Systems | Development | Analytics | API | Testing

Why traditional test metrics fall short in the AI era

Most QA teams already track the basic metrics: how many tests ran, how many passed, how much coverage exists, and how many defects turned up. Those numbers still matter, and engineering leaders will keep asking for them. The real challenge is turning those numbers into decisions, and that gets harder as AI-assisted development speeds up the volume, frequency, and complexity of software change.

What SmartBear's AWS AI Software Competency means for software teams

AI is changing how software gets built. That raises the bar for every team responsible for keeping it working. SmartBear has been developing AI capabilities across the entire quality lifecycle that help teams deliver software they trust will work at AI speed and scale. Today, SmartBear announced it has achieved AWS AI Software Competency status in the Agentic AI category through the AWS Partner program.

How to design & test APIs with OpenAPI & Swagger | What's changed in 3.1 & 3.2

Outdated API docs and last-minute bugs cost teams time and trust. Learn how the OpenAPI Specification help you document, govern, and test your APIs from design to deployment – all inside SmartBear Swagger. SmartBear's Yousaf Nabi, Developer Advocate, and Chris Armstrong, Manager of Developer Relations, explain why API documentation drifts out of sync and walk through what's changed between OpenAPI 3.0, 3.1, and 3.2. After covering a brief history of Swagger and the OpenAPI specification, they demo the full API workflow across Swagger.

Enterprise test management: Should you build or buy in the age of AI?

AI has opened the door for teams to build tools they previously had to buy. With the right prompts and internal workflows, teams can generate test cases, summarize results, analyze defects, and automate parts of the testing process faster than ever. For enterprise QA and engineering leaders, that raises a practical question: “should we build our own test management layer, or adopt an AI-powered test management platform?” It’s a fair conversation to have.

Ship production-ready APIs faster and confidently with SmartBear ReadyAPI | Demo Den

API testing gets harder as it grows: fragmented tools, brittle scripts, thousands of endpoints, and external dependencies that block progress. SmartBear ReadyAPI lets teams ship production-ready APIs faster by validating functionality, performance, and security in one test, with virtualization built in – no separate tools to juggle. In this Demo Den, Thomas Hurley, senior manager of product management at SmartBear, shows how one test does the work of three, so teams cut maintenance time and stop waiting on external dependencies.

AI tip #2: Improve pull requests with AI

AI tip: For pull requests, let your AI agent take the first pass before your team ever sees it. That's the workflow Ilia Mogilevsky, Software Engineering Manager at SmartBear, built. By packaging prompts into a skill loaded with Git history, Jira context, and CI checks, he turned a basic AI assistant into a reviewer he trusts. The skill then generates a structured report with approval-ready fixes. Accept the changes, adjust what's off, and push – review cycles shrink and deploys move faster.

SmartBear Swagger: Meeting You Where You Work

Some approaches to API governance interrupt developers mid-flow, forcing them to context-switch into a separate tool and manually verify their API definition before they can ship. That approach has never really worked. Not because developers don’t care about quality, they do, but because the best time to fix an API is the moment you’re already thinking about it. That’s what has always guided how Swagger grows. Not “come to us.” But “we’ll be there.”