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

Trust but verify the output, ensure the LLM has not hallucinated or made assumptions based on gaps in the prompted information.

Mixing the CREATE Formula with the Patterns such as Chain of Thought, Chain of Feedback, ReAct, Question Refinement, Flipped Interaction, Risk Assessment Matrix, and Cognitive Verifier to have very well context, specified structure and clear guidance consolidated by given materials controlled by the validation techniques and continuous fact check to the outputs against the trusted and known primary sources; might lead up to 95% and above of receiving an accurate, relevant, and aligned result with your original goals expected.

Mixing the CREATE Formula with the Patterns such as Chain of Thought, Chain of Feedback, ReAct, Question Refinement, Flipped Interaction, Risk Assessment Matrix, and Cognitive Verifier to have very well context, specified structure and clear guidance consolidated by given materials controlled by the validation techniques and continuous fact check to the outputs against the trusted and known primary sources; might lead up to 95% and above of receiving an accurate, relevant, and aligned result with your original goals expected.