
Start with the risks, not the method
In this post I set out how looking at risks before approaches can improve your test approaches.
Quality Engineering and strategic thinking in the AI era
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In this post I set out how looking at risks before approaches can improve your test approaches.

I was an AI testing sceptic and wrote it down. Here's why garbage in, garbage out is good news for testers and how AI rewards testing skill rather than replacing it.

In this post I describe how setting a risk appetite is crucial for defining quality expectations in organisations. Without this risks are accepted by people without the authority to do so.

AI can run your exploratory testing, but only as well as the charter, risk appetite and heuristics you give it. Here I show how you can do this.

Most teams can’t actually measure change failure rate. Here’s why that foundational gap turns AI-driven delivery speed into a hidden source of business risk.

In this post I describe a model for engineering teams to use in assessing their readiness for AI adoption safely.

The post provides guidance on crafting conference talk abstracts, emphasizing title importance, core messages, and speaker credentials.

A Playwright E2E test framework using AI was developed, achieving near-complete workflow coverage with minimal team involvement and effective reviews.

The blog discusses the challenges faced by Quality Engineers, emphasizing communication, accountability, and the need for a collaborative quality culture.

Quality professionals must adapt to engineering’s evolving needs to rebuild trust and credibility, ensuring valuable collaboration and impactful influence.