Case Study · Building with AI

One designer, the whole stack.

For seventeen years I designed the systems behind games like Star Wars: Galaxy of Heroes and Marvel Strike Force. Then the industry’s AI wave moved the ground under all of us. Instead of waiting it out, I sat down with the same tools and learned to direct them — and shipped more, solo, than I thought one person could.

Context
Solo · ~1 year past full-time games
Role
Designer as director
Stack
Vanilla JS · Neon · Supabase · Cloudflare
Tooling
Claude Code as the engineering team

The situation

The mobile games industry that employed me for most of two decades got hit hard — contraction, layoffs, and an AI shift that has a lot of brilliant people scared for their craft. I was out of a full-time seat for a while (partly the market, partly a deliberate choice to be home with two young kids). The easy move was to treat AI as the thing that came for my job.

I made the opposite bet: that the tool that disrupts a craft is also the best thing that ever happened to anyone who can direct craft. So I stopped reading about it and started building with it.

What I set out to prove

  • That a designer who can’t hand-write a backend can still ship one — by directing, not typing.
  • That seventeen years of systems judgment transfers directly to working with AI.
  • That “solo” doesn’t have to mean “small” anymore.

The approach — direct it like a team

I’ve spent my career telling engineers and designers what “good” looks like and reviewing until it got there. It turns out directing a model is the same job: set the vision, define done, hand over the problem instead of the steps, then review hard and own the calls it can’t make.

So I built a system for it — a personal operating system with specialist roles (capture & planning, building, research) running over a Markdown knowledge graph that gives the AI persistent memory across sessions. The guardrails are borrowed from good engineering culture: think before coding, build the simplest thing, make surgical changes, work toward a definition of done. The skill that carries the whole thing isn’t syntax. It’s decomposition, taste, and knowing the moment an answer is wrong.

I’d spent a career telling a team what “good” looks like and reviewing until it got there. Directing a model turned out to be the same job.

What I built

A self-governing personal OS

A three-agent system over a structured knowledge base that plans my week, keeps a journal, runs research routines, and remembers context between sessions instead of starting cold each time. It’s the workbench everything else gets built from — and proof that I think in systems and operating models, not one-off prompts.

An 11-game web arcade

A scatter of prototype game repos, consolidated into a single deploy with a gallery front end and one clean home for everyone to play. Midway through, the platform blocked the obvious path; rather than stall, I had the build re-route its own architecture — repurpose an existing home, re-point everything, ship. Turning a hard constraint into a one-move workaround is the same instinct I’ve always brought to design.

A card-game engine with live multiplayer

Multiplayer Deck Gateway — a browser workshop where card games are modules on one shared engine: a real 52-card deck, a poker hand evaluator, and host-authoritative networking. A dozen games and design tools plug in, and any of them can be dealt to friends live over a room code. Where the arcade was the content, this is the platform underneath it — the clearest proof that I build the systems, not just the things that run on them.

A private backend control plane

Auth, databases, and infrastructure across Neon, Supabase, and Cloudflare Workers for a handful of projects — unified behind one private “control plane” with a strict no-secrets-in-git discipline and a registry that maps exactly where every credential really lives. I ran a security pass on my own repos in the process and closed the gaps I found.

What actually made it work

  • Judgment over syntax. The muscle that balanced a 200+ character roster — decompose the problem, define done, review for correctness, decide under ambiguity — is the exact muscle that gets good work out of a model.
  • Systems thinking as the unlock. The reason I could direct a backend I couldn’t hand-write is that I understood the shape of the system and could tell when the pieces were wrong.
  • Honesty about the edges. I’m a director and a systems designer, not a from-scratch software engineer. I know what good looks like, and I can get a model there fast. In this era, that’s the job.

Where this points

The next era rewards the people who can aim these tools with taste — who can turn intent into shipped systems and tell the difference between impressive and correct. I want to do that work, and I especially want to help the people whose industries are being remade (the way mine was) learn to wield it instead of fear it. Whether that’s a studio of my own or a team building this future, it’s the same craft I’ve practiced for seventeen years — pointed at a new kind of collaborator.

AI-Native Building Systems Thinking Multi-Agent Solo → Shipped

Written as a portfolio piece. The build was solo, recent, and real — some systems are private, and I’m happy to walk through any of them live.