Product architecture
Turning an idea into explicit boundaries, contracts, data flows, and a staged delivery plan.
Chicago · Building in public and private
I build the systems behind ideas that need to ship.
Full-stack and AI product engineering across developer tools, real-time systems, mobile foundations, and production-minded infrastructure.
2,700+GitHub contributions in the last year
10 yearsBuilding and learning on GitHub
End to endFrom product architecture to release workflows
Selected work
Products with depth.
Most current product code is private. These case studies publish the problem, architecture, decisions, and engineering evidence without exposing credentials, customer data, or proprietary source.
01 / Mobile systems
App Factory
A shared foundation for creating, testing, and releasing mobile products with controlled AI assistance.
02 / AI discoveryKeyword Graph Explorer
Graph-based App Store keyword discovery using live metrics, semantic expansion, and novelty memory.
03 / Logistics platformLoadHaste
A production cargo-search and spider-orchestration platform for freight-board automation and operational monitoring.
04 / Real-time productBattle 2048
A multiplayer adaptation of 2048 with live matches, matchmaking, strategic mechanics, and persistent player data.
Capabilities
From ambiguity to a maintainable system.
Full-stack delivery
React and mobile interfaces, Node or Rails services, databases, real-time communication, and integrations.
Operational quality
Testing, security boundaries, observability, documentation, release automation, and human-controlled AI workflows.
Public engineering
Code you can inspect.
Shipri ↗
Privacy-first peer-to-peer file transfer with WebRTC, E2EE design, Socket.IO signaling, Coturn, and a self-hosted deployment model.
App Store Scraper + MCP ↗
A substantially extended open-source fork with a TypeScript MCP server, resilient HTTP layer, App Store research tools, schemas, and tests.
Approach
Practical systems, explicit decisions.
I prefer the smallest architecture that can survive real use. AI accelerates scaffolding, research, implementation, and testing; product and architecture decisions remain human-controlled.