About
Independent Consultant — AI Transformation, Product & Technical Strategy
I help companies turn ambiguous business problems into practical software, AI-enabled workflows, and operating systems that teams can actually use.
My work sits at the intersection of engineering leadership, product ownership, operations, and business process design. I have led software engineering teams, managed technical budgets, owned custom platform development, and worked with business leaders to translate messy operational needs into clear technical execution.
Increasingly, my focus is on AI implementation — not AI as a slogan, and not AI as a collection of tools, but AI as a practical way to redesign work. That means identifying workflows that consume too much time, money, or organizational attention; defining the product and business requirements; designing the technical architecture; and coordinating the people, systems, and AI agents needed to deliver the work.
I am especially interested in problems where the first question is not "What should we build?" but "What is actually challenging right now?" From there, the work becomes clearer: understand the workflow, define the outcome, decide what should not be automated, design the system, and build toward measurable business value.
I tend to work best with founders, executives, and teams who have real opportunity but need more structure around product, technology, operations, and execution. Sometimes that means acting as a fractional CTO. Sometimes it means owning product and operations. Sometimes it means helping a company find the right AI workflow to implement first. In every case, the goal is the same: create clarity, build useful systems, and move the business forward.
How I work
Step 01
Talk through the actual workflow, who owns it, where the handoffs break down, what decisions are being made, what information is missing, and where time or money is being wasted.
Step 02
What should be faster? More accurate? Easier to manage? More visible? What should not be automated? What risk has to be controlled? Only then does the technical design make sense.
Step 03
The implementation might involve AI agents, software automation, better internal tooling, clearer product requirements, a new operating cadence, or better engineering process. The point is not the newest tool — it is the right system.
What I believe
AI is an accelerant, but accelerants do not choose the destination.
AI makes mediocrity faster. The value is not in producing more output. The value is in applying better judgment to the right problem.
The first question should not be "How can we use AI?" The better question is "What problem are we actually solving?"
Good implementation starts with understanding the work — not the tooling.
A useful system has ownership, workflow clarity, business rules, technical architecture, exception handling, and a definition of success.
Founders and executives do not need more noise. They need leverage.
Most real business problems do not fit neatly into one department. The work requires product judgment, technical architecture, operational design, and leadership cadence at the same time.
If your company has a workflow, product idea, technical decision, or operating problem that feels important but unclear, reach out. The first conversation is about understanding what is actually going on.