Selected projects

Products, platforms,
and better ways to deliver.

Practical examples of my product judgment, technical depth, and approach to AI-assisted delivery. Each project explains my contribution and its current stage.

Explore my full skills profile
Independent work

Products I’m building.

Hands-on work from product strategy and requirements through implementation and validation.

Independent product buildActive development · Cross-platform alpha

RepQuest

A privacy-first sports learning game that adapts to each player’s age, experience, and progress. The 23-sport platform combines guided playbooks, real-game clips, interactive challenges, and meaningful progression across web and mobile.

My contribution

I own product strategy, requirements, experience architecture, content and data modeling, privacy design, and hands-on implementation. I use AI-assisted development, then validate the work through code review, automated checks, and TestFlight releases.

What this demonstrates

  • End-to-end product execution across web and mobile
  • Reusable learning architecture spanning 23 sports
  • Privacy and parental-consent system design
  • Adaptive learning, mastery, and progression
Read the project details

The problem

Teach the complexity of sports across ages and experience levels without reducing learning to generic trivia or collecting unnecessary information from younger players.

My approach

Designed a reusable content model and game engine with adaptive remediation, concept-level mastery, XP, streaks, badges, and age-aware pacing. Added real-game media and beginner guidance, built an Expo and React Native mobile companion, and designed Cloudflare D1-backed accounts, parental consent, privacy events, progress sync, and safe-league architecture.

Skills & tools

  • React
  • TypeScript
  • Expo
  • React Native
  • Cloudflare D1
  • API design
Try the TestFlight beta (opens in a new tab)Read the product requirements (opens in a new tab)View the source on GitHub (opens in a new tab)
Independent product conceptActive development · Functional alpha

AI Quality Intelligence

A local-first product concept that connects code changes to affected business behavior, related tests, regression guidance, and release risk through explainable analysis.

My contribution

I built the React and TypeScript alpha, shaping the product around deterministic analysis, source tracing, test discovery, and explicit human review controls.

What this demonstrates

  • Strongly typed application design
  • Explainable risk modeling
  • Automated verification
  • Release decision-support architecture
Read the project details

The problem

Reduce repetitive quality-assurance effort while giving teams enough evidence to make consequential release decisions.

My approach

Connected code-change analysis, source evidence, and test discovery in a privacy-conscious local workflow. Kept the reasoning visible so people can review the release guidance and decide what to do next.

Skills & tools

  • React
  • TypeScript
  • Change-impact analysis
  • Evidence tracing
  • Automated testing
Enterprise initiatives

Improving how teams work.

Internal projects described at a high level, with clear ownership, adoption, and maturity.

Internal ProjectWorkflow adopted · Automation pilot pending

Requirements-to-Delivery Workflow

An internal operating model that keeps requirements, delivery work, scenarios, design artifacts, and change history aligned as decisions change.

My contribution

I created the workflow, gained program adoption, and originated the automation idea. I defined the change taxonomy, source-of-truth rules, approval path, safety guardrails, and two-phase automation concept. The automation has been developed and locally tested; live pilot validation is pending.

What this demonstrates

  • Program adoption of the operating model
  • Human approval before controlled changes
  • Requirements-to-delivery traceability
  • Explicit automation safety guardrails
Read the project details

The problem

Requirements and delivery artifacts can drift apart as decisions change, creating rework, unclear ownership, and downstream risk across teams.

My approach

Designed a flow to detect, validate, propose, approve, apply, and verify changes. The model distinguishes requirement changes from defects and routine updates, prepares traceable proposals, and requires human approval. Safeguards address conflicts, stale proposals, ownership, many-to-many impact, and automation loops.

Skills & tools

  • Requirements governance
  • Change-impact analysis
  • AI agent design
  • Git workflows
  • Gherkin
  • Human review
Internal ProjectImplemented and in use

AI-Assisted Delivery Preparation

Five coordinated agents that turn complex requirements into review-ready delivery packages: finding gaps, decomposing features, preparing documentation, and connecting test scenarios.

My contribution

I designed and built the agent system, including the roles, sequencing, review controls, documentation outputs, and traceability model. It is now used to prepare complex delivery work, with people reviewing the output and approving decisions.

What this demonstrates

  • Five-agent workflow in active use
  • Consistent delivery-preparation outputs
  • Human review and approval retained
  • Requirements-to-test traceability
Read the project details

The problem

Manual delivery preparation could take weeks and still leave engineering, design, and quality teams resolving gaps late in the process.

My approach

Coordinated five specialized agents around shared requirements, with checkpoints for missing decisions, conflicts, independently testable work, engineering and design documentation, and connected Gherkin scenarios.

Early result An early comparison suggests preparation for comparable work decreased from about four weeks to one week. This is an initial estimate, rather than a formal measurement.

Skills & tools

  • AI agent orchestration
  • Requirements analysis
  • Gherkin
  • Documentation systems
  • Human review
Internal ProjectDeveloped and in use

Portfolio Delivery Intelligence

A self-service platform that brings multi-team progress, trends, dependencies, and planning signals into one view, with links to the underlying delivery evidence.

My contribution

I co-developed the platform, shaping its product model, planning and reporting experience, shared delivery definitions, validation rules, and executive decision context while partnering on implementation.

What this demonstrates

  • Operational self-service platform
  • Standardized delivery definitions
  • Cross-team dependency visibility
  • Automated validation and performance controls
Read the project details

The problem

Delivery signals were spread across teams and tools, making progress, dependency, and planning conversations slower and harder to validate.

My approach

Combined source integrations, standardized progress definitions, flexible reporting periods, automated validation, caching, and performance controls to support a consistent view of delivery health.

Skills & tools

  • React
  • GitLab APIs
  • Portfolio analytics
  • Data validation
  • Caching
  • Delivery planning
More context

The experience behind the projects.

See the enterprise roles, integration decisions, and measurable outcomes that inform how I build.

View my experience