Testing the Tester: Who Validates the Humans Evaluating AI?
What calibration runs have taught us about human judgment, ground truth, and the hidden QA problem inside AI evaluation.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Modernizing at the speed of AI: How state and local governments can keep quality in check
For the first time ever, artificial intelligence has topped NASCIO’s annual ranking of state CIO priorities, ending cybersecurity’s 12-year reign at number one. It’s easy to see why: public agencies – like their private sector counterparts – see real potential in AI to modernize operations, accelerate service delivery, and help lean teams do more with fewer resources.
Digital Autonomy in the Cloud Era: Reducing Reliance on Hyperscalers
What would happen if you had to move a mission-critical application off your current cloud platform within the next year? In this webinar highlights reel, experts from Perforce OpenLogic explore why cloud portability, digital autonomy, and operational ownership are becoming strategic priorities for enterprise organizations. The panel opens with a simple but revealing question: How painful would it be to replatform a critical workload in the next 12 months? The answer often exposes hidden dependencies, operational risk, and the true state of an organization's cloud resilience.
Stop your AI agent's $100,000 reordering mistake
See how Fivetran and dbt help an AI reordering agent make more reliable retail decisions. This end-to-end demo shows how trusted data supports smarter inventory decisions across the enterprise.
Quantum Computing's Impact on Cloud Testing
Quantum computing is beginning to influence complex scenarios in cloud testing, offering the potential to process vast possibilities in parallel. However, as of 2026, the technology remains experimental. Early hardware is limited in scale and prone to errors, so broad business impact is still several years away. Teams running large-scale performance testing or cryptography simulations should monitor quantum’s progress, but avoid overcommitting resources until the technology matures.
Cheap Tokens, Exploding Bills: The Hidden Cost of AI Agents
80% cheaper AI model. Nearly 2X the data warehouse bill. Switching to a cheaper AI model can cut your token costs by 80%, but it might accidentally double your public cloud data warehouse bill. In this video, we break down the "Agentic Cost Shift"—how autonomous AI agents generate hidden, high-compute SQL queries that drive up data lakehouse costs—and how to fix it using Cloudera. See where the real cost of AI is shifting.
What's Next Is Not More AI. It's Better Foundations.
The next real advantage in artificial intelligence will not come from the next AI tool or application. It will come from a stronger data foundation beneath it. At Hitachi Vantara we work every day with customers on the data supporting their systems. That vantage point has led me to a simple conclusion: the leaders who pull ahead will not be the ones with the most advanced AI. The leaders will be those whose data foundations are strong enough so that AI can be trusted to act.
Top 17 AI Testing Tools
Generating tests isn’t the hard part anymore. Ask an LLM to create Playwright tests, and it will produce hundreds of them in no time. The problem lies in deciding whether those tests are useful, maintaining them as your application changes, and knowing if you’ve even chosen the right tool in the first place. This article compares 17 AI testing tools across 5 categories. We’ll look at what each of them does, where it fits, what makes it different, and where it falls short.
Why do my apps keep crashing? 6 causes and how to fix them
An app crash is one of the fastest ways to drain both users and rankings. Many users will uninstall an app after just one crash, and both the App Store and Google Play will penalize crash-prone or unstable apps. At Bugfender, we’ve been investigating app crashes since 2014. In this post we’re going to share all our key learnings, so you can: You’ll come away with a reliable, repeatable way to anticipate app crashes – wherever they happen. This post is generally platform-agnostic.
Testing at AI speed: We built a drift detection capability, then used it on ourselves
Drift detection stays narrow on purpose. It checks contract conformance – structure, status codes, schema – and deliberately leaves workflows and business logic to functional and end-to-end tests. That’s what makes it a fast add to our pipeline to prevent API drift. That narrow scope keeps it cheap to run. Fast execution, low flakiness, low maintenance cost – the kind of checks that make you more confident shipping. Catching drift early is the whole point.