Systems | Development | Analytics | API | Testing

AI Coding Tools and API Governance: Here's Why You Need Both.

GitHub Copilot, Claude, and Cursor have become genuine superpowers for API development. They draft OpenAPI definitions, generate endpoints, propose schema changes, and write test cases — all from inside the IDE, in real time. Teams using these tools are generating API definitions faster than most thought possible even a few years ago. That velocity is real, and it’s reshaping how engineering teams think about their toolchain.

Four signs your automation suite is costing you more than it's saving

An automation suite that’s losing ground rarely makes it obvious. Coverage numbers look reasonable. Tests are running. The CI pipeline is green more often than not. Meanwhile, the team is quietly working around what isn’t working – rerunning tests until they pass, deferring maintenance, or accepting a regression window that’s wider than it should be. Those workarounds can feel normal. They aren’t.

Why your automated UI tests keep breaking

Automated test suites tend to follow the same arc. The suite works well until the application changes and a block of tests fails. Someone fixes them. The application changes again. At some point, the work of keeping tests current starts consuming the time that should go toward coverage decisions, risk assessment, and the testing work that requires human judgment.

Automated testing vs. autonomous testing

Autonomous testing is one of the most talked about developments in software quality right now. It shows up in analyst reports, vendor pitches, conference talks, and job descriptions – often in the same breath as automated testing. Most of those conversations treat the two as interchangeable, or worse, position autonomous testing as simply a smarter, more advanced version of what teams already do.

Build resilient end-to-end tests with AI agents in SmartBear Reflect | Demo Den

See how SmartBear Reflect uses agentic AI to build end-to-end tests in minutes and keep them resilient as your application changes. In under 20 minutes, Reflect co-creator, and SmartBear Director of Product Management, Todd McNeil walks through live test creation across web and mobile, with zero fluff.

TestComplete vs. Reflect: Which SmartBear test automation platform fits your team?

Not every test automation problem looks the same. A team maintaining complex desktop applications in a controlled financial services environment has different automation needs than a team shipping web and mobile updates every two weeks. The application, the environment, and the people creating tests all shape what “good automation” has to do.

Automatically catch API drift before your users do | Swagger Contract Testing

our API didn't break – it just stopped matching its contract. API drift is one of the sneakiest problems in modern API development. Your OpenAPI definition says one thing, your running implementation does another, and nobody notices until a consumer integration fails or a user hits an unexpected error. The longer it goes undetected, the harder it is to trace back to the source.

First look: Agents are coming to your favorite SmartBear products

AI is accelerating how teams build and ship software, but validating quality is getting harder, not easier. More AI-generated code means more to test, more API drift to catch, and more documentation that falls behind. The work is growing faster than teams can keep up.

The best tools don't force teams to change how they work

They fit into the workflows, processes, and environments teams already have. As Chris Armstrong, Manager of Developer Relations at SmartBear, explains, every organization is on a different stage of its journey. Some are exploring AI. Others are scaling it. Many are managing a mix of legacy systems, modern platforms, and everything in between. What teams need isn't another platform that demands a complete overhaul. They need solutions that respect their context while helping them move forward with confidence.

Building Confidence Across APIs and AI Agents with the Swagger Contract Testing Kiro Power

There is a specific kind of confidence that comes with deploying software. Not just “the tests passed” confidence, but the kind that comes from knowing the services your application depends on still behave the way you expect them to. Preserving that integrity becomes harder as systems grow, teams move faster, and AI agents become active participants in delivery workflows.

QMetry walkthrough: Test management, automation & AI-powered testing

Discover how QMetry streamlines test management with this comprehensive walkthrough covering requirements management, test design, test execution, automation, reporting, and AI-powered productivity features. Struggling with disconnected testing processes, manual test execution, and limited visibility into quality across your software development lifecycle? This complete QMetry tutorial shows testers, QA teams, and engineering organizations how to manage the entire testing workflow in a single platform, from requirements to release.