Systems | Development | Analytics | API | Testing

For a long time, we spoke about “AI agents” like they were a future concept, something that might eventually book flights, run workflows, or make payments on our behalf.

Developers and Quality Assurance (QA) teams utilize many different API testing and validation tools to help them simplify the processes of testing, debugging, and validating APIs in the increasingly API-centric world of software development. Modern teams often combine End-to-End Testing with API-level testing to ensure full workflow reliability.

If you find that your team is struggling to get releases out the door, it could be inefficient testing practices. Oftentimes, software teams don’t know what their tests actually cover, or which tests are relevant after each code change — so they run everything. This means spending hours executing full test suites for minor updates or burning through CI/CD resources while bugs slip through untested paths. On top of this, software is always becoming more complex.

In the last ten years, software testing has advanced significantly, but today’s applications require more than just using conventional forms of automated software testing or entry-level tools that employ artificial intelligence (AI). The rise of microservice architectures, API calls, and continuous deployment has led to another category of software testing products called "Generative" AI Testing tools.

Digital Transformation has raised the bar for speed, scalability and reliability. Modern applications are expected to run 24/7, deliver seamless experiences and adapt quickly to market shifts. But traditional, manual-heavy QA simply cannot meet these expectations.

Accessibility and localization often seem like separate disciplines, each with its own set of guidelines and goals.

Manual testing is still essential, but it’s often disconnected from automation. The new Manual to Automation capability in Katalon bridges that gap. It converts manual test runs into automated scripts instantly, linking them for unified coverage.

One of the most critical ways to validate real user journeys across any application is through end-to-end testing. Modern software stacks have grown so distributed that manual E2E testing grows increasingly hard to maintain and nearly impossible to scale. This is where automation in end-to-end testing helps engineering teams with the reliability, speed, and confidence during every release.