For most of my career, shipping software meant assembling a team: engineers, designers, domain experts, all of them human, all on a payroll. Now I can assemble a different kind of team: industry SMEs, product-development architects, and design experts, spun up on demand and working at AI speed.

What I've found is that experience compounds when it meets that team. Two careers in one (software engineering, then enterprise product leadership) turn into the layer that removes bottlenecks. Knowing what to build, knowing how to build it, knowing what to skip, knowing how procurement and CISOs and migration plans actually work. The AI team does the heavy lift. The human does the judgment.

The result is that one motivated person, fluent in an industry, can iterate fast on existing products and ship net-new ones at a pace that wasn't possible eighteen months ago. Not “AI as a productivity tool.” A different way of working.

ProductIntel is an operating system for product teams who'd rather centralize their knowledge, automate the repetitive workflows, and turn every conversation into traceable work, instead of stitching together six SaaS tools and hoping for the best.

I built it solo, with an AI team. It's live, in use, and shipping new capabilities most weeks.

Most small businesses don't need an AI strategy deck. They need one useful operational moment: a repeated question answered, a handoff cleaned up, an estimate produced without three rounds of email.

I've been sketching what a productized AI consulting offering for that audience could look like, captured as Holloway Consulting. Two example engagements:

The Blueprint would be the focused entry point: sit with the owner, map the business, identify high-value AI workflow opportunities, deliver a concrete plan with cost estimates. Optionally build the first workflow.

The Vibe Check would be a production-readiness audit for apps built in Lovable, v0, or Cursor.

I'm a VP of Product Management at a Fortune 500 FinTech. The first two decades of my career were spent writing software (production systems, financial services platforms, enterprise architecture) before I moved into product leadership. I bring both sides of that arc to the table now: I've shipped financial services software to Fortune 500 customers, navigated procurement cycles longer than most startups exist, and sat across the table from CISOs who killed projects for security requirements no one anticipated.

Starting in Fall 2025 I've also been building AI agent systems from scratch: multi-agent orchestration, context engineering, token economics, the whole stack. The engineering background is why the AI-team approach works for me: I can read what gets generated, debug what breaks, and tell the difference between a working system and a demo.

Outside of product, I shoot natural-light portraits: families, seniors, detail work.