More code. Faster releases. Less confidence. That's the AI coding paradox. Most engineering leaders know their QA capacity is lagging. Few have the data to prove it. AI accelerated your development velocity. Did your testing keep pace?
Why Your Software Engineering Metrics Need to Go Beyond DORA in 2026

Why Your Software Engineering Metrics Need to Go Beyond DORA in 2026

Publish Date: April 27, 2026

DORA scores look great, but production still breaks. In 2026, elite engineering leaders are closing the gap with software engineering metrics that track AI code quality, developer experience, and real business outcomes, not just deployment speed.

Quality Engineering in the AI Era: From Gatekeeper to Strategic Guardrail

Quality Engineering in the AI Era: From Gatekeeper to Strategic Guardrail

Publish Date: April 24, 2026

This blog explores how AI-driven development is accelerating code output while weakening quality signals, highlighting risks like flaky tests and pipeline decay. It outlines how engineering leaders can reposition QA into a strategic function with guardrails, governance, and observability.

How AI Code Security Vulnerabilities Are Creating a New Security Bottleneck

How AI Code Security Vulnerabilities Are Creating a New Security Bottleneck

Publish Date: April 23, 2026

AI coding tools are shipping faster than ever. But AI code security vulnerabilities are scaling at the same pace. This blog breaks down the root causes, consequences, and what engineering leaders must do before the next breach.

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Our bloggers are the test management experts at QASource. They are executives, QA managers, team leads, and testing practitioners. Their combined experience exceeds 100 years and they know how to optimize QA efforts in a variety of industries, domains, tools, and technologies.