18+ years keeping global pharma marketing programs on track.

I've spent my career inside some of the most complex delivery environments in pharma marketing: multi-market campaigns, strict legal/medical/regulatory review cycles, and stakeholders spanning brand, digital, analytics and technology. My job is to make all of that move smoothly — governance, resourcing, risk, reporting — so the people doing the creative and strategic work can focus on it.

Outside of client delivery, I have a hands-on technical streak that doesn't show up on a typical resume: I design and build software, including a working suite of AI tools (see Jason AI) that integrates multiple language and image-generation providers with automatic fallback logic. I like understanding systems from the inside — whether that's a marketing operating model or a piece of software.

That combination is rarer than it sounds. Most operations leaders can brief a Gen AI vendor and evaluate a pitch deck. Fewer have actually integrated an LLM API, hit its rate limits, debugged a failure mode at 2am, and shipped a fallback path that keeps working when the primary provider doesn't. I've done that — not as a side hobby disconnected from my day job, but as the same delivery discipline applied to a different kind of system. It's exactly the perspective I bring to conversations about where Gen AI genuinely fits into a marketing operation, versus where it's just this year's slide in a strategy deck.

If you're evaluating how Gen AI, automation, or AI-assisted content workflows should fit into your marketing operations — not as a science project, but as something that actually needs to run reliably in production — that's a conversation I'm glad to have. See Consulting for how that works, or get in touch directly.