Finding bugs is what testing produces; understanding quality is why it exists. QA's future belongs to those who understand products, customers, and risks, not just bugs.
When optimizing Spring Boot integration tests, developers often focus on obvious metrics, but they do not always explain why an integration test suite is slow.
Reliable AI delivery isn't either/or—it's both/and. Test conventionally for functionality. Evaluate probabilistically for quality. Deploy with dual-discipline confidence.
Build a Slack bot using AWS Bedrock and MCP to answer GitHub questions. Learn setup, architecture, and how to extend it with new tools and data sources.
Building a Slack bot with traditional APIs led to 400 lines of code. Using MCP and AWS Bedrock reduced complexity, enabling scalable, tool-driven automation.
Setting up a data catalog isn’t just a tool problem. My work with Azure Purview and Collibra showed success depends on governance, metadata, and adoption.
AI generates code faster than tests can cover. Coverage stays green while gaps grow. Treat AI code as untested by default and scale testing to match generation speed.
Unbounded retries and autoscaling can turn minor latency into cascading outages. API reliability must be bounded and load-aware to prevent retry storms.
SAP cloud TCO is driven more by landscape sprawl than by EC2 costs; optimize environments and use Terraform, S3, and EFS lifecycle policies to reduce costs.