Systems | Development | Analytics | API | Testing

The ability to push an update directly to your users’ devices without App Store review, without delay, without any action required from the user, is one of the most powerful capabilities available to a React Native team. Over-the-air (OTA) updates change how fast you can respond to bugs, iterate on features, and ship improvements. But that power cuts both ways. A bad OTA update reaching 100% of your users at once is considerably worse than a bad store release.

The rise of AI-assisted coding has transformed how software is built. With tools generating entire features in seconds, the bottleneck is no longer writing code—it’s verifying it. Because AI can generate boilerplate and handle API integrations instantly, more service changes are being pushed into authentication logic, API calls, and configurations. Teams desperately need a way to verify these changes before merging, especially when the code touches external dependencies.

Agentic Testing and QA is a practice in which AI agents operate directly on a project — reading files, planning tasks, generating framework code, and interacting with a browser — rather than simply answering prompts inside a chat window. Tools like Claude Code bring this capability to the terminal, giving QA teams a command-line assistant that understands repository context, proposes changes before applying them, and generates test assets across Playwright, Selenium, and API testing workflows.

AI agents do not just respond. They interpret goals, use tools, follow workflows, apply context, and sometimes change real systems. That means they need a different kind of testing.

Enterprises are buying AI infrastructure faster than their platform teams can operationalize it. Dell and ClearML are working together to close that gap, giving enterprises a faster, simpler path from Dell AI Factory hardware to a production-grade AI platform. Dell carries the hardware. ClearML provides the AI infrastructure layer on top. Together, the two give platform teams a way to deliver AI as a service to their organization without a multi-year integration project.

Modern performance testing is evolving beyond the traditional choice between enterprise platforms and open-source tools. Teams increasingly need the flexibility of JMeter, k6, Gatling, or Locust combined with enterprise-grade reporting, scalability, security, and support. A new generation of platforms helps reduce operational complexity, lower total cost of ownership, and accelerate adoption through AI-assisted workflows and simplified onboarding.