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When using AI systems, what are some best practices for ensuring the results you receive are accurate, relevant, and aligned with your original goals?

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Sarah Philbrick
PMI Team Member
Director, Learning Design & Development| PMI Asheville, 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?

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Anonymous
Jun 08, 2024 11:44 AM
Replying to Giorgos Sioutzos
...
Providing the specific context in clear and consise way is essential.
Agree
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Anonymous

For me the trick is in not being lazy while prompting and really trying to explain the task in the most precise way

Being Specific and providing the right context, prompts, Iterations matching your scenario will help to get the right feedback from AI which might match your goals.

When using AI systems, there are a few simple best practices to get accurate and relevant results.

Be clear and specific – Give detailed instructions and context.

Ask focused questions – Avoid vague prompts.

Verify information – Double-check important facts from trusted sources.

Refine your prompts – Adjust and re-ask if results aren’t right.

Set constraints – Mention format, length, or style you want.

Use examples – Show what kind of answer you expect.

Stay critical – Don’t assume everything AI says is correct.

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John Navas Guayaquil, , Ecuador
My approach is to use the AI as a conversation with an expert, then I present the subject, ask recommendations, share my thoughts/doubts and check again AI responses. Finally I use the information collected during this session to prepare by myself the information that I need in the format needed. I know this take much more time that just provide a good prompt to AI, but for now I use this approach to be totally convinced about the information I'm delivering
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Damodar Kaza Hyderabad, TG, India
High-quality AI results come from a loop:
Clear goal → rich context → clarification → structured output → critical validation → iteration
If you follow that cycle, AI becomes not just accurate—but consistently aligned with what you actually need.
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Damodar Kaza Hyderabad, TG, India
High-quality AI results come from a loop:
Clear goal → rich context → clarification → structured output → critical validation → iteration
If you follow that cycle, AI becomes not just accurate—but consistently aligned with what you actually need.

validating AI output

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Anonymous

validate AI output .

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OLUSEYI ILUPEJU Project Manager (Construction)| BSA Group LLC Bethesda, Md, United States

To ensure that I get adequate and relevant results, I use methods like cross-referencing of information against trusted sources, check for hallucinations and request for citations.

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