About

Hi, I'm Antonin.

Staff Engineer building AI-backed systems, engineering standards, and the workflows that let teams ship serious software.

Staff engineer focused on the infrastructure production LLM systems run on: evaluation harnesses, multi-provider dispatch, rate-limit handling, and guardrails on model output.

Years building: 20+
Blogging since: 2012
GitHub stars: 600+

LinkedIn GitHub

Portrait of Antonin against greenery — 4-tone dither · 30 KBoriginal 116 KBsaves 86 KB

§ 01See the proverbs project →

Principles

A deployed MVP is worth two prototyped.
Dance like nobody is watching, code like everybody is.
Today's fashion is tomorrow's legacy.
Debugging becomes easier if you first admit that you are the problem.
The best code is no code at all.

§ 02

Antonin hiking in Colorado — original · 8 KBalready smaller than its dither, so served as-is and only tinted

Beyond Code

The rest of the operating system

Photography
I shoot animals, landscapes, people, and street scenes. The camera is how I stay observant.
Fiction
I write AI-themed fiction and short stories when technical writing is not enough.
Podcasts & Games
I have opinions about Final Fantasy, narrative design, and the overlap between games and technology.

§ 03

What I work with now

Capabilities

The stack changes. The throughline doesn't. I'm usually working where backend systems, product delivery, and AI workflows collide.

AI & LLM Systems
Measuring model output, routing it across providers, and trusting none of it by default.
LLM Evaluation & Judge GradingMulti-Provider LLM DispatchToken Budgeting & Rate-Limit EngineeringStructured Output & GuardrailsModel Context Protocol (MCP)Agent Tooling & Orchestration
Languages
Python on the backend, TypeScript for everything else, SQL wherever the data lives.
PythonTypeScriptSQL
Platforms & Tools
Async services on Kubernetes, databases picked per job, front ends in React or Svelte.
FastAPIRedisPostgresSQLiteKubernetes on AzureReact & Next.jsSvelteKit
Leadership
Setting technical direction and standards, then reviewing what ships against them.
Technical StrategyEngineering StandardsCross-Team DeliveryCode ReviewMentoring

§ 04

Selected work

Work	Kind
cc-dash	TypeScript · Model Context Protocol
Skillbox	Claude Code · Agent tooling
Agent Compiler	CLI that embeds agent skills into CLAUDE.md and fails CI when the embedded content drifts.
Using Git Worktrees to Parallelize AI Agents	Writing
17 Side Projects I Built With Claude Code in Two Months	Writing
Programmer's Proverbs	680 stars

I help teams implement AI-enabled product work, sharpen engineering practices, and build systems that survive real usage.

Get in touch →