Tech stack¶
A summary of the tools and methodologies I work with most often.
Methodologies¶
AI-first development — designing and delivering complete features using Specification-Driven Development (SDD) and AI-assisted tooling.
Agile / SAFe.
Frontend¶
React & Next.js with TypeScript — SPAs, functional components, testing with Testing Library.
Angular — both the MVC model of AngularJS and the MVW model of Angular 2+.
CSS Modules, Formik, react-select.
Languages¶
JavaScript & TypeScript
Python
Tooling & infrastructure¶
Vite, Webpack, Oxlint, Oxfmt
Vitest, Jest, Jasmine + Enzyme, Cypress, Selenium
GraphQL
Backstage + TechDocs
Cloud¶
Cloudflare Pages — hosting and CDN for this site.
AWS — Amazon Chime SDK for real-time audio/video in browser-based applications.
Azure — Azure DevOps for source control, CI/CD pipelines, and work management across enterprise projects.
AI¶
Claude Code — Anthropic’s terminal-based agentic coding tool; primary driver for multi-file refactors and feature work that needs deep codebase context.
OpenAI Codex — cloud-based autonomous coding agent for delegating sandboxed tasks that return as pull requests.
Augment (Auggie) — AI-driven development tool I’ve used end-to-end to deliver features under Spec-Driven Development.
Subagents & agent teams — specialized agents with their own context window, prompt, and tool permissions, coordinated by a main agent for bounded tasks (code review, QA, security, test running).
Skills (
SKILL.md) — reusable instruction packs that bundle instructions, resources, and triggering conditions to shape how an agent behaves for a given task or domain.MCP (Model Context Protocol) — the open standard (now governed by the Linux Foundation’s Agentic AI Foundation) for connecting AI agents to external systems like GitHub, Slack, Notion, and Postgres.
Robotics¶
ROS and ROS2
Gazebo simulation
Reinforcement learning (TD3 for autonomous navigation)
Collaboration¶
Git, GitHub, Bitbucket
Azure DevOps, Jira, Confluence