Practical views on AI, engineering, quality, governance and technology leadership, grounded in what is changing now and what it means in real organisations.
API testing is easy to start, but its real value goes far beyond checking 200 responses. It is about validating business rules, failure behaviour, integrations and whether systems keep the promises they make to each other. I would keep AI completely out of the headline tomorrow. Four consecutive articles screaming AI would start making the profile look one-dimensional. This article makes you look like someone who understands core testing engineering as well as AI, which is much stronger profess
A green test suite proves what we decided to test. But when something unexpected fails in production, can we actually understand why? This article looks at why observability, failure evidence and production signals are becoming an important part of modern Quality Engineering.
AI can now generate automated tests quickly, but more tests do not automatically mean better quality. This article looks at the next QA challenge: validating whether AI-generated tests are meaningful, reliable and actually worth trusting.
AI can generate code and tests faster than ever, but speed does not automatically create confidence. This article looks at how QA is shifting from simply executing tests to evaluating risk, evidence, assumptions and whether a software change can genuinely be trusted.
AI agents are moving beyond chat and into action. That makes governance, access control, behavioural testing and human approval far more important than most organisations realise.