About

I lead technology where commerce gets complicated.

For more than 15 years, I’ve moved between design, code, engineering leadership, IT, data, operations, and vendor management. That range matters when the problem crosses team lines.

At Tommy John, a $100M+ omnichannel brand, I served as VP of Technology and grew delivery from two internal engineers to six employees and 15 consultants. My work included Shopify replatforming, ERP and 3PL migrations, integration redesign, data-platform consolidation, vendor negotiations, and hands-on product delivery.

The Work

Problems I’m usually asked to untangle

The stack grew one urgent purchase at a time, and now nobody can explain what is essential.
Commerce, finance, fulfillment, and marketing report different versions of the truth.
A migration is on the calendar, but ownership, sequencing, and risk are still fuzzy.
Technology spending has grown faster than its contribution to the business.
Leadership wants AI in the plan, but the team has no reason to trust another pilot.

Operating Style

I stay close to the work

I can work with a board on priorities in the morning and review an integration or production release in the afternoon. Staying close to the details helps me catch bad assumptions early and make better calls on scope, cost, and risk.

It also means the team gets clear decisions. Engineers understand the business reason, operators know what will change, and leadership knows what the work should return.

AI, Without the Theater

Start with the workflow, not the model.

Most commerce brands do not need an “AI strategy” in the abstract. They need cleaner product operations, faster analysis, fewer repetitive handoffs, and better decisions from the people they already have.

I look for the point where work stalls, where data gets re-keyed, or where a decision depends on someone assembling the same report again. Then I decide whether the right answer is a better process, an integration, conventional automation, or AI.

Automate repetitive product, content, merchandising, and reporting work.
Pull commercial and operational signals into one useful daily picture.
Flag inventory, performance, and customer issues before they become expensive.
Keep a human review step wherever a bad answer could reach a customer or change a critical record.

If a use case cannot name the work it removes, the decision it improves, or the risk it catches, it is not ready to build.

Platform and Vendor Decisions

Every tool has to earn its place.

What problem will this solve, and what will we stop paying for or doing by hand?
Can the team own it after launch, or are we buying a permanent dependency?
Does it simplify the stack, or add another source of truth and another failure point?
Will we use enough of the product to justify the contract?

The Outcome

A technology function the business can rely on.

Clear priorities, fewer unnecessary systems, numbers people trust, and a team that can change the business without holding its breath.

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