Systems | Development | Analytics | API | Testing

How to build a desktop application test automation strategy

To build a desktop application test automation strategy, cover both two layers: use SmartBear ReadyAPI to test the APIs and services behind the app and SmartBear TestComplete to automate the desktop UI. Run both on your own infrastructure, and start with the manual regression cycle that costs your team the most time.

Who approved that? The AI agent question security teams can't skip

In late October 2026, developers found that a routine update to a widely used desktop API client had changed their AI coding agents without asking. For security and compliance teams, the tool matters less than the question the incident raises: when something changes how your AI agents behave, who approved it?

How AI is transforming build vs. buy strategy

When I talk to engineering leaders about how their team decides whether to build a piece of software instead of buying something off the shelf, the decision usually starts at, “well, can we?” For most of the last decade, that was a reasonable first question, because unless the team had a quarter’s worth of runway and a specialist to spare, the answer was “no.” But now, AI has made the answer “yes,” at least on the surface.

Native test management for Jira: What it is and when you need it

Native test management for Jira is a dedicated test management layer that runs inside Jira. It adds the capabilities Jira doesn’t provide on its own: reusable test cases, test cycles, execution history, requirements-to-test traceability, and release reporting. Jira doesn’t include built-in test management, so teams either adapt Jira work items to track tests or add a test management app from the Atlassian Marketplace.

ReadyAPI vs. Postman for enterprise API testing

As API programs grow, teams need to test beyond individual requests. Functional checks, performance under load, security validation, and dependent services can involve different workflows, while teams still need a clear view of results and where tests run. Postman combines collaborative API development with collection-based functional and performance testing. SmartBear ReadyAPI brings functional, security, and performance testing together with service virtualization and broad protocol support.

Control the spend and usage of your AI testing agents | SmartBear BearQ

Worried an AI teammate could rack up a surprise bill? In this video, you’ll learn how SmartBear BearQ gives you real governance over AI testing spent – built with pre-baked monthly limits, so your team always knows what to expect before a single agent gets to work.

How to test Jira tickets automatically with an AI QA agent | SmartBear BearQ for Jira

You can add AI-driven testing to your Jira workflow by handing tickets to the QA Lead Agent in SmartBear BearQ for Jira. Move a finished ticket, and the agent checks for an existing test, links or creates one, runs it, and reports back. If your team builds with coding agents like Claude or Cursor in Jira, BearQ, the agentic QA system, adds the quality step to that AI-driven software development lifecycle (SDLC).

From AI chaos to agentic QA, ft. Andy Weir, author of The Martian and Project Hail Mary

10x faster coding. Same QA. Until now. You're coding faster with AI. But if your agents are siloed and disconnected, those gains aren’t yet showing up in your quality or delivery – it's getting lost in the handoffs. Join SmartBear for a live demonstration of the connected agentic SDLC. See how BearQ extends beyond creating tests to coordinating quality work across Jira, GitHub, and AI-powered workflows – detecting issues, triggering the right next action, and carrying context from one agent to the next.

Connect agentic testing with Jira, Linear, and Azure DevOps| SmartBear BearQ

Watch this video to see how see how SmartBear BearQ keeps bug reports and test results in sync with Jira, Linear, and Azure DevOps at AI speed and scale, with no manual copy-pasting. BearQ’s agentic QA system connects to the tools your team already relies on, so its three built-in agents can pull in context and push results right where your team lives.

SaaS or on-premise? How to settle the Swagger deployment question

Choosing between SaaS and on-premise for SmartBear Swagger Studio, SmartBear Swagger Portal, and SmartBear Swagger Contract Testing The question that most often stalls an API solution evaluation is a simple one: do we run this as SaaS or on-premise? It’s simple to ask and hard to answer, because three teams each hold a veto. Security needs to know where your data will live. Your platform team has to decide whether it can take on another workload.