How I operate with AI, not just how I use it. Most People Operations and Talent Management teams treat AI as a productivity gadget. I treat it as an operating layer. The difference shows up in the work.
I run a multi-tool AI workflow because each tool has a distinct role. Knowing which tool to reach for is its own kind of fluency.
Two years of daily Claude use embedded in real People Ops work taught me these. They're not opinions, they're the patterns that consistently produce good output.
Two years of operating this way at Netflix. Real metrics from real work.
The cumulative effect of operating this way for two years at Netflix is measurable, but the metrics don't tell the whole story.
I built a library of reusable prompt playbooks that other team members can adopt to scale their own work. I shipped AI-augmented learning loops built into manager development programs. I designed scenario-based practice partners that let managers rehearse difficult conversations before they have them in real life.
The pattern recognition across organizations. The judgment calls about what to surface to leadership. The relationship work that builds trust. AI didn't replace any of that. It made room for more of it.
The next decade of People Operations work will be defined by people who can make AI an operating layer for their function, not a feature in their toolkit. The skill that matters isn't prompting, it's translating real operational problems into structured prompts and architecting workflows that scale beyond any single person.
That's the work I want to keep doing. The artifacts on this site, the playbooks I share, and the systems I've built reflect that bet.
Open to Senior Program Manager, AI Enablement, Learning & Development, People Operations, Talent Management, and Executive Business Partner roles. Full-time, contract, or fractional. Fully remote.