01Independent product buildActive development · Cross-platform alpha
RepQuest
A privacy-first sports learning game that adapts the playbook to each player’s age, experience, and progress.
A 23-sport learning platform for responsive web and mobile that combines guided beginner playbooks, real short-form game clips, sport and position pathways, interactive challenges, and meaningful progression.
My ownershipI own the product strategy, requirements, experience architecture, content and data modeling, privacy design, and hands-on implementation across React, TypeScript, Expo, and React Native. I use an AI-assisted development workflow, then validate the result through code review, automated checks, and TestFlight releases.
ChallengeTeach the complexity of sports across ages and experience levels without reducing learning to generic trivia—or collecting unnecessary information from younger players.
ApproachDesigned a reusable React and TypeScript 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; unified the experience with an Expo and React Native mobile companion; and designed Cloudflare D1-backed account, parental-consent, privacy-event, progress-sync, and safe-league architecture.
What it demonstratesEnd-to-end cross-platform product execution
Reusable 23-sport learning architecture
Privacy and parental-consent system design
Adaptive learning, mastery, and gamification
ReactTypeScriptExpoReact NativeCloudflare D1API designPrivacy-first architecture
02Independent product conceptActive development · Functional alpha
AI Quality Intelligence
Release intelligence designed around explainability, traceability, and human judgment.
A local-first product concept exploring how engineering teams can connect code changes to affected business behavior, related tests, regression guidance, and release risk through explainable automation.
ChallengeReduce repetitive quality-assurance effort without turning consequential release decisions into a black box.
ApproachBuilt a privacy-conscious React and TypeScript alpha with deterministic analysis, source tracing, test discovery, and explicit human review controls.
What it demonstratesStrongly typed application design
Explainable risk modeling
Automated verification
Release decision-support architecture
ReactTypeScriptChange-impact analysisEvidence tracingAutomated testing
03Internal ProjectConcept exploration
Engineering Analytics Platform
Multi-repository activity translated into operational intelligence for engineering leaders.
A React-based platform concept designed to analyze activity across multiple GitLab repositories and make delivery health, development activity, defect trends, and status insights easier to see.
ChallengeGive engineering leaders a coherent view of delivery signals spread across multiple repositories.
ApproachExplored GitLab API integrations, caching strategies, data persistence, and evidence synthesis to convert repository activity into operational reporting.
What it demonstratesCross-repository analysis
Delivery-health reporting
Caching and persistence strategy
AI-assisted insight generation
ReactGitLab APIsData persistenceCachingEvidence synthesis
04Internal ProjectDelivered enterprise initiative
Engineering Knowledge Platform
Searchable documentation that reduced tribal knowledge and improved onboarding.
An engineering documentation modernization initiative built with MkDocs and automated delivery practices.
ChallengeCritical technical knowledge was difficult to discover, creating friction for onboarding and day-to-day delivery.
ApproachBuilt a searchable MkDocs platform with CI/CD deployment and led the migration of technical requirements from Agility to GitLab.
What it demonstratesSearchable knowledge architecture
Automated documentation delivery
Standardized technical requirements
Improved portfolio visibility
MkDocsGitLabCI/CDInformation architectureDocumentation