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?
Irakli EliavaOperations Director| Solid Group GeorgiaTbilisi, Georgia
I can recommend one interactive tool that helps you brainstorm the missing details from your prompts. It asks you questions about your projects and then generates a prompt that matches the latest prompt engineering standards. When it comes to project management it has been gamechanger.
In my experience with GenAI, refining a prompt by providing a clear explanation of the goal and setting specific limits drastically improves the quality of the output. When the expectations, context, and boundaries are clearly defined, the AI produces results that are more accurate, focused, and aligned with the intended outcome. Saving Changes...
ashutosh mahapatraSenior Program Manager| SalesforceHyderabad, Telangana, India
THis course is very informative for Project Managers who are new to AI. It explains how can we create effective Prompts to make our day to day activities efficiently and get extra time to focus on other priority tasks. This is a must recommended course for all PMs.
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).
As a project manager, I view prompt engineering less as a technical exercise and more as an extension of structured thinking. The way we frame prompts closely mirrors how we define scope, constraints, assumptions, and success criteria in project management. In practice, generative AI becomes most effective when treated like a junior project analyst: it performs best with clear objectives, context, guardrails, and iterative feedback. Prompting patterns such as ReAct and role-based prompting align well with Agile and hybrid delivery models, enabling continuous refinement as project priorities evolve. Rather than replacing judgement, AI augments it—supporting planning, risk analysis, stakeholder communication, and documentation—while the project manager remains accountable for decision-making, governance, and outcomes. Used this way, AI is not a shortcut, but a force multiplier for disciplined project management. Saving Changes...
Robert BrownRobert L. Brown, PMP| NoneBirmingham, AL, United States
AI is also excellent at engineering prompts for itself - A hybrid approach is to provide your prompt, ask AI to propose the chain, review and tweak, then execute the resulting chain with AI. I find it helps keep me from being overly prescriptive. When I wrote code, unexpected results were always bad - with AI, unexpected results could mean alt framing, structure, or insight. Saving Changes...
Josephine CheungSenior Specialist, Product & Solution Support| Fujifilm Business Innovation Hong Kong LimitedHong Kong, Hk, Hong Kong
try asking ai in different ways to see his response
Saving Changes...
John AndersonProject Lead| MetroStar SystemsIndependence, Mo, United States
Thank you all for providing information on useful frameworks to implement when generating AI prompts! The training has been very informative and useful. Look forward to applying what I have learned in this training to help generate useful AI output in my day to day!
Saving Changes...
Anonymous
I expect my future use of prompt refinement will improve the quality of outputs that I currently receive from GenAI. I look forward to implementing some of these new skills.
Saving Changes...
Anonymous
Saving Changes...
Doga ilterProject Manager| ÜlkerBa?C?Lar, ?Stanbul, Türkiye
PMI Team Member
