I'm Aleksei Papushin — a DevOps architect who builds and runs production systems, and trains engineering teams to use AI coding agents where it actually counts: in production, under real constraints.
It usually starts the same way — a team that wants AI in its engineering workflow, and someone who has actually shipped with it under production constraints, not just talked about it.
Hands-on programs that take your engineers from cautious to fluent with Claude Code and AI coding agents — on your repos, your stack, your review standards. Where agents earn their keep, where they don't, and how humans stay in control of merged code.
Architecture and review for systems running real workloads: infrastructure, delivery pipelines, reliability, and cost. The discipline I use to design and operate production systems solo, applied to your teams — pragmatic, reversible, cheap to operate.
Advisory for leaders deciding how AI fits the delivery pipeline. We design the guardrails and team habits that make agentic workflows safe to adopt at scale — so the productivity gain survives contact with your codebase.
The teams that win with AI aren't the ones that prompt the hardest. They're the ones who know exactly what to delegate, what to review, and what to never hand over.
I teach AI-assisted engineering because I use it to ship. Here's the work that backs the advice.
Cloud cost control for dev and staging. Architected and built solo: a Python platform where teams lease AWS and GCP machines for a fixed window over Slack, Telegram, or web — the VM auto-stops when the lease ends, and every shutdown stays a human decision.
Visit idlefy.comAn interactive course that teaches engineers to work with AI — Claude Code as the primary tool, from install to running a team of agents.
Ask about accessTraining, architecture, or a straight second opinion on your AI strategy. Tell me what your team is trying to do — I'll tell you honestly whether and how I can help.