My Approach Centers AI Strategy, Systems Thinking and Leadership

It's the hardest part and it's always in progress.

When I led the best practices aspect of building AI-assisted editorial workflows across a major media portfolio, the prompting was the straightforward part. The harder work is helping hundreds of editors understand why this is worth their time, address their legitimate concerns about quality and autonomy, and develop the judgment to know when to use the tools and when not to. That's not a communications problem. The change management element of projects like this should be at least as rigorous as the technical requirements.

The most valuable thing I do is help teams that speak different languages find common ground. Editorial teams think in stories and reader relationships. Product teams think in problems, systems and solutions. When these teams are too busy to understand each other's priorities, good ideas die in handoffs. I'm developing frameworks that result in content performance, product adoption, and organizational trust.

When Good Housekeeping's search revenue dropped 36% year over year, the easy answer was to chase the most obvious symptoms. The more useful answer was to step back and understand the system — the content, the workflows, the platform dynamics, and the team capacity — well enough to know what was actually broken and in what order to fix it. The result was a cross-functional action plan that drove a +40% year-over-year recovery by the end of that year. That kind of turnaround doesn't come from finding one thing to fix. It comes from understanding enough of the whole to know where to start.

Teams do their best thinking when they feel safe surfacing problems, challenging assumptions, and saying "I don't know." I design meetings, workshops, and working relationships to create that safety. Without it, the information you need to make good decisions never makes it to the surface.

Anything that can help my team get valuable time back is a win. When I first took over Good Housekeeping content planning in 2021, this heavily-research, data-backed process was meticulous and took nearly 40 hours a week. Over the years, I found ways to cut corners without diminishing the value of this research, getting the work down to 10 hours. When my work was checked by other teams in 2025, they found the same stories we were suggesting were the most effective to touch.

In 2025-2026, I passed this process off to a report after working with an AirTable Automations expert to turn the whole research process into an automated formula with a quick gutcheck that takes a couple hours at most.

I believe that AI is here to stay. The concerns about job market volatility, environmental impact and longterminism are entirely founded, but that is why learning about AI is more important than ever, especially for those who care deeply about the future. I am constantly up-skilling in the AI space, but it's not about checking a box on my resume. It's about being the person who, when the organization inevitably asks a team to "make AI happen" can do it in a way that is elegant, human-centered and makes sense.