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Scaling with Atlassian: AI Testing and No-Code Automation, All Inside Jira 

Testing is falling behind delivery. Teams ship faster than ever, but they still write test cases by hand, and adopting automation usually means a separate tool and someone who can code. AI makes it easy to generate tests fast. The harder question is whether you can trust the output, and whether your testing keeps up …

API Performance Testing in the Age of AI-Generated Code | Webinar

Thursday August 20th As developers build and release APIs faster in an Agentic AI assisted world, many enterprises are having to reshape existing API testing to ensure their APIs don’t lose quality and scale. Existing functional tests and unit tests may not suffice in identifying API quality introduced via agentic development.  ReadyAPI’s performance test module can build an extensive test suite based off existing infrastructure to capture minute slow-downs or …

Earn production confidence: why passing tests don’t mean production-ready APIs

Most API failures don’t look like failures. The service responds. The status code is green. But somewhere between the last time an API was tested and the moment it’s called in production, the contract quietly changed, and nobody was watching. New data shows that 63% of APIs drift from their tested behavior within 90 days1, and when things do break, most of the …

Same Spec, Zero Drift: ​Keeping API Tests in Sync with AI and MCP​

The challenge  Your OpenAPI spec changes on a Tuesday. Your test suite finds three sprints later, usually in production.  That gap between what your API actually does and what your tests assume it does is the sync gap. It is expensive. 41% of APIs drift within 30 days, and teams still lose a quarter to half of their QA capacity just keeping test suites current …