Over the years, across different roles, there's something I've repeatedly grappled with: why is it so hard to accomplish what appears to be a straightforward goal? Why does objectivity break down even when teams are capable and well-intentioned? Too often, focus shifts toward headlines and optics rather than the inner core of the work. I know I'm not immune to this either.
This persistent gap between intent and execution is what I've come to think of as human engineering. I've become increasingly intentional about trying to master it — not as a soft skill, but as a discipline. I'm learning that excellence is less about pushing harder and more about designing environments where:
• incentives and context outweigh individual brilliance
• alignment is the default setting
• friction surfaces early rather than being buried
What intrigues me is how this lens applies to agentic AI. As digital workers evolve, familiar themes reappear: context accumulation, domain understanding, and the need for guardrails that balance autonomy with control. It makes me wonder whether the evolution of AI agents will eventually require a new kind of behavior design — echoing the same human engineering challenges we've been navigating for years.
First published on LinkedIn, January 15, 2026.