AI in production, under governance.

What I run

A standing fleet of 13 agents does the research, building, publishing and measuring across 14 ventures. 12 of them have a live product. One operator, no employees. The counts are read from the same registries this site builds from, so they cannot drift from what you see on the ventures page and the agents page.

How it is governed

1. Money going live — payment wiring, pricing changes, payouts, refunds, new paid seats or plans.
2. Auth and secrets — never create, rotate or commit a credential; write the code that reads an environment variable and leave the value to a human.
3. External sends and posting — email, DMs, social posts, anything that contacts a third party in your name.
4. Scheduled automation — creating, disabling or rescheduling anything that will run without a person present.
5. Destructive or irreversible change — deleting data, DNS and domain changes, production migrations.

Everything else is allowed without asking. Every item handled is written to an append-only ledger with its status — built, partial, escalated or killed — and nothing counts as done until a check has run. The whole model is published as an open AI Governance Playbook.

AI at organisation scale

At NoOnes, a digital-asset trading platform with 2M+ customers, I rolled out AI-driven programmatic SEO in summer 2025: an LLM pipeline that generated and localised 4,000+ landing pages in 8 languages. Before that: a decade of large-scale programmes at Nokia and Microsoft, and CMO of two KYC-regulated fintech platforms (8M+ and 2M+ customers) with P&L ownership — which is why I start every rollout with what the data rules allow.