AI-powered testing platform. Write tests in plain English, run them everywhere.
Developers
The rule "never test in production" comes from an era when production was a black box — no observability, no rollbacks, no feature flags. Netflix deliberately kills EC2 instances in production to test resilience. Google tests new search algorithms on 1% of live queries. The real rule is: never
QA Engineers
A Reddit thread in r/QualityAssurance asked a simple question: "Is anyone successfully using gen AI in their QA?" The responses told the real story — not the one you see in tech press. Most teams are experimenting. Few are shipping. The chasm between what media reports and what
Test Automation
Every feature your users love is held together by API calls you never see. When one of those calls fails silently, your frontend shows stale data, your mobile app crashes, and your users think it's a bug in the UI. API testing catches the real failures — before your
Testing Strategy
Your scripted tests cover every scenario you thought of when you wrote them. Exploratory testing finds the scenarios you didn't think of — the ones users will discover on day one. It's not unstructured chaos; it's skilled investigation. Key Takeaways Exploratory testing finds bugs that
Developers
Your code coverage is 80%. You feel confident. Then you flip a > to >= in your payment validation — and all your tests still pass. Coverage measures what your tests run. Mutation testing measures whether your tests would catch a bug. Key Takeaways Code coverage measures what your tests execute,
Test Automation
A bug caught at commit time takes 10 minutes to fix. The same bug caught in production takes 10 hours. CI/CD testing is the practice of moving that discovery window as early as possible — so every change is verified before anyone else has to deal with it. Key Takeaways
Testing Strategy
The average cost of a data breach is $4.88 million. The average cost of catching a security vulnerability during development is a one-hour code review. Security testing is not a separate phase you add at the end — it's the practice of making the expensive option disappear. Key
Testing Strategy
Everyone calls them mocks. They're not all mocks. Dummy, Stub, Spy, Mock, Fake — these five types of test doubles serve different purposes, and using the wrong one produces tests that either verify nothing or are so tightly coupled to implementation that they break every refactor. Key Takeaways "
Testing Strategy
Your QA team passed every test. Your users still found a broken checkout. Acceptance testing is the last gate between your code and your customers — it answers the only question that actually matters: does this software do what the business needs it to do? Key Takeaways Acceptance testing validates business
Testing Strategy
Your coverage report says 85%. Your lead developer feels good. Then someone removes the assert from a critical test — coverage stays at 85%, but that test now catches nothing. Coverage measures how much code your tests run. It doesn't measure whether your tests would actually catch a bug.
Testing Strategy
You just deployed. Before your QA team runs four hours of regression tests, there's one question worth asking: is the build even worth testing? Smoke tests answer that in five minutes — and save everyone from discovering the login page is broken two hours into a full test run.
Testing Strategy
Your application works perfectly with 10 users. You launch, get on Product Hunt, and it falls over at 200. Performance testing is how you find that ceiling before your users do — and how you avoid the worst possible first impression. Key Takeaways Performance testing answers questions that functional tests cannot.