My career moved from field project management to enterprise program delivery and eventually directing a configuration services division. Along the way, I kept running into the same problems: information scattered across disconnected spreadsheets, reporting that consumed hours of manual assembly, inconsistent handoffs, and important relationships buried inside processes that only a handful of people fully understood.
I got tired of working around those limitations and started building solutions instead. Now I combine operational leadership with hands-on systems development. I map the workflows, trace the data relationships behind them, and build dashboards, automations, and internal tools that give teams a clear picture of what's happening and what needs attention.
The common theme in all of it is curiosity, and it started early. At eight years old I had a TI 99/4A and two books: the User's Reference Guide and Beginner's BASIC. I typed in programs line by line with no way to save, starting over every time, and when something didn't run I had to figure out why on my own. Around the same time, I was taking apart electronics to see how they were built. Both taught me the same lesson: complicated systems get less intimidating once you start tracing how the pieces connect. That's still how I approach operations today. I want to understand how a system works, why it behaves the way it does, and how its parts can be reorganized into something better, grounded in the principle that data is only as good as its source. Bad data in, bad data out.
I use AI-assisted development as an execution accelerator within a structured design process. I define the operational problem, map the workflow and data relationships, set the requirements, direct the architecture, and validate the outputs.
It lets me build at a pace that's closer to how fast I can think through a complex system. The operational knowledge, design decisions, and accountability remain mine.
Applied AI in operations: executive reporting that turns production, backlog, and billing data into leadership briefings; risk and exception detection that surfaces stalled work, aging backlog, and billing gaps before they become escalations; and SOP knowledge assistants that convert operational documentation into searchable guidance for technicians, leads, and onboarding.
Program leadership, quality governance, system design, and operational delivery across hardware production, NPI, enterprise programs, and technical development.
Challenge: New hardware platforms and configuration services cannot enter production safely based on technical capability alone. They require controlled validation, documented work instructions, quality criteria, production isolation, supplier-variation testing, launch metrics, and formal exit decisions.
Role: Lead eBryIT’s operational participation in NPI, production-pilot, and Safe Launch programs spanning imaging, hardware-platform qualification, Autopilot, Chromebook enrollment, and specialized UV-print services. Coordinate pilot-unit intake, production isolation, qualification criteria, controlled validation, technical-issue resolution, launch metrics, supplier variation, and go-live readiness with OEM engineering, quality, operations, and supply-chain teams.
Outcome: Created repeatable governance for determining when new platforms and services were ready to move from isolated testing into controlled production.
When an incorrect etch passed production and quality control, Matt helped lead the recovery, including device retrieval, lid replacement, re-etching, retraining, and implementation of stronger production and QC controls. The affected devices were recovered in approximately two weeks, and manager validation, enhanced QC checkpoints, and improved instruction controls were added to prevent recurrence.
~Two-Week Recovery · Root Cause Identified · Production and QC Controls Strengthened · Corrective Actions Implemented
Challenge: A custom WMS modernization and OEM API integration required translating operational workflows into testable acceptance scenarios, then validating that the system handled real production conditions including partial shipments, exceptions, DOA/repair routing, and carrier edge cases. A subsequent WMS1-to-WMS2 migration added data integrity requirements across 4,422 orders, 136K inventory records, and 186K service records, all needing business-rule validation and formal release readiness before cutover.
Role: Led business-focused operational UAT across both initiatives. Translated operational requirements into acceptance scenarios, performed functional and transaction-level validation, documented defects and edge cases, coordinated remediation with developers and external partners, and established smoke-test, rollback, and production-readiness criteria.
Outcome: WMS modernization and migration reached production release with documented acceptance decisions, validated data integrity, and confirmed smoke-test and rollback readiness.
Leadership had no unified view of operations. Project status, production, inventory, billing, and revenue existed in disconnected spreadsheets that required hours of manual assembly. WPR replaced that with a connected reporting layer that gives the operation a single, automatically updated view of itself.
Designer & Builder · eBryIT, Inc. · Connected Operational Visibility
View Case Study →When controlled testing showed that ChromeOS versions 143 through 146 failed across both USB Recovery and Enterprise Rollback while versions 147 through 149 succeeded, Matt analyzed the results, identified version 147 as the probable hardware or firmware baseline, and directed escalation through the OEM’s Google support channel. The validation unit was held before customer enrollment or shipment.
Probable platform baseline identified · Escalation directed through OEM channel · Unit held pending OEM confirmation
Relational data model connecting projects, devices, revenue, billing, and inventory into a single operational view. Demonstrates the data architecture behind enterprise deployment reporting.
Portfolio Demo · Interactive relational data model
View Case Study →State-machine lifecycle tracking with immutable audit records, dwell time analysis, and technician-level production performance reporting. That’s the same reporting layer automated at eBryIT.
Portfolio Demo · 305K devices annually
View Case Study →Full business management platform built for a small business client. Covers the complete estimate-to-payment workflow: estimate creation with status tracking, invoice generation, client CRM, a 100+ item pricing catalog organized by category, room-based estimating, payment logging, outstanding balance tracking, and business reporting. All running in the browser with no backend infrastructure required.
Key advantages: Zero hosting cost, works offline, all data stays local to the client, no subscription fees, purpose-built around how the business actually estimates and invoices work.
Client Project · IndexedDB · HTML/CSS/JS · Proprietary, not publicly available
Strong operations run on clear ownership, useful information, and teams that understand how their work connects to the larger outcome. My job as a leader is to build that clarity, remove what's in the way, and give people the systems and accountability structures they need to actually deliver.
In 2026, I founded CommitState, an independent technology and operations consulting practice focused on practical systems, workflow automation, reporting, integration, and custom software solutions. The practice complements my full-time leadership experience by providing an additional environment for developing operational systems and solving real business problems.
CommitState follows the Resolve · Commit · Deploy method: understand the current state completely before designing a solution, and design completely before building.
Computer Science coursework (junior standing) · transitioned to full-time professional role in the technology industry
Completed September 2026 · View credential
Completed September 2026 · View credential