Enterprise delivery.
Practical AI workflows.

I carry product decisions through implementation.

I own product direction, interface design, and implementation for Passal and Leasekite. Passal connects lecture sources, study choices, and practice. Leasekite brings vehicle comparison and lease requests into a workflow that prepares drafts for review and keeps negotiation decisions with the user.

For Lockfield, a Workiva consulting practice, I shaped the positioning, website, and reporting resources around training and client ownership.

AI coding tools are part of how I explore alternatives, build interfaces and supporting features, and work through changes. My selected work shows the products alongside tools for agent access, evidence checks, and failed-action recovery.

I’m interested in enterprise implementation leadership, solutions architecture, and applied AI roles.

Accounting education. A career in technology.

I studied accounting. My career has been in software implementation and customer delivery.

I earned a B.S. in Accounting and a Master of Accounting at Iowa State. That education helps me understand finance teams’ data, reporting requirements, and controls. I bring that context to software delivery for finance teams.

Close to the customer and the technical work.

I started at Workiva in 2015, supporting public-company customers with SEC reporting and XBRL. At Ambra Health, I worked with customer IT teams on medical-imaging and EHR integrations. Back at Workiva as a Solutions Architect, I led implementations from requirements workshops through production use.

At Citrin Cooperman, I managed a five-person implementation team and led a connected-reporting engagement through go-live and executive sign-off. Today, I’m a Senior Manager at LSL, leading Workiva delivery for city and county finance teams.

The through-line is translating what a customer needs into a workable system: defining scope, working through integration and access issues, testing with users, and helping the team take ownership.

Tools for complex work.

I develop Python tools for reporting links, formulas, and validation checks, and use AI coding tools in build and review work. My personal projects explore agent access to APIs, evidence checks, approvals, and recovery when an automated action fails.

Those projects are public code and test cases, not claims of client AI deployments. They show what I’m building and give a technical team something concrete to inspect.

Help people understand the technical decisions.

I run customer demos, requirements workshops, and training, and coach implementation consultants. That work has taught me to explain a technical choice through the task someone needs to finish.

My interactive workflow lesson applies that approach to AI. Visitors can test an update, see why a proposal is rejected, and reconcile a lost response using fictional data.