Systems | Development | Analytics | API | Testing

Best AI Test Case Generation Tools in 2026

AI test case generation tools are transforming how QA teams create, maintain, and execute tests by automating repetitive work and improving coverage. Teams that adopt AI for QA now will reduce manual test creation time while expanding their test coverage. Software testing has always been a balancing act between thoroughness and speed. You want comprehensive coverage, but you also want to ship features before your competitors do.

Why AI Agents Need Their Own Identity: Lessons from OWASP's MCP Security Guide

The recently released OWASP, “A Practical Guide for Securely Using Third-Party MCP Servers,” highlights a fundamental challenge in modern AI deployments: how do we govern, secure, and audit systems that are inherently non-deterministic? Unlike traditional, static software, AI agents dynamically adapt their execution paths, tool selection, and decisions based on context and real-time resources, allowing the same agent to achieve identical goals through entirely different approaches.

Preparing for Agentic AI: Top Trends in Data and AI 2026

In this season premiere of The Data Chief podcast, host Cindi Howson sits down with three industry leaders to unpack what’s next for AI, and the concrete moves data and AI leaders need to make in 2026—many of which are detailed in ThoughtSpot’s Top Data & AI Trends of 2026 ebook. Get ready for a deep dive into: Consider this your field guide to navigating AI in 2026.

Trust Through Transparency: AI Answers You Can Verify with Spotter

Trust, verified. Powered by Spotter. Why settle for AI hallucinations when you can have governed truth? Spotter maps natural language to business tokens, giving you 100% transparency down to the code. Experience AI you can actually explain. Discover what Spotter can do.

Building Bitrise's AI platform: Scaling AI features across teams

This is the fourth and final installment in our series about bringing AI to Bitrise. In Part 1, we explained why we built our own AI coding agent. Part 2 covered our browser-integrated AI Assistant. Part 3 detailed how we brought AI to the Bitrise Build Cloud. In this final post, we'll explore how we unified these efforts into a cohesive AI Platform.

Multi-agent AI systems need infrastructure that can keep up

When you're building agentic AI applications with multiple agents working together, the infrastructure challenges show up fast. Agents need to coordinate, users need visibility into what's happening, and the whole system needs to stay responsive even as tasks branch out across specialised workers. We built a multi-agent travel planning system to understand these problems better. What we learned applies well beyond holiday booking.

Qlik and Snowflake Cortex AISQL - Show Me What's Possible

Discover how Qlik and Snowflake Cortex AI-SQL are revolutionizing data enrichment and analytics accessibility. This introductory video explores how SQL-savvy data engineers can invoke powerful AI functionality at scale—without complex data science programming—using Snowflake's SQL wrapper for AI capabilities. Learn how Qlik operationalizes Cortex AI-SQL across your entire data pipeline, from enriching data in-flight through Qlik Talend Cloud to enabling business users to interact with AI-powered insights through Qlik Sense analytics.

Qlik and Snowflake Cortex AISQL - Show Me How It Works

See Snowflake Cortex AI-SQL in action with comprehensive demonstrations across the entire analytics lifecycle. This deep-dive video showcases real-world implementations including sentiment analysis on healthcare survey data, emotional classification using the Plutchik Wheel of Emotions, and sophisticated prompt engineering for actionable business recommendations. Watch how Qlik operationalizes these AI capabilities within data pipelines, storing enriched insights as structured data that any user can access—no SQL or data science expertise required.

Qlik and Snowflake Cortex AISQL - Show Me How to Build It

Ready to implement Snowflake Cortex AI-SQL in your Qlik environment? This technical walkthrough provides step-by-step guidance for building AI-powered analytics applications using two proven architectural approaches. Learn how to leverage Qlik's partial reload functionality for user-triggered AI queries, and discover the advanced analytics connector method for creating fully responsive, selection-aware AI interactions. Master the techniques for passing aggregated data alongside questions to ensure security compliance, honor role-based access controls, and maintain multiple versions of truth across different departments.

Why AI can't debug your API integrations (yet)

The next generation of debugging doesn’t depend exclusively on the quality of AI models, but it’s heavily dependent on feeding AI tools the context they need to be useful. AI coding assistants have transformed how we write code. For example, GitHub Copilot, Cursor, and ChatGPT can generate Stripe integration boilerplate in seconds. They'll scaffold your payment flow, suggest error handling patterns, and even write unit tests.