Systems | Development | Analytics | API | Testing

Testing is a very important and necessary step in the SDLC, but most teams ignore it or don’t care much about it, while some teams spend most of their time on testing instead of building features. AI is really changing the way we write code, but most people use it mainly for writing test cases, and we still end up doing it manually. So in this blog, let’s see what AI testing is, how AI helps in testing our software, what AI tools are available, and which tools help with which part of testing.

Better audience data means better ROAS, and ClickUp demonstrated this using Census to enhance ad performance, personalization, and cross-channel consistency.

This guide focuses on the critical configurations every DreamFactory administrator must understand: memory_limit, upload_max_filesize, post_max_size, PHP-FPM worker settings, and the often-overlooked configuration hierarchy where pool settings override php.ini values.

APIs are no longer just simple integration interfaces. As AI models, agents, and digital ecosystems become increasingly interlinked, APIs have become products. They have their own usage patterns, costs, and business implications. To make informed, data-driven, and business decisions, you require deep visibility into your systems. To address these challenges, the latest v4.6.0 release of WSO2 API Manager includes a dedicated API intelligence engine, powered by Moesif.

If you’ve worked in QA long enough, you’ve seen how much testing has changed inside Jira. What started as a mix of spreadsheets, manual checklists, and endless review cycles has grown into fully integrated Test Management workflows. But even with automation, some challenges never went away. Writing test cases from requirements still takes time.

Note: This article is the third instalment in a four-part series. Check out the first two posts here:- Why we ditched frontier AI agents and built our own- Building Bitrise’s context-aware, browser-integrated AI copilot that keeps engineers in control.

As artificial intelligence (AI) adoption has grown over the last several years, it has become increasingly clear to companies and observers that successful AI requires real-time data and context. And it’s not just AI—every critical business function that relies on data inputs needs that data to be as trustworthy and fresh as possible.

‍ Healthcare’s most significant bottleneck in 2025 isn’t technology, it’s people. Across hospitals and clinics, staff shortages, burnout, and scheduling chaos are threatening the quality of care and driving operational costs upward. The U.S. alone is projected to face a shortfall of up to 3.2 million healthcare workers by 2026, according to Mercer.