Beyond the Resume

Hobby & Continued Learning

Outside the Workday

Star Wars Galaxies and SWGEmu were a huge early spark for me. I went from hosting a local emulator server to building custom content, web tooling, and auth flows around game data for a community of 50+ daily active players.
That same curiosity shows up in the AI projects I build for fun today, especially when I can blend systems thinking, personality design, and full-stack product work.
I naturally gravitate toward projects that feel playful on the surface but still involve real architecture, retrieval, orchestration, or interface design underneath.

Personal AI Side Quests

A couple of hobby projects that feel especially “me” because they blend games, AI, and product thinking.

Personal AI project

AI Quest System for WoW Players

Personalized AI quest generation for World of Warcraft players

Built around player preference inputs like zone, faction, reward goals, and whether the experience should favor lore, rewards, or leveling speed.

Personal AI project

SoloCode

Offline-first coding assistance platform PWA for Apple Silicon Macs

I built SoloCode as my own coding assistance platform PWA for Apple Silicon Macs, similar in spirit to tools like Codex or Claude Code, but designed to work locally and stay useful even in more restricted or offline-first environments.

At a high level, it combines local coding models, a management dashboard, MCP-backed code and knowledge retrieval, persistent session memory, and an OpenAI-compatible proxy so different coding clients can all plug into the same local intelligence layer.

What I'm Leaning Into

Current focus

I’m intentionally growing toward roles where I can pair hands-on engineering with architectural leadership, especially across AI-native products, full-stack platforms, and technically ambitious teams. AI, blockchain, and full-stack development remain the areas I’m most excited to keep pushing forward.

Learning style

I communicate in a direct, collaborative, and low-ego way. I like to stay close to the work, mentor through pairing and practical feedback, and help teams make thoughtful technical decisions without overcomplicating things. Strong opinions loosely held, and the best engineers are lifelong learners are two of my favorite sayings.

Udemy Course Summaries

A compact log of AI courses I've completed, with project work and core takeaways I can keep building on.

Projects Built

1
AI-powered brochure generator that scrapes and navigates company websites intelligently.
2
Multi-modal customer support agent for an airline with UI and function-calling.
3
Meeting-minutes and action-items generator from audio using open- and closed-source models.
4
Python-to-optimized-C++ conversion workflow that demonstrated a 60,000x performance boost.
5
RAG-powered AI knowledge worker that becomes an expert on company-related matters.
6
Capstone Part A: frontier-model price prediction from short product descriptions.
7
Capstone Part B: fine-tuned open-source model to compete with frontier models on price prediction.
8
Capstone Part C: autonomous multi-agent deal hunter that spots bargains and sends notifications.

What I Took Away

Compared the latest performance-improvement techniques for LLM systems, including RAG, fine-tuning, and agentic workflows.
Evaluated leading frontier and open-source LLMs to choose the best model for a given task.