I spent a decade running real projects, customers, crews, vendors, materials and schedules. Now I use AI and modern development tools to turn those messy workflows—and ambitious product ideas—into working software.
The common thread is not a technology stack. It is moving from ambiguity to something tangible: understand the workflow, identify the friction, design the system, prototype quickly, and get a working product in front of a user.
A working inventory and purchasing system designed around a construction operation—because “on the shelf” and “actually available for the next job” are not the same thing.
A company brain designed around a simple idea: the business should not have to answer the same question twice.
What if configuring an expensive physical product felt less like filling out a form—and more like experiencing what you were about to buy?
A personal operating system designed around a simple constraint: one mission, ten standards, every day.
A race-training planner that turns a few athlete inputs into a structured, date-aware training plan.
Software built from a domain I already knew: turn customer court choices into something visual, measurable and installable.
Start with what actually happens—not what a software diagram says should happen.
Identify where information, handoffs or decisions create friction.
Use modern AI and development tools to make the idea tangible fast.
Test the workflow, learn what is wrong, and iterate toward useful.
Before I was building software, I was responsible for the consequences when operations broke: customers waiting, crews missing information, materials not where they needed to be, permits holding up schedules, and dozens of active projects competing for attention.
That is why I care about software that removes friction instead of adding another system to babysit. I bring the perspective of someone who has managed the work and now has the tools to build around it.
Stockton and Ask Adam use the same product principle: the model should be connected to evidence, constrained by what the system actually knows, and honest when the answer is missing. That is the kind of AI implementation work I want to do next.
Ask Adam is grounded in my résumé, product work, and case studies. A hiring manager can ask what I have actually shipped, where my experience maps to a role, or paste a job description and get an evidence-backed fit analysis.
That is the work I want to do next: AI implementation, product operations, technical project management, or solutions.
Hi — I'm the evidence layer for this portfolio.
Ask what Adam has actually built, why his operations background matters, what his strongest AI work is, or paste a job description and I’ll map requirements to proof.