurate response. Saving Changes...
Mechel GlassConsumer Financial Protection Bureau (CFPB)
An example I worked on was a calculator. At first, I typed all the information in a word document and then copied and pasted all the information into the AI prompt and it was immediately overloaded. The output was very broad and unorganized. What I have learned from taking these courses is that in the future I need to start with selecting the correct formula and not write a novel.
Next, I should break down what I want the output to be in smaller chunks and import my examples. I am happy to learn about prompt chaining because this will be very helpful in the full creation of my project.
My experience further points to three areas where I will be able to immediately improve: Conciseness (not loading the entire project and all outputs needed), Specificity (using the correct formula for my project goals) and Prompt Chaining (allowing additional context for future outputs and allowing the AI to continuously learn and refine). Saving Changes...
Anonymous
Thanks! Saving Changes...
VenkataRatnakumar ChavakulaIT Solution Architect | Project Management | ERP Implementation Expert| Wipro Technologies, New JerseyMonroe Township, NJ, United States
I have experiment with different prompts depending on the technique to incorporate. I use the following format to get a better output and also share an example I use (will refine this template based on the need)
Note: Prior to PMI infinity used to use ChatGPT, Co-Pilot and now addicted to use PMI Infinity. Using Infinity most of the time and getting better results. Also I run the same prompt to make sure that, I'm getting the same results or near to what I'm getting in PMI Infinity and encourage all PMs to use this tool for better results and experience.
Example prompt for reference (refine and use it to fit your needs:
GOAL: to Create a comprehensive Project Management Plan with this Infinity prompt, covering scope, timelines, budget, and risk strategies.
● My type of business: In house Software Development
● My project scope: Develop a new customer relationship management (CRM) initiative for a manufacturing organization, develop and launch an advanced AI-driven platform to automate business processes.
● My project timeline: July 2025 - June 2026
● My budget constraints: Limited budget prioritizing cost-effective solutions and maximizing ROI, not to exceed $500,000.
● My team size: 15 team members including developers, designers, and project managers.
1. Define the project scope and objectives clearly
2. Outline specific deliverables and milestones
3. Create a detailed timeline with key dates and deadlines
4. Develop a comprehensive budget breakdown
5. Conduct a thorough risk assessment and mitigation strategy
6. Assign team roles and responsibilities
7. Establish communication protocols and reporting structures
It's quite intuitive, because we're modeling the input thinking in the output, in each specific feature of the output. It's like requirement tracking. As a PM I believe we must think in this way. Saving Changes...
Shaunelle HarrisHead, Implementation| International Air Transport Association (IATA)Geneva, Switzerland
I find that CONTEXT and PURPOSE of the request are the two key pillars of any formula. Saving Changes...
Pranav LakhkarFounder| ProMiles Management ConsultingPune, MH, India
Refining a prompt can significantly improve the quality and relevance of AI output.
In my experience, vague prompts often lead to generic or off-target responses. But when I clearly define the objective, audience, format, and context, AI delivers much more precise and usable results. Even small adjustments, like adding an industry example or specifying tone, can turn a basic answer into a high-impact solution. Iterating with follow-up prompts helps fine-tune the output further. It’s a process of guiding the AI more intelligently, and the difference in quality is often dramatic. Prompt engineering truly makes or breaks the result Saving Changes...
Janice TimchuckChief of Staff| Wayne State University School of MedicineSaint Clair Shores, Mi, United States
Jun 23, 2024 5:19 PM
Replying to Booma Pugazhenthi
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You make an excellent point. Generative AI, while powerful, functions as predictive text on steroids and needs clear, unambiguous prompts to produce accurate results. Using frameworks like R-T-F can help manage this by specifying the role, context, tasks, and desired format, reducing the risk of ambiguous or erroneous outputs. To get better results from GenAI, provide context-rich, detailed prompts that include specific instructions and desired outcomes. This reduces ambiguity and guides the AI to generate more accurate and relevant responses.
Just learning about AI. I appreciate all of the feedback. Saving Changes...
In my experience, refining a prompt can significantly improve the quality and relevance of GenAI outputs. A vague input like “Write a marketing report” yields a generic response. But refining it to “Write a 500-word executive summary for a Gen Z-focused retail campaign using TikTok strategies” produces a targeted, actionable result.
Adding context (audience, tone, goals) and constraints (format, length, examples) guides the AI to deliver content that’s aligned with your needs, especially valuable in project management for reports, plans, or stakeholder communication.
Precision in your prompt = precision in your output.
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