Systems | Development | Analytics | API | Testing

Velocity can't come at the cost of quality

AI-generated code is flooding your pipelines. Your test automation debt is piling up. If this sounds familiar, you're not alone. Velocity can't come at the cost of quality. As AI transforms how we build software, API testing must evolve. Join Justin Collier, Senior Director, Product Management, and Yousaf Nabi, Developer Advocate, to explore the future of API testing in an AI-driven world.

Git review for TestComplete projects

Teams using TestComplete face a common problem: one small test change can produce a wide set of modified files, and not all of them deserve the same level of scrutiny. The fix is not to review everything equally – it is to classify TestComplete artifacts by risk, then standardize how your team reviews, stages, and merges them. This article outlines this process and offers best practices for using Git effectively with TestComplete projects.

Why the "tsunami of code" is breaking QA | From the Bear Cave Ep. 3

Recent SmartBear research shows that 70% of teams are already seeing quality degrade with AI-generated code, creating a real bottleneck in the software-development lifecycle (SDLC). As output increases, QA teams are left choosing between delaying releases to validate changes or shipping faster with less confidence in what’s actually working. In this From the Bear Cave clip, SmartBear CEO Dan Faulkner and CMO Kelly Wenzel dig into a growing gap in modern software development: how AI is accelerating code generation but testing and quality validation aren’t scaling with it.

Complete beginner's guide to test automation | TestComplete

Learn how to get started with TestComplete in this comprehensive beginner's tutorial. TestComplete is an automated testing platform for desktop, web, and mobile applications – and this guide will help you create your first test in just minutes. What You'll Learn: This video is perfect for test automation engineers and developers new to automated testing. Whether you're testing desktop applications, web apps, or mobile interfaces, this tutorial covers the essential features every TestComplete user needs to know.

How does BearQ autonomous QA work? Your top questions answered

Testing software at scale has always been a race against change. Then, AI-coding turned what was once a challenge into a crisis: rapid development cycles accelerated by AI have made it impossible to maintain comprehensive test coverage and catch issues before they impact users. In SmartBear’s Closing the AI Software Quality Gap Study, 60% of software experts told us they experienced quality issues as development outpaces testing.

How to scale API standards across large teams | Swagger Studio

When multiple designers and teams contribute APIs, you face inconsistent schemas, divergent patterns, and broken assumptions. However, the "shift-left" approach to API standardization helps you catch issues early, automate compliance, and maintain quality without manual gating – making your API program truly scalable. In this video, SmartBear Senior Solution Engineer Joe Joyce demonstrates how to enforce consistent API standards across large development teams using Swagger Studio's governance, collaboration, and CI/CD integration features.

Inside the SmartBear Roadmap: Delivering Application Integrity Across the SDLC

As software teams move faster across APIs, testing, and observability, keeping application integrity intact is harder than ever. Join SmartBear product leaders for a Now / Next / Later look at how we’re evolving our platform to help teams build, test, and operate software with confidence. What you’ll get from this session: Get a clear view of where SmartBear is headed and how these capabilities come together to help your teams scale quality alongside velocity across the SDLC.

SmartBear testing tools compared

AI-accelerated development has fundamentally changed how software is built, and across the industry, its impact on quality is already measurable. In SmartBear’s Closing the AI software quality gap study, we found nearly 70% of software professionals report application quality is declining as AI speeds up code generation, with development velocity increasingly outpacing teams’ ability to test effectively.

The testing disconnect that's undermining your API quality

In 2026, APIs have moved far beyond simple integration points. They’re now strategic business assets powering AI transformation, microservices architectures, and multi-cloud ecosystems. But a critical challenge threatens to undermine digital initiatives: the fragmentation of API testing. As organizations rush to deliver faster, they’re discovering that their testing infrastructure – cobbled together from disparate tools and disconnected processes – has become the bottleneck.

How to Add Intent and Metadata to OpenAPI in Swagger Studio for AI Agents

Modern APIs aren’t just read by developers anymore; they’re also interpreted by tools and AI agents. In this video, Solutions Architect Joe Joyce walks through how to enrich an OpenAPI definition in Swagger Studio with meaningful metadata such as descriptions, summaries, operation IDs, tags, schemas, and examples. You’ll see step-by-step how these additions help tools and automated agents better understand API intent, purpose, and semantics. This turns your OpenAPI definition into a contract that scales beyond documentation.