Demos run the real front end against fixture data, not screenshots. Everything here is open source. The writing lives at davidgomez.cc.
An MCP server that turns a five-node Linux fleet into a pool of AI workers. 21 typed tools, quota-aware routing across three cloud providers and a local open-weight model, and jobs serialised by the resource they touch rather than the machine that runs them.
A self-hosted photo culler with its own ML pipeline: face clustering, scene and aesthetic scoring across roughly 80,000 frames, all running on owned GPU hardware. The demo is the real front end over a hand-authored fixture, so it behaves exactly like the logged-in app.
The operator surface for Tower: live node health, running and finished agent jobs with the evidence each returned, and tiered retrieval over a private corpus — summary cards first, a separate vector index second, raw sources only for an audit.
A self-hosted job application tracker. A browser extension captures a posting into structured fields as you look at it, normalises inconsistent markup through a per-site adapter registry, and writes into a versioned SQLite schema. Local-first, because that record is not data to hand to a third party.
A study and credential workspace that answers “what should I study next” from recorded progress rather than a static plan, pairing a durable milestone store with a corpus-and-coaching engine behind one authenticated origin.
A house-hunting workspace built on immutable capture. Listing sites edit and pull their own pages, so every capture is archived as evidence first and the comparable-property database rebuilds from it. A delisted property keeps its record.