AI-native engineering, where agents are colleagues — not chat windows.
I build engineering organizations where AI agents do real work — reviewing code, writing docs, operating desktops, running deployments — each with its own identity, policy and audit trail. The infrastructure underneath is sovereign by design: the keys, the data and the record belong to the people running it. Before that, a couple of decades of security work for people who learned the hard way what dependency costs. This site is a working notebook and a home for the systems I ship.
Current areas of work
Designing the environments agents do their best work in: semantic interfaces, deterministic context, closed feedback loops.
Autonomous agents as accountable colleagues — real cryptographic identities, policies, and audit trails, and no raw keys.
What agents need to remember — reference truth, episodic recall, institutional doctrine — as separate, provenance-tracked services.
Deployments, review and shared state as signed events on infrastructure you own — platforms optional.
- 01Agents that keep their promises
Give an agent a memory and it gets smarter. Give it commitments and it gets character.
- 02Notes on writing here
Why this site exists, what it contains, and a confession about how it started.
- 03Nostr as an engineering substrate
Not a social network — a signed, portable event log I run my whole stack on.
- 04Zero-Trust identity for AI agent fleets
What MCP doesn't give you for free
A Nostr-native deployment and runtime control plane. It tracks your builds, deploys your containers, and tells you when something goes wrong.
A NIP-46 Nostr bunker for agent fleets. Every agent gets an identity; no agent ever sees a private key.
Automated code review for NIP-34 Nostr repositories. Local LLMs read your patches; nothing leaves your infrastructure.
- Autonomy is earned
An authority model for agent fleets: promotion by boring reliability, demotion at the speed of doubt, and a break-glass lever for 2am. Draft.
- The sovereign engineer
On owning your tools, your keys, your data, and the systems that shape your work. Draft — being rewritten from the actual practice.
- Agent experience
The environments agents work in matter more than the models working in them. Notes toward a discipline. Draft.
Available for talks on building AI-native engineering organizations, agent experience, and running fleets of AI agents you can actually audit.
Speaking →Most of what I build ships as an open repository — and much of it was built alongside the same kinds of agents it exists to support.
GitHub →