Developer profile · creator of Vectrexia

Sean Findley

Senior .NET / Azure Engineer · AI Systems Builder

I build production AI and Azure cloud systems. Vectrexia brings that same systems thinking to a browser-based Vectrex experience: careful low-level emulation, research-backed title pages, and a polished interface built to feel worthy of the original machine.

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.NET 10
Azure
WebGPU
WebGL2
Edge AI
Product systems

Sean Findley, developer of Vectrexia — **Sean Findley** AI systems developer · .NET, Azure, and edge AI

A little about me

Enterprise discipline, product taste, and practical AI.

I am a senior full-stack engineer with more than ten years of experience shipping secure .NET and SQL-heavy applications across government, higher education, and enterprise environments. My current work focuses on WebLLM, ONNX and PyTorch edge inference, agentic workflows, Azure cloud operations, and software surfaces that stay calm and credible under real production constraints.

I work where enterprise discipline, cloud operations, and practical AI meet: modernizing legacy systems, building operator-friendly administration surfaces, wiring AI into real workflows, and shipping products that feel calm, fast, secure, and credible in production. MBA-backed product judgment keeps those technical decisions connected to the people, costs, and operational realities around them.

Under the glass

The technology behind Vectrexia

Vectrexia is a full production web application, not a canvas demo wrapped in a landing page. The server, emulator, rendering pipeline, catalog, research layer, and deployment checks are designed as one system.

Server-rendered .NET 10

ASP.NET Core MVC serves canonical game and demo pages, metadata, structured data, APIs, the sitemap, and assembly-embedded BIOS and cartridge resources.

WebGPU-first vector rendering

The display prefers WebGPU, falls back to WebGL2, and retains a Canvas2D compatibility path while preserving phosphor persistence, bloom, scanlines, and vector-beam character.

Browser-side machine emulation

JavaScript models the 6809-era CPU path, VIA behavior, analog vector timing, sound generation, controller input, local ROM loading, and original 3-D Imager signaling.

Azure production delivery

The application deploys to Azure App Service through a clean ZIP pipeline with source validation, deterministic ROM diagnostics, route checks, integrity checks, and live health probes.

Research-backed title archive

Stable game and demo URLs carry credits, history, gameplay notes, related titles, source records, and transparent research-confidence labels before JavaScript runs.

Hand-crafted product surface

The Razor, CSS, and JavaScript interface is custom-built rather than assembled from a purchased theme, component kit, or front-end framework. AI assistance supports the work; engineering judgment remains the final gate.

Why this project

Retro hardware is a demanding systems problem.

The Vectrex combines CPU timing, analog integration, vector geometry, audio, input, and a physical display aesthetic that exposes shortcuts immediately. Building Vectrexia means respecting those constraints while making the experience approachable in a modern browser. It is preservation, engineering, and product design in the same frame.

Production AI, Azure systems, edge AI, and software architecture.

See my broader portfolio, current projects, articles, résumé, and contact information on my main site.

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