When I first started using AI seriously, I'd just throw questions at it and hope for the best. Zero-shot prompting. No examples, no context, just "figure it out." Sometimes it worked. Most times? Not so much. Then I started giving it examples first. One, two, three samples of what I actually wanted. Few-shot prompting. Night and day difference. The trick is knowing when each approach makes sense. I walk through real comparisons in this carousel. I walk through techniques like this in my Thursday workshop (9 AM PST, next up April 2nd). Comment "Adapt" if you're curious. #PromptEngineering #AITips #DatasphereDynamics

What if your AI could review its own work before you even look at it? That's reflective prompting. One extra line changes everything: "Review your response for errors, gaps, or assumptions. Then correct them." I built this habit from years of enterprise project management. You never submit a deliverable without a QA pass. Why would you treat AI outputs any differently? This carousel walks through the self-review framework I use. If this resonates, come hang out at my Thursday workshop, 9 AM PST. Comment "Adapt" or shoot me a DM. #ReflectivePrompting #AIQuality #DatasphereDynamics