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What if reflection wasn’t a year-end memory dump but a working system that sharpens judgment? We sat down to examine how AI quietly changed the way we think, plan, and lead—shifting focus from task speed to decision quality, from outcomes to assumptions, and from rigid plans to resilient learning loops. Instead of asking what happened, we asked who we grew, where we created real leverage, and how our narrative as leaders evolved.

We unpack the prompts that force clarity without comfort: where did our judgment create outsized impact, which decisions aged well given the information we had, and how well our calendars matched our stated priorities. Along the way, we show how AI reconstructs decisions at the moment they were made, turning private reasoning into an artifact we can analyze without ego. That distance unlocks clean counterfactuals—what alternatives were viable, which assumptions mattered most, and where risk was mispriced—so we stop relitigating ourselves and start improving the system.

From there, we build a true decision quality loop: track choices, inputs, confidence, and results to expose patterns in judgment. Strengths become repeatable, biases become addressable, and learning accelerates. The payoff isn’t just productivity; it’s resilience. AI lowers the friction around thinking, helps separate signal from noise, and makes it easier to update beliefs quickly. If next year looked exactly like this one, would that excite you or concern you? Press play to grab the questions, run your own review, and set a sharper direction.

If this resonated, subscribe, share with a friend who leads, and leave a review with the one question you’re taking into your year-end reflection.

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