Systems | Development | Analytics | API | Testing

We spend thousands of dollars "token maxing" and running endless debugging cycles just to walk our LLMs through a problem. But is the AI actually failing, or are we just withholding the right environment? Giving your AI assistant its own sandbox to test hypotheses might just be the missing link in your development workflow.

Why Observability Systems Fail AI Code.

Mobile Recorder Interactive Mode is now official in Katalon Studio 11.4. Interact directly on the device view and Studio reflects exactly what you're doing. Select an object in Device View, and your test steps follow that selection automatically. We've also improved the action flow so common recorder tasks feel more natural inside your session. Less guesswork. Faster mobile testing. Tell us in the comments which feature you want covered in next month's update.

Katalon Studio 11.4 can now generate API test cases with AI. Import your OpenAPI specification and Studio automatically creates the Web Service requests in an API Collection. From there, generate tests and save them straight into your project. The AI doesn't just show you a preview. You get real test cases covering positive flows, boundary values, NULL values and empty strings, ready to run and build on like any other test case in your project.

Assaf Henkin, Co-Founder and CEO of Jedify, joins the Snowflake Summit 2026 News Desk to discuss how enterprises can build AI applications that truly understand their business context. Drawing from 15 years of experience building open source intelligence platforms, Henkin shares insights on balancing innovation with operations, staying true to founding principles while adapting to market changes, and how Snowflake's AI Data Cloud is enabling Jedify to reach new heights in the agentic AI era. Learn what's driving enterprise AI adoption and what founders should focus on for the back half of 2026.

"To get real value from AI at scale, you need to put AI in a process," explains Jake Rank, VP of Product at Appian. That's how leading organizations move beyond AI experimentation to automate work, improve efficiency, and deliver measurable business outcomes.

Hear from our Lead Product Marketing Manager for Tricentis Tosca as she describes how to align your test automation with the reality of your business processes—moving beyond brittle scripts to build tests that reflect real business logic.

Jason Secola, Tricentis Lead Product Marketing Manager, explains how performance teams can leverage NeoLoad to avoid becoming a bottleneck and get ahead as agentic AI speeds up developer workflows.

In this video, Mike Tarallo shows you a simple Qlik Automate workflow with defined inputs, then uses the Automate Agent in Qlik Answers to pass those inputs directly into the automation. This demonstrates how users can move beyond simply asking questions and begin taking action based on their data—all from a conversational experience. You’ll see how Qlik Answers and Qlik Automate work together to turn natural-language requests into real, automated workflows with minimal setup.

Every AI agent starts every session with zero memory. No context, no history, just a blank slate that has to rediscover its environment from scratch, and that costs you real time and money. In this episode of Inside the Stack, Jase Lindgren, Principal P4 User Advocate at Perforce, shows a simple fix: instead of re-prompting your agent every time, capture what it learns in a markdown file, then go one step further and turn that into a custom script. The result, tested across 15 runs: lower cost, faster execution, and better accuracy at catching real issues.