I turn operational ambiguity into execution infrastructure — the systems, planning rhythms, and AI-native workflows that let product and delivery orgs move with precision instead of noise.
I'm a strategic operations leader with 14 years operating at the intersection of product, engineering, and go-to-market — across ad tech, security and compliance SaaS, data infrastructure, and AI-native voice systems.
My work lives one level above delivery and one level below strategy: translating complex goals into operating models, planning systems, and cross-functional rhythms that hold up under pressure and scale with the org.
I've built and rebuilt operating systems inside some of the most demanding environments in tech — joining Peloton pre-IPO and operating through hypergrowth, building compliance infrastructure at Drata during its scale-up, driving verification platform programs at DoubleVerify, and most recently designing AI-native voice infrastructure at Hatch.
More recently I've focused on one question: how do AI-native workflows change what operations looks like? Not AI as a feature, but AI as the backbone of how an org plans, decides, and executes. That's what the tools on this site are built around.
At Hatch, that question got a concrete answer: when a client issue turned out to trace back to shared platform infrastructure rather than one account's configuration, I designed a backward-compatible fix that protected every other live client and escalated it as a formal product enhancement — the kind of judgment call that sits above individual implementation work.
I'm looking for roles where I can own the operating model — not manage the execution layer, not chase teams for updates, but design and run the system that makes excellent product and operational work possible.
These aren't portfolio pieces. They're working tools built on the frameworks I use to diagnose and fix product operating models. If you run a product org, they'll tell you something real.
Most product ops failures trace back to five universal problems — ideas that get lost, strategy that doesn't drive decisions, planning driven by politics, execution that goes dark, and lessons that never stick. The PIL is a multi-agent system designed around all five. One layer per problem. Twelve agents. A scoring matrix, a planning lock, and a loop that closes.
I'm selectively exploring roles where I can own the operating model — planning systems, roadmap infrastructure, AI-native workflows, and the judgment to know when a fix is bigger than one team. Product, delivery, or operations org — the system is the point.