I’ve never stopped preaching operational excellence, and this article by Kelsey Brandt at The National CIO Review captures the “why” perfectly.
At Amazon Web Services (AWS), I got a masterclass in operational ownership. It wasn’t optional. If my product suffered an incident, I was expected to explain at a detailed, technical level exactly what happened, why, and what we were doing about it. I was on the proverbial “hot seat” until my peers (and AWS top execs) understood the “why” as well as I did. And that meant at a dive-deep level.
Even in absence of an incident, I was called upon at random intervals to explain the “why” behind my operational metrics. At no time could I, as the leader, NOT understand what was happening to my service.
If that sounds uncomfortable, well … it was.
However, the discipline of “getting to why” made me a better product leader. Understanding operations meant I felt the pain my customers felt. My product decisions were almost always better with that operational knowledge than without it.
In the years since, I’ve coached teams to take on this same ownership.
The pushback has always puzzled me. “That’s the ops team’s job.” “I don’t need to know that level of detail.”
You do.
You absolutely do.
AI can absolutely help close the gap between “what happened” and “why” … AI can pull the data, surface the correlations, compress the investigative time.
BUT the critical thinking needed to turn operational insight into great product decisions? That still needs a human in the loop who’s done the work to truly understand their systems.
The tools are getting better. The question is whether we leaders will use them to go deeper … or use them as another layer of abstraction to hide behind.
Originally shared on LinkedIn, February 24, 2026.