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The article is an internal engineering write-up about running AI coding agents in remote environments so they can build and test iOS and Android apps in parallel, without tying up developer laptops. For AI readers, the useful signal is the shift from one-off assistant use to delegated, autonomous work (builds, tests, CI triage, PR feedback), with the bottleneck moving to compute and tooling. The claims are self-reported and unquantified, so the real test is how reliably such agents handle failures without supervision.
Surse care acoperăShopify Engineering Blog, arXiv, AWS, Latent Space
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We gave AI agents a mobile dev environment

Shopify Engineering Blog9 min de cititArticolul și perspectiva sunt în engleză.

We built agentic workflows to tackle mobile development tasks in parallel, but quickly hit the limits of our development machines. Just three or four workflows were enough to max out a laptop, with compilers, simulators, and emulators competing for resources. And we had to keep it awake. If someone accidentally closed a laptop lid, the work stopped. Our web and backend teams were already using River (our AI agent in Slack) to work without tying up their development machines. We needed the same thing for mobile. But River ran on Linux: it could edit Swift, but building and testing the iOS app still meant going back to the same laptops we’d already maxed out. Our ability to delegate work had outgrown our ability to run it. So we built Remote Dev. Two constraints: too many builds sharing one Mac, or missing iOS tooling on Linux. With Remote Dev, we're no longer limited by how many builds and simulators our laptops can handle. Each River session gets its own environment, so we can have one agent debugging something on Android, another working on an iOS feature, and another testing a…

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