Building in AI. Mostly big data - structuring it, then running agents across it.
I build the data layer as much as the analysis. Replicated datasets, cross-source APIs, MCP servers - then swarms of agents on top for due-diligence and anti-hallucination work. Findings that each trace to a real source, or an honest account of what couldn't be established. No vibes, no confident guessing.
Dig puts it all together: a rebuilt Discogs catalog, served over MCP, agents digging through it.
Ran it across a few domains this year: legal AI (a handful of pilots, last six months), plus e-commerce and music.
Sidelines, mostly for my own use, some published: Wario Style (type any song, get the 8-bit Game Boy version), Boss Whisperer, a stack of Claude skills.
Ship fast, across domains. London.
🏆 WAR.MARKET — winner, HyperLiquid London Community Hackathon (Jan 2026)
▸ GhostClaw · ghostclaw.io — a Claude SDK agent that runs on your own machine. Bare metal, no sandbox, autonomous execution. What it feels like with the guardrails off.
▸ Wario.Style — type any song, get the 8-bit Game Boy version. Four channels of raw chiptune, zero samples. (tap through for sound — GitHub won't play it here) · source
A supervised-autonomy workspace and statute-grounded skills that plug into it. Everything here drafts for a solicitor to verify, names the framework it works under, and surfaces the trap before it bites.
Plus a suite of statute-grounded skills across employment and litigation → all repos
Music-tech (Dig, ghost-pattern), a generative London garden, and DeFi (WAR.MARKET, compost) → all repos





