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

Carefully construct your prompt according to the output you wish to receive. Use different prompt strategies and work with the AI tool until you achieve what you are looking for.

Carefully construct your prompt according to the output you wish to receive. Use different prompt strategies and work with the AI tool until you achieve what you are looking for.

Hi, I fully agree to your comparison and I cannot stress enough how important it is to communicate your own criteria to an AI system in small, clear steps

I usually ask the AI to cite the source in cases that require accuracy. In many cases, I do selective reviews of sources and ask how to come to a conclusion. Also, ask him to be objective and stay away from courtesy in evaluation.

Always verify AI outputs against reliable sources, provide clear and specific prompts, iterate based on results, and maintain human oversight. Cross-check data with your project context and never accept AI responses at face value without critical review.

After completing this course, I’ve realized how critical clear instructions are to achieving the desired outcomes. While I previously applied methods like RTF (Role-Task-Format) intuitively, I now focus on providing the GenAI with as much context as possible, using real-world sources to ensure detailed analysis. The results are highly satisfactory, requiring only a final human review to fine-tune the tone and ensure the message perfectly reflects my intent.

Using the right context, persona, and continuously refining the prompt until the desired output is achieved from the target LLM.

1 - We can check the accuracy and relevance of the outputs generated by AI with the help of subject matter experts who have vast knowledge about that particular problem.

2 - Ask AI about the sources referred to give the final outputs, Do validation check to check if it aligns with our expectations and needs.

3 - Fine tune the prompts using any on the prompting techniques based on their application to use.

4 - Keep the data clean to get effective responses.

5 - Keep the prompts concise and precise.