Automating Mobile QA with Cloud Agents

Explore an agentic QA workflow targeting 30% less manual effort across mobile, web, and TV, with test selection, failure triage, and validation.

Use Appduct to give AI QA agents access to app functions for setting test conditions, triggering events, and checking results with UI automation.

See how e2e uses agent-device for AI-driven iOS and Android tests, combines exact assertions with agent actions, and replays cached steps without model calls.

Szymon Rybczak explains how TesterArmy tests web and mobile apps with AI agents, creates test plans for pull requests, and fits into QA workflows.

Code review and green CI checks do not prove a mobile app still works. Learn how cloud agents, agent-device, and runtime evidence can verify app behavior before merge.

AI can increase code output faster than teams can verify the real app. See why behavior review matters before merge.

Sniffler maps changed files to affected E2E tests, so teams can avoid running the full suite on every pull request.

Zack Ebenfeld joins React Universe On Air to talk about how AI is changing React Native workflows, testing, QA, and day-to-day engineering work.

Agent React DevTools gives AI agents access to the React component tree, state, and performance data, enabling deeper debugging and more reliable QA for React and React Native apps.

A discussion on Agent Device, AI-driven workflows, and testing mobile apps using simulators and accessibility data.

Learn how React Native Harness bridges the gap between mocking and E2E testing: real device tests, full native access, Jest-style simplicity.

This episode of the React Native Show dives into the recent introduction of End-to-End (E2E) testing in RNTester. Join us as we unpack the thought process, technical considerations, and practical implementation of this new approach to testing in React Native.

Learn how React Native AI uses a unified provider model to switch between cloud and on-device LLMs without rewriting application logic, enabling reliable AI experiences online and offline.

Learn how on-device models in React Native can call tools, interact with external APIs, and return structured outputs you can use directly in application logic.

Learn how to run third-party on-device LLMs in React Native using MLC LLM. Choose your models, run them efficiently across platforms, and keep a unified JavaScript API with React Native AI.

Learn how to use Apple’s built-in Foundation Models in React Native apps, reduce memory usage, and enable fast, fully on-device AI with React Native AI Apple.

Learn why on-device AI matters for React Native apps, how local LLMs behave offline, and what problems React Native AI is designed to solve from day one.

Learn how to implement a React Native TurboModule on Android, from the TypeScript spec and Codegen to the Kotlin implementation and package registration.

Learn how JavaScript, native module, background, and main threads interact in React Native TurboModules, and how to use GCD queues to run async work safely in Swift.

Learn how to expose typed, immutable constants from a Swift TurboModule using Codegen, and get full end-to-end type safety between native and JavaScript.

Learn how to emit native events from a Swift TurboModule and subscribe to them in JavaScript, including proper memory management and Codegen integration.

Learn how to build a fully working TurboModule in Swift, integrate it with Codegen, and bridge it through Objective‑C inside an Expo app.