Jose Antonio Licon · Pittsburgh, PA

One person.
Many very different projects.
One engine.
Shipping constantly.

I build apps, games, and platforms — powered by an AI development system I built myself. Product manager and engineer, open to consulting.

Get more from AI →See the workThe engine →

Xanadu isn't an AI assistant. It's an .

Not “Antonio uses AI to help him code” — an unattended system that plans the work, writes the code, tests it, and fixes its own mistakes, then brings back only the decisions that need a human.

Most people describing AI-assisted development mean : a smarter autocomplete with someone at the keyboard. This is categorically different. Nobody is at the keyboard.

The apps below aren't just products. They're the benchmarks.

That's Xanadu. How it works →

What could it do for your team? →

Projects

The engine

Xanadu

An that compresses two weeks of work into two days of wall-clock time. Here's how it works.

Xanadu architecture: a task backlog runs through four local model tiers, escalating to Claude only when stuck; failures and fixes feed a shared learning store; the same engine scales from a solo Mac to parallel workers to rented cloud GPUs.
Automation, learning, and scaling run as one loop. Click to enlarge.

Tasks completed autonomously

1,200+

First-pass success rate

70%

Commits in the last 30 days

581

From the task logs and git history across 21 of the last 30 days; updated 2026-09-27.

The loop

A turns a into small, testable . An executor writes each change. A validator runs and the task’s own — nothing counts as done until they . Failures are classified, fed back into the next attempt, and escalated if they keep coming. All state lives in the roadmap and , so a run survives being stopped and picks up where it left off.

The ladder

Every task starts on , on . Day to day, that’s a Mac running a coding model through Apple’s — and in practice it handles nearly everything. For big sprints it scales out to : one rented or many, each running agents , with headroom for larger models if a job ever calls for them; most of Galaxican’s 600+ tasks ran that way. Claude sits at the top, reached only when a task has beaten every open-model , so compute goes to the problems that genuinely need it. Gemini is the outside voice: I consult it for creative work and as a sanity check on what the loop produces.

Swappable by design

Every rung of the ladder is a setting, not a rewrite. Each tier names a model, and swapping one in — a newer release, a bigger dense model, a small fast one, a coding specialist — is a config change. When a better open model ships, Xanadu gets better the same day.

It learns

A immune system blocks mistakes it has already seen. A loop turns repeated fixes into permanent rules shared across every machine. And a of every task shapes what gets planned next.

In practice

ProjectsDash

From an idea to a working tool in under three days

I woke up with the idea, had a quick chat with Claude to shape a , and pointed Xanadu at it. On a single Mac, with a and no cloud bill, it worked through the roadmap largely unattended. Then I polished the rough edges with Claude.

first to finished roadmap
2.75 days
roadmap tasks done — 35 by Xanadu
49 of 49
lines of , with test suites
4,455
cloud compute: one laptop
$0
See ProjectsDash →

Galaxican

Scaling out when the roadmap is big

Galaxican is where Xanadu was proven and hardened. For its biggest push, the same loop scaled out to on a rented — capacity that costs a few dollars an hour — and the game shipped to both app stores.

tasks completed autonomously
626
passed on the first attempt
483
for the parallel
2 weeks
App Store and Google Play
2 stores
See Galaxican →

Want a loop like this for your team or your product? Get more from AI →

Why I built it

I started where everyone starts — Claude, Gemini, the usual suspects. I was amazed at what was possible. Then I ran out of .

Most people slow down at that point. I bought a maxed-out MacBook Air and started learning instead.

What began as a workaround turned into something more interesting: a complete development loop. Product ideation. analysis. generation. Code execution across . Models that fail over to more capable when a task is too hard. Error patterns that get learned and encoded so they don't burn retries twice.

Now I set it running overnight. By morning, the project is mostly done. When I need more firepower, I spin up and the backlog burns down in parallel, at a cost that doesn't require a VC.

It didn't replace the craft — my background as a full-stack developer and technical product manager is what makes the system work, not what it replaced. I still drive. I still take the wheel when the models hit a wall, or the project needs a pivot. methodology is the backbone of the whole system — not just a buzzword, but the actual structure that keeps every project on this page moving at once.

This isn't a silver bullet. It's a superpower.

Background

Product manager and engineer — I write the , and I build the thing it describes.

Before Xanadu, I spent my career on both sides of the product line: as a product owner and manager setting direction, and as the web and mobile developer shipping the code. That work spans podcasting, public media, higher education, 3D software and games — including live-audio apps and Alexa skills for Pittsburgh public radio.

Xanadu is what happens when those two jobs meet: product discipline, encoded into a system that does the building.

Product and technical leadership roles with

  • Libsyn
  • SoundStack
  • Autodesk
  • University of Pittsburgh
  • WYEP 91.3 FM
  • Wild Pockets
  • Asia City Media Group

More on LinkedIn and GitHub.

Want that on your team? Get more from AI →

Consulting

Get more from AI.

I turn product people into builders, and help dev teams ship more — and better — with AI. ProjectsDash started as an idea one morning — and was working software three days later.

I spend most of my time building and traveling, so I'm not looking for a full-time role. I take on a few focused engagements at a time.

For product leaders

Turn your roadmap into running software

For technical , product leads, and founders. I help you set up a development loop and learn the workflow I use: shape a with a , hand the bulk of the build to an , then polish with an . You stop waiting on a queue and start shipping your own ideas.

For dev teams

A measured , not a promise

For engineering leaders. We baseline one team’s , , and , set up the loop on your real — with as the for “done” — and compare after about six weeks, with a first read at two. You keep the setup and the numbers either way.

For existing codebases

Modernize without the big rewrite

Clean up, extend, port, or re-architect an existing codebase — splitting out services where it actually pays, not because it’s fashionable. We start with an assessment and a that pins down what the code does today, then the loop modernizes it in small, tested steps, and your code stays on . Proven in Dart, TypeScript, Python, and Go; older languages welcome, COBOL included. If yours is new to the system, I’ll prove it out on a small project first, on me.

A side effect: most of the work runs on on hardware you control, so your AI bill grows far more slowly as you add developers.

What happens after you hire me, step by step: how I build software →

Book a 30-minute callor email dev@spyderboy.com