Selected projects
Twenty-eight years of systems built around consequential problems.
This is selected evidence from a 28-year career in technology: platforms, production systems, delivery tools, volunteer infrastructure, and independent builds I have architected, built, or led. Every flagship identifies the operating problem, my contribution, and what the available evidence can honestly prove.
Flagship projects
Consequential problems. Traceable decisions. Honest proof.
These projects carry the strongest combination of business consequence, architecture, leadership responsibility, and implementation evidence. Each page says plainly what is measured, implemented, deployed, or private.
- Read Strategic account intelligence platform
Enterprise AI and go-to-market systems
Strategic account intelligence platform
A governed intelligence system that helped sales teams and leaders move from fragmented account research to current, evidence-backed decisions.
- Read Enterprise AI knowledge platform
Enterprise AI platforms
Enterprise AI knowledge platform
A governed enterprise assistant for meeting intelligence, knowledge bases, organizational data, retrieval, and agent workflows.
- Read AI delivery engineering platform
Delivery systems and automation
AI delivery engineering platform
A low-code engineering environment that helped delivery teams build governed AI automation without unnecessary configuration burden.
- Read Agent Fabric
Agent-development systems
Agent Fabric
A multi-agent development system built around a repeatable Research, Plan, Implement, and Validate methodology.
- Read Flowplane
Agent-development infrastructure
Flowplane
A workflow engine for AI-assisted software development with isolated execution, durable work tracking, and persistent knowledge.
- Read Church communications platform
Volunteer technology
Church communications platform
A volunteer-built platform for churches to manage podcasts, newsletters, email and SMS campaigns, audience lists, users, services, and scheduled delivery.
Tools and platforms
The wider technical practice behind the flagship projects.
Platforms, automation, recursive systems, developer infrastructure, and applied education show the continuity of the work across domains.
- Read Account data intelligence platform
Data and insight systems
Account data intelligence platform
A scalable processing system that turned large account datasets into normalized, evaluated, and useful sales intelligence.
- Read OEM automation platform
Human-governed automation
OEM automation platform
A natural-language administration system that planned, executed, and verified complex changes across APIs and management interfaces.
- Read TerraFlux
Recursive development systems
TerraFlux
A coding harness that carried decisions, insights, and outcomes forward across recursive agent workflows.
- Read Shipyard
Developer infrastructure
Shipyard
A fleet of isolated AI development environments accessible from anywhere through a private network.
- Read Harness Academy
Applied AI education
Harness Academy
A practical learning platform with distinct paths for builders, solution architects, and technology leaders.
Prototypes and experiments
Smaller builds and open-ended research.
Not every useful system begins as a business initiative. These projects test an idea, solve a narrow problem, or simply make room to learn.
Hobby project
Longhearth
A persistent world simulation where player and NPC decisions reshape shared knowledge and world state across generations—with lineage, houses and families, land, and competing control at its center.
AI writing system
Quill
An AI-assisted macOS environment for planning, drafting, and revising novel-length work—with safe agent collaboration, checkpoints, and Git-backed history.
Interactive algorithm experiments
Thinking in Algorithms
A TypeScript collection that makes algorithmic thinking tangible through responsive 4×4 and 6×6 memory-matching games for solo and multiplayer play, alongside experiments in chess-board diagonals and periodic-table word construction.
Applied neural-network experiment
Neural-network driving simulation
An in-browser driving simulation built without machine-learning libraries. Five distance sensors feed a 5→10→10→4 neural network that decides forward, left, right, and reverse while navigating traffic and road boundaries.