Uses

AI-assisted development

AI is a daily development multiplier for me — but only because of the infrastructure around it. The tooling below keeps agents aligned with project architecture instead of guessing.

• Cursor

  Primary development environment. Agents contribute directly to commit history for refactoring, testing, and code generation.

• Persistent rule systems

  Domain-specific rule files that act as standing system prompts, constraining agent output to match architecture and standards.

• MCP (Model Context Protocol) servers

  Tool integrations for Git operations, design-to-code, cloud documentation, and browser-based testing — agents work across the full lifecycle in one session.

• Agent skills & plugins

  Skills covering CI monitoring, PR workflows, merge conflict resolution, smoke testing, and code style cleanup.

• Truth-stack documentation

  Structured implementation plans and scoped docs that agents treat as the source of truth — this site was built that way end to end.

Core stack

The technologies I reach for on production work, from database to UI.

• Languages

  TypeScript, JavaScript, SQL — plus Perl and Python where legacy systems live.

• Frontend

  React, Vue, Next.js, Tailwind CSS, Storybook.

• Backend

  Node.js, Express, REST APIs, ORPC with Zod for contract-first type safety.

• Databases

  PostgreSQL (with Drizzle ORM), MySQL, MongoDB.

• Testing & CI

  Vitest, Playwright, React Testing Library, GitHub Actions.

• Infrastructure

  Docker, AWS, GCP, Vercel, Electron for desktop.

Hardware & desk