Director, Learning Design & Development| PMIAsheville, NC, United States
Validating and checking outputs is critical when working with AI systems like Generative AI. Such validation approaches may include establishing clear criteria, implementing strong testing protocols, and continuous refinement.
In your experience with AI, what are some best practices for ensuring the results you receive are accurate, relevant, and aligned with your original goals?
Paul WaggonerProgram Manager| Consultant - FreelancePapillion, Ne, United States
Note that a project manager should be working with a team that also adds unique project details and business requirements. Not every detail will need to come from AI via prompt engineering.
Inputs to the model should be clear, focused, contextualized, exemplified, and avoid excessive emphasis on the desired outcome (I've found this can lead to hallucinations). Always verify output and check references Saving Changes...
To ensure AI results are accurate and aligned with your goals, we have to use clear and specific prompts, apply structured prompting techniques, refine prompts iteratively, and verify outputs against trusted sources. Maintain context, use prompt chaining for complex tasks, request structured outputs, and involve team review for quality assurance. Additionally, protect sensitive data and document effective prompts for consistent future use. Saving Changes...
Mohammed Nabil AhmedIT Director KAP1| Khatib & AlamiRiyadh, Riyadh, Saudi Arabia
From a project management perspective, one of the best practices when working with AI is to treat its outputs as a draft that requires validation, not as a final deliverable. First, it is important to define clear objectives and acceptance criteria before using the AI tool. The prompt should explain the expected outcome, the context, the target audience, the required format, and any constraints. This helps ensure that the response is aligned with the original purpose. Second, I always recommend applying reliability checks. This means reviewing whether the output is accurate, consistent, complete, and supported by reliable information. For technical, legal, financial, or contractual matters, the AI response should be compared against official sources, internal documents, standards, regulations, or expert judgment. Third, iterative prompt refinement is very useful. If the first response is too general, incomplete, or not aligned with the goal, the prompt should be adjusted with more context, examples, or specific instructions. This improves the quality of the final result. Finally, AI should support decision-making, but it should not replace professional responsibility. The user or project manager must review the output, identify risks, validate assumptions, and confirm that the result adds value to the project objectives. In summary, the best practices are: define clear criteria, provide structured prompts, verify outputs with reliable sources, refine the prompt iteratively, and apply human judgment before using the result formally. Saving Changes...
AI is a broader term. Generative AI is just an ancient model but everything "explode" when Google published the new architecture called transformer in 2017. So, with that said, take into account that generative AI is just "predictive test with steroids" just simplifying the model. With that said, two key points has to be taking into account when somebody works with AI: 1-human in the loop. 2-AI without Data (today called data science discipline or big data or whatever) is the same thing that live without oxygen. Talking about generative AI all related to technology has almost not impact with relation to all related to non-technological roles and activities. What you stated about accuracy and things like that are easy to implement because there are a lot inside disciplines like statistics. Most of them to make things "a priori" to prevent instead of cure. Few organizations taking into account that when generative AI environments are put in place almost a new business unit has to be created where roles like lawyers, linguistic, diversity and inclusion specialist must be hire to help on put it in place.
I agree.
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Anonymous
Jun 07, 2024 9:24 AM
Replying to Sergio Luis Conte
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AI is a broader term. Generative AI is just an ancient model but everything "explode" when Google published the new architecture called transformer in 2017. So, with that said, take into account that generative AI is just "predictive test with steroids" just simplifying the model. With that said, two key points has to be taking into account when somebody works with AI: 1-human in the loop. 2-AI without Data (today called data science discipline or big data or whatever) is the same thing that live without oxygen. Talking about generative AI all related to technology has almost not impact with relation to all related to non-technological roles and activities. What you stated about accuracy and things like that are easy to implement because there are a lot inside disciplines like statistics. Most of them to make things "a priori" to prevent instead of cure. Few organizations taking into account that when generative AI environments are put in place almost a new business unit has to be created where roles like lawyers, linguistic, diversity and inclusion specialist must be hire to help on put it in place.
Thank you for your view! Saving Changes...
Anonymous
Great question, in my limited experience I also try to be very specific in what, when and where describing the situation and the roles and purpose. This response improves somewhat in my search.
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Deborah MfonCaracal Oil and Gas Service LimitedLagos, Nigeria
AI is one tool that has relieve many from going through books, authors manually. so i learnt that when new to a project that i don't understand, i try to give details of what i need and it gets difficult when you don't really know what you are looking for but have a deadline to your request, worst is when you meet an expert in that field, everyone comes in with different version and it all sound cumbersome, but i realized that after several prompt, chat and research, AI gets to understand my search and simplifies it and tells me what i need, but this didn't happen on the first day i gave the prompt, it was over time. Saving Changes...
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