AI doesn't change what hard engineering leadership looks like — it just makes weak engineering leadership more expensive.
I lead engineering on a regulated cross-border payments program. I build open-source infrastructure for AI agents that touch real systems — Approva, Codencer, Rhodd. I write here when something I've seen often enough becomes worth naming. Sixteen years inside engineering teams, eight of them leading.
Recent short pieces.
One task in my workflow can be researched in ChatGPT, implemented by Codex, challenged by Claude, and updated through MCP.
Most project tools still assume every participant is human, which leaves someone acting as the relay between chats, repositories, decisions and the board.
Read →I can run several agents in parallel — that does not mean I should let all of them think before I do.
Judgment is partly built in the uncomfortable phase before the options arrive, which is exactly the phase parallel agents remove.
Read →A conversation that follows you across devices is a feature — authority that follows it is a security decision.
Portable agent sessions carry two things at once: context, which should travel freely, and authority, which was granted for a specific action in a specific state.
Read →Essays worth the time.
Infrastructure I'm building.
Human approval for risky AI agent actions — with passkey identity, scoped capabilities, and a verifiable audit trail.
A persistent daemon that manages, executes, validates, and audits tasks performed by external coding agents.
Turns architecture definitions into production-ready code, infrastructure, and CI/CD pipelines. Zero boilerplate.
Things outside the day job — music, mentoring, a book in progress, older essays.
Engineering is not the only thing I think about. The Elsewhere page collects the parts of my work that do not fit a portfolio frame — a progressive metal project, mentoring work at h.careers, a Russian-language book on career growth in IT, older essays.
Visit Elsewhere →