I never planned to study AI-assisted decision-making formally—but after 2,500 ChatGPT interactions, I couldn't ignore the clear patterns that emerged. Over two years, I've leveraged ChatGPT across diverse projects: launching the AiBuddy blog, coding complex software solutions, and even producing an entire metal album dedicated to my cat, Mr. Fluffles. Each of these projects revealed something crucial: structured engagement with AI consistently yielded better results.
Curious about why some AI engagements succeeded while others fell flat, I began an extensive, methodical analysis of my own conversations. Inspired by principles from Test-Driven Development (TDD) and Decision Intelligence, I identified what I now call the AI Decision Loop, a structured five-step process that profoundly transformed my collaboration with AI:
My findings revealed something crucial: structured AI engagement dramatically reduced automation bias, enhanced creativity, and improved overall outcomes. Conversations where I followed all five steps were consistently more innovative, insightful, and effective. Conversely, skipping or rushing steps almost always resulted in outputs that required significant rework or lacked depth.
Perhaps my most significant insight is that AI's real potential isn't fully realized through passive automation. Instead, it's unlocked through thoughtful, structured interaction where AI acts as an adaptive cognitive partner rather than just an "answer machine." By treating AI as an active participant in my decision-making process, I've experienced remarkable improvements in creativity, problem-solving efficiency, and productivity.
If you're curious about how to optimize your interactions with AI, enhance decision-making, and unlock deeper insights, I encourage you to explore my full case study in detail [here].
I lead the strategic direction and execution of AI initiatives, helping organizations turn the promise of AI into real-world impact.