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quality assurance

Diagram of the delivery pipeline in three lanes: Android to Google Play (commit on main, host gate of 44 tests, signed build, emulator smoke on a real device, Play production); iOS to TestFlight (App Store Connect subscription-approval gate, cloud macOS build, build number from Apple); and a daily device round that reseeds four subscription states and reads the screen back by OCR. Beside it, the real screenshot the pipeline pulls off the emulator on every publish.

Mit Håndværk publishes itself to two app stores — and a real phone holds the veto

Mit Håndværk — Danish marketplace app for craft, art and design (mithaandvaerk.dk); Flutter on Android and iOS, Laravel backend
Mobile delivery automation — Flutter CI/CD, on-device acceptance testing, Google Play and App Store publishing

Mit Håndværk is a Danish marketplace app for craft, art and design — a Flutter app on Android and iOS over a Laravel backend, with subscriptions, real-time chat and push. This case is not about the app's screens. It is about the machinery that puts a new version of it in front of users: a pipeline that takes a commit on main and, roughly ten minutes later, has published it to Google Play production — but only after the release has been installed and cold-started on a real Android device and survived it.

The same pipeline covers Apple from a Linux server that cannot build iOS at all: a release tag hands the build to a cloud macOS machine, which signs it and uploads it to TestFlight — and the tag itself cannot be pushed unless the app's subscriptions are actually approved and priced in App Store Connect.

Everything in the picture above is read off the running system: the counters come out of the pipeline's own log, and the phone panel is the screenshot the publish gate pulls off the emulator on every single release.

By Greg Nowak , 19 July, 2026
Illustrated infographic summarizing: Your AI Workflow Needs an Acceptance Test Before It Meets Customers

Your AI Workflow Needs an Acceptance Test Before It Meets Customers

A practical way to test AI workflows using realistic scenarios, tool checks, human rubrics, regression suites, and clear release gates.

Tags

  • AI workflow automation
  • LLM evaluation
  • release governance
  • OpenAI integrations
  • quality assurance
quality assurance

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