e2e by TesterArmy
End-to-end testing framework where you describe a goal in natural language and an agent drives the app to reach it, with decision-model executors and replay that avoids repeat model calls.
Why it matters
Mixes agent-driven actions with classic locators/assertions in one test file, and replays recorded agent runs without new model calls until the app changes.
What you could build with it
A small SaaS team could replace flaky selector-based browser tests with e2e's hybrid approach, letting the agent handle UI drift while deterministic assertions verify billing-critical flows, cutting test maintenance time while keeping checkout confidence high.
Does it hold up?
Works in practice: an independent migration of 302 existing tests passed with real AI assertions, actions, waits, and extraction. Caveat: AI steps run ~9.5x slower than deterministic checks and cost ~$2 per full suite run, so keep exact locators for stable elements.
Built with e2e by TesterArmy
- AI-Powered Testing: Introducing e2e Frameworkarticle · Hands-on migration of a 302-test Playwright suite to e2e with measured costs: 303 tests passing, ~$2 per fully AI-driven UI run, ~0.7 cents per AI assertion, 9.5x slower runtime than deterministic checks; runnable demo on GitHub.
- New open-source testing framework just changed everythingyoutube · Animated explainer walking through the README's billing-upgrade example: a renamed button breaking a selector, the agent finding the new button, and replay avoiding repeat model calls.
- LambdaTest/e2egithub · Fork of tester-army/e2e adding a @e2e-dev/testmu package for hosted Android emulators, iOS simulators, and real devices in the mobile engine.
Learn more
First spotted on github: source.
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