Benchmark scores predicted our LLM would succeed. It failed spectacularly. Here's why 92% vs 89% means nothing and what metrics actually matter in production.
QA is evolving for AI-driven business, focusing on data quality, model validation, and risk management to ensure reliable, trustworthy, well-governed systems.
Learn how to automate CloudWatch alerts, Kubernetes remediation, and incident reporting using multi-agent AI workflows with the AWS Strands Agents SDK.
A comprehensive guide to migrating from Apache Spark 3.x to Spark 4.0, covering breaking changes, new features, and mandatory updates for smooth transition.
Using AI in quality assurance is now essential to staying competitive, but teams still need to stay grounded and involve people to balance the hype with real results.
Modern cloud systems need performance engineering, not just load testing. Proactively ensure reliability, scalability, and resilience across the lifecycle.