Practical guides: AI agent harnesses, CI/CD with fastlane, Android builds on a private Linux VPS, and running multiple AI agents in Docker.
Articles are in English.
AI coding agents can write a feature in minutes. The hard part is everything after that: tests, signing, builds and the moment code reaches real users. Here is how I wrap a mobile CI/CD pipeline around agents with fastlane, so they move fast and still can't ship anything on their own.
Long-running AI agents work best on a dedicated machine, not on the laptop you close at night. For Android that machine can be a plain Linux VPS: cheap, always on, and fast enough for Gradle. The catch is reaching it safely. Here is the setup I use: a private WireGuard VPN, where nothing else listens on the public internet.
“Use AI agents” is easy advice. Getting AI-written code to hold up inside a large system is not. The difference is the harness — and most teams don't have one yet.
One AI agent on one task is useful. Four agents on four tasks — while you review the first pull request — is where a remote machine pays off. The trick is keeping them out of each other's way and out of anything they shouldn't touch. Here is how I run several agents side by side with Docker.